February 21, 2019 by dominiccummings

On the referendum #30: Genetics, genomics, predictions & ‘the Gretzky game’ — a chance for Britain to help the world

Britain could contribute huge value to the world by leveraging existing assets, including scientific talent and how the NHS is structured, to push the frontiers of a rapidly evolving scientific field — genomic prediction — that is revolutionising healthcare in ways that give Britain some natural advantages over Europe and America. We should plan for free universal ‘SNP’ genetic sequencing as part of a shift to genuinely preventive medicine — a shift that will lessen suffering, save money, help British advanced technology companies in genomics and data science/AI, make Britain more attractive for scientists and global investment, and extend human knowledge in a crucial field to the benefit of the whole world.

‘SNP’ sequencing means, crudely, looking at the million or so most informative markers or genetic variants without sequencing every base pair in the genome. SNP sequencing costs ~$50 per person (less at scale), whole genome sequencing costs ~$1,000 per person (less at scale). The former captures most of the predictive power now possible at 1/20th of the cost of the latter.

Background: what seemed ‘sci fi’ ~2010-13 is now reality

In my 2013 essay on education and politics, I summarised the view of expert scientists on genetics (HERE between pages 49-51, 72-74, 194-203). Although this was only a small part of the essay most of the media coverage focused on this, particularly controversies about IQ.

Regardless of political affiliation most of the policy/media world, as a subset of ‘the educated classes’ in general, tended to hold a broadly ‘blank slate’ view of the world mostly uninformed by decades of scientific progress. Technical terms like ‘heritability’, which refers to the variance in populations, caused a lot of confusion.

When my essay hit the media, fortunately for me the world’s leading expert, Robert Plomin, told hacks that I had summarised the state of the science accurately. (I never tried to ‘give my views on the science’ as I don’t have ‘views’ — all people like me can try to do with science is summarise the state of knowledge in good faith.) Quite a lot of hacks then spent some time talking to Plomin and some even wrote about how they came to realise that their assumptions about the science had been wrong (e.g Gaby Hinsliff).

Many findings are counterintuitive to say the least. Almost everybody naturally thinks that ‘the shared environment’ in the form of parental influence ‘obviously’ has a big impact on things like cognitive development. The science says this intuition is false. The shared environment is much less important than we assume and has very little measurable effect on cognitive development: e.g an adopted child who does an IQ test in middle age will show on average almost no correlation with the parents who brought them up (genes become more influential as you age). People in the political world assumed a story of causation in which, crudely, wealthy people buy better education and this translates into better exam and IQ scores. The science says this story is false. Environmental effects on things like cognitive ability and education achievement are almost all from what is known as the ‘non-shared environment’ which has proved very hard to pin down (environmental effects that differ for children, like random exposure to chemicals in utero). Further, ‘The case for substantial genetic influence on g [g = general intelligence ≈ IQ] is stronger than for any other human characteristic’ (Plomin) and g/IQ has far more predictive power for future education than class does. All this has been known for years, sometimes decades, by expert scientists but is so contrary to what well-educated people want to believe that it was hardly known at all in ‘educated’ circles that make and report on policy.

Another big problem is that widespread ignorance about genetics extends to social scientists/economists, who are much more influential in politics/government than physical scientists. A useful heuristic is to throw ~100% of what you read from social scientists about ‘social mobility’ in the bin. Report after report repeats the same clichés, repeats factual errors about genetics, and is turned into talking points for MPs as justification for pet projects. ‘Kids who can read well come from homes with lots of books so let’s give families with kids struggling to read more books’ is the sort of argument you read in such reports without any mention of the truth: children and parents share genes that make them good at and enjoy reading, so causation is operating completely differently to the assumptions. It is hard to overstate the extent of this problem. (There are things we can do about ‘social mobility’, my point is Insider debate is awful.)

A related issue is that really understanding the science requires serious understanding of statistics and, now, AI/machine learning (ML). Many social scientists do not have this training. This problem will get worse as data science/AI invades the field.

A good example is ‘early years’ and James Heckman. The political world is obsessed with ‘early years’ such as Sure Start (UK) and Head Start (US). Politicians latch onto any ‘studies’ that seem to justify it and few have any idea about the shocking state of the studies usually quoted to justify spending decisions. Heckman has published many papers on early years and they are understandably widely quoted by politicians and the media. Heckman is a ‘Nobel Prize’ winner in economics. One of the world’s leading applied mathematicians, Professor Andrew Gelman, has explained how Heckman has repeatedly made statistical errors in his papers but does not correct them: cf. How does a Nobel-prize-winning economist become a victim of bog-standard selection bias? This really shows the scale of the problem: if a Nobel-winning economist makes ‘bog standard’ statistical errors that confuse him about studies on pre-school, what chance do the rest of us in the political/media world have?

Consider further that genomics now sometimes applies very advanced mathematical ideas such as ‘compressed sensing’. Inevitably few social scientists can judge such papers but they are overwhelmingly responsible for interpreting such things for ministers and senior officials. This is compounded by the dominance of social scientists in Whitehall units responsible for data and evidence. Many of these units are unable to provide proper scientific advice to ministers (I have had personal experience of this in the Department for Education). Two excellent articles by Duncan Watts recently explained fundamental problems with social science and what could be done (e.g a much greater focus on successful prediction) but as far as I can tell they have had no impact on economists and sociologists who do not want to face their lack of credibility and whose incentives in many ways push them towards continued failure (Nature paper HERE, Science paper HERE — NB. the Department for Education did not even subscribe to the world’s leading science journals until I insisted in 2011).

1) The problem that the evidence for early years is not what ministers and officials think it is is not a reason to stop funding but I won’t go into this now. 2) This problem is incontrovertible evidence, I think, of the value of an alpha data science unit in Downing Street, able to plug into the best researchers around the world, and ensure that policy decisions are taken on the basis of rational thinking and good science or, just as important, everybody is aware that they have to make decisions in the absence of this. This unit would pay for itself in weeks by identifying flawed reasoning and stopping bad projects, gimmicks etc. Of course, this idea has no chance with those now at the top of Government and the Cabinet Office would crush such a unit as it would threaten the traditional hierarchy. One of the arguments I made in my essay was that we should try to discover useful and reliable benchmarks for what children of different abilities are really capable of learning and build on things like the landmark Study of Mathematically Precocious Youth. This obvious idea is anathema to the education policy world where there is almost no interest in things like SMPY and almost everybody supports the terrible idea that ‘all children must do the same exams’ (guaranteeing misery for some and boredom/time wasting for others). NB. Most rigorous large-scale educational RCTs are uninformative. Education research, like psychology, produces a lot of what Feynman called ‘cargo cult science’.

Since 2013, genomics has moved fast and understanding in the UK media has changed probably faster in five years than over the previous 35 years. As with the complexities of Brexit, journalists have caught up with reality much better than MPs. It’s still true that almost everything written by MPs about ‘social mobility’ is junk but you could see from the reviews of Plomin’s recent book, Blueprint, that many journalists have a much better sense of the science than they did in 2013. Rare good news, though much more progress is needed…

What’s happening now?

In 2013 it was already the case that the numbers on heritability derived from twin and adoption studies were being confirmed by direct inspection of DNA — therefore many of the arguments about twin/adoption studies were redundant — but this fact was hardly known.

I pointed out that the field would change fast. Both Plomin and another expert, Steve Hsu, made many predictions around 2010-13 some of which I referred to in my 2013 essay. Hsu is a physics professor who is also one of the world’s leading researchers on genomics.

Hsu predicted that very large samples of DNA would allow scientists over the next few years to start identifying the actual genes responsible for complex traits, such as diseases and intelligence, and make meaningful predictions about the fate of individuals. Hsu gave estimates of the sample sizes that would be needed. His 2011 talk contains some of these predictions and also provides a physicist’s explanation of ‘what is IQ measuring’. As he said at Google in 2011, the technology is ‘right on the cusp of being able to answer fundamental questions’ and ‘if in ten years we all meet again in this room there’s a very good chance that some of the key questions we’ll know the answers to’. His 2014 paper explains the science in detail. If you spend a little time looking at this, you will know more than 99% of high status economists gabbling on TV about ‘social mobility’ saying things like ‘doing well on IQ tests just proves you can do IQ tests’.

In 2013, the world of Westminster thought this all sounded like science fiction and many MP said I sounded like ‘a mad scientist’. Hsu’s predictions have come true and just five years later this is no longer ‘science fiction’. (Also NB. Hsu’s blog was one of the very few places where you would have seen discussion of CDOs and the 2008 financial crash long BEFORE it happened. I have followed his blog since ~2004 and this from 2005, two years before the crash started, was the first time I read about things like ‘synthetic CDOs’: ‘we have yet another ill-understood casino running, with trillions of dollars in play’. The quant-physics network had much better insight into the dynamics behind the 2008 Crash than high status mainstream economists like Larry Summers responsible for regulation.)

His group and others have applied machine learning to very large genetic samples and built predictors of complex traits. Complex traits like general intelligence and most diseases are ‘polygenic’ — they depend on many genes each of which contributes a little (unlike diseases caused by a single gene).

‘There are now ~20 disease conditions for which we can identify, e.g, the top 1% outliers with 5-10x normal risk for the disease. The papers reporting these results have almost all appeared within the last year or so.’

For example, the height predictor ‘captures nearly all of the predicted SNP heritability for this trait — actual heights of most individuals in validation tests are within a few cm of predicted heights.’ Height is similar to IQ — polygenic and similar heritability estimates.

These predictors have been validated with out-of-sample tests. They will get better and better as more and more data is gathered about more and more traits.

This enables us to take DNA from unborn embryos, do SNP genetic sequencing costing ~$50, and make useful predictions about the odds of the embryo being an outlier for diseases like atrial fibrillation, diabetes, breast cancer, or prostate cancer. NB. It is important that we do not need to sequence the whole genome to do this (see below). We will also be able to make predictions about outliers in cognitive abilities (the high and low ends). (My impression is that predicting Alzheimers is still hampered by a lack of data but this will improve as the data improves.)

There are many big implications. This will obviously revolutionise IVF. ~1 million IVF embryos per year are screened worldwide using less sophisticated tests. Instead of picking embryos at random, parents will start avoiding outliers for disease risks and cognitive problems. Rich people will fly to jurisdictions offering the best services.

Forensics is being revolutionised. First, DNA samples can be used to give useful physical descriptions of suspects because you can identify ethnic group, height, hair colour etc. Second, ‘cold cases’ are now routinely being solved because if a DNA sample exists, then the police can search for cousins of the perpetrator from public DNA databases, then use the cousins to identify suspects. Every month or so now in America a cold case murder is solved and many serial killers are being found using this approach — just this morning I saw what looks to be another example just announced, a murder of an 11 year-old in 1973. (Some companies are resisting this development but they will, I am very confident, be smashed in court and have their reputations trashed unless they change policy fast. The public will have no sympathy for those who stand in the way.)

Hsu recently attended a conference in the UK where he presented some of these ideas to UK policy makers. He wrote this blog about the great advantages the NHS has in developing this science.

‘The UK could become the world leader in genomic research by combining population-level genotyping with NHS health records… The US private health insurance system produces the wrong incentives for this kind of innovation: payers are reluctant to fund prevention or early treatment because it is unclear who will capture the ROI [return on investment]… The NHS has the right incentives, the necessary scale, and access to a deep pool of scientific talent. The UK can lead the world into a new era of precision genomic medicine.

‘NHS has already announced an out-of-pocket genotyping service which allows individuals to pay for their own genotyping and to contribute their health + DNA data to scientific research. In recent years NHS has built an impressive infrastructure for whole genome sequencing (cost ~$1k per individual) that is used to treat cancer and diagnose rare genetic diseases. The NHS subsidiary Genomics England recently announced they had reached the milestone of 100k whole genomes…

‘At the meeting, I emphasized the following:

1. NHS should offer both inexpensive (~$50) genotyping (sufficient for risk prediction of common diseases) along with the more expensive $1k whole genome sequencing. This will alleviate some of the negative reaction concerning a “two-tier” NHS, as many more people can afford the former.

2. An in-depth analysis of cost-benefit for population wide inexpensive genotyping would likely show a large net cost savings: the risk predictors are good enough already to guide early interventions that save lives and money. Recognition of this net benefit would allow NHS to replace the $50 out-of-pocket cost with free standard of care.’ (Emphasis added)

NB. In terms of the short-term practicalities it is important that whole genome sequencing costs ~$1,000 (and falling) but is not necessary: a version 1/20th of the cost, looking just at the most informative genetic variants, captures most of the predictive benefits. Some have incentives to distort this, such as companies like Illumina trying to sell expensive machines for whole genome sequencing, which can distort policy — let’s hope officials are watching carefully. These costs will, obviously, keep falling.

This connects to an interesting question… Why was the likely trend in genomics clear ~2010 to Plomin, Hsu and others but invisible to most? Obviously this involves lots of elements of expertise and feel for the field but also they identified FAVOURABLE EXPONENTIALS. Here is the fall in the cost of sequencing a genome compared to Moore’s Law, another famous exponential. The drop over ~18 years has been a factor of ~100,000. Hsu and Plomin could extrapolate that over a decade and figure out what would be possible when combined with other trends they could see. Researchers are already exploring what will be possible as this trend continues.

Identifying favourable exponentials is extremely powerful. Back in the early 1970s, the greatest team of computer science researchers ever assembled (PARC) looked out into the future and tried to imagine what could be possible if they brought that future back to the present and built it. They were trying to ‘compute in the future’. They created personal computing. (Chart by Alan Kay, one of the key researchers — he called it ‘the Gretzky game’ because of Gretzky’s famous line ‘I skate to where the puck is going to be, not where it has been.’ The computer is the Alto, the first personal computer that stunned Steve Jobs when he saw a demo. The sketch on the right is of children using a tablet device that Kay drew decades before the iPad was launched.)

Hopefully the NHS and Department for Health will play ‘the Gretzky game’, take expert advice from the likes of Plomin and Hsu and take this opportunity to make the UK a world leader in one of the most important frontiers in science.

We can imagine everybody in the UK being given valuable information about their health for free, truly preventive medicine where we target resources at those most at risk, and early (even in utero) identification of risks.
This would help bootstrap British science into a stronger position with greater resources to study things like CRISPR and the next phase of this revolution — editing genes to fix problems, where clinical trials are already showing success.
It would also give a boost to British AI/data science companies — the laws, rules on data etc should be carefully shaped to ensure that British companies (not Silicon Valley or China) capture most of the financial value (though everybody will gain from the basic science).
These gains would have positive feedback effects on each other, just as investment in basic AI/ML research will have positive feedback effects in many industries.
I have argued many times for the creation of a civilian UK ‘ARPA’ — a centre for high-risk-high-payoff research that has been consistently blocked in Whitehall (see HERE for an account of how ARPA-PARC created the internet and personal computing). This fits naturally with Britain seeking to lead in genomics/AI. Thinking about this is part of a desperately needed overall investigation into the productivity of the British economy and the ecosystem of universities, basic science, venture capital, startups, regulation (data, intellectual property etc) and so on.

There will also be many controversies and problems. The ability to edit genomes — and even edit the germline with ‘gene drives’ so all descendants have the same copy of the gene — is a Promethean power implying extreme responsibilities. On a mundane level, embracing new technology is clearly hard for the NHS with its data infrastructure. Almost everyone I speak to using the NHS has had similar problems that I have had — nightmares with GPs, hospitals, consultants et al being able to share data and records, things going missing, etc. The NHS will be crippled if it can’t fix this, but this is another reason to integrate data science as a core ‘utility’ for the NHS.

On a political note…

Few scientists and even fewer in the tech world are aware of the EU’s legal framework for regulating technology and the implications of the recent Charter of Fundamental Rights (the EU’s Charter, NOT the ECHR) which gives the Commission/ECJ the power to regulate any advanced technology, accelerate the EU’s irrelevance, and incentivise investors to invest outside the EU. In many areas, the EU regulates to help the worst sort of giant corporate looters defending their position against entrepreneurs. Post-Brexit Britain will be outside this jurisdiction and able to make faster and better decisions about regulating technology like genomics, AI and robotics. Prediction: just as Insiders now talk of how we ‘dodged a bullet’ in staying out of the euro, within ~10 years Insiders will talk about being outside the Charter/ECJ and the EU’s regulation of data/AI in similar terms (assuming Brexit happens and UK politicians even try to do something other than copy the EU’s rules).

China is pushing very hard on genomics/AI and regards such fields as crucial strategic ground for its struggle for supremacy with America. America has political and regulatory barriers holding it back on genomics that are much weaker here. Britain cannot stop the development of such science. Britain can choose to be a backwater, to ignore such things and listen to MPs telling fairy stories while the Chinese plough ahead, or it can try to lead. But there is no hiding from the truth and ‘for progress there is no cure’ (von Neumann). We will never be the most important manufacturing nation again but we could lead in crucial sub-fields of advanced technology. As ARPA-PARC showed, tiny investments can create entire new industries and trillions of dollars of value.

Sadly most politicians of Left and Right have little interest in science funding with tremendous implications for future growth, or the broader question of productivity and the ecosystem of science, entrepreneurs, universities, funding, regulation etc, and we desperately need institutions that incentivise politicians and senior officials to ‘play the Gretzky game’. The next few months will be dominated by Brexit and, hopefully, the replacement of the May/Hammond government. Those thinking about the post-May landscape and trying to figure out how to navigate in uncharted and turbulent waters should focus on one of the great lessons of politics that is weirdly hard for many MPs to internalise: the public rewards sustained focus on their priorities!

One of the lessons of the 2016 referendum (that many Conservative MPs remain desperate not to face) is the political significance of the NHS. The concept described above is one of those concepts in politics that maximises positive futures for the force that adopts it because it draws on multiple sources of strength. It combines, inter alia, all the political benefits of focus on the NHS, helping domestic technology companies, incentivising global investment, doing something that shows the world that Britain is (contra the May/Hammond outlook) open to science and high skilled immigrants, it is based on intrinsic advantages that Europe and America will find hard to overcome over a decade, it supplies (NB. MPs/spads) a never-ending string of heart-wrenching good news stories, and, very rarely in SW1, those pushing it would be seen as leading something of global importance. It will, therefore, obviously be rejected by a section of Conservative MPs who much prefer to live in a parallel world, who hate anything to do with science and who are ignorant about how new industries and wealth are really created. But for anybody trying to orient themselves to reality, connect themselves to sources of power, and thinking ‘how on earth could we clamber out of this horror show’, it is an obvious home run…

NB. It ought to go without saying that turning this idea into a political/government success requires focus on A) the NHS, health, science, NOT getting sidetracked into B) arguments about things like IQ and social mobility. Over time, the educated classes will continue to be dragged to more realistic views on (B) but this will be a complex process entangled with many hysterical episodes. (A) requires ruthless focus…

Please leave comments, fix errors below. I have not shown this blog in draft to Plomin or Hsu who obviously are not responsible for my errors.

Further reading

Plomin’s excellent new book, Blueprint. I would encourage journalists who want to understand this subject to speak to Plomin who works in London and is able to explain complex technical subjects to very confused arts graduates like me.

On the genetic architecture of intelligence and other quantitative traits, Hsu 2014.

Cf. this thread by researcher Paul Pharaoh on breast cancer.

Hsu blogs on genomics.

Some recent developments with AI/ML, links to papers.

On how ARPA-PARC created the modern computer industry and lessons for high-risk-high-payoff science research.

My 2013 essay.

September 11, 2018 by dominiccummings

#29 On the referendum & #4c on Expertise: On the ARPA/PARC ‘Dream Machine’, science funding, high performance, and UK national strategy

Post-Brexit Britain should be considering the intersection of 1) ARPA/PARC-style science research and ‘systems management’ for managing complex projects with 2) the reform of government institutions so that high performance teams — with different education/training (‘Tetlock processes’) and tools (including data science and visualisations of interactive models of complex systems) — can make ‘better decisions in a complex world’.

This paper examines the ARPA/PARC vision for computing and the nature of the two organisations. In the 1960s visionaries such as Joseph Licklider, Robert Taylor and Doug Engelbart developed a vision of networked interactive computing that provided the foundation not just for new technologies but for whole new industries. Licklider, Sutherland, Taylor et al provided a model (ARPA) for how science funding can work. Taylor provided a model (PARC) of how to manage a team of extremely talented people who turned a profound vision into reality. The original motivation for the vision of networked interactive computing was to help humans make good decisions in a complex world.

This story suggests ideas about how to make big improvements in the world with very few resources if they are structured right. From a British perspective it also suggests ideas about what post-Brexit Britain should do to help itself and the world and how it might be possible to force some sort of ‘phase transition’ on the rotten Westminster/Whitehall system.

For the PDF of the paper click HERE. Please correct errors with page numbers below. I will update it after feedback.

Further Reading

The Dream Machine.

Dealers of Lightning.

‘Sketchpad: A man-machine graphical communication system’, Ivan Sutherland 1963.

Oral history interview with Sutherland, head of ARPA’s IPTO division 1963-5.

This link has these seminal papers:

Man-Computer Symbiosis, Licklider (1960)
The computer as a communications device, Licklider & Taylor (1968)

Watch Alan Kay explain how to invent the future to YCombinator classes HERE and HERE.

HERE for Kay quotes from emails with Bret Victor.

HERE for Kay’s paper on PARC, The Power of the Context.

Kay’s Early History of Smalltalk.

HERE for a conversation between Kay and Engelbart.

Alan Kay’s tribute to Ted Nelson at “Intertwingled” Fest (an Alto using Smalltalk).

Personal Distributed Computing: The Alto and Ethernet Software1, Butler Lampson.

You and Your Research, Richard Hamming.

AI nationalism, essay by Ian Hogarth. This concerns implications of AI for geopolitics.

Drones go to work, Chris Anderson (one of the pioneers of commercial drones). This explains the economics of the drone industry.

Meditations on Moloch, Scott Alexander. This is an extremely good essay in general about deep problems with our institutions.

Intelligence Explosion Microeconomics, Yudkowsky.

Autonomous technology and the greater human good. Omohundro.

Can intelligence explode? Hutter.

For the issue of IQ, genetics and the distribution of talent (and much much more), cf. Steve Hsu’s brilliant blog.

Bret Victor.

Michael Nielsen.

For some pre-history on computers, cf. The birth of computational thinking (some of the history of computing devices before the Turing/von Neumann revolution) and The crisis of mathematical paradoxes, Gödel, Turing and the basis of computing (some of the history of ideas about mathematical foundations and logic such as the famous papers by Gödel and Turing in the 1930s)

Part I of this series of blogs is HERE.

Part II on the emergence of ‘systems management’, how George Mueller used it to put man on the moon, and a checklist of how successful management of complex projects is systematically different to how Whitehall works is HERE.

June 23, 2017 by dominiccummings

On the referendum #23, a year after victory: ‘a change of perspective is worth 80 IQ points’ & ‘how to capture the heavens’

‘Just like all British governments, they will act more or less in a hand to mouth way on the spur of the moment, but they will not think out and adopt a steady policy.’ Earl Cromer, 1896.

‘Fascinating that the same problems recur time after time, in almost every program, and that the management of the program, whether it happened to be government or industry, continues to avoid reality.’ George Mueller, pioneer of systems management and head of the Apollo programme to put man on the moon.

Traditional cultures, those that all humans lived in until quite recently and which still survive in pockets, don’t realise that they are living inside a particular perspective. They think that what they see is ‘reality’. It is, obviously, not their fault. It is not because they are stupid. It is a historical accident that they did/do not have access to mental models that help more accurate thinking about reality.

Westminster and the other political cultures dotted around the world are similar to these traditional cultures. They think they they are living in ‘reality’. The MPs and pundits get up, read each other, tweet at each other, give speeches, send press releases, have dinner, attack, fuck or fight each other, do the same tomorrow and think ‘this is reality’. Like traditional cultures they are wrong. They are living inside a particular perspective that enormously distorts reality.

They are trapped in thinking about today and their careers. They are trapped in thinking about incremental improvements. Almost nobody has ever been part of a high performance team responsible for a complex project. The speciality is a hot take to explain post facto what one cannot predict. They mostly don’t know what they don’t know. They don’t understand the decentralised information processing that allows markets to enable complex coordination. They don’t understand how scientific research works and they don’t value it. Their daily activity is massively constrained by the party and state bureaucracies that incentivise behaviour very different to what humanity needs to create long-term value. As Michael Nielsen (author of Reinventing Science) writes:

‘[M]uch of our intellectual elite who think they have “the solutions” have actually cut themselves off from understanding the basis for much of the most important human progress.’

Unlike traditional cultures, our modern political cultures don’t have the excuse of our hunter-gatherer ancestors. We could do better. But it is very very hard to escape the core imperatives that make big bureaucracies — public companies as well as state bureaucracies — so bad at learning. Warren Buffet explained decades ago how institutions actively fight against learning and fight to stay in a closed and vicious feedback loop:

‘My most surprising discovery: the overwhelming importance in business of an unseen force that we might call “the institutional imperative”. In business school, I was given no hint of the imperative’s existence and I did not intuitively understand it when I entered the business world. I thought then that decent, intelligence, and experienced managers would automatically make rational business decisions. But I learned the hard way that isn’t so. Instead rationality frequently wilts when the institutional imperative comes into play.

‘For example, 1) As if governed by Newton’s First Law, any institution will resist any change in its current direction. 2) … Corporate projects will materialise to soak up available funds. 3) Any business craving of the leader, however foolish, will quickly be supported by … his troops. 4) The behaviour of peer companies … will be mindlessly imitated.’

Almost nobody really learns from the world’s most successful investor about investing and how to run a successful business with good corporate governance. (People read what he writes but almost no investors choose to operate long-term like him, I think it is still true that not a single public company has copied his innovations with corporate governance like ‘no pay for company directors’, and governments have consistently rejected his and Munger’s advice about controlling the looting of public companies by management.) Almost nobody really learns how to do things better from the experience of dealing with this ‘institutional imperative’. We fail over and over again in the same way, trusting in institutions that are programmed to fail.

It is very very hard for humans to lift our eyes from today and to go out into the future and think about what could be done to bring the future back to the present. Like ants crawling around on the leaf, we political people only know our leaf.

Science has shown us a different way. Newton looked up from his leaf, looked far away from today, and created a new perspective — a new model of reality. It took an extreme genius to discover something like calculus but once discovered billions of people who are far from being geniuses can use this new perspective. Science advances by turning new ideas into standard ideas so each generation builds on the last.

Politics does the equivalent of constantly trying to reinvent children’s arithmetic and botching it. It does not build reliable foundations of knowledge. Archimedes is no longer cutting edge. Thucydides and Sun Tzu are still cutting edge. Even though Tetlock and others have shown how to start making similar progress with politics, our political cultures fiercely resist learning and fight ferociously to stay in closed and failing feedback loops.

In many ways our political culture has regressed as it has become more and more audio-visual and less and less literate. (Only 31% of US college graduates can read at a basic level. I’d guess it’s similar here. See end.) I’ve experimented with the way Jeff Bezos runs meetings at Amazon: i.e start the meeting with giving people a 5-10 page memo to read. Impossible in Westminster, nobody will sit and read like that! Officials have tried and failed for a year to get senior ministers to engage with complex written material about the EU negotiations. TV news dominates politics and is extremely low-bandwidth: it contains a few hundred words and rarely uses graphics properly. Evan Davis illustrates a comment about ‘going down the plughole’ with a picture of water down a plughole and Nick Robinson illustrates a comment about ‘the economy taking off’ with a picture of a plane taking off. The constant flow of bullshit from the likes of Robert Peston and Jon Snow dominates the medium because competition has been impossible until recently. BUT, although technology is making these charlatans less relevant (good) it also creates new problems and will not necessarily improve the culture.

Watching political news makes you dumber — switch it off and read books! If you work in it, either QUIT or go on holiday and come back determined to subvert it. How? Start with a previous blog which has some ideas, like tracking properly which people have a record of getting things right and wrong. Every editor I’ve suggested this to winces and says ‘impossible’. Insiders fear accountability and competition.

Today, the anniversary of the referendum, is a good day to forget the babble in the bubble and think about lessons from another project that changed the world, the famous ARPA/PARC team of the 1960s and 1970s.

ARPA/PARC and ‘capturing the heavens’: The best way to predict the future is to invent it

The panic over Sputnik brought many good things such as a huge increase in science funding. America also created the Advanced Research Projects Agency (ARPA, which later added ‘Defense’ and became DARPA). Its job was to fund high risk / high payoff technology development. In the 1960s and 1970s, a combination of unusual people and unusually wise funding from ARPA created a community that in turn invented the internet, or ‘the intergalactic network’ as Licklider originally called it, and the personal computer. One of the elements of this community was PARC, a research centre working for Xerox. As Bill Gates said, he and Steve Jobs essentially broke into PARC, stole their ideas, and created Microsoft and Apple.

The ARPA/PARC project has created over 35 TRILLION DOLLARS of value for society and counting.

The whole story is fascinating in many ways. I won’t go into the technological aspects. I just want to say something about the process.

What does a process that produces ideas that change the world look like?

One of the central figures was Alan Kay. One of the most interesting things about the project is that not only has almost nobody tried to repeat this sort of research but the business world has even gone out of its way to spread mis-information about it because it was seen as so threatening to business-as-usual.

I will sketch a few lessons from one of Kay’s pieces but I urge you to read the whole thing.

‘This is what I call “The power of the context” or “Point of view is worth 80 IQ points”. Science and engineering themselves are famous examples, but there are even more striking processes within these large disciplines. One of the greatest works of art from that fruitful period of ARPA/PARC research in the 60s and 70s was the almost invisible context and community that catalysed so many researchers to be incredibly better dreamers and thinkers. That it was a great work of art is confirmed by the world-changing results that appeared so swiftly, and almost easily. That it was almost invisible, in spite of its tremendous success, is revealed by the disheartening fact today that, as far as I’m aware, no governments and no companies do edge-of-the-art research using these principles.’

‘[W]hen I think of ARPA/PARC, I think first of good will, even before brilliant people… Good will and great interest in graduate students as “world-class researchers who didn’t have PhDs yet” was the general rule across the ARPA community.

‘[I]t is no exaggeration to say that ARPA/PARC had “visions rather than goals” and “funded people, not projects”. The vision was “interactive computing as a complementary intellectual partner for people pervasively networked world-wide”. By not trying to derive specific goals from this at the funding side, ARPA/PARC was able to fund rather different and sometimes opposing points of view.

‘The pursuit of Art always sets off plans and goals, but plans and goals don’t always give rise to Art. If “visions not goals” opens the heavens, it is important to find artistic people to conceive the projects.

‘Thus the “people not projects” principle was the other cornerstone of ARPA/PARC’s success. Because of the normal distribution of talents and drive in the world, a depressingly large percentage of organizational processes have been designed to deal with people of moderate ability, motivation, and trust. We can easily see this in most walks of life today, but also astoundingly in corporate, university, and government research. ARPA/PARC had two main thresholds: self-motivation and ability. They cultivated people who “had to do, paid or not” and “whose doings were likely to be highly interesting and important”. Thus conventional oversight was not only not needed, but was not really possible. “Peer review” wasn’t easily done even with actual peers. The situation was “out of control”, yet extremely productive and not at all anarchic.

‘”Out of control” because artists have to do what they have to do. “Extremely productive” because a great vision acts like a magnetic field from the future that aligns all the little iron particle artists to point to “North” without having to see it. They then make their own paths to the future. Xerox often was shocked at the PARC process and declared it out of control, but they didn’t understand that the context was so powerful and compelling and the good will so abundant, that the artists worked happily at their version of the vision. The results were an enormous collection of breakthroughs.

‘Our game is more like art and sports than accounting, in that high percentages of failure are quite OK as long as enough larger processes succeed… [I]n most processes today — and sadly in most important areas of technology research — the administrators seem to prefer to be completely in control of mediocre processes to being “out of control” with superproductive processes. They are trying to “avoid failure” rather than trying to “capture the heavens”.

‘All of these principles came together a little over 30 years ago to eventually give rise to 1500 Altos, Ethernetworked to: each other, Laserprinters, file servers and the ARPAnet, distributed to many kinds of end-users to be heavily used in real situations. This anticipated the commercial availability of this genre by 10-15 years. The best way to predict the future is to invent it.

‘[W]e should realize that many of the most important ARPA/PARC ideas haven’t yet been adopted by the mainstream. For example, it is amazing to me that most of Doug Engelbart’s big ideas about “augmenting the collective intelligence of groups working together” have still not taken hold in commercial systems. What looked like a real revolution twice for end-users, first with spreadsheets and then with Hypercard, didn’t evolve into what will be commonplace 25 years from now, even though it could have. Most things done by most people today are still “automating paper, records and film” rather than “simulating the future”. More discouraging is that most computing is still aimed at adults in business, and that aimed at nonbusiness and children is mainly for entertainment and apes the worst of television. We see almost no use in education of what is great and unique about computer modeling and computer thinking. These are not technological problems but a lack of perspective. Must we hope that the open-source software movements will put things right?

‘The ARPA/PARC history shows that a combination of vision, a modest amount of funding, with a felicitous context and process can almost magically give rise to new technologies that not only amplify civilization, but also produce tremendous wealth for the society. Isn’t it time to do this again by Reason, even with no Cold War to use as an excuse? How about helping children of the world grow up to think much better than most adults do today? This would truly create “The Power of the Context”.’

Note how this story runs contrary to how free market think tanks and pundits describe technological development. The impetus for most of this development came from government funding, not markets.

Also note that every attempt since the 1950s to copy ARPA and JASON (the semi-classified group that partly gave ARPA its direction) in the UK has been blocked by Whitehall. The latest attempt was in 2014 when the Cabinet Office swatted aside the idea. Hilariously its argument was ‘DARPA has had a lot of failures’ thus demonstrating extreme ignorance about the basic idea — the whole point is you must have failures and if you don’t have lots of failures then you are failing!

People later claimed that while PARC may have changed the world it never made any money for XEROX. This is ‘absolute bullshit’ (Kay). It made billions from the laser printer alone and overall Xerox made 250 times what they invested in PARC before they went bust. In 1983 they fired Bob Taylor, the manager of PARC and the guy who made it all happen.

‘They hated [Taylor] for the very reason that most companies hate people who are doing something different, because it makes middle and upper management extremely uncomfortable. The last thing they want to do is make trillions, they want to make a few millions in a comfortable way’ (Kay).

Someone finally listened to Kay recently. ‘YC Research’, the research arm of the world’s most successful (by far) technology incubator, is starting to fund people in this way. I am not aware of any similar UK projects though I know that a small network of people are thinking again about how something like this could be done here. If you can help them, take a risk and help them! Someone talk to science minister Jo Johnson but be prepared for the Treasury’s usual ignorant bullshit — ‘what are we buying for our money, and how can we put in place appropriate oversight and compliance?’ they will say!

Why is this relevant to the referendum?

As we ponder the future of the UK-EU relationship shaped amid the farce of modern Whitehall, we should think hard about the ARPA/PARC example: how a small group of people can make a huge breakthrough with little money but the right structure, the right ways of thinking, and the right motives.

Those of us outside the political system thinking ‘we know we can do so much better than this but HOW can we break through the bullshit?’ need to change our perspective and gain 80 IQ points.

This real picture is a metaphor for the political culture: ad hoc solutions that are either bad or don’t scale.

Screenshot 2017-06-14 16.58.14.png

ARPA said ‘Let’s get rid of all the wires’. How do we ‘get rid of all the wires’ and build something different that breaks open the closed and failing political cultures? Winning the referendum was just one step that helps clear away dead wood but we now need to build new things.

The ARPA vision that aligned the artists ‘like little iron filings’ was:

‘Computers are destined to become interactive intellectual amplifiers for everyone in the world universally networked worldwide’ (Licklider).

We need a motivating vision aimed not at tomorrow but at changing the basic wiring of the whole system, a vision that can align ‘the little iron filings’, and then start building for the long-term.

I will go into what I think this vision could be and how to do it another day. I think it is possible to create something new that could scale very fast and enable us to do politics and government extremely differently, as different to today as the internet and PC were to the post-war mainframes. This would enable us to build huge long-term value for humanity in a relatively short time (less than 20 years). To create it we need a process as well suited to the goal as the ARPA/PARC project was and incorporating many of its principles.

We must try to escape the current system with its periodic meltdowns and international crises. These crises move 500-1,000 times faster than that of summer 1914. Our destructive potential is at least a million-fold greater than it was in 1914. Yet we have essentially the same hierarchical command-and-control decision-making systems in place now that could not even cope with 1914 technology and pace. We have dodged nuclear wars by fluke because individuals made snap judgements in minutes. Nobody who reads the history of these episodes can think that this is viable long-term, and we will soon have another wave of innovation to worry about with autonomous robots and genetic engineering. Technology gives us no option but to try to overcome evolved instincts like destroying out-group competitors.

In a previous blog I outlined how the ‘systems management’ approach used to put man on the moon provides principles for a new approach.

Ironically, one of the very few people in politics who understood the sort of thinking needed was … Jean Monnet, the architect of the EEC/EU! Monnet understood how to step back from today and build institutions. He worked operationally to prepare the future:

‘If there was stiff competition round the centres of power, there was practically none in the area where I wanted to work – preparing the future.’

Monnet was one of the few people in modern politics who really deserve the label ‘genius’. The story of how he wangled the creation of his institutions through the daily chaos of post-war politics is a lesson to anybody who wants to get things done.

But the institutions he created are in many ways the opposite of what the world needs. Their core operating principle is perpetual centralisation of power in the hands of an all powerful bureaucracy (Commission) and Court (ECJ). Nothing that works well in the world works like this!

Thanks to the prominence of Farage the dominant story among educated people is that those who got us out of the EU want to take us back to the pre-1914 era of hostile competing nation states. Nothing could be further from the truth. The key people in Vote Leave wanted and want not just what is best for Britain but what is best for all humanity. We want more international cooperation, not less. The problem with the EU is not that it is about international cooperation but that it is so bad at it and actually undermines it.

Britain leaving forces those with power to ask: how can all European countries trade freely and cooperate without subscribing to Monnet’s bureaucratic centralism? This will help Europe in the long-term. To those who favour this bureaucratic centralism and uniformity, reflect on the different trajectories of Europe and China post-Renaissance. In Europe, regulatory competition (so Columbus could chase funding in Spain after rejection in Portugal) brought immense gains. In China, centrally directed uniformity led to centuries of stagnation. America’s model of competitive federalism created by the founding fathers has been a far more effective engine of civilisation, growth, and new knowledge than the Monnet-Delors Single Market model.

If Britain were to focus on science and education with huge resources and a new-found seriousness, then this regulatory diversity would help not just Britain but all Europe and the global science community. We could make Britain the best place in the world to be for those who can invent the future. Like Alan Kay and his colleagues, we could create whole new industries. We could call Jeff Bezos and say, ‘Ok Jeff, you want a permanent international manned moon base, let’s talk about who does what, but not with that old rocket technology.’ No country on earth funds science as well as we already know how it could be done — that is something for Britain to do that would create real long-term value for humanity, instead of the ‘punching above our weight’ and ‘special relationship’ bullshit that passes for strategy in London. How we change our domestic institutions is within our power and will have much much greater influence on our long-term future than whatever deal is botched together with Brussels. We have the resources. But can we break the system open? If we don’t then we’re likely to go down the path we were already going down inside the EU, like the deluded Norma Desmond in Sunset Boulevard claiming ‘I am big, it’s the pictures that got small.’

Vote Leave and ‘good will’

Although Vote Leave was enmeshed in a sort of collective lunacy we managed, barely, to fend it off from the inner working of the campaign. Much of my job (sadly) was just trying to maintain a cordon around the core team so they could deliver the campaign with as little disruption as possible. We managed this because among the core people we had great good will. The stories of the campaign focus on the lunacy, but the people who really made it work remember the goodwill.

A year ago tonight I was sitting alone in a room thinking ‘we’ve won, now…’ when the walls started rumbling. At first I couldn’t make it out then, as Tim Shipman tells the story in his definitive book on the campaign, I heard ‘Dom, Dom, DOM’ — the team had declared victory. I went next door…

Thanks to everybody who sacrificed something. As I said that night and as I said in my long blog on the campaign, I’ve been given credit I don’t deserve and which rightly belongs to others — Cleo Watson, Richard ‘Ricardo’ Howell, Brother Starkie, Oliver Lewis, Lord Suart et al. Now, let’s think about what should come next…

Watch Alan Kay explain how to invent the future HERE and HERE.

Ps. Kay also points out that the real computer revolution won’t happen until people fulfil the original vision of enabling children to use this powerful way of thinking:

‘The real printing revolution was a qualitative change in thought and argument that lagged the hardware inventions by almost two centuries. The special quality of computers is their ability to rapidly simulate arbitrary descriptions, and the real computer revolution won’t happen until children can learn to read, write, argue and think in this powerful new way. We should all try to make this happen much sooner than 200 or even 20 more years!’

Almost nobody in education policy is aware of the educational context for the ARPA/PARC project which also speaks volumes about the abysmal field of ‘education research/policy’.

* Re the US literacy statistic, cf. A First Look at the Literacy of America’s Adults in the 21st Century, National Assessment of Adult Literacy, U.S. Dept of Education, NCES 2006.

January 23, 2017 by dominiccummings

Specialist maths schools – some facts

The news reports that the Government will try to promote more ‘specialist maths schools’ similar to the King’s College and Exeter schools.

The idea for these schools came when I read about Perelman, the Russian mathematician who in 2003 suddenly posted on arXiv a solution to the Poincaré Conjecture, one of the most important open problems in mathematics. Perelman went to one of the famous Russian specialist maths schools that were set up by one of the most important mathematicians of the 20th Century, Kolmogorov.

I thought – a) given the fall in standards in maths and physics because of the corruption of the curriculum and exams started by the Tories and continued by Blair, b) the way in which proper teaching of advanced maths and physics is increasingly limited to a tiny number of schools many of which are private, and c) the huge gains for our civilisation from the proper education of the unusual small fraction of children who are very gifted in maths and physics, why not try to set up something similar.

Gove’s team therefore pushed the idea through the DfE. Dean Acheson, US Secretary of State, said, ‘I have long been the advocate of the heretical view that, whatever political scientists might say, policy in this country is made, as often as not, by the necessity of finding something to say for an important figure committed to speak without a prearranged subject.’ This is quite true (it also explains a lot about how Monnet created the ECSC and EEC). Many things that the Gove team did relied on this. We prepared the maths school idea and waited our chance. Sure enough, the word came through from Downing Street – ‘the Chancellor needs an announcement for the Budget, something on science’. We gave them this, he announced it, and bureaucratic resistance was largely broken.

If interested in some details, then look at pages 75ff of my 2013 essay for useful links. Other countries have successfully pursued similar ideas, including France for a couple of centuries and Singapore recently.

One of the interesting aspects of trying to get them going was the way in which a) the official ‘education world’ loathed not just the idea but also the idea about the idea – they hated thinking about ‘very high ability’ and specialist teaching; b) when I visited maths departments they all knew about these schools because university departments in the West employ a large number of people who were educated in these schools but they all said ‘we can’t help you with this even though it’s a good idea because we’d be killed politically for supporting “elitism” [fingers doing quote marks in the air], good luck I hope you succeed but we’ll probably attack you on the record.’ They mostly did.

The only reason why the King’s project happened is because Alison Wolf made it a personal crusade to defeat all the entropic forces that elsewhere killed the idea (with the exception of Exeter). Without her it would have had no chance. I found few equivalents elsewhere and where I did they were smashed by their VCs.

A few points…

1) Kolmogorov-type schools are a particular thing. They undoubtedly work. But they are aimed at a small fraction of the population. Given what the products of these schools go on to contribute to human civilisation they are extraordinarily cheap. They are also often a refuge for children who have a terrible time in normal schools. If they were as different to normal kids in a negative sense as they are in a positive sense then there would be no argument about whether they have ‘special needs’.

2) Don’t believe the rubbish in things like Gladwell’s book about maths and IQ. There is now very good data on this particularly in the form of the unprecedented SMPY multi-decade study. Even a short crude test at 11-13 gives very good predictions of who is likely to be very good at maths/physics. Further there is a strong correlation between performance at the top 1% / 1:1,000 / 1:10,000 level and many outcomes in later life such as getting a doctorate, a patent, writing a paper in Science and Nature, high income, health etc. The education world has been ~100% committed to rejecting the science of this subject though this resistance is cracking.

This chart shows the SMPY results (maths ability at 13) for the top 1% of maths ability broken down into quartiles 1-4: the top quartile of the top 1% clearly outperforms viz tenure, publication and patent rates.

screenshot-2017-01-23-11-53-01

3) The arguments for Kolmogorov schools do not translate to arguments for selection in general – ie. they are specific to the subject. It is the structure of maths and the nature of the brain that allows very young people to make rapid progress. These features are not there for English, history and so on. I am not wading into the grammar school argument on either side – I am just pointing out a fact that the arguments for such maths schools are clear but should not be confused with the wider arguments over selection that involve complicated trade-offs. People on both sides of the grammar debate should, if rational, be able to support this policy.

4) These schools are not ‘maths hot houses’. Kolmogorov took the children to see Shakespeare plays, music and so on. It is important to note that teaching English and other subjects is normal – other than you are obviously dealing with unusually bright children. If these children are not in specialist schools, then the solution is a) specialist maths teaching (including help from university-level mathematicians) and b) keeping other aspects of their education normal. Arguably the greatest mathematician in the world, Terry Tao, had wise parents and enjoyed this combination. So it is of course possible to educate such children without specialist schools but the risks are higher that either parents or teachers cock it up.

5) Extended wisely across Britain they could have big benefits not just for those children and elite universities but they could also play an important role in raising standards generally in their area by being a focus for high quality empirical training. One of the worst aspects of the education world is the combination of low quality training and resistance to experiments. This has improved since the Gove reforms but the world of education research continues to be dominated by what Feynman called ‘cargo cult science’.

6) We also worked with a physicist at Cambridge, Professor Mark Warner, to set up a project to improve the quality of 6th form physics. This project has been a great success thanks to his extraordinary efforts and the enthusiasm of young Cambridge physicists. Thousands of questions have been answered on their online platform from many schools. This project gives kids the chance to learn proper problem solving – that is the core skill that the corruption of the exam system has devalued and increasingly pushed into a ghetto of of private education. Needless to say the education world also was hostile to this project. Anything that suggests that we can do much much better is generally hated by all elements of the bureaucracy, including even elements such as the Institute of Physics that supposedly exist to support exactly this. A handful of officials helped us push through projects like this and of course most of them have since left Whitehall in disgust, thus does the system protect itself against improvement while promoting the worst people.

7) This idea connects to a broader idea. Kids anywhere in the state system should be able to apply some form of voucher to buy high quality advanced teaching from outside their school for a wide range of serious subjects from music to physics.

8) One of the few projects that the Gove team tried and failed to get going was to break the grip of GCSEs on state schools (Cameron sided with Clegg and although we cheated a huge amount through the system we hit a wall on this project). It is extremely wasteful for the system and boring for many children for them to be focused on existing exams that do not develop serious skills. Maths already has the STEP paper. There should be equivalents in other subjects at age 16. There is nothing that the bureaucracy will fight harder than this and it will probably only happen if excellent private schools decide to do it themselves and political pressure then forces the Government to allow state schools to do them.

Any journalists who want to speak to people about this should try to speak to Dan Abramson (the head of the King’s school), Alison Wolf, or Alexander Borovik (a mathematician at Manchester University who attended one of these schools in Russia).

It is hopeful that No10 is backing this idea but of course they will face determined resistance. It will only happen if at least one special adviser in the DfE makes it a priority and has the support of No10 so officials know they might as well fight about other things…

This is the most interesting comment probably ever left on this blog and it is much more interesting than the blog itself so I have copied it below. It is made by Borovik, mentioned above, who attended one of these schools in Russia and knows many who attended similar…

‘There is one more aspect of (high level) selective specialist mathematics education that is unknown outside the professional community of mathematicians.

I am not an expert on “gifted and talented” education. On the other hand, I spent my life surrounded by people who got exclusive academically selective education in mathematics and physics, whether it was in the Lavrentiev School in Siberia, or Lycée Louis-le-Grand in Paris, or Fazekas in Budapest, or Galatasaray Lisesi (aka Lycée de Galatasaray) in Istanbul — the list can be continued.

The schools have nothing in common, with the exception of being unique, each one in its own way.

I had research collaborators and co-authors from each of the schools that Ilisted above. Why was it so easy for us to find a common language?

Well, the explanation can be found in the words of Stanislas Dehaene, the leading researcher of neurophysiology of mathematical thinking:

“We have to do mathematics using the brain which evolved 30 000 years ago for survival in the African savanna.”

In humans, the speed of totally controlled mental operations is at most 16 bits per second. Standard school maths education trains children to work at that speed.

The visual processing module in the brain crunches 10,000,000,000 bits per second.

I offer a simple thought experiment to the readers who have some knowledge of school level geometry.

Imagine that you are given a triangle; mentally rotate it about the longest side. What is the resulting solid of revolution? Describe it. And then try to reflect: where the answer came from?

The best kept secret of mathematics: it is done by subconsciousness.

Mathematics is a language for communication with subconsciousness.

There are four conversants in a conversation between two mathematicians: two people and two their “inner”, “intuitive” brains.

When mathematicians talk about mathematics face-to-face, they
* frequently use language which is very fluid and informal;
* improvised on the spot;
* includes pauses (for a lay observer—very strange and awkwardly timed) for absorbtion of thought;
* has almost nothing in common with standardised mathematics “in print”.

Mathematician is trying to convey a message from his “intuitive brain” directly to his colleagues’ “intuitive brain”.

Alumni of high level specialist mathematics schools are “birds of feather” because they have been initiated into this mode of communication at the most susceptible age, as teenagers, at the peak of intensity of their socialisation / shaping group identity stream of self-actualisation.

In that aspect, mathematics is not much different from arts. Part of the skills that children get in music schools, acting schools, dancing school, and art schools is the ability to talk about music, acting, dancing, art with intuitive, subconscious parts of their minds — and with their peers, in a secret language which is not recognised (and perhaps not even registered) by uninitiated.

However, specialist mathematics schools form a continuous spectrum from just ordinary, with standard syllabus, but good schools with good maths teachers to the likes of Louis-le-Grand and Fazekas. My comments apply mostly to the top end of the spectrum. I have a feeling that the Green Paper is less ambitious and does not call for setting up mathematics boarding schools using Chetham’s School of Music as a model. However, middle tier maths school could also be very useful — if they are set up with realistic expectations, properly supported, and have strong connections with universities.’

A Borovik

November 24, 2016 by dominiccummings

A review of Tetlock’s ‘Superforecasting’ (2015)

Spectator Review, October 2015

Forecasts have been fundamental to mankind’s journey from a small tribe on the African savannah to a species that can sling objects across the solar system with extreme precision. In physics, we developed models that are extremely accurate across vastly different scales from the sub-atomic to the visible universe. In politics we bumbled along making the same sort of errors repeatedly.

Until the 20th century, medicine was more like politics than physics. Its forecasts were often bogus and its record grim. In the 1920s, statisticians invaded medicine and devised randomised controlled trials. Doctors, hating the challenge to their prestige, resisted but lost. Evidence-based medicine became routine and saved millions of lives. A similar battle has begun in politics. The result could be more dramatic.

In 1984, Philip Tetlock, a political scientist, did something new – he considered how to assess the accuracy of political forecasts in a scientific way. In politics, it is usually impossible to make progress because forecasts are so vague as to be useless. People don’t do what is normal in physics – use precise measurements – so nobody can make a scientific judgement in the future about whether, say, George Osborne or Ed Balls is ‘right’.

Tetlock established a precise measurement system to track political forecasts made by experts to gauge their accuracy. After twenty years he published the results. The average expert was no more accurate than the proverbial dart-throwing chimp on many questions. Few could beat simple rules like ‘always predict no change’.

Tetlock also found that a small fraction did significantly better than average. Why? The worst forecasters were those with great self-confidence who stuck to their big ideas (‘hedgehogs’). They were often worse than the dart-throwing chimp. The most successful were those who were cautious, humble, numerate, actively open-minded, looked at many points of view, and updated their predictions (‘foxes’). TV programmes recruit hedgehogs so the more likely an expert was to appear on TV, the less accurate he was. Tetlock dug further: how much could training improve performance?

In the aftermath of disastrous intelligence forecasts about Iraq’s WMD, an obscure American intelligence agency explored Tetlock’s ideas. They created an online tournament in which thousands of volunteers would make many predictions. They framed specific questions with specific timescales, required forecasts using numerical probability scales, and created a robust statistical scoring system. Tetlock created a team – the Good Judgement Project (GJP) – to compete in the tournament.

The results? GJP beat the official control group by 60% in year 1 and by 78% in year 2. GJP beat all competitors so easily the tournament was shut down early.

How did they do it? GJP recruited a team of hundreds, aggregated the forecasts, gave extra weight to the most successful, and applied a simple statistical rule. A few hundred ordinary people and simple maths outperformed a bureaucracy costing tens of billions.

Tetlock also found ‘superforecasters’. These individuals outperformed others by 60% and also, despite a lack of subject-specific knowledge, comfortably beat the average of professional intelligence analysts using classified data (the size of the difference is secret but was significant).

Superforecasters explores the nature of these unusual individuals. Crucially, Tetlock has shown that training programmes can yield big improvements. Even a mere sixty minute tutorial on some basics of statistics improves performance by 10%. The cost:benefit ratio of training forecasting is huge.

It would be natural to assume that this work must be the focus of intense thought and funding in Whitehall. Wrong. Whitehall has ignored this entire research programme. Whitehall experiences repeated predictable failure while simultaneously seeing no alternative to their antiquated methods, like 1950s doctors resisting randomised control trials that threaten prestige.

This may change. Early adopters could use Tetlock’s techniques to improve performance. Success sparks mimicry. Everybody reading this could do one simple thing: ask their MP whether they have done Tetlock’s training programme. A website could track candidates’ answers before the next election. News programmes could require quantifiable predictions from their pundits and record their accuracy.

We now expect that every medicine is tested before it is used. We ought to expect that everybody who aspires to high office is trained to understand why they are so likely to make mistakes forecasting complex events. The cost is tiny. The potential benefits run to trillions of pounds and millions of lives. Politics is harder than physics but Tetlock has shown that it doesn’t have to be like astrology.

Superforecasting: the art and science of prediction, by Philip Tetlock (Random House, 352 pages)

Ps. When I wrote this (August/September 2015) I was assembling the team to fight the referendum. One of the things I did was hire people with very high quantitative skills, as I describe in this blog HERE.

November 13, 2014 by dominiccummings

Low quality journalism from Prospect on the sensitive subject of genes and IQ

Prospect has published a big piece on genes that also goes into the controversy surrounding my essay last year (non-paywall version HERE). The author is someone called Philip Ball.

It is not as misleading as much media coverage was. After all, Polly Toynbee wrote ‘wealth is more heritable than genes’ and the Guardian put it in the headline even though it is pure gobbledegook (the word ‘heritable’ has a technical meaning that renders Polly’s argument meaningless). Even a genuine expert, Professor Steve Jones, made the unfortunate mistake of believing what he read in the media and had to retract comments.

However, the Prospect piece is substantially misleading. It is unprofessional journalism, riddled with errors, on a subject that senior people at Prospect ought to take seriously, given the proven potential for such articles to cause trouble on such a sensitive subject.

As an actual expert on this field (@StuartJRitchie) tweeted after reading it, it’s ‘one of those articles proving that a small amount of genetics knowledge is dangerous’.

A few examples regarding me…

The author writes:

‘A real problem with Cummings’ comments was not that they attribute some of our characteristics to our genes but that they gave the impression of genetics as a fait accompli – if you don’t have the right genes, nothing much will help. This goes against the now accepted consensus that genes exert their effects in interaction with their environment. While IQ is often quoted as being about 50% inheritable, the association with genetics much weaker in children from poor backgrounds: good genes won’t help you much if the circumstances are against it.’

In fact, I explicitly argued against the ‘impression’ he asserts I gave and discuss the lower heritability numbers for poorer children. The implication that I oppose the view that ‘genes exert their effects in interaction with their environment’ is simply ludicrous.

He writes, ‘But if he [Cummings] were to look a little more deeply into what it has already discovered (and sometimes un-discovered again), he might wonder what it offers education policy.’ He then discusses the issue of ‘false positives’ – which I discussed.

He then writes, ‘So it’s not clear, pace Cummings, what this kind of study adds to the conventional view that some kids are more academically able than others. It’s not clear why it should alter the goal of helping all children achieve what they can, to the best of their ability.’

I not only did not make the argument he implies I did – i.e. we should ‘alter the goal of helping all children…’ – I actually explicitly argued that this would be the WRONG conclusion!

He also makes errors in the bits that do not discuss me but I’ll leave experts to answer those.

It is hard to decide whether the author is being dishonest or incompetent. I strongly suspect that like many other journalists, Ball did not read my essay but only other media coverage of it.

Either way, Prospect should do a much better job on such sensitive subjects if it wants to brand itself as ‘the leading magazine of ideas’.

If Ball or anybody else at Prospect wants to understand the errors regarding my essay in detail, then look at THIS LINK between pages 49-51, 72-74, 194-203.

Prospect should insist that the author removes the factually wrong assertions that Ball makes regarding my essay as they will otherwise ripple on through other pieces, as previously wrong pieces have rippled into Ball’s.

For any hacks reading this, please note – the world’s foremost expert on the subject of IQ/genes is Professor Robert Plomin and he has stated on the record that in my essay I summarised the state of our scientific knowledge in this field accurately. This knowledge is uncomfortable for many but that is all the more reason for publications such as Prospect to tread carefully – my advice to them would be ‘do not publish journalism on this subject without having it checked by a genuine expert’.

If you want to understand the cutting edge of thinking on this subject, then do not read my essay but read this recent paper by Steve Hsu, a physics professor who is also working with BGI on large scale scans of the genome to discover the genes which account for a significant fraction of the total population variation in g/IQ: ‘On the genetic architecture of intelligence and other quantitative traits‘. Hsu is continuing the long tradition of mathematicians and physicists invading other spheres and bringing advanced mathematical tools that take time to percolate (cf. his recent paper ‘Applying compressed sensing to genome-wide association studies‘ which applies very advanced maths used in physics to genetic studies).

Or call Plomin, he’s at King’s. Do not trust Prospect on such issues unless there is evidence of a more scientific attitude from them.

UPDATE. Ball has replied to this blog HERE. His blog makes clear that he actually decided to go through my essay after reading this blog, not before writing his piece. He wriggles around a semi-admission of a cockup with ‘The point here is not that Cummings doesn’t want all children to achieve what they can – I genuinely believe he does want that’ – why did you imply the opposite then? – instead of simply apologising for his wrong claim.

He also makes a reference to ‘Gove’s expenses’ – something that has zero to do with the subject in any way. It is generally fruitless to comment on people’s motives so I won’t speculate on why he chucks this in.

Overall, he doesn’t quite admit he boobed in claiming I made various arguments when I actually said the opposite. He ignores his errors or obfuscates and introduces new errors.

For example, he quotes a paper ‘by a professor of education’ (NB. Ball, this does not make it sound more authoritative) saying, ‘Social class remains the strongest predictor of educational achievement in the UK.’

Ball says this view is ‘fairly well established’. There is no doubt that this represents the conventional wisdom of MPs, civil servants, journalists, and academics in fields such as sociology and education.

It is not, however, true.

‘General cognitive ability (g) predicts key social outcomes such as educational and occupational levels far better than any other trait.’ This is from the gold standard textbook, Behavioral Genetics by Robert Plomin (p. 186). This is not exactly surprising in itself, but it is an important point given much elite debate is based on assuming the opposite.

Ball – to see the point, ask yourself this… Look at a standard family, husband / wife / two kids. One child goes on to be a professor of physics, his brother goes on to dig ditches. They have the same social class. Why the difference? Social class is useless in explaining this because the kids share social class. This does not mean that ‘class is irrelevant’ but that its predictive power is limited, and g/IQ has stronger predictive power. (NB. everything about heritability involves population statistics, not individuals – to put the point crudely, if you smash an individual over the head with a bat, the effect of genes on performance will fall to zero, hence the unsurprising but important finding that heritability estimates are lower for very deprived children.) There is a vast literature on all this and my essay has a lot of references / links. E.g. this recent Plomin paper HERE.

One of the problems in discussions of this subject is that journalists are programmed to quote sociologists and ‘professors of education’ who often have no understanding of genetics and, often, none of the mathematical training required to understand the technical concepts.

So some further free advice to Ball and his editors at Prospect – do not rely on sociologists and ‘professors of education’ when it comes to issues like ‘social mobility’ – in my experience they are almost never even aware of the established findings in genetics. As Plomin says, ‘There is a wide gap between what laypeople (including scientists in other fields) believe and what experts believe’ (p.187).

Ball then quotes from my essay: ‘Raising school performance of poorer children is an inherently worthwhile thing to try to do but it would not necessarily lower parent-offspring correlations (nor change heritability estimates). When people look at the gaps between rich and poor children that already exist at a young age (3-5), they almost universally assume that these differences are because of environmental reasons (‘privileges of wealth’) and ignore genetics.’

And Ball comments: ‘So what is Cummings implying here, if not that the differences in school performance between rich and poor children might be, at least in large part, genetic? That the poor are, in other words, a genetic underclass as far as academic achievement is concerned – that they are poor presumably because they are not very bright?… Cummings does not say that we should give up on the poor simply because they are genetically disadvantaged in the IQ stakes – but comments like the one above surely give a message that neither better education nor less social disadvantage will make an awful lot of difference to academic outcomes.’

Ah, so after claiming that I said X when I actually said ‘not X’, Ball clutches at the the old ‘you believe in a genetic underclass’ gag! He still has not read what I wrote about the ability of schools to improve radically and he misses the point about what the first part of my quote means. I was making the point that Plomin made to the Commons Education Committee (though I do not think they understood what he meant) – if you improve the education system such that poorer children get better schooling (as we should do), you are reducing environmental reasons for the variation in performance, and therefore if you imagine a perfect school system (other things being equal) heritability would rise because if you remove environmental factors then the remaining genetic factors would grow in importance. This is a counterintuitive conclusion and the first time Plomin explained it to me I had to ask a few dumb questions to see whether I understood the point properly. I can see why Ball would miss the point and I should have expressed it better by simply quoting Plomin.

On the issue of the search for the genes accountable for the population variation in g/IQ, Ball seems unaware of various aspects of current scholarship, e.g. the search for genes associated with height. If he reads the Hsu paper linked above, he will see what I mean.

This tedious exchange is even more of a waste of time than usual because the real science has become so clear. As Plomin says, the GWAS are the ‘beginning of the end’ of the long argument about ‘nature v nurture’ because ‘it is much more difficult to dispute results based on DNA data than it is to quibble about twin and adoptee studies’ (emphasis added). In 2011, a GWAS confirmed the rough numbers from the twin/adoption studies for IQ (‘Genome-wide association studies establish that human intelligence is highly heritable and polygenic’, Nature, October 2011). This will eventually sink in but this field is an interesting example of how the more educated people are the more likely they are to believe false ideas than uneducated people are.

Contra the claims of Ball and others, I have never argued that there is some link between understanding genes/IQ and ‘writing off’ people as a ‘genetic underclass’. If these people actually read what I wrote instead of relying on other hacks’ wrong stories, they would see I made the opposite argument:

‘Far from being a reason to be pessimistic, or to think that ‘schools and education don’t matter, nature will out’, the scientific exploration of intelligence and learning is not only a good in itself but will help us design education policy more wisely (it may motivate people to spend more on the education of the less fortunate). One can both listen to basic science on genetics and regard as a priority the improvement of state schools; accepting we are evolved creatures does not mean ‘giving up on the less fortunate’ (the fear of some on the Left) or ‘giving up on personal responsibility’ (the fear of some on the Right).’ (From my essay, p. 74.)

Next time, Ball, do your research BEFORE you write your column – and leave out dumb comments about ‘Gove’s expenses’ that are more suitable for a dopey spin doctor than a ‘science writer’. And Prospect – raise your game if you’re going to brand yourself ‘the leading magazine of ideas’!

UPDATE (17/11). Interestingly, the prominent Socialist Workers Party supporter Michael Rosen has written a comment below Ball’s blog. It is bilge – totally irreconcilable with established findings in behavioural genetics. As Stuart Richie, an actual expert on genetics, wrote, Rosen’s comment ‘is one of the most poorly-informed things I’ve ever read on IQ.’

Ball replied to Rosen, ‘I agree completely with your comments on traditionally limited views of what intelligence is, and how to nurture it. So thanks for that.’

So Ball takes seriously comments by Rosen that are spectacularly ill-informed. How seriously should we take Ball as ‘a science writer’ on this subject?

Hsu also points out in comments the issue about finding ‘causal variants’ for polygenetic traits such as IQ or height – something it seems clear Ball did not research before writing his misconceived piece.

As S Richie wrote to Ball, ‘It’s a shame that you didn’t properly research this area before stating a tentative, unclear, and possibly nation-dependent finding from a single, small study as absolute fact. Perhaps this sort of sloppiness is one reason people familiar with the science get ‘touchy’ when they read your articles.’

In a further blog, HERE, Ball goes down another rabbit hole. He does not even try to answer the points I make above re his obvious errors. S Richie explains underneath the blog how Ball has introduced even more errors.

Prospect has no credibility in this area if it stands by such sloppy work, and Ball should reflect on the ethics of making claims about what people think that are 180 degrees off what they actually say – but it doesn’t look like he will. Time to re-read Feynman’s famous speech on ‘Cargo Cult Science’, Ball…

August 19, 2014 by dominiccummings

‘Standin’ by the window, where the light is strong’: de-extinction, machine intelligence, the search for extra-solar life, autonomous drone swarms bombing Parliament, genetics & IQ, science & politics, and much more @ SciFoo 2014

‘SciFoo’ 8-10 August 2014, the Googleplex, Silicon Valley, California.

On Friday 8 August, I woke up in Big Sur (the coast of Northern California), looked out over the waves breaking on the wild empty coastline, munched a delicious Mexican breakfast at Deetjen’s, then drove north on Highway 1 towards Palo Alto where a few hours later I found myself looking through the windows of Google’s HQ at a glittering sunset in Silicon Valley.

I was going to ‘SciFoo’. SciFoo is a weekend science conference. It is hosted by Larry Page at Google’s HQ in Silicon Valley and organised by various people including the brilliant Timo Hannay from Digital Science.

I was invited because of my essay that became public last year (cf. HERE). Of the 200+ people, I was probably the only one who made zero positive contribution to the fascinating weekend and therefore wasted a place, so although it was a fantastic experience for me the organisers should not invite me back and I feel guilty about the person who could not go because I was there. At least I can let others know about some of the things discussed… (Although it was theoretically ‘on the record unless stated otherwise’, I could tell that many scientists were not thinking about this and so I have left out some things that I think they would not want attributed. Given they were not experienced politicians being interviewed but scientists at a scientific conference, I’m erring on the side of caution, particularly given the subjects discussed.)

It was very interesting to see many of the people whose work I mentioned in my essay and watch them interacting with each other – intellectually and psychologically / physically.

I will describe some of the things that struck me though, because there are about 7-10 sessions going on simultaneously, this is only a small snapshot.

In my essay, I discuss some of the background to many of these subjects so I will put references [in square brackets] so people can refer to it if they want.

Please note that below I am reporting what I think others were saying – unless it is clear, I am not giving my own views. On technical issues, I do not have my ‘own’ views – I do not have relevant skills. All I can do is judge where consensus lies and how strong it is. Many important issues involve asking at least 1) is there a strong scientific consensus on X among physical scientists with hard quantitative data to support their ideas (uber-example, the Standard Model of particle physics), b) what are the non-science issues, such as ‘what will it cost, who pays/suffers and why?’ On A, I can only try to judge what technically skilled people think. B is a different matter.

Whether you were there or not, please leave corrections / additions / questions in the comments box. Apologies for errors…

In a nutshell, a few likely scenarios / ideas, without spelling out caveats… 1) Extinct species are soon going to be brought back to life and the same technology will be used to modify existing species to help prevent them going extinct. 2) CRISPR – a new gene editing technology – will be used to cure diseases and ‘enhance’ human performance but may also enable garage bio-hackers to make other species extinct. 3) With the launch of satellites in 2017/18, we may find signs of life by 2020 among the ~10¹¹ exoplanets we now know exist just in our own galaxy though it will probably take 20-30 years, but the search will also soon get crowdsourced in a way schools can join in. 4) There is a reasonable chance we will have found many of the genes for IQ within a decade via BGI’s project, and the rich may use this information for embryo selection. 5) ‘Artificial neural networks’ are already outperforming humans on various pattern-recognition problems and will continue to advance rapidly. 6) Automation will push issues like a negative income tax onto the political agenda as millions lose their jobs to automation. 7) Autonomous drones will be used for assassinations in Europe and America shortly. 8) Read Neil Gershenfeld’s book ‘FAB’ if you haven’t and are interested in science education / 3D printing / computer science (or at least watch his TED talks). 9) Scientists are desperate to influence policy and politics but do not know how.

Biological engineering / computational biology / synthetic biology [Section 4]

George Church (Harvard), a world-leading biologist, spoke at a few sessions and his team’s research interests were much discussed. (Don’t assume he said any specific thing below.)

The falling cost of DNA sequencing continues to spur all sorts of advances. It has fallen from a billion dollars per genome a decade ago to less than a thousand dollars now (a million-fold improvement), and the Pentagon is planning on it reaching $100 soon. We can also sequence cancer cells to track their evolution in the body.

CRISPR. CRISPR is a new (2012) and very hot technology that is a sort of ‘cut and paste’ gene editing tool. It allows much more precise and effective engineering of genomes. Labs across America are rushing to apply it to all sorts of problems. In March this year, it was used to correct faulty genes in mice and cure them of a liver condition. It plays a major part in many of the biological issues sketched below.

‘De-extinction’ (bringing extinct species back to life). People are now planning the practical steps for de-extinction to the extent that they are scoping out land in Siberia where woolly mammoths will roam. As well as creating whole organisms, they will also grow organs modified by particular genes to test what specific genes and combinations do. This is no longer sci-fi – it is being planned and is likely to happen. The buffalo population was recently re-built (Google serves buffalo burgers in its amazing kitchens) from a tiny population to hundreds of thousands and there seems no reason to think it is impossible to build a significant population from scratch.

What does this mean? You take the DNA from an animal, say a woolly mammoth buried in the ground, sequence it, then use the digitised genome to create an embryo and either grow it in a similar animal (e.g. elephant for a mammoth) or in an artificial womb. (I missed the bit explaining the rationale for some of the proposed projects but, apart from the scientific reasons, one rationale for the mammoth was described as a conservation effort to preserve the frozen tundra and prevent massive amounts of greenhouse gases being released from beneath it.)

There are also possibilities of using this technology for conservation. For example, one could re-engineer the Asian elephant so that it could survive in less hospitable climates (e.g. modify the genes that produce haemoglobin so it is viable in colder places).

Now that we have sequenced the genome for Neanderthals (and learned that humans interbred with them, so you have traces of their DNA – unless you’re an indigenous sub-Saharan African), there is no known physical reason why we could not bring a Neanderthal back to life once the technology has been refined on other animals. This obviously raises many ethical issues – e.g. if we did it, they would have to be given the same legal rights as us (one distinguished person said that if there were one in the room with us we would not notice, contra the pictures often used to illustrate them). It is assumed by many that this will happen (nobody questioned the assumption) – just as it seemed to be generally assumed that human cloning will happen – though probably not in a western country but somewhere with fewer legal restrictions, after the basic technologies have been refined. (The Harvard team gets emails from women volunteering to be the Neanderthal’s surrogate mum.)

‘Biohacking’. Biohacking is advancing faster than Moore’s Law. CRISPR editing will allow us to enhance ourselves. E.g. Tibetans have evolved much more efficient systems for coping with high altitude, and some Africans have much stronger bones than the rest of us (see below). Will we reengineer ourselves to obtain these advantages? CRISPR obviously also empowers all sorts of malevolent actors too – cf. this very recent paper (by Church et al). It may soon be possible for people in their garages to edit genomes and accidentally or deliberately drive species to extinction as well as attempt to release deadly pathogens. I could not understand why people were not more worried about this – I hope I was missing a lot. (Some had the attitude that ‘nature already does bio-terrorism’ so we should relax. I did not find this comforting and I’m sure I am in the majority so for anybody influential reading this I would strongly advise you not to use this argument in public advocacy or it is likely to accelerate calls for your labs to be shut down.)

‘Junk’. There is more and more analysis of what used to be called ‘junk DNA’. It is now clear that far from being ‘junk’ much of this has functions we do not understand. This connects to the issue that although we sequenced the human genome over a decade ago, the quality of the ‘reference’ version is not great and (it sounded like from the discussions) it needs upgrading.

‘Push button’ cheap DNA sequencers are around the corner. Might such devices become as ubiquitous as desktop printers? Why doesn’t someone create a ‘gene web browser’ that can cope with all the different data formats for genomes?

Privacy. There was a lot of talk about ‘do you want your genome on the web?’. I asked a quick informal pop quiz (someone else’s idea): there was unanimity that ‘I’d much rather my genome was on the web than my browsing history’. [UPDATE: n<10 and perhaps they were tongue in cheek!? One scientist pointed out in a session that when he informed his insurance company, after sequencing his own genome, that he had a very high risk of getting colon cancer, they raised his premiums. There are all sorts of reasons one would want to control genomic information and I was being a bit facetious.]

In many ways, computational biology and synthetic biology have that revolutionary feeling of the PC revolution in the 1970s – huge energy, massive potential for people without big resources to make big contributions, the young crowding in, the feeling of dramatic improvements imminent. Will this all seem ‘too risky’? It’s hard to know how the public will respond to risk. We put up with predictable annual carnage from car accidents but freak out over trivia. We ignore millions of deaths in the Congo but freak out over a handful in Israel/Gaza. My feeling is some of the scientists are too blasé about how the public will react to the risks, but I was wrong about how much fear there would be about the news that scientists recently deliberately engineered a much more dangerous version of an animal flu.

AI / machine learning / neuroscience [Section 5].

Artificial neural networks (NNs), now often referred to as ‘deep learning’, were first created 50 years ago but languished for a while when progress slowed. The field is now hot again. (Last year Google bought some companies leading the field, and a company, Boston Dynamics, that has had a long-term collaboration with DARPA.)

Jurgen Schmidhuber explained progress and how NNs have recently approached or surpassed human performance in various fields. E.g. recently NNs have surpassed human performance in recognising traffic signals (0.56% error rate for the best NN versus 1.16% for humans). Progress in all sorts of pattern recognition problems is clearly going to continue rapidly. E.g. NNs are now being used to automate a) the analysis of scans for cancer cells and b) the labelling of scans of human brains – so artificial neural networks are now scanning and labelling natural neural networks.

Steve Hsu has blogged about this session here:

http://infoproc.blogspot.co.uk/2014/08/neural-networks-and-deep-learning.html?m=1

Michael Nielsen is publishing an education project online for people to teach themselves the basics of neural networks. It is brilliant and I would strongly advise teachers reading this blog to consider introducing it into their schools and doing the course with the pupils.

http://neuralnetworksanddeeplearning.com

Neil Gershenfeld (MIT) gave a couple of presentations. One was on developments in computer science connecting: non-‘von Neumann architecture’, programmable matter, 3D printing, ‘the internet of things’ etc. [Cf. Section 3.] NB. IBM announced this month substantial progress in their quest for a new computer architecture that is ‘non-Von Neumann’: cf. this –

http://venturebeat.com/2014/08/07/ibms-synapse-marshals-the-power-of-the-human-brain-in-a-computer/view-all/

Another was on the idea of an ‘interspecies internet’. We now know many species can recognise each other, think, and communicate much better than we realised. He showed bonobos playing music with Peter Gabriel and dolphins communicating. He and others are plugging them into the internet. Some are doing this to help the general goal of figuring out how we might communicate with intelligent aliens – or how they might communicate with us.

(Gershenfeld’s book FAB led me to push 3D printing into the new National Curriculum and I would urge school science teachers to watch his TED talks and read this book. [INSERTED LATER: Some people have asked about this point. I (I thought obviously) did not mean I wrote the NC document. I meant – I pushed the subject into the discussions with the committees/drafters who wrote the NC. Experts in the field agreed it belonged. When it came out, this was not controversial. We also funded pilots with 3D printers so schools could get good advice about how to teach the subject well.] His point about 3D printers restoring the connection between thinking and making – lost post-Renaissance – is of great importance and could help end the foolishly entrenched ‘knowledge’ vs ‘skills’ and academic vs vocational trench wars. Gove actually gave a speech about this not long before he was moved and as far as I could tell it got less coverage than any speech he ever gave, thus proving the cliché about speeches on ‘skills’.)

There were a few presentations about ‘computational neuroscience’. I could not understand anything much as they were too technical. It was clear that there is deep concern among EU neuroscientists about the EU’s huge funding for Henry Markram’s Human Brain Project. One leading neuroscientist said to me that the whole project is misguided as it does not have clear focused goals and the ‘overhype’ will lead to public anger in a few years. Apparently, the EU is reconsidering the project and its goals. I have no idea about the merits of these arguments. I have a general prejudice that, outside special circumstances, experience suggests that it is better to put funding into many pots and see what works, as DARPA does.

There are all sorts of crossovers between: AI / neuroscience / big data / NNs / algorithmic pattern recognition in other fields.

Peter Norvig, a leader in machine intelligence, said that he is more worried about the imminent social implications of continued advances making millions unemployed than he is about a sudden ‘Terminator / SKYNET’ scenario of a general purpose AI bootstrapping itself to greater than human intelligence and exterminating us all. Let’s hope so. It is obvious that this field is going to keep pushing boundaries – in open, commercial, and classified projects – so we are essentially going to be hoping for the best as we make more and more advances in AI. The idea of a ‘negative income tax’ – or some other form of essentially paying people X just to live – seems bound to return to the agenda. I think it could be a way around all sorts of welfare arguments. The main obstacle, it seems to me, is that people won’t accept paying for it if they think uncontrolled immigration will continue as it is now.

Space [Section 2]

There was great interest in various space projects and some senior people from NASA. There is much sadness at how NASA, despite many great people, has become a normal government institution – ie. caught in DC politics, very bureaucratic, and dysfunctional in various ways. On the other hand, many private ventures are now growing. E.g. Elon Musk is lowering the $/kg of getting material into orbit and planning a non-government Mars mission. As I said in my essay, really opening up space requires a space economy – not just pure science and research (such as putting telescopes on the far side of the moon, which we obviously should do). Columbus opened up America – not the Vikings.

There is another obvious motive. As Carl Sagan said, if the dinosaurs had had a space programme, they’d still be here. In the long-term we either develop tools for dealing with asteroids or we will be destroyed. We know this for sure. I think I heard that NASA is planning to park a small asteroid close to the moon around 2020 but I may have misheard / misunderstood.

Mario Livio led a great session on the search for life on exoplanets. The galaxy has ~10¹¹ stars and there is ~1 planet on average per star. There are ~10¹¹ galaxies, so a Fermi estimate is there are ~10²² planets – 10 billion trillion planets – in the observable universe (this number is roughly 1,000 times bigger than the number you get in the fable of putting a grain of rice on the first square of a chessboard and doubling on each subsequent square). Many of them are in the ‘habitable zone’ around stars.

In 2017/18, there are two satellites launching that will be able to do spectroscopy on exoplanets – i.e. examine their atmospheres and detect things like oxygen and water. ‘If we get lucky’, these satellites will find ‘bio-signatures’ of life. If they find life having looked at only a few planets, then it would mean that life is very common. ‘More likely’ is it will take 20-30 years and a new generation of space-based telescopes to find life. If planets are found with likely biosignatures, then it would make sense to turn SETI’s instruments towards them to see if they find anything. (However, we are already phasing out the use of radio waves for various communications – perhaps the use of radio waves is only a short window in the lifetime of a civilisation.) There are complex Bayesian arguments about what we might infer about our own likely future given various discoveries but I won’t go into those now. (E.g. if we find life is common but no traces of intelligent life, does this mean a) the evolution of complex life is not a common development from simple life; b) intelligent life is also common but it destroys itself; c) they’re hiding, etc.)

A very impressive (and helpful towards the ignorant like me) young scientist working on exoplanets called Oliver Guyon demonstrated a fascinating project to crowdsource the search for exoplanets by building a global network of automated cameras – PANOPTES (www.projectpanoptes.org). His team has built a simple system that can find exoplanets using normal digital cameras costing less than $1,000. They sit in a box connected to a 12V power supply, automatically take pictures of the night sky every few seconds, then email the data to the cloud. There, the data is aggregated and algorithms search for exoplanets. These units are cheap (can’t remember what he said but I think <$5,000). Everything is open-source, open-hardware. They will start shipping later this year and will make a brilliant school science project. Guyon has made the project with schools in mind so that assembling and operating the units will not require professional level skills. They are also exploring the next move to connect smartphone cameras.

Building the >15m diameter space telescopes we need to search for life seems to me an obvious priority for scientific budgets – it is one of the handful of the most profound questions facing us.

There was an interesting cross-over discussion about ‘space and genetics’ in which people discussed various ways in which space exploration would encourage / require genetic modification. E.g.1 some sort of rocket fuel has recently been discovered to exist in large quantities on Mars. This is very handy but the substance is toxic. It might therefore make sense to modify humans going to live on Mars to be resistant. E.g.2 Space travel weakens bones. It has been discovered that mutations in the human population can improve bone strength by 8 standard deviations. This is a massive improvement – for comparison, 8 SDs in IQ covers people from severely mentally disabled to Nobel-winners. This was discovered by a team of scientists in Africa who noticed that people in a local tribe who got hit by cars did not suffer broken bones, so they sequenced the locals’ genomes. (Someone said there have already been successful clinical trials testing this discovery in a real drug to deal with osteoporosis.) E.g.3 Engineering E. Coli shows that just four mutations can improve resistance to radiation by ?1,000 times (can’t read my note).

Craig Venter and others are thinking about long-term projects to send ‘von Neumman-bots’ (self-replicating space drones) across the universe containing machines that could create biological life once they arrive somewhere interesting, thus avoiding the difficult problems of keeping humans alive for thousands of years on spaceships. (Nobel-winning physicist Gerard t’ Hooft explains the basic principles of this in his book Playing with planets.)

This paper (August 2014) summarises issues in the search for life:

http://www.pnas.org/content/early/2014/08/01/1304213111.full.pdf

Finding the genes for IQ and engineering possibilities [Section 5].

When my essay came out last year, there was a lot of mistaken reporting that encouraged many in the education world to grab the wrong end of the stick about IQ, though the BBC documentary about the controversy (cf. below) was excellent and a big step forward. It remains the case that very few people realise that in the last couple of years direct examination of DNA has now vindicated the consistent numbers on IQ heritability from decades of twin/adoption studies.

The rough heritability numbers for IQ are no longer in doubt among physical scientists who study this field: it is roughly 50% heritable at age ~18-20 and this number rises towards 70-80% for older adults. This is important because IQ is such a good predictor of the future – it is a better predictor than social class. E.g. The long-term Study of Mathematically Precocious Youth, which follows what has happened to children with 1:10,000 ability, shows among many things that a) a simple ‘noisy’ test administered at age 12-13 can make amazingly accurate predictions about their future, and b) achievements such as scientific breakthroughs correlate strongly with IQ. (If people looked at the data from SMPY, then I think some of the heat and noise in the debate would fade but it is a sad fact that approximately zero senior powerful people in the English education world had even heard of this study before the furore over Plomin last year.)

Further, the environmental effects that are important are not the things that people assume. If you test the IQ of an adopted child in adulthood and the parents who adopted it, you find approximately zero correlation – all those anguished parenting discussions had approximately no measurable impact on IQ. (This does not mean that ‘parenting doesn’t matter’ – parents can transfer narrow skills such as playing the violin.) In the technical language, the environmental effects that are important are ‘non-shared’ environmental effects – i.e. they are things that two identical twins do not experience in the same way. We do not know what they are. It is reasonable to think that they are effectively random tiny events with nonlinear effects that we may never be able to track in detail – cf. this paper for a discussion of this issue in the context of epidemiology: http://ije.oxfordjournals.org/content/40/3/537.full.pdf+html

There remains widespread confusion on this subject among social scientists, education researchers, and the worlds of politics and the media where people were told misleading things in the 1980s and 1990s and do not realise that the debates have been transformed. To be fair, however, it was clear from this weekend that even many biologists do not know about new developments in this field so it is not surprising that political journalists and education researchers do not.

(An example of confusion in the political/media world… In my essay, I used the technical term ‘heritable’ which is a population statistic – not a statement about an individual. I also predicted that media coverage would confuse the subject (e.g. by saying things like ‘70% of your IQ comes from genes’). Sure enough some journalists claimed I said the opposite of what I actually said then they quoted scientists attacking me for making a mistake that not only did I not make but which I actually warned about. Possibly the most confused sentence of all those in the media about my essay was the line ‘wealth is more heritable than genes’, which was in Polly Toynbee’s column and accompanying headline in the Guardian. This sentence is a nonsense sentence as it completely mangles the meaning of the term ‘heritable’. Much prominent commentary from politicians and sociologists/economists on ‘social mobility’ is gibberish because of mistaken assumptions about genes and environment. The Endnote in my essay has links to work by Plomin, Hsu et al that explains it all properly. This interview with Plomin is excellent: http://www.spectator.co.uk/features/8970941/sorry-but-intelligence-really-is-in-the-genes/. This recent BBC radio programme is excellent and summarises the complex issues well: http://www.bbc.co.uk/programmes/b042q944/episodes/guide)

I had a fascinating discussion/tutorial at SciFoo with Steve Hsu. Steve Hsu is a professor of theoretical physics (and successful entrepreneur) with a long interest in IQ (he also runs a brilliant blog that will keep you up to speed on all sorts). He now works part time on the BGI project in China to discover the genes responsible for IQ.

IQ is very similar to height from the perspective of behavioural genetics. Height has the advantage that it is obviously easier to measure than IQ but it has roughly the same heritability. Large scale GWAS are already identifying some of the genes responsible for height. Hsu recently watched a talk by Fields Medallist Terry Tao and realised that a branch of maths could be used to examine the question – how many genomes do we need to scan to identify a substantial number of the genes for IQ? His answer: ‘roughly 10k moderately rare causal variants of mostly negative effect are responsible for normal population variation’ and finding them will require sequencing roughly a million genomes. The falling cost of sequencing DNA means that this is within reach. ‘At the time of this writing SNP genotyping costs are below $50 USD per individual, meaning that a single super-wealthy benefactor could independently fund a crash program for less than $100 million’ (Hsu).

The BGI project to find these genes has hit some snags recently (e.g. a US lawsuit between the two biggest suppliers of gene sequencing machines). However, it is now expected to start again soon. Hsu thinks that within a decade we could find many of the genes responsible for IQ. He has just put his fascinating paper on this subject on his blog (there is also a Q&A on p.27 that will be very useful for journalists):

http://infoproc.blogspot.co.uk/2014/08/genetic-architecture-of-intelligence.html

Just discovering a substantial fraction of the genes would be momentous in itself but there is more. It is already the case that farmers use genomes to make predictions about cows’ properties and behaviour (‘genotype to phenotype’ predictions). It is already the case that rich people could use in vitro fertilisation to select the egg which they think will be most advantageous, because they can sequence genomes of multiple eggs and examine each one to look for problems then pick the one they prefer. Once we identify a substantial number of IQ genes, there is no obvious reason why rich people will not select the egg that has the highest prediction for IQ.

This clearly raises many big questions. If the poor cannot do the same, then the rich could quickly embed advantages and society could become not only more unequal but also based on biological classes. One response is that if this sort of thing does become possible, then a national health system should fund everybody to do this. (I.e. It would not mandate such a process but it would give everybody a choice of whether to make use of it.) Once the knowledge exists, it is hard to see what will stop some people making use of it and offering services to – at least – the super-rich.

It is vital to separate two things: a) the basic science of genetics and cognition (which must be allowed to develop), and b) the potential technological applications and their social implications. The latter will rightly make people deeply worried, given our history, and clearly require extremely serious public debate. One of the reasons I wrote my essay was to try to stimulate such debate on the biggest – and potentially most dangerous – scientific issues. By largely ignoring such issues, Westminster, Whitehall, and the political media are wasting the time we have to discuss them so technological breakthroughs will be unnecessarily shocking when they come.

Hsu’s contribution to this research – and his insight when listening to Tao about how to apply a branch of mathematics to a problem – is also a good example of how the more abstract fields of maths and physics often make contributions to the messier study of biology and society. The famous mathematician von Neumann practically invented some new fields outside maths and made many contributions to others. The physicist-mathematician Freeman Dyson recently made a major contribution to Game Theory which had lain unnoticed for decades until he realised that a piece of maths could be applied to uncover new strategies (Google “Dyson zero determinant strategies” and cf. this good piece: http://www.americanscientist.org/issues/id.16112,y.0,no.,content.true,page.1,css.print/issue.aspx).

However, this also raises a difficult issue. There is a great deal of Hsu’s paper – and the subject of IQ and heritability generally – that I do not have the mathematical skills to understand. This will be true of a large fraction of education researchers in education departments – I would bet a large majority. This problem is similar for many other vital issues (and applies to MPs and their advisers) and requires general work on translating such research into forms that can be explained by the media.

Kathryn Ashbury also did a session on genes and education but I went to a conflicting one with George Church so unfortunately I missed it.

‘Big data’, simulations, and distributed systems [Section 6&7]

The rival to Markram’s Brain Project for mega EU funding was Dirk Helbing (ETH Zurich) and his project for new simulations to aid policy-making. Helbing was also at SciFoo and gave a couple of presentations. I will write separately about this.

Helbing says convincingly: ‘science must become a fifth pillar of democracies, besides legislation, executive, jurisdiction, and the public media’. Many in politics hope that technology will help them control things that now feel out of control. This is unlikely. The amount of data is growing at a faster rate than the power of processing and the complexity of networked systems grows factorially therefore top-down control will become less and less effective.

The alternative? ‘Distributed (self-)control, i.e. bottom-up self-regulation’. E.g. Helbing’s team has invented self-regulating traffic lights driven by traffic flows that can ‘outperform the classical top-down control by a conventional traffic center.’

‘Can we transfer and extend this principle to socio-economic systems? Indeed, we are now developing mechanisms to overcome coordination and cooperation failures, conflicts, and other age-old problems. This can be done with suitably designed social media and sensor networks for real-time measurements, which will eventually weave a Planetary Nervous System. Hence, we can finally realize the dream of self-regulating systems… [S]uitable institutions such as certain social media – combined with suitable reputation systems – can promote other-regarding decision-making. The quick spreading of social media and reputation systems, in fact, indicates the emergence of a superior organizational principle, which creates collective intelligence by harvesting the value of diversity…’

His project’s website is here:

http://www.futurict.eu

I wish MPs and spads in all parties would look at this project and Helbing’s work. It provides technologically viable and theoretically justifiable mechanisms to avoid the current sterile party debates about delivery of services. We must move from Whitehall control to distributed systems…

Science and politics

Unsurprisingly, there was a lot of grumbling about politicians, regulation, Washington gridlock, bureaucracy and so on.

Much of it is clearly justified. Some working in genetics had stories about how the regulations forbid them to tell people about imminently life threatening medical problems they discover. Others were bemoaning the lack of action on asteroid defence and climate change.

Some of these problems are inherently extremely difficult, as I discuss in my essay. On top of this, though, is the problem that many (most?) scientists do not know how to go about changing things.

It was interesting that some very eminent scientists, all much cleverer than ~100% of those in politics [INSERT: better to say ‘all with higher IQ than ~100% of those in politics’], have naive views about how politics works. In group discussions, there was little focused discussion about how they could influence politics better even though it is clearly a subject that they care about very much. (Gershenfeld said that scientists have recently launched a bid to take over various local government functions in Barcelona, which sounds interesting.)

A few times I nearly joined in the discussion but I thought it would disrupt things and distract them. In retrospect, I think this may have been a mistake and I should have spoken up. But also I am not articulate and I worried I would not be able to explain their errors and it would waste their time.

I will blog on this issue separately. A few simple observations…

To get things changed in politics, scientists need mechanisms a) to agree priorities in order to focus their actions on b) roadmaps with specifics. Generalised whining never works. The way to influence politicians is to make it easy for them to fall down certain paths without much thought, and this means having a general set of goals but also a detailed roadmap the politicians can apply, otherwise they will drift by default to the daily fog of chaos and moonlight.

Scientists also need to be prepared to put their heads above the parapet and face controversy. Many comments amounted to ‘why don’t politicians do the obviously rational thing without me having to take a risk of being embroiled in media horrors’. Sorry guys but this is not how it works.

Many academics are entirely focused on their research and do not want to lose time to politics. This is entirely reasonable. But if you won’t get involved you can have little influence other than lending your name to the efforts of others.

Working in the Department for Education, I have experienced in England that very few scientists were prepared to face controversy over the issue of A Levels (exams at 18) and university entry / undergraduate standards even though this problem directly affected their own research area. Many dozens sought me out 2007-14 to complain about existing systems. I can count on the fingers of one hand those who rolled the dice and did things in the public domain that could have caused them problems. I have heard many scientists complain about media reports but when I’ve said – ‘write a blog explaining why they’re wrong’, the answer is almost invariably ‘oh, the VC’s office would go mad’. If they won’t put their heads above the parapet on an issue that directly touches their own subject and career, how much are they likely to achieve in moving political debate in areas outside their own fields?

Provided scientists a) want to avoid controversy and b) are isolated, they cannot have the leverage they want. The way to minimise controversy is to combine in groups – for the evolutionary biologists reading this, think SHOALS! – so that each individual is less exposed. But you will only join a shoal if you agree a common purpose.

I’m going to do a blog on ‘How scientists can learn from Bismarck and Jean Monnet to influence politics‘. Monnet avoided immediate battles for power in favour of ‘preparing the future’ – i.e. having plans in his pocket for when crises hit and politicians were desperate. He created the EEC in this way. In the same way people find it extremely hard to operationalise the lessons of Thucydides or Bismarck, they do not operationalise the lessons from Monnet. It would be interesting if scientists did this in a disciplined way. In some ways, it seems to me vital if we are to avoid various disasters. It is also necessary, however, to expose scientists to the non-scientific factors in play.

Anyway, it would be worth exploring this question: can very high IQ people with certain personality traits (like von Neumann, not like Gödel) learn enough in half a day’s exposure to case studies of successful political action to enable them to change something significant in politics, provided someone else can do most of the admin donkey work? I’m willing to bet the answer is YES. Whether they will then take personal risks by ACTING is another question.

A physicist remarked: ‘we’re bitching about politicians but we can’t even sort out our own field of scientific publishing which is a mess’.

NB. for scientists who haven’t read anything I’ve read before, do not make the mistake of thinking I am defending politicians. If you read other stuff I’ve written you will see that I have made all the criticisms that you have. But that doesn’t mean that scientists cannot do much better than they are at influencing policy.

A few general comments

1. It has puzzled me for over a decade that a) one of the few things the UK still has that is world class is Oxbridge, b) we have the example of Silicon Valley and our own history of post-1945 bungling to compare it with (e.g. how the Pentagon treated von Neumann and how we treated Turing viz the issue of developing computer science), yet c) we persistently fail to develop venture capital-based hubs around Oxbridge on the scale they deserve. As I pottered down University Avenue in Palo Alto looking for a haircut, past venture capital offices that can provide billions in start-up investment, I thought: you’ve made a few half-hearted attempts to persuade people to do more on this, when you get home try again. So I will…

2. It was interesting to see how physicists have core mathematical skills that allow them to grasp fundamentals of other fields without prior study. Watching them reminded me of Mandelbrot’s comment that:

‘It is an extraordinary feature of science that the most diverse, seemingly unrelated, phenomena can be described with the same mathematical tools. The same quadratic equation with which the ancients drew right angles to build their temples can be used today by a banker to calculate the yield to maturity of a new, two-year bond. The same techniques of calculus developed by Newton and Leibniz two centuries ago to study the orbits of Mars and Mercury can be used today by a civil engineer to calculate the maximum stress on a new bridge… But the variety of natural phenomena is boundless while, despite all appearances to the contrary, the number of really distinct mathematical concepts and tools at our disposal is surprisingly small… When we explore the vast realm of natural and human behavior, we find the most useful tools of measurement and calculation are based on surprisingly few basic ideas.’

3. High status people have more confidence in asking basic / fundamental / possibly stupid questions. One can see people thinking ‘I thought that but didn’t say it in case people thought it was stupid and now the famous guy’s said it and everyone thinks he’s profound’. The famous guys don’t worry about looking stupid and they want to get down to fundamentals in fields outside their own.

4. I do not mean this critically but watching some of the participants I was reminded of Freeman Dyson’s comment:

‘I feel it myself, the glitter of nuclear weapons. It is irresistible if you come to them as a scientist. To feel it’s there in your hands. To release the energy that fuels the stars. To let it do your bidding. And to perform these miracles, to lift a million tons of rock into the sky, it is something that gives people an illusion of illimitable power, and it is in some ways responsible for all our troubles, I would say, this is what you might call ‘technical arrogance’ that overcomes people when they see what they can do with their minds.’

People talk about rationales for all sorts of things but looking in their eyes the fundamental driver seems to be – am I right, can I do it, do the patterns in my mind reflect something real? People like this are going to do new things if they can and they are cleverer than the regulators. As a community I think it is fair to say that outside odd fields like nuclear weapons research (which is odd because it still requires not only a large collection of highly skilled people but also a lot of money and all sorts of elements that are hard (but not impossible) for a non-state actor to acquire and use without detection), they believe that pushing the barriers of knowledge is right and inevitable. Fifteen years on from the publication by Silicon Valley legend Bill Joy of his famous essay (‘Why the future doesn’t need us’), it is clear that many of the things he feared have proceeded and there remains no coherent government approach or serious international discussion. (I am not suggesting that banning things is generally the way forward.)

5. The only field where there was a group of people openly lobbying for something to be made illegal was the field of autonomous lethal drones. (There is a remorseless logic that means that countermeasures against non-autonomous drones (e.g. GPS-spoofing) incentivises one to make one’s drones autonomous. They can move about waiting to spot someone’s face then destroy them without any need for human input.) However, the discussion confirmed my view that even if this might be a good idea – it is doomed, in the short-term at least. I wonder what is to stop someone sending a drone swarm across the river and bombing Parliament during PMQs. Given it will be possible to deploy autonomous drones anonymously, it seems there may be a new era of assassinations coming, apart from all the other implications of drones. Given one may need a drone swarm to defend against drone swarm, I can’t see them being outlawed any time soon. (Cf. Suarez’s Kill Decision for a great techno-thriller on the subject.)

(Also, I thought that this was an area where those involved in cutting edge issues could benefit from talking to historians. E.g. my understanding is that we filmed the use of anthrax on a Scottish island and delivered the footage to the Nazis with the message that we would anthrax Germany if they used chemical weapons – i.e. the lack of chemical warfare in WWII was a case of successful deterrence, not international law.)

6. A common comment is – ‘technology X [e.g. in vitro fertilisation] was denounced at the time but humans adapt to such changes amazingly fast, so technology Y will be just the same’. This is a reasonable argument in some ways but I cannot help but think that many will think de-extinction, engineered bio-weapons, or human clones are going to be perceived as qualitative changes far beyond things like in vitro fertilisation.

7. Daniel Suarez told me what his next techno-thriller is about but if I put it on my blog he will deploy an autonomous drone with face recognition AI to kill me, so I’m keeping quiet. If you haven’t read Daemon, read it – it’s a rare book that makes you laugh out loud about how clever the plot is.

8. Von Neumann was heavily involved not only in the Manhattan Project but also the birth of the modern computer, the creation of the hydrogen bomb, and nuclear strategy. Before his tragic early death, he wrote a brilliant essay about the political problem of dealing with advanced technology which should be compulsory reading for all politicians aspiring to lead. It summarises the main problems that we face – ‘for progress, there is no cure…’

http://features.blogs.fortune.cnn.com/2013/01/13/can-we-survive-technology/

As I said at the top, any participants please tell me where I went wrong, and thanks for such a wonderful weekend.

Share this:

Share this:

Share this:

Share this:

Share this:

Share this:

Share this: