On the referendum #29: Genetics, genomics, predictions & ‘the Gretzky game’ — a chance for Britain to help the world

On the referendum #29: 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 possibly at 1/20th of the cost of the latter.

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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 HEREScience 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 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…

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What’s happening now?

Screenshot 2019-02-19 15.35.49

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.’

Screenshot 2019-02-19 15.00.14

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.

Screenshot 2019-02-19 15.00.37

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.

Screenshot 2019-02-20 10.32.37

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.)

Screenshot 2019-02-15 12.42.47

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.

#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.

On the referendum #26: How to change science funding post-Brexit [updated with comment by Alan Kay]

There was an excellent piece in the Telegraph yesterday by two young neuroscientists on how SW1 should be thinking about science post-Brexit. The byline says that James Phillips works at Janelia, a US lab that has explicitly tried to learn about how to fund science research from the famous successes of Bell Labs, the ARPA-PARC project that invented the internet and PC, and similar efforts. He must see every day how science funding can work so much better than is normal in Britain.

Today, the UK a) ties research up in appalling bureaucracy, such as requiring multi-stage procurement processes literally to change a lightbulb, and b) does not fund it enough. The bureaucracy around basic science is so crazy that a glitch in paper work means thousands of animals are secretly destroyed in ways the public would be appalled to learn if made public.

Few in SW1 take basic science research seriously. And in all the debates over Brexit, practically the entire focus is 1980s arguments over the mechanism for regulating product markets created by Delors to centralise power in Brussels — the Internal Market (aka Single Market). Thirty years after they committed to this mechanism and two years after the referendum that blew it up, most MPs still don’t understand what it is and how it works. Dismally, the last two years has been a sort of remedial education programme and there has been practically zero discussion about how Britain could help create the future

During the referendum, Vote Leave argued that the dreadful Cameron/Osborne immigration policy (including the net migration target) was damaging and said we should make Britain MORE welcoming to scientists. Obviously Remain-SW1 likes to pretend that the May/Hammond Remain team’s shambles is the only possible version of Brexit. Nothing could be further from the truth. If the government had funded the NHS, ditched the ‘tens of thousands’ absurdity, and, for example, given maths, physics and computer science PhDs ‘free movement’ then things would be very different now — and Corbyn would probably be a historical footnote.

Regardless of how you voted in the referendum, reasonable people outside the rancid environment of SW1 should pressure their MPs to take their responsibilities to science x100 more seriously than they do.

I strongly urge you to read it all, send it to your MP, and politely ask for action…

(Their phrase ‘creating the future’ invokes Alan Kay’s famous line — the best way to predict the future is to invent it.)


Science holds the key, by James & Matthew Phillips

The 2008 crisis should have led us to reshape how our economy works. But a decade on, what has really changed? The public knows that the same attitude that got us into the previous economic crisis will not bring us long-term prosperity, yet there is little vision from our leaders of what the future should look like. Our politicians are sleeping, yet have no dreams. To solve this, we must change emphasis from creating “growth” to creating the future: the former is an inevitable product of the latter.

Britain used to create the future, and we must return to this role by turning to scientists and engineers. Science defined the last century by creating new industries. It will define this century too: robotics, clean energy, artificial intelligence, cures for disease and other unexpected advances lie in wait. The country that gives birth to these industries will lead the world, and yet we seem incapable of action.

So how can we create new industries quickly? A clue lies in a small number of institutes that produced a strikingly large number of key advances. Bell Labs produced much of the technology underlying computing. The Palo Alto Research Centre did the same for the internet. There are simple rules of thumb about how great science arises, embodied in such institutes. They provided ambitious long-term funding to scientists, avoided unnecessary bureaucracy and chased high-risk, high-reward projects.

Today, scientists spend much of their time completing paperwork. A culture of endless accountability has arisen out of a fear of misspending a single pound. We’ve seen examples of routine purchases of LEDs that cost under £10 having to go through a nine-step bureaucratic review process.

Scientists on the cusp of great breakthroughs can be slowed by years mired in review boards and waiting on a decision from on high. Their discoveries are thus made, and capitalised on, elsewhere. We waste money, miss patents, lose cures and drive talented scientists away to high-paid jobs. You don’t cure cancer with paperwork. Rather than invigilate every single decision, we should do spot checks retrospectively, as is done with tax returns.

A similar risk aversion is present in the science funding process. Many scientists are forced to specify years in advance what they intend to do, and spend their time continually applying for very short, small grants. However, it is the unexpected, the failures and the accidental, which are the inevitable cost and source of fruit in the scientific pursuit. It takes time, it takes long-term thinking, it takes flexibility. Peter Higgs, Nobel laureate who predicted the Higgs Boson, says he wouldn’t stand a chance of being funded today for lack of a track record. This leads scientists collectively to pursue incremental, low-risk, low-payoff work.

The current funding system is also top-down, prescriptive and homogenous, administered centrally from London. It is slow to respond to change and cut off from the real world.

We should return to funding university departments more directly, allowing more rapid, situation-aware decision-making of the kind present in start-ups, and create a diversity of funding systems. This is how the best research facilities in history operated, yet we do not learn their key lesson: that science cannot be managed by central edict, but flourishes through independent inquiry.

While Britain built much of modern science, today it neglects it, lagging behind other comparable nations in funding, and instead prioritising a financial industry prone to blowing up. Consider that we spent more money bailing out the banks in a single year than we have on science in the entirety of history.

We scarcely pause to consider the difference in return on investment. Rather than prop up old industries, we should invest in world-leading research institutes with a specific emphasis on high-risk, high-payoff research.

Those who say this is not government’s role fail the test of history. Much great science has come from government investment in times of crisis. Without Nasa, there would be no SpaceX. These government investments were used to provide a long-term, transformative vision on a scale that cannot be achieved through private investment alone – especially where there is a high risk of failure but high reward in success. The payoff of previous investments was enormous, so why not replicate the defence funding agencies that led to them with peacetime civilian equivalents?

In order to be the nation where new discoveries are made, we must take decisive steps to make the UK a magnet for talented young scientists.

However, a recent report on ensuring a successful UK research endeavour scarcely mentioned young scientists at all. An increased focus on this goal, alongside simple steps like long-term funding and guaranteed work visas for their spouses, would go a long way. In short, we should be to scientific innovation what we are to finance: a highly connected nerve centre for the global economy.

The political candidate that can leverage a pro-science platform to combine economic stimulus with the reality of economic pragmatism will transform the UK. We should lead the future by creating it.

James Phillips is a PhD student in neuroscience at the HHMI Janelia Research Campus in the US and the University of Cambridge. 
Matthew Phillips is a PhD student in neuroscience at the Sainsbury Wellcome Centre, University College London


UPDATE

Alan Kay, the brilliant researcher I mentioned above, happened to read this blog and posted this comment which I will also paste below here…

[From Alan Kay]

Good advice! However, I’m afraid that currently in the US there is nothing like the fabled Bell Labs or ARPA-PARC funding, at least in computing where I’m most aware of what is and is not happening (I’m the “Alan Kay” of the famous quote).

It is possible that things were still better a few years ago in the US than in the UK (I live in London half the year and in Los Angeles the other half). But I have some reasons to doubt. Since the new “president”, the US does not even have a science advisor, nor is there any sign of desire for one.

A visit to the classic Bell Labs of its heyday would reveal many things. One of the simplest was a sign posted randomly around: “Either do something very useful, or very beautiful”. Funders today won’t fund the second at all, and are afraid to fund at the risk level needed for the first.

It is difficult to sum up ARPA-PARC, but one interesting perspective on this kind of funding was that it was both long range and stratospherically visionary, and part of the vision was that good results included “better problems” (i.e. “problem finding” was highly valued and funded well) and good results included “good people” (i.e. long range funding should also create the next generations of researchers). in fact, virtually all of the researchers at Xerox PARC had their degrees funded by ARPA, they were “research results” who were able to get better research results.

Since the “D” was put on ARPA in the early 70s, it was then not able to do what it did in the 60s. NSF in the US never did this kind of funding. I spent quite a lot of time on some of the NSF Advisory Boards and it was pretty much impossible to bridge the gap between what was actually needed and the difficulties the Foundation has with congressional oversight (and some of the stipulations of their mission).

Bob Noyce (one of the founders of Intel) used to say “Wealth is created by Scientists, Engineers and Artists, everyone else just moves it around”.

Einstein said “We cannot solve important problems of the world using the same level of thinking we used to create them”.

A nice phrase by Vi Hart is “We must insure human wisdom exceeds human power”.

To make it to the 22nd century at all, and especially in better shape than we are now, we need to heed all three of these sayings, and support them as the civilization we are sometimes trying to become. It’s the only context in which “The best way to predict the future is to invent it” makes any useful sense.

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.’

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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.