January 2, 2020 by dominiccummings

‘Two hands are a lot’ — we’re hiring data scientists, project managers, policy experts, assorted weirdos…

‘This is possibly the single largest design flaw contributing to the bad Nash equilibrium in which … many governments are stuck. Every individual high-functioning competent person knows they can’t make much difference by being one more face in that crowd.’ Eliezer Yudkowsky, AI expert, LessWrong etc.

‘[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.’ Michael Nielsen, physicist and one of the handful of most interesting people I’ve ever talked to.

‘People, ideas, machines — in that order.’ Colonel Boyd.

‘There isn’t one novel thought in all of how Berkshire [Hathaway] is run. It’s all about … exploiting unrecognized simplicities.’ Charlie Munger,Warren Buffett’s partner.

‘Two hands, it isn’t much considering how the world is infinite. Yet, all the same, two hands, they are a lot.’ Alexander Grothendieck, one of the great mathematicians.

There are many brilliant people in the civil service and politics. Over the past five months the No10 political team has been lucky to work with some fantastic officials. But there are also some profound problems at the core of how the British state makes decisions. This was seen by pundit-world as a very eccentric view in 2014. It is no longer seen as eccentric. Dealing with these deep problems is supported by many great officials, particularly younger ones, though of course there will naturally be many fears — some reasonable, most unreasonable.

Now there is a confluence of: a) Brexit requires many large changes in policy and in the structure of decision-making, b) some people in government are prepared to take risks to change things a lot, and c) a new government with a significant majority and little need to worry about short-term unpopularity while trying to make rapid progress with long-term problems.

There is a huge amount of low hanging fruit — trillion dollar bills lying on the street — in the intersection of:

the selection, education and training of people for high performance
the frontiers of the science of prediction
data science, AI and cognitive technologies (e.g Seeing Rooms, ‘authoring tools designed for arguing from evidence’, Tetlock/IARPA prediction tournaments that could easily be extended to consider ‘clusters’ of issues around themes like Brexit to improve policy and project management)
communication (e.g Cialdini)
decision-making institutions at the apex of government.

We want to hire an unusual set of people with different skills and backgrounds to work in Downing Street with the best officials, some as spads and perhaps some as officials. If you are already an official and you read this blog and think you fit one of these categories, get in touch.

The categories are roughly:

Data scientists and software developers
Economists
Policy experts
Project managers
Communication experts
Junior researchers one of whom will also be my personal assistant
Weirdos and misfits with odd skills

We want to improve performance and make me much less important — and within a year largely redundant. At the moment I have to make decisions well outside what Charlie Munger calls my ‘circle of competence’ and we do not have the sort of expertise supporting the PM and ministers that is needed. This must change fast so we can properly serve the public.

A. Unusual mathematicians, physicists, computer scientists, data scientists

You must have exceptional academic qualifications from one of the world’s best universities or have done something that demonstrates equivalent (or greater) talents and skills. You do not need a PhD — as Alan Kay said, we are also interested in graduate students as ‘world-class researchers who don’t have PhDs yet’.

You should have the following:

PhD or MSc in maths or physics.
Outstanding mathematical skills are essential.
Experience of using analytical languages: e.g. Python, SQL, R.
Familiarity with data tools and technologies such as Postgres, Scikit Learn, NEO4J.

A few examples of papers that you will be considering:

This Nature paper, Early warning signals for critical transitions in a thermoacoustic system, looking at early warning systems in physics that could be applied to other areas from finance to epidemics.
Statistical & ML forecasting methods: Concerns and ways forward, Spyros Makridakis, 2018. This compares statistical and ML methods in a forecasting tournament (won by a hybrid stats/ML approach).
Complex Contagions : A Decade in Review, 2017. This looks at a large number of studies on ‘what goes viral and why?’. A lot of studies in this field are dodgy (bad maths, don’t replicate etc), an important question is which ones are worth examining.
Model-Free Prediction of Large Spatiotemporally Chaotic Systems from Data: A Reservoir Computing Approach, 2018. This applies ML to predict chaotic systems.
Scale-free networks are rare, Nature 2019. This looks at the question of how widespread scale-free networks really are and how useful this approach is for making predictions in diverse fields.
On the frequency and severity of interstate wars, 2019. ‘How can it be possible that the frequency and severity of interstate wars are so consistent with a stationary model, despite the enormous changes and obviously non-stationary dynamics in human population, in the number of recognized states, in commerce, communication, public health, and technology, and even in the modes of war itself? The fact that the absolute number and sizes of wars are plausibly stable in the face of these changes is a profound mystery for which we have no explanation.’ Does this claim stack up?
The papers on computational rationality below.
The work of Judea Pearl, the leading scholar of causation who has transformed the field.

You should be able to explain to other mathematicians, physicists and computer scientists the ideas in such papers, discuss what could be useful for our projects, synthesise ideas for other data scientists, and apply them to practical problems. You won’t be expert on the maths used in all these papers but you should be confident that you could study it and understand it.

We will be using machine learning and associated tools so it is important you can program. You do not need software development levels of programming but it would be an advantage.

Those applying must watch Bret Victor’s talks and study Dynamic Land. If this excites you, then apply; if not, then don’t. I and others interviewing will discuss this with anybody who comes for an interview. If you want a sense of the sort of things you’d be working on, then read my previous blog on Seeing Rooms, cognitive technologies etc.

B. Unusual software developers

We are looking for great software developers who would love to work on these ideas, build tools and work with some great people. You should also look at some of Victor’s technical talks on programming languages and the history of computing.

You will be working with data scientists, designers and others.

C. Unusual economists

We are looking to hire some recent graduates in economics. You should a) have an outstanding record at a great university, b) understand conventional economic theories, c) be interested in arguments on the edge of the field — for example, work by physicists on ‘agent-based models’ or by the hedge fund Bridgewater on the failures/limitations of conventional macro theories/prediction, and d) have very strong maths and be interested in working with mathematicians, physicists, and computer scientists.

The ideal candidate might, for example, have a degree in maths and economics, worked at the LHC in one summer, worked with a quant fund another summer, and written software for a YC startup in a third summer!

We’ve found one of these but want at least one more.

The sort of conversation you might have is discussing these two papers in Science (2015): Computational rationality: A converging paradigm for intelligence in brains, minds, and machines, Gershman et al and Economic reasoning and artificial intelligence, Parkes & Wellman.

You will see in these papers an intersection of:

von Neumann’s foundation of game theory and ‘expected utility’,
mainstream economic theories,
modern theories about auctions,
theoretical computer science (including problems like the complexity of probabilistic inference in Bayesian networks, which is in the NP–hard complexity class),
ideas on ‘computational rationality’ and meta-reasoning from AI, cognitive science and so on.

If these sort of things are interesting, then you will find this project interesting.

It’s a bonus if you can code but it isn’t necessary.

D. Great project managers.

If you think you are one of the a small group of people in the world who are truly GREAT at project management, then we want to talk to you. Victoria Woodcock ran Vote Leave — she was a truly awesome project manager and without her Cameron would certainly have won. We need people like this who have a 1 in 10,000 or higher level of skill and temperament.

The Oxford Handbook on Megaprojects points out that it is possible to quantify lessons from the failures of projects like high speed rail projects because almost all fail so there is a large enough sample to make statistical comparisons, whereas there can be no statistical analysis of successes because they are so rare.

It is extremely interesting that the lessons of Manhattan (1940s), ICBMs (1950s) and Apollo (1960s) remain absolutely cutting edge because it is so hard to apply them and almost nobody has managed to do it. The Pentagon systematically de-programmed itself from more effective approaches to less effective approaches from the mid-1960s, in the name of ‘efficiency’. Is this just another way of saying that people like General Groves and George Mueller are rarer than Fields Medallists?

Anyway — it is obvious that improving government requires vast improvements in project management. The first project will be improving the people and skills already here.

If you want an example of the sort of people we need to find in Britain, look at this on CC Myers — the legendary builders. SPEED. We urgently need people with these sort of skills and attitude. (If you think you are such a company and you could dual carriageway the A1 north of Newcastle in record time, then get in touch!)

E. Junior researchers

In many aspects of government, as in the tech world and investing, brains and temperament smash experience and seniority out of the park.

We want to hire some VERY clever young people either straight out of university or recently out with with extreme curiosity and capacity for hard work.

One of you will be a sort of personal assistant to me for a year — this will involve a mix of very interesting work and lots of uninteresting trivia that makes my life easier which you won’t enjoy. You will not have weekday date nights, you will sacrifice many weekends — frankly it will hard having a boy/girlfriend at all. It will be exhausting but interesting and if you cut it you will be involved in things at the age of ~21 that most people never see.

I don’t want confident public school bluffers. I want people who are much brighter than me who can work in an extreme environment. If you play office politics, you will be discovered and immediately binned.

F. Communications

In SW1 communication is generally treated as almost synonymous with ‘talking to the lobby’. This is partly why so much punditry is ‘narrative from noise’.

With no election for years and huge changes in the digital world, there is a chance and a need to do things very differently.

We’re particularly interested in deep experts on TV and digital. We also are interested in people who have worked in movies or on advertising campaigns. There are some very interesting possibilities in the intersection of technology and story telling — if you’ve done something weird, this may be the place for you.

I noticed in the recent campaign that the world of digital advertising has changed very fast since I was last involved in 2016. This is partly why so many journalists wrongly looked at things like Corbyn’s Facebook stats and thought Labour was doing better than us — the ecosystem evolves rapidly while political journalists are still behind the 2016 tech, hence why so many fell for Carole’s conspiracy theories. The digital people involved in the last campaign really knew what they are doing, which is incredibly rare in this world of charlatans and clients who don’t know what they should be buying. If you are interested in being right at the very edge of this field, join.

We have some extremely able people but we also must upgrade skills across the spad network.

G. Policy experts

One of the problems with the civil service is the way in which people are shuffled such that they either do not acquire expertise or they are moved out of areas they really know to do something else. One Friday, X is in charge of special needs education, the next week X is in charge of budgets.

There are, of course, general skills. Managing a large organisation involves some general skills. Whether it is Coca Cola or Apple, some things are very similar — how to deal with people, how to build great teams and so on. Experience is often over-rated. When Warren Buffett needed someone to turn around his insurance business he did not hire someone with experience in insurance: ‘When Ajit entered Berkshire’s office on a Saturday in 1986, he did not have a day’s experience in the insurance business’ (Buffett).

Shuffling some people who are expected to be general managers is a natural thing but it is clear Whitehall does this too much while also not training general management skills properly. There are not enough people with deep expertise in specific fields.

If you want to work in the policy unit or a department and you really know your subject so that you could confidently argue about it with world-class experts, get in touch.

It’s also the case that wherever you are most of the best people are inevitably somewhere else. This means that governments must be much better at tapping distributed expertise. Of the top 20 people in the world who best understand the science of climate change and could advise us what to do with COP 2020, how many now work as a civil servant/spad or will become one in the next 5 years?

G. Super-talented weirdos

People in SW1 talk a lot about ‘diversity’ but they rarely mean ‘true cognitive diversity’. They are usually babbling about ‘gender identity diversity blah blah’. What SW1 needs is not more drivel about ‘identity’ and ‘diversity’ from Oxbridge humanities graduates but more genuine cognitive diversity.

We need some true wild cards, artists, people who never went to university and fought their way out of an appalling hell hole, weirdos from William Gibson novels like that girl hired by Bigend as a brand ‘diviner’ who feels sick at the sight of Tommy Hilfiger or that Chinese-Cuban free runner from a crime family hired by the KGB. If you want to figure out what characters around Putin might do, or how international criminal gangs might exploit holes in our border security, you don’t want more Oxbridge English graduates who chat about Lacan at dinner parties with TV producers and spread fake news about fake news.

By definition I don’t really know what I’m looking for but I want people around No10 to be on the lookout for such people.

We need to figure out how to use such people better without asking them to conform to the horrors of ‘Human Resources’ (which also obviously need a bonfire).

Send a max 1 page letter plus CV to ideasfornumber10@gmail.com and put in the subject line ‘job/’ and add after the / one of: data, developer, econ, comms, projects, research, policy, misfit.

I’ll have to spend time helping you so don’t apply unless you can commit to at least 2 years.

I’ll bin you within weeks if you don’t fit — don’t complain later because I made it clear now.

I will try to answer as many as possible but last time I publicly asked for job applications in 2015 I was swamped and could not, so I can’t promise an answer. If you think I’ve insanely ignored you, persist for a while.

I will use this blog to throw out ideas. It’s important when dealing with large organisations to dart around at different levels, not be stuck with formal hierarchies. It will seem chaotic and ‘not proper No10 process’ to some. But the point of this government is to do things differently and better and this always looks messy. We do not care about trying to ‘control the narrative’ and all that New Labour junk and this government will not be run by ‘comms grid’.

As Paul Graham and Peter Thiel say, most ideas that seem bad are bad but great ideas also seem at first like bad ideas — otherwise someone would have already done them. Incentives and culture push people in normal government systems away from encouraging ‘ideas that seem bad’. Part of the point of a small, odd No10 team is to find and exploit, without worrying about media noise, what Andy Grove called ‘very high leverage ideas’ and these will almost inevitably seem bad to most.

I will post some random things over the next few weeks and see what bounces back — it is all upside, there’s no downside if you don’t mind a bit of noise and it’s a fast cheap way to find good ideas…

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.

May 22, 2018 by dominiccummings

Effective action #4a: ‘Expertise’ from fighting and physics to economics, politics and government

‘We learn most when we have the most to lose.’ Michael Nielsen, author of the brilliant book Reinventing Discovery.

‘There isn’t one novel thought in all of how Berkshire [Hathaway] is run. It’s all about … exploiting unrecognized simplicities…Warren [Buffett] and I aren’t prodigies.We can’t play chess blindfolded or be concert pianists. But the results are prodigious, because we have a temperamental advantage that more than compensates for a lack of IQ points.’ Charlie Munger,Warren Buffett’s partner.

I’m going to do a series of blogs on the differences between fields dominated by real expertise (like fighting and physics) and fields dominated by bogus expertise (like macroeconomic forecasting, politics/punditry, active fund management).

Fundamental to real expertise is 1) whether the informational structure of the environment is sufficiently regular that it’s possible to make good predictions and 2) does it allow high quality feedback and therefore error-correction. Physics and fighting: Yes. Predicting recessions, forex trading and politics: not so much. I’ll look at studies comparing expert performance in different fields and the superior performance of relatively very simple models over human experts in many fields.

This is useful background to consider a question I spend a lot of time thinking about: how to integrate a) ancient insights and modern case studies about high performance with b) new technology and tools in order to improve the quality of individual, team, and institutional decision-making in politics and government.

I think that fixing the deepest problems of politics and government requires a more general and abstract approach to principles of effective action than is usually considered in political discussion and such an approach could see solutions to specific problems almost magically appear, just as you see happen in a very small number of organisations — e.g Mueller’s Apollo program (man on the moon), PARC (interactive computing), Berkshire Hathaway (most successful investors in history), all of which have delivered what seems almost magical performance because they embody a few simple, powerful, but largely unrecognised principles. There is no ‘solution’ to the fundamental human problem of decision-making amid extreme complexity and uncertainty but we know a) there are ways to do things much better and b) governments mostly ignore them, so there is extremely valuable low-hanging fruit if, but it’s a big if, we can partially overcome the huge meta-problem that governments tend to resist the institutional changes needed to become a learning system.

This blog presents some basic background ideas and examples…

Extreme sports: fast feedback = real expertise

In the 1980s and early 1990s, there was an interesting case study in how useful new knowledge jumped from a tiny isolated group to the general population with big effects on performance in a community. Expertise in Brazilian jiu-jitsu was taken from Brazil to southern California by the Gracie family. There were many sceptics but they vanished rapidly because the Gracies were empiricists. They issued ‘the Gracie challenge’.

All sorts of tough guys, trained in all sorts of ways, were invited to come to their garage/academy in Los Angeles to fight one of the Gracies or their trainees. Very quickly it became obvious that the Gracie training system was revolutionary and they were real experts because they always won. There was very fast and clear feedback on predictions. Gracie jiujitsu quickly jumped from an LA garage to TV. At the televised UFC 1 event in 1993 Royce Gracie defeated everyone and a multi-billion dollar business was born.

People could see how training in this new skill could transform performance. Unarmed combat changed across the world. Disciplines other than jiu jitsu have had to make a choice: either isolate themselves and not compete with jiu jitsu or learn from it. If interested watch the first twenty minutes of this documentary (via professor Steve Hsu, physicist, amateur jiu jitsu practitioner, and predictive genomics expert).

Video: Jiu Jitsu comes to Southern California

Royce Gracie, UFC 1 1993

Screenshot 2018-05-22 10.41.20

Flow, deep in the zone

Another field where there is clear expertise is extreme skiing and snowboarding. One of the leading pioneers, Jeremy Jones, describes how he rides ‘spines’ hurtling down the side of mountains:

‘The snow is so deep you need to use your arms and chest to swim, and your legs to ride. They also collapse underfoot, so you’re riding mini-avalanches and dodging slough slides. Spines have blind rollovers, so you can’t see below. Or to the side. Every time the midline is crossed, it’s a leap into the abyss. Plus, there’s no way to stop and every move is amplified by complicated forces. A tiny hop can easily become a twenty-foot ollie. It’s the absolute edge of chaos. But the easiest way to live in the moment is to put yourself in a situation where there’s no other choice. Spines demand that, they hurl you deep into the zone.’ Emphasis added.

Video: Snowboarder Jeremy Jones

What Jones calls ‘the zone’ is also known as ‘flow‘ — a particular mental state, triggered by environmental cues, that brings greatly enhanced performance. It is the object of study in extreme sports and by the military and intelligence services: for example DARPA is researching whether stimulating the brain can trigger ‘flow’ in snipers.

Flow — or control on ‘the edge of chaos’ where ‘every move is amplified by complicated forces’ — comes from training in which people learn from very rapid feedback between predictions and reality. In ‘flow’, brains very rapidly and accurately process environmental signals and generate hypothetical scenarios/predictions and possible solutions based on experience and training. Jones’s performance is inseparable from developing this fingertip feeling. Similarly, an expert fireman feels the glow of heat on his face in a slightly odd way and runs out of the building just before it collapses without consciously knowing why he did it: his intuition has been trained to learn from feedback and make predictions. Experts operating in ‘flow’ do not follow what is sometimes called the ‘rational model’ of decision-making in which they sequentially interrogate different options — they pattern-match solutions extremely quickly based on experience and intuition.

The video below shows extreme expertise in a state of ‘flow’ with feedback on predictions within milliseconds. This legendary ride is so famous not because of the size of the wave but its odd, and dangerous, nature. If you watch carefully you will see what a true expert in ‘flow’ can do: after committing to the wave Hamilton suddenly realises that unless he reaches back with the opposite hand to normal and drags it against the wall of water behind him, he will get sucked up the wave and might die. (This wave had killed someone a few weeks earlier.) Years of practice and feedback honed the intuition that, when faced with a very dangerous and fast moving problem, almost instantly (few seconds maximum) pattern-matched an innovative solution.

Video: surfer Laird Hamilton in one of the greatest ever rides

The faster the feedback cycle, the more likely you are to develop a qualitative improvement in speed that destroys an opponent’s decision-making cycle. If you can reorient yourself faster to the ever-changing environment than your opponent, then you operate inside their ‘OODA loop’ (Observe-Orient-Decide-Act) and the opponent’s performance can quickly degrade and collapse.

This lesson is vital in politics. You can read it in Sun Tzu and see it with Alexander the Great. Everybody can read such lessons and most people will nod along. But it is very hard to apply because most political/government organisations are programmed by their incentives to prioritise seniority, process and prestige over high performance and this slows and degrades decisions. Most organisations don’t do it. Further, political organisations tend to make too slowly those decisions that should be fast and too quickly those decisions that should be slow — they are simultaneously both too sluggish and too impetuous, which closes off favourable branching histories of the future.

Video: Boxer Floyd Mayweather, best fighter of his generation and one of the quickest and best defensive fighters ever

The most extreme example in extreme sports is probably ‘free soloing’ — climbing mountains without ropes where one mistake means instant death. If you want to see an example of genuine expertise and the value of fast feedback then watch Alex Honnold.

Video: Alex Honnold ‘free solos’ El Sendero Luminoso (terrifying)

Music is similar to sport. There is very fast feedback, learning, and a clear hierarchy of expertise.

Video: Glenn Gould playing the Goldberg Variations (slow version)

Our culture treats expertise/high performance in fields like sport and music very differently to maths/science education and politics/government. As Alan Kay observes, music and sport expertise is embedded in the broader culture. Millions of children spend large amounts of time practising hard skills. Attacks on them as ‘elitist’ don’t get the same damaging purchase as in other fields and the public don’t mind about elite selection for sports teams or orchestras.

‘Two ideas about this are that a) these [sport/music] are activities in which the basic act can be seen clearly from the first, and b) are already part of the larger culture. There are levels that can be seen to be inclusive starting with modest skills. I think a very large problem for the learning of both science and math is just how invisible are their processes, especially in schools.’ Kay

When it comes to maths and science education, the powers-that-be (in America and Britain) try very hard and mostly successfully to ignore the question: where are critical thresholds for valuable skills that develop true expertise. This is even more a problem with the concept of ‘thinking rationally’, for which some basic logic, probability, and understanding of scientific reasoning is a foundation. Discussion of politics and government almost totally ignores the concept of training people to update their opinions in response to new evidence — i.e adapt to feedback. The ‘rationalist community’ — people like Scott Alexander who wrote this fantastic essay (Moloch) about why so much goes wrong, or the recent essays by Eliezer Yudkowsky — are ignored at the apex of power. I will return to the subject of how to create new education and training programmes for elite decision-makers. It is a good time for UK universities to innovate in this field, as places like Stanford are already doing. Instead of training people like Cameron and Adonis to bluff with PPE, we need courses that combine rational thinking with practical training in managing complex projects. We need people who practice really hard making predictions in ways we know work well (cf. Tetlock) then update in response to errors.

A more general/abstract approach to reforming government

If we want to get much higher performance in government, then we need to think rigorously about: the selection of people and teams, their education and training, their tools, and the institutions (incentives and so on) that surround and shape them.

Almost all analysis of politics and government considers relatively surface phenomena. For example, the media briefly blasts headlines about Carillion’s collapse or our comical aircraft carriers but there is almost no consideration of the deep reasons for such failures and therefore nothing tends to happen — the media caravan moves on and the officials and ministers keep failing in the same ways. This is why, for example, the predicted abject failure of the traditional Westminster machinery to cope with Brexit negotiations has not led to self-examination and learning but, instead, mostly to a visible determination across both sides of the Brexit divide in SW1 to double down on long-held delusions.

Progress requires attacking the ‘system of systems’ problem at the right ‘level’. Attacking the problems directly — let’s improve policy X and Y, let’s swap ‘incompetent’ A for ‘competent’ B — cannot touch the core problems, particularly the hardest meta-problem that government systems bitterly fight improvement. Solving the explicit surface problems of politics and government is best approached by a more general focus on applying abstract principles of effective action. We need to surround relatively specific problems with a more general approach. Attack at the right level will see specific solutions automatically ‘pop out’ of the system. One of the most powerful simplicities in all conflict (almost always unrecognised) is: ‘winning without fighting is the highest form of war’. If we approach the problem of government performance at the right level of generality then we have a chance to solve specific problems ‘without fighting’ — or, rather, without fighting nearly so much and the fighting will be more fruitful.

This is not a theoretical argument. If you look carefully at ancient texts and modern case studies, you see that applying a small number of very simple, powerful, but largely unrecognised principles (that are very hard for organisations to operationalise) can produce extremely surprising results.

We have no alternative to trying. Without fundamental changes to government, we will lose our hourly game of Russian roulette with technological progress.

‘The combination of physics and politics could render the surface of the earth uninhabitable… [T]he ever accelerating progress of technology and changes in the mode of human life … gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue.’ John von Neumann

As Steve Hsu says: Pessimism of the Intellect, Optimism of the Will.

Ps. There is an interesting connection between the nature of counterfactual reasoning in the fast-moving world of extreme sports and the theoretical paper I posted yesterday on state-of-the-art AI. The human ability to interrogate stored representations of their environment with counter-factual questions is fundamental to the nature of intelligence and developing expertise in physical and mental skills. It is, for now, absent in machines.

June 16, 2017 by dominiccummings

Complexity and Prediction Part V: The crisis of mathematical paradoxes, Gödel, Turing and the basis of computing

Before the referendum I started a series of blogs and notes exploring the themes of complexity and prediction. This was part of a project with two main aims: first, to sketch a new approach to education and training in general but particularly for those who go on to make important decisions in political institutions and, second, to suggest a new approach to political priorities in which progress with education and science becomes a central focus for the British state. The two are entangled: progress with each will hopefully encourage progress with the other.

I was working on this paper when I suddenly got sidetracked by the referendum and have just looked at it again for the first time in about two years.

The paper concerns a fascinating episode in the history of ideas that saw the most esoteric and unpractical field, mathematical logic, spawn a revolutionary technology, the modern computer. NB. a great lesson to science funders: it’s a great mistake to cut funding on theory and assume that you’ll get more bang for buck from ‘applications’.

Apart from its inherent fascination, knowing something of the history is helpful for anybody interested in the state-of-the-art in predicting complex systems which involves the intersection between different fields including: maths, computer science, economics, cognitive science, and artificial intelligence. The books on it are either technical, and therefore inaccessible to ~100% of the population, or non-chronological so it is impossible for someone like me to get a clear picture of how the story unfolded.

Further, there are few if any very deep ideas in maths or science that are so misunderstood and abused as Gödel’s results. As Alan Sokal, author of the brilliant hoax exposing post-modernist academics, said, ‘Gödel’s theorem is an inexhaustible source of intellectual abuses.’ I have tried to make clear some of these using the best book available by Franzen, which explains why almost everything you read about it is wrong. If even Stephen Hawking can cock it up, the rest of us should be particularly careful.

I sketched these notes as I tried to pull together the story from many different books. I hope they are useful particularly for some 15-25 year-olds who like chronological accounts about ideas. I tried to put the notes together in the way that I wish I had been able to read at that age. I tried hard to eliminate errors but they are inevitable given how far I am from being competent to write about such things. I wish someone who is competent would do it properly. It would take time I don’t now have to go through and finish it the way I originally intended to so I will just post it as it was 2 years ago when I got calls saying ‘about this referendum…’

The only change I think I have made since May 2015 is to shove in some notes from a great essay later that year by the man who wrote the textbook on quantum computers, Michael Nielsen, which would be useful to read as an introduction or instead, HERE.

As always on this blog there is not a single original thought and any value comes from the time I have spent condensing the work of others to save you the time. Please leave corrections in comments.

The PDF of the paper is HERE (amended since first publication to correct an error, see Comments).

‘Gödel’s achievement in modern logic is singular and monumental – indeed it is more than a monument, it is a land mark which will remain visible far in space and time.’ John von Neumann.

‘Einstein had often told me that in the late years of his life he has continually sought Gödel’s company in order to have discussions with him. Once he said to me that his own work no longer meant much, that he came to the Institute merely in order to have the privilege of walking home with Gödel.’ Oskar Morgenstern (co-author with von Neumann of the first major work on Game Theory).

‘The world is rational’, Kurt Gödel.

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

January 14, 2017 by dominiccummings

Please help: how to make a big improvement in the alignment of political parties’ incentives with the public interest?

I am interested in these questions:

1) What incentives drive good/bad behaviour for UK political parties?

2) How could they be changed (legal and non-legal) to align interests of existing parties better with the public interest?

3) If one were setting up a new party from scratch what principles could be established in order to align the party’s interests with the public interest much more effectively than is now the case anywhere in the world, and how could one attract candidates very different to those who now dominate Parliament (cleverer, quantitative problem-solving skills, experience in managing complex organisations etc)?

4) Is there a good case for banning political parties (as sometimes was attempted in ancient Greece), how to do it, what would replace them, why would this be better etc (I assume this is a bad and/or impractical idea but it’s worth asking why)?

5) In what ways do existing or plausible technologies affect these old questions?

What are the best things written on these problems?

What are the best examples around the world of how people have made big improvements?

Assume that financial resources are effectively unlimited for the entity trying to make these changes, let me worry about things like ‘would the public buy it’ etc – focus on policy not communication/PR advice.

The more specific the better: an ideal bit of help would be detailed draft legislation. I don’t expect anybody to produce this, but just to show what I mean…

The overall problem is: how to make government performance dramatically, quantifiably, and sustainably better?

Please leave ideas in comments or email dmc2.cummings@gmail.com

Thanks

January 13, 2017 by dominiccummings

Unrecognised simplicities of effective action #1: expertise and a quadrillion dollar business

‘The combination of physics and politics could render the surface of the earth uninhabitable.’ John von Neumann.

Introduction

This series of blogs considers:

the difference between fields with genuine expertise, such as fighting and physics, and fields dominated by bogus expertise, such as politics and economic forecasting;
the big big problem we face – the world is ‘undersized and underorganised’ because of a collision between four forces: 1) our technological civilisation is inherently fragile and vulnerable to shocks, 2) the knowledge it generates is inherently dangerous, 3) our evolved instincts predispose us to aggression and misunderstanding, and 4) there is a profound mismatch between the scale and speed of destruction our knowledge can cause and the quality of individual and institutional decision-making in ‘mission critical’ institutions – our institutions are similar to those that failed so spectacularly in summer 1914 yet they face crises moving at least ~10³ times faster and involving ~10⁶ times more destructive power able to kill ~10¹⁰ people;
what classic texts and case studies suggest about the unrecognised simplicities of effective action to improve the selection, education, training, and management of vital decision-makers to improve dramatically, reliably, and quantifiably the quality of individual and institutional decisions (particularly 1) the ability to make accurate predictions and b) the quality of feedback);
how we can change incentives to aim a much bigger fraction of the most able people at the most important problems;
what tools and technologies can help decision-makers cope with complexity.

[I’ve tweaked a couple of things in response to this blog by physicist Steve Hsu.]

Summary of the big big problem

The investor Peter Thiel (founder of PayPal and Palantir, early investor in Facebook) asks people in job interviews: what billion (10⁹) dollar business is nobody building? The most successful investor in world history, Warren Buffett, illustrated what a quadrillion (10¹⁵) dollar business might look like in his 50th anniversary letter to Berkshire Hathaway investors.

‘There is, however, one clear, present and enduring danger to Berkshire against which Charlie and I are powerless. That threat to Berkshire is also the major threat our citizenry faces: a “successful” … cyber, biological, nuclear or chemical attack on the United States… The probability of such mass destruction in any given year is likely very small… Nevertheless, what’s a small probability in a short period approaches certainty in the longer run. (If there is only one chance in thirty of an event occurring in a given year, the likelihood of it occurring at least once in a century is 96.6%.) The added bad news is that there will forever be people and organizations and perhaps even nations that would like to inflict maximum damage on our country. Their means of doing so have increased exponentially during my lifetime. “Innovation” has its dark side.

‘There is no way for American corporations or their investors to shed this risk. If an event occurs in the U.S. that leads to mass devastation, the value of all equity investments will almost certainly be decimated.

‘No one knows what “the day after” will look like. I think, however, that Einstein’s 1949 appraisal remains apt: “I know not with what weapons World War III will be fought, but World War IV will be fought with sticks and stones.”’

Politics is profoundly nonlinear. (I have written a series of blogs about complexity and prediction HERE which are useful background for those interested.) Changing the course of European history via the referendum only involved about 10 crucial people controlling ~£10⁷ while its effects over ten years could be on the scale of ~10⁸ – 10⁹people and ~£10¹²: like many episodes in history the resources put into it are extremely nonlinear in relation to the potential branching histories it creates. Errors dealing with Germany in 1914 and 1939 were costly on the scale of ~100,000,000 (10⁸) lives. If we carry on with normal human history – that is, international relations defined as out-groups competing violently – and combine this with modern technology then it is extremely likely that we will have a disaster on the scale of billions (10⁹) or even all humans (~10¹⁰). The ultimate disaster would kill about 100 times more people than our failure with Germany. Our destructive power is already much more than 100 times greater than it was then: nuclear weapons increased destructiveness by roughly a factor of a million.

Even if we dodge this particular bullet there are many others lurking. New genetic engineering techniques such as CRISPR allow radical possibilities for re-engineering organisms including humans in ways thought of as science fiction only a decade ago. We will soon be able to remake human nature itself. CRISPR-enabled ‘gene drives’ enable us to make changes to the germ-line of organisms permanent such that changes spread through the entire wild population, including making species extinct on demand. Unlike nuclear weapons such technologies are not complex, expensive, and able to be kept secret for a long time. The world’s leading experts predict that people will be making them cheaply at home soon – perhaps they already are. These developments have been driven by exponential progress much faster than Moore’s Law reducing the cost of DNA sequencing per genome from ~$10⁸ to ~$10³in roughly 15 years.

screenshot-2017-01-16-12-24-13

It is already practically possible to deploy a cheap, autonomous, and anonymous drone with facial-recognition software and a one gram shaped-charge to identify a relevant face and blow it up. Military logic is driving autonomy. For example, 1) the explosion in the volume of drone surveillance video (from 71 hours in 2004 to 300,000 hours in 2011 to millions of hours now) requires automated analysis, and 2) jamming and spoofing of drones strongly incentivise a push for autonomy. It is unlikely that promises to ‘keep humans in the loop’ will be kept. It is likely that state and non-state actors will deploy low-cost drone swarms using machine learning to automate the ‘find-fix-finish’ cycle now controlled by humans. (See HERE for a video just released for one such program and imagine the capability when they carry their own communication and logistics network with them.)

In the medium-term, many billions are being spent on finding the secrets of general intelligence. We know this secret is encoded somewhere in the roughly 125 million ‘bits’ of information that is the rough difference between the genome that produces the human brain and the genome that produces the chimp brain. This search space is remarkably small – the equivalent of just 25 million English words or 30 copies of the King James Bible. There is no fundamental barrier to decoding this information and it is possible that the ultimate secret could be described relatively simply (cf. this great essay by physicist Michael Nielsen). One of the world’s leading experts has told me they think a large proportion of this problem could be solved in about a decade with a few tens of billions and something like an Apollo programme level of determination.

Not only is our destructive and disruptive power still getting bigger quickly – it is also getting cheaper and faster every year. The change in speed adds another dimension to the problem. In the period between the Archduke’s murder and the outbreak of World War I a month later it is striking how general failures of individuals and institutions were compounded by the way in which events moved much faster than the ‘mission critical’ institutions could cope with such that soon everyone was behind the pace, telegrams were read in the wrong order and so on. The crisis leading to World War I was about 30 days from the assassination to the start of general war – about 700 hours. The timescale for deciding what to do between receiving a warning of nuclear missile launch and deciding to launch yourself is less than half an hour and the President’s decision time is less than this, maybe just minutes. This is a speedup factor of at least 10³.

Economic crises already occur far faster than human brains can cope with. The financial system has made a transition from people shouting at each other to a a system dominated by high frequency ‘algorithmic trading’ (HFT), i.e. machine intelligence applied to robot trading with vast volumes traded on a global spatial scale and a microsecond (10^-6) temporal scale far beyond the monitoring, understanding, or control of regulators and politicians. There is even competition for computer trading bases in specific locations based on calculations of Special Relativity as the speed of light becomes a factor in minimising trade delays (cf. Relativistic statistical arbitrage, Wissner-Gross). ‘The Flash Crash’ of 9 May 2010 saw the Dow lose hundreds of points in minutes. Mini ‘flash crashes’ now blow up and die out faster than humans can notice. Given our institutions cannot cope with economic decisions made at ‘human speed’, a fortiori they cannot cope with decisions made at ‘robot speed’. There is scope for worse disasters than 2008 which would further damage the moral credibility of decentralised markets and provide huge chances for extremist political entrepreneurs to exploit. (* See endnote.)

What about the individuals and institutions that are supposed to cope with all this?

Our brains have not evolved much in thousands of years and are subject to all sorts of constraints including evolved heuristics that lead to misunderstanding, delusion, and violence particularly under pressure. There is a terrible mismatch between the sort of people that routinely dominate mission critical political institutions and the sort of people we need: high-ish IQ (we need more people >145 (+3SD) while almost everybody important is between 115-130 (+1 or 2SD)), a robust toolkit for not fooling yourself including quantitative problem-solving (almost totally absent at the apex of relevant institutions), determination, management skills, relevant experience, and ethics. While our ancestor chiefs at least had some intuitive feel for important variables like agriculture and cavalry our contemporary chiefs (and those in the media responsible for scrutiny of decisions) generally do not understand their equivalents, and are often less experienced in managing complex organisations than their predecessors.

The national institutions we have to deal with such crises are pretty similar to those that failed so spectacularly in summer 1914 yet they face crises moving at least ~10³ times faster and involving ~10⁶ times more destructive power able to kill ~10¹⁰ people. The international institutions developed post-1945 (UN, EU etc) contribute little to solving the biggest problems and in many ways make them worse. These institutions fail constantly and do not – cannot – learn much.

If we keep having crises like we have experienced over the past century then this combination of problems pushes the probability of catastrophe towards ‘overwhelmingly likely’.

What Is To be Done? There’s plenty of room at the top

‘In a knowledge-rich world, progress does not lie in the direction of reading information faster, writing it faster, and storing more of it. Progress lies in the direction of extracting and exploiting the patterns of the world… And that progress will depend on … our ability to devise better and more powerful thinking programs for man and machine.’ Herbert Simon, Designing Organizations for an Information-rich World, 1969.

‘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 engineering’ and ‘systems management’ and the man most responsible for the success of the 1969 moon landing.

Somehow the world has to make a series of extremely traumatic and dangerous transitions over the next 20 years. The main transition needed is:

Embed reliably the unrecognised simplicities of high performance teams (HPTs), including personnel selection and training, in ‘mission critical’ institutions while simultaneously developing a focused project that radically improves the prospects for international cooperation and new forms of political organisation beyond competing nation states.

Big progress on this problem would automatically and for free bring big progress on other big problems. It could improve (even save) billions of lives and save a quadrillion dollars (~$10¹⁵). If we avoid disasters then the error-correcting institutions of markets and science will, patchily, spread peace, prosperity, and learning. We will make big improvements with public services and other aspects of ‘normal’ government. We will have a healthier political culture in which representative institutions, markets serving the public (not looters), and international cooperation are stronger.

Can a big jump in performance – ‘better and more powerful thinking programs for man and machine’ – somehow be systematised?

Feynman once gave a talk titled ‘There’s plenty of room at the bottom’ about the huge performance improvements possible if we could learn to do engineering at the atomic scale – what is now called nanotechnology. There is also ‘plenty of room at the top’ of political structures for huge improvements in performance. As I explained recently, the victory of the Leave campaign owed more to the fundamental dysfunction of the British Establishment than it did to any brilliance from Vote Leave. Despite having the support of practically every force with power and money in the world (including the main broadcasters) and controlling the timing and legal regulation of the referendum, they blew it. This was good if you support Leave but just how easily the whole system could be taken down should be frightening for everybody .

Creating high performance teams is obviously hard but in what ways is it really hard? It is not hard in the same sense that some things are hard like discovering profound new mathematical knowledge. HPTs do not require profound new knowledge. We have been able to read the basic lessons in classics for over two thousand years. We can see relevant examples all around us of individuals and teams showing huge gains in effectiveness.

The real obstacle is not financial. The financial resources needed are remarkably low and the return on small investments could be incalculably vast. We could significantly improve the decisions of the most powerful 100 people in the UK or the world for less than a million dollars (~£10⁶) and a decade-long project on a scale of just ~£10⁷could have dramatic effects.

The real obstacle is not a huge task of public persuasion – quite the opposite. A government that tried in a disciplined way to do this would attract huge public support. (I’ve polled some ideas and am confident about this.) Political parties are locked in a game that in trying to win in conventional ways leads to the public despising them. Ironically if a party (established or new) forgets this game and makes the public the target of extreme intelligent focus then it would not only make the world better but would trounce their opponents.

The real obstacle is not a need for breakthrough technologies though technology could help. As Colonel Boyd used to shout, ‘People, ideas, machines – in that order!’

The real obstacle is that although we can all learn and study HPTs it is extremely hard to put this learning to practical use and sustain it against all the forces of entropy that constantly operate to degrade high performance once the original people have gone. HPTs are episodic. They seem to come out of nowhere, shock people, then vanish with the rare individuals. People write about them and many talk about learning from them but in fact almost nobody ever learns from them – apart, perhaps, from those very rare people who did not need to learn – and nobody has found a method to embed this learning reliably and systematically in institutions that can maintain it. The Prussian General Staff remained operationally brilliant but in other ways went badly wrong after the death of the elder Moltke. When George Mueller left NASA it reverted to what it had been before he arrived – management chaos. All the best companies quickly go downhill after the departure of people like Bill Gates – even when such very able people have tried very very hard to avoid exactly this problem.

Charlie Munger, half of the most successful investment team in world history, has a great phrase he uses to explain their success that gets to the heart of this problem:

‘There isn’t one novel thought in all of how Berkshire [Hathaway] is run. It’s all about … exploiting unrecognized simplicities… It’s a community of like-minded people, and that makes most decisions into no-brainers. Warren [Buffett] and I aren’t prodigies. We can’t play chess blindfolded or be concert pianists. But the results are prodigious, because we have a temperamental advantage that more than compensates for a lack of IQ points.’

The simplicities that bring high performance in general, not just in investing, are largely unrecognised because they conflict with many evolved instincts and are therefore psychologically very hard to implement. The principles of the Buffett-Munger success are clear – they have even gone to great pains to explain them and what the rest of us should do – and the results are clear yet still almost nobody really listens to them and above average intelligence people instead constantly put their money into active fund management that is proved to destroy wealth every year!

Most people think they are already implementing these lessons and usually strongly reject the idea that they are not. This means that just explaining things is very unlikely to work:

‘I’d say the history that Charlie [Munger] and I have had of persuading decent, intelligent people who we thought were doing unintelligent things to change their course of action has been poor.’ Buffett.

Even more worrying, it is extremely hard to take over organisations that are not run right and make them excellent.

‘We really don’t believe in buying into organisations to change them.’ Buffett.

If people won’t listen to the world’s most successful investor in history on his own subject, and even he finds it too hard to take over failing businesses and turn them around, how likely is it that politicians and officials incentivised to keep things as they are will listen to ideas about how to do things better? How likely is it that a team can take over broken government institutions and make them dramatically better in a way that outlasts the people who do it? Bureaucracies are extraordinarily resistant to learning. Even after the debacles of 9/11 and the Iraq War, costing many lives and trillions of dollars, and even after the 2008 Crash, the security and financial bureaucracies in America and Europe are essentially the same and operate on the same principles.

Buffett’s success is partly due to his discipline in sticking within what he and Munger call their ‘circle of competence’. Within this circle they have proved the wisdom of avoiding trying to persuade people to change their minds and avoiding trying to fix broken institutions.

This option is not available in politics. The Enlightenment and the scientific revolution give us no choice but to try to persuade people and try to fix or replace broken institutions. In general ‘it is better to undertake revolution than undergo it’. How might we go about it? What can people who do not have any significant power inside the system do? What international projects are most likely to spark the sort of big changes in attitude we urgently need?

This is the first of a series. I will keep it separate from the series on the EU referendum though it is connected in the sense that I spent a year on the referendum in the belief that winning it was a necessary though not sufficient condition for Britain to play a part in improving the quality of government dramatically and improving the probability of avoiding the disasters that will happen if politics follows a normal path. I intended to implement some of these ideas in Downing Street if the Boris-Gove team had not blown up. The more I study this issue the more confident I am that dramatic improvements are possible and the more pessimistic I am that they will happen soon enough.

Please leave comments and corrections…

* A new transatlantic cable recently opened for financial trading. Its cost? £300 million. Its advantage? It shaves 2.6 milliseconds off the latency of financial trades. Innovative groups are discussing the application of military laser technology, unmanned drones circling the earth acting as routers, and even the use of neutrino communication (because neutrinos can go straight through the earth just as zillions pass through your body every second without colliding with its atoms) – cf. this recent survey in Nature.

December 4, 2014 by dominiccummings

Times op-ed: What Is To Be Done? An answer to Dean Acheson’s famous quip

On Tuesday 2 December, the Times ran an op-ed by me you can see HERE. It got cut slightly for space. Below is the original version that makes a few other points.

I will use this as a start of a new series on what can be done to improve the system including policy, institutions, and management.

NB1. The article is not about the election or party politics. My suggested answer to Acheson is, I think, powerful partly because it is something that could be agreed upon, in various dimensions, across the political spectrum. I left the DfE in January partly because I wanted to have nothing to do with the election and this piece should not be seen as advocating ‘something Tories should say for the election’. I do not think any of the three leaders are interested in or could usefully pursue this goal – I am suggesting something for the future when they are all gone, and they could quite easily all be gone by summer 2016.

NB2. My view is not – ‘public bad, private good’. As I explained in The Hollow Men II, a much more accurate and interesting distinction is between a) large elements of state bureaucracies, dreadful NGOs like the CBI, and many large companies (that have many of the same HR and incentive problems as bureaucracies), where very similar types rise to power because the incentives encourage political skills rather than problem-solving skills, and b) start-ups, where entrepreneurs and technically trained problem-solvers can create organisations that operate extremely differently, move extremely fast, create huge value, and so on.

(For a great insight into start-up world I recommend two books. 1. Peter Thiel’s new book ‘Zero To One‘. 2. An older book telling the story of a mid-90s start-up that was embroiled in the Netscape/Microsoft battle and ended up selling itself to the much better organised Bill Gates – ‘High Stakes, No Prisoners‘ by Charles Ferguson. This blog, Creators and Rulers, by physicist Steve Hsu also summarises some crucial issues excellently.)

Some parts of government can work like start-ups but the rest of the system tries to smother them. For example, DARPA (originally ARPA) was set up as part of the US panic about Sputnik. It operates on very different principles from the rest of the Pentagon’s R&D system. Because it is organised differently, it has repeatedly produced revolutionary breakthroughs (e.g. the internet) despite a relatively tiny budget. But also note – DARPA has been around for decades and its operating principles are clear but nobody else has managed to create an equivalent (openly at least). Also note that despite its track record, D.C. vultures constantly circle trying to make it conform to the normal rules or otherwise clip its wings. (Another interesting case study would be the alternative paths taken by a) the US government developing computers with one genius mathematician, von Neumann, post-1945 (a lot of ‘start-up’ culture) and b) the UK government’s awful decisions in the same field with another genius mathematician, Turing, post-1945.)

When I talk about new and different institutions below, this is one of the things I mean. I will write a separate blog just on DARPA but I think there are two clear action points:

1. We should create a civilian version of DARPA aimed at high-risk/high-impact breakthroughs in areas like energy science and other fundamental areas such as quantum information and computing that clearly have world-changing potential. For it to work, it would have to operate outside all existing Whitehall HR rules, EU procurement rules and so on – otherwise it would be as dysfunctional as the rest of the system (defence procurement is in a much worse state than the DfE, hence, for example, billions spent on aircraft carriers that in classified war-games cannot be deployed to warzones). We could easily afford this if we could prioritise – UK politicians spend far more than DARPA’s budget on gimmicks every year – and it would provide huge value with cascading effects through universities and businesses.

2. The lessons of why and how it works – such as incentivising goals, not micromanaging methods – have general application that are useful when we think generally about Whitehall reform.

Finally, government institutions also operate to exclude from power scientists, mathematicians, and people from the start-up world – the Creators, in Hsu’s term. We need to think very hard about how to use their very rare and valuable skills as a counterweight to the inevitable psychological type that politics will always tend to promote.

Please leave comments, corrections etc below.

What Is to Be Done?

There is growing and justified contempt for Westminster. Number Ten has become a tragi-comic press office with the prime minister acting as Über Pundit. Cameron, Miliband, and Clegg see only the news’s flickering shadows on their cave wall – they cannot see the real world behind them. As they watch floundering MPs, officials know they will stay in charge regardless of an election that won’t significantly change Britain’s trajectory.

Our institutions failed pre-1914, pre-1939, and with Europe. They are now failing to deal with a combination of debts, bad public services, security threats, and profound transitions in geopolitics, economics, and technology. They fail in crises because they are programmed to fail. The public knows we need to reorient national policy and reform these institutions. How?

First, we need a new goal. In 1962, Dean Acheson quipped that Britain had failed to find a post-imperial role. The romantic pursuit of ‘the special relationship’ and the deluded pursuit of a leading EU role have failed. This role should focus on making Britain the best country for education and science. Pericles described Athens as ‘the school of Greece’: we could be the school of the world because this role depends on thought and organisation, not size.

This would give us a central role in tackling humanity’s biggest problems and shaping the new institutions, displacing the EU and UN, that will emerge as the world makes painful transitions in coming decades. It would provide a focus for financial priorities and Whitehall’s urgent organisational surgery. It’s a goal that could mobilise very large efforts across political divisions as the pursuit of knowledge is an extremely powerful motive.

Second, we must train aspirant leaders very differently so they have basic quantitative skills and experience of managing complex projects. We should stop selecting leaders from a subset of Oxbridge egomaniacs with a humanities degree and a spell as spin doctor.

In 2012, Fields Medallist Tim Gowers sketched a ‘maths for presidents’ course to teach 16-18 year-olds crucial maths skills, including probability and statistics, that can help solve real problems. It starts next year. [NB. The DfE funded MEI to turn this blog into a real course.] A version should be developed for MPs and officials. (A similar ‘Physics for Presidents‘ course has been a smash hit at Berkeley.) Similarly, pioneering work by Philip Tetlock on ‘The Good Judgement Project‘ has shown that training can reduce common cognitive errors and can sharply improve the quality of political predictions, hitherto characterised by great self-confidence and constant failure.

New interdisciplinary degrees such as ‘World history and maths for presidents’ would improve on PPE but theory isn’t enough. If we want leaders to make good decisions amid huge complexity, and learn how to build great teams, then we should send them to learn from people who’ve proved they can do it. Instead of long summer holidays, embed aspirant leaders with Larry Page or James Dyson so they can experience successful leadership.

Third, because better training can only do so much, we must open political institutions to people and ideas from outside SW1.

A few people prove able repeatedly to solve hard problems in theoretical and practical fields, creating important new ideas and huge value. Whitehall and Westminster operate to exclude them from influence. Instead, they tend to promote hacks and apparatchiks and incentivise psychopathic narcissism and bureaucratic infighting skills – not the pursuit of the public interest.

How to open up the system? First, a Prime Minister should be able to appoint Secretaries of State from outside Parliament. [How? A quick and dirty solution would be: a) shove them in the Lords, b) give Lords ministers ‘rights of audience’ in the Commons, c) strengthen the Select Committee system.]

Second, the 150 year experiment with a permanent civil service should end and Whitehall must open to outsiders. The role of Permanent Secretary should go and ministers should appoint departmental chief executives so they are really responsible for policy and implementation. Expertise should be brought in as needed with no restrictions from the destructive civil service ‘human resources’ system that programmes government to fail. Mass collaborations are revolutionising science [cf. Michael Nielsen’s brilliant book]; they could revolutionise policy. Real openness would bring urgent focus to Whitehall’s disastrous lack of skills in basic functions such as budgeting, contracts, procurement, legal advice, and project management.

Third, Whitehall’s functions should be amputated. The Department for Education improved as Gove shrank it. Other departments would benefit from extreme focus, simplification, and firing thousands of overpaid people. If the bureaucracy ceases to be ‘permanent’, it can adapt quickly. Instead of obsessing on process, distorting targets, and micromanaging methods, it could shift to incentivising goals and decentralising methods.

Fourth, existing legal relationships with the EU and ECHR must change. They are incompatible with democratic and effective government

Fifth, Number Ten must be reoriented from ‘government by punditry’ to a focus on the operational planning and project management needed to convert priorities to reality over months and years.

Technological changes such as genetic engineering and machine intelligence are bringing revolution. It would be better to undertake it than undergo it.

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…

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