Government and Institutions

Bayesian inference, the maths of hunches, and revolutionising big government


Much has been written already on Number 10 adviser Dominic Cummings’ New Year appeal to “assorted weirdos” to smash up, then rebuild government to make it better. Cato economist Ryan Bourne challenges it from a public choice perspective, left-leaning professor Jonathan Portes on whether he has picked the right targets in civil servants rather than their ministers, and Len Shackleton of this parish on doing less being more important than doing it better – all good points and exactly the kind of “red team” review Cummings says he likes for challenging his thinking.

Cummings’ piece is complex, referencing his own back catalogue of thinking on the state and politics, the reading of which is essential for anyone thinking of applying. I am therefore going to focus more narrowly on the microeconomics references in the piece, bad Nash equilibriums in Game Theory and Bayesian inference. The former, in this context, is “the problem” – why does government keep failing to deliver big projects on time and on budget, and then never learn from its mistakes – or more rarely successes – to do better in future? The latter is a mathematical tool for updating our beliefs, based on evidence that when applied repetitively, particularly via machine learning within Artificial Intelligence (AI) tools, then communicated effectively in the right environment for maximum impact, might enable government to make better decisions, faster.

This is contrasted with asking a generalist senior “public school bluffer” with no expertise or evidence for their best guess, and getting an answer that approximates to what they think you want to hear, while they assiduously bury bad news, then promoting them for their wisdom in not rocking the boat, rather than any evidence of competence or concern for public service. That at least appears to be his characterisation of the culture he is trying to change, while recognising the efforts of “brilliant individuals” within the system who are trying to help.

In brief, Cummings cites evidence that megaprojects (>$1 billion in cost) run by all types of government often fail and fail for reasons that are often repeated. From defence procurement to tackling climate change to lifelong learning, bad decisions are made, bad projects contrived, with bad leadership, which are then badly run, to the lingering harm of the public and any future governments now saddled with both the debts from failure and personnel trained to repeat it.  Nothing changes.

Worse, government culture is designed to repel disruptive innovators who might do better, and in political leadership there is a willingness to “fail conventionally” rather than risk ridicule for thinking differently, even if that might yield longer-term success. It is not hard to see his experience of trying to reform the Department for Education in the Cameron era as shaping these thoughts.

The bad Nash equilibriums in this context are the assured failures of government projects due to the structure of incentives and interplay of decisions and actors that lead to them. Their repetition suggests current government learning strategies such as project reviews do not work, the incentives don’t change, the people don’t change (or rather the type of person doesn’t – too rapid change of personnel is part of the complaint, as is groupthink). Repetitive failure then is baked into the way government works, or rather does not work. Cummings does not believe it needs to be this way. What if small teams of highly able people, selected for their brilliance were able to sit outside the conventional structures of government and do things differently, encouraging change by example?

This is not entirely novel: Cummings cites examples of “getting it right” through successful megaprojects in history such as the Apollo and Manhattan Projects, although he notes their success was not sustained, in no small part due to the departure of visionary leaders, which begs a question as to why he thinks he can make himself redundant in a year. What is new is his particular take, applied to the modern context, particularly around the adoption of AI to improve project decisions and organisational learning within the machinery of the state. He wants brilliant minds in data science, software, economics, policy, communications and project management, unconventional enough to embrace concepts from each other’s disciplines (something Hayek was rather good at), while well managed enough to be focused on delivery, cognisant as to how their contribution contributes to whatever overarching objective they are set. It’s an exciting idea and a challenge to free-marketeers who believe that government, and particularly big government, is generally doomed to fail.

In Game Theory a bad outcome can be avoided by co-operation, changing incentives or breaking the game. Cummings I suspect is trying to do all three. Co-operation here means at one level cutting through departmental silos and the culture of “failing and moving on” to force government to learn from its mistakes. This is more organisational than technical, but within projects better communication is part of the process of how incentives can be changed. In a repetitive game we learn from our mistakes, but this only makes a difference if we can communicate that learning to other decision makers. How we learn is where Bayesian inference is important. If we believe we know the probability of an event and receive new information, we apply that information to update our assessment of probability. This inference then updates our calculation of pay-offs (or incentives) and might lead to us making a different decision. If we can convey that change to the other decision makers we can avoid the certainty of second best, and change the “minimax” culture where we seek to avoid losses rather than pursue success. At least I think that’s what he’s saying.

Bayesian inference more mundanely is a mathematical way of modelling how people think and importantly how they change their minds. That it is mathematical and repeated at scale, a computational challenge, makes it central to AI. Machines use maths, we use hunches, but those hunches are rooted in decades of acquired, processed and simplified memories, and how rapidly these can be accessed and compared – or our intelligence, to inform our decisions about what to do. When these hunches prove to be correct we call it a good guess, and when they do so repetitively we call it knowledge or expertise. Artificial intelligence then is hunches with maths, repeated faster than any human can, to acquire knowledge from guessing faster, and in doing so inform better decisions – at least in circumstances where that advantage can be established.

A relevant and current example of this is the tools Facebook and others use to improve the serving of digital adverts on social media. Ad-variants are constantly tested by the ad server, prioritising those that get the most likes or retweets, updating those priorities as people get bored and stop clicking. This is vastly more efficient than the way old media campaigns used to work, with instant feedback on advertising effectiveness rather than lengthy and costly market research measures providing planners with better hunches on concepts, and where and when to show them. Cummings doesn’t just believe this is revolutionary; he applied it to the Vote Leave campaign in 2015/16, claiming 98% of the marketing spend was on data-driven social media, whereas the politicians wanted to spend it on billboards. Nor does he claim this necessarily won the referendum, just that it was a far more effective use of resources than spending by the other side, and allowed him to prove a point about the skills he is seeking.

It is less clear how Cummings can use his “misfits” and these tools to achieve the outcome he desires in government. I can well imagine a new situation room in Downing Street that clearly and in real time visually explains to ministers why a corporate pitch to secure government funding for carbon capture and storage as a solution to climate change is doomed to failure in the UK, not just in the form presented but in a range of realistic scenarios rooted in evidence that largely point to Chinese leadership. I can well imagine them showing the returns possible from putting a fraction of that request into researching the extraction of biofuels from GM algae in solar tubes, without subsidising the pilot. But both those conclusions are possible now with conventional planning tools, albeit less engagingly presented. That though may be crucial to persuading a minister with attention deficit disorder and an inbuilt phobia for scary words to make a tough decision, with fewer opportunities for hi-vis jacket photographs.

I can imagine this team finding aspects of government activities, for example the processing of welfare payments, where machine learning could seriously improve the avoidance of harmful errors, and the training of staff in how to avoid them. But I’m not sure this constitutes a megaproject. I can imagine them applying some of these approaches to concurrent trade negotiations, ensuring each bilateral trade team is acutely aware of the trade-offs being requested by different potential partners and the quantum impact on UK exports and consumer choice. These could be genuinely revolutionary approaches that have serious impact. I could imagine attempts to scrap all ministerial and high-level civil service salaries, replacing them with incentive schemes linked to agreed evidence of actual success. I could imagine linking MPs’ pay to the state of the economy rather than their own notions of their importance relative to benchmark wealth creators and public servants. That might address aspects of the political incentives problem, at least until replaced by gender-pay gap targets by the next woke government.

It is then possible to see this as being quite ground-breaking and positive – that is if the Cummings disruptors can overcome resistance, and are allowed to fail as well as succeed, which they assuredly will from time to time (and this will trigger the politicians to try and shut them down).

There are though other issues, some alluded to in the opening links. It’s not obvious in some cases that the issue is the culture of government, more that the government is involved at all. We don’t clearly need state planning of agriculture in the 2020s and there is no big question of food security to solve as was feared in the 1940s, yielding nearly a century of ill-conceived interventions and malinvestment. Is climate change a mega-project or has making it a mega-project rather than a market been a major cause of failure to address it?

There is also the economic calculation problem, a test that should be applied to all the claims of big tech sales pitches as much as it was applied to the illusions of socialist central planning. Is the issue really either an insufficiency of data, the failure to use data to drive better decisions, or not having scientists involved; or is it that technocratic allocation, however sophisticated, is the wrong approach? In the NHS for example, it’s quite fun to imagine replacing NICE (the body that decides what drugs you can queue to receive in the hope you get them before being maimed or killed by waiting) with an AI immune to the entreaties of lobbyists. But it’s not clear why you’d do that rather than simply recognising other competent authorities and their recommendations, thereby allowing their sale more widely in the UK, potentially broadening access to better, cheaper treatments and therapies at a stroke. The AI’s decisions would still kill people and “the computer says no” is unlikely to appease the voters.

It would be good then if the future Downing Street Red Team included a few non-Reds to ask the difficult questions of any project proposal, “should we be doing this?” and “what if we did nothing?”, with their conclusions regularly published.

If that were a part of the project, alongside better managed mega missions, both could be genuinely transformative.

 

Andy Mayer is Chief Operating Officer, Company Secretary and Energy Analyst at the IEA. Andy is responsible for developing our people, all operations, and managing the reputation of the IEA, including for example over-turning the Charity Commission’s unlawful attempt to ban one of the IEA’s publications, and dealing with failed attempt to smear the organisation by activists at the same time. When not leading operations, Andy writes and comments on free market issues around energy and climate change, and occasionally general commentary. He was previously the Head of UK public affairs for the world’s largest chemical company and green energy advisor to the UK’s largest company. He has over 25 years of experience in strategic communications and the operations that support them in the business and think tank worlds.


5 thoughts on “Bayesian inference, the maths of hunches, and revolutionising big government”

  1. Posted 09/01/2020 at 14:44 | Permalink

    The fact that Bayesian methods have been used (formally never mind informally) in insurance for 30 years or more demonstrates why the government should focus on doing less rather than doing it better. And, perhaps once we have got down to the small number of things that governments should do, maybe it is better to have them run by generalists than by scientists who may suffer from the problem of believing they know more than they do and be attracted to central planning.

  2. Posted 09/01/2020 at 16:38 | Permalink

    I have a lot of time for Cummings.
    I think the first question is; can his vision of a neutral (remember, he’s not exactly a Tory fan-club member) government ‘brain’ function without political interference sabotaging it? I don’t think it can.
    While yes, there are great examples of high-level team achievement that resulted in the atomic bomb, and the Apollo missions, these are a world apart from what he is advocating to achieve in Whitehall.
    For one, they were military/scientific ideological projects backed by Washington DC. They had no budget once they passed a certain point, it was simply going to run and run until completion, and it became such a matter of national importance, and pride, that budget constraints were basically nil.
    We CAN actually point to a project here that we could, and should, treat in this way. That would be the NHS, with social care factored-in. If we had our best and brightest looking at it, it could quickly turn into the 8th wonder of the world. But in order to do, it needs to be the highest aspiration of the government to do so, money no object, go. But it isn’t. I don’t detect that being the case at all. And so what are we going to collate all these elite thinkers for? To deliver a no-deal Brexit? To deliver HS2? To create 30,000 new policemen?
    My concern is that it’s hard to know what Cummings thinks is broken, and what is it that he thinks that Asperger’s finest can deliver for us?
    I sit in a local government office, right now, typing this. On your time.
    I’m under-utilised, I’m capable of so much more, I’m paid a ghastly wage, with no real chances of progressing. I study law in my free-time, I long to be engaged with a problem. I’m probably quite typical of a great many young office-based local government employees. We’re being utterly destroyed by management that are unable to see opportunities, to change, to help Councillors drive their communities to be better. We live in an age of fear, nobody wants to lose their jobs, and local government does not reward risk-takers.
    That, is the big quest that Cummings should identify. Our greatest resource as a country, is people. And one of the biggest employers is government. Why not target something you already own? Invest in local government workers. Oversee and design our development. Make us learn new skills, make us operate more effectively, set goals, up-skill everyone who is capable, create local authorities that have room and resource to ‘think’ and take risks. Not only do you get more out of us as workers, but you get more out of us as potential innovators in our own time, of setting-up great businesses using the skill we learn. Sadly at present, the senior managers of local authorities are mostly devoid of these skills, nearing pension age, they just want to keep the boat steady and set balanced budgets and avoid drawing attention to themselves. That’s not effective leadership. And whatever it is you do in Whitehall, with your misfit geniuses, remember that there are tons more natural resources to be mined already, up and down the country, in shabby Town Halls.
    I’m a firm believer in changing the old rules, challenging tired ideas and approaches, especially in local government. I think some of the issues we face are also replicated in big government. Older ministers, older heads of service, they conform, they don’t push. And a lot of it is based on the fear of losing very good jobs, and you have to recognise that, these people have families and mortgages. No, we don’t owe them a living, but we also should break it to them gently that their time is up and to make new plans.
    Securing a local government job should be winning a competition. You should feel honoured to be chosen, and the place should be brimming with ideas and energy, it should be lit-up like a beacon, it’s like getting a job with NASA, you should feel part of something brilliant that will help everyone. And getting a job as a minister or Whitehall senior officer should feel like the next step, like becoming an astronaut.

  3. Posted 09/01/2020 at 20:05 | Permalink

    We have a positive example in Sir John Cowperthwaite of both the extent of government and what the default reflex should be.
    His track record in Hong Kong is stellar in comparison to management of the UK economy.
    Instead of trying to manage things, get govt out of the way. Why do so many people keep trying to improve the NHS, when there are functioning examples of good health care systems from Scandinavia to Australia via Austria or Singapore.
    Just copy what works elsewhere, for example would an Austrian or Swiss want to move to a managed monlith like our Healthcare system?
    Copy what works.

  4. Posted 10/01/2020 at 17:18 | Permalink

    Throughout the 1960s, Cowperthwaite refused to implement free universal primary education, contributing to relatively high illiteracy rates in today’s older generation.
    At a time when Hong Kong’s roads were crippled by traffic congestion, Cowperthwaite also steadfastly opposed construction of the Mass Transit Railway, a costly undertaking which was nevertheless built following his retirement, and would later become one of the world’s most heavily utilised (and profitable) railways.

    Please stop finding individual accounts of mediocre achievements and holding them up as a template. There is nothing we have in common now with post-war Hong Kong. If you start off with close to nothing, then you can do anything. HK people were poor. We are not. You have to factor-in such things.

    Cummings has 4 years to make a plan start to work. He may well have a plan for 20 years, but it will not matter if people have less money in their pocket in 4 years, they will vote the government out.

  5. Posted 12/01/2020 at 10:21 | Permalink

    How to change the civil service from reactive to dynamic

    The Hollow Man lecture, by Dominic Cummings (IPPR 2014),clearly outlines the dysfunctionality of the current system of government – the lack of: long-term vision, focus on goals, management experience, service knowledge, and stability of leadership.

    The Civil Service’s own Reform Plan provides a damning description of its culture.
    ‘But it’s culture can be cautious and slow-moving, focused on process not outcomes, bureaucratic, hierarchical and resistant to change’

    The main cause of this dysfunctionality is that Ministers and civil servants have impossible jobs.
    Ministers are de facto Chief Executives of huge organisations. Yet few have any management experience, or in-depth knowledge of either the senior management of their departments, or of the services it provides. They are in post for too short a period to learn or to provide stability and they have no control over the staff in their departments.

    The senior civil servant of a department has the title of Permanent Secretary, described by the Oxford Dictionary as ‘the principal assistant of a UK government minister’ to advise and carry out the wishes of the Minister. They cannot set the vision or goals, as priorities change with each new minister. They also change their jobs too frequently.

    So without stable leadership and a long-term vision and goals, government departments have become rudderless, seeking instant solutions to long term-problems.

    To introduce leadership the roles of Ministers and Civil Servants need to be redefined.
    Each department should be an independent entity. It should set its own objectives, plans and budgets for approval by the Prime Minister and the Cabinet.

    The Secretary of State should become Non-Executive Chairman. They may bring little knowledge or management experience but this enables them to bring objectivity.

    A new role of Chief Executive should be created to replace the Permanent Secretary. The CEO should have wide management experience and come from a culture where ‘action this day’ is the norm. Initially, this would exclude most senior civil servants who are imbued with the civil service culture.

    As the Chief Executive is accountable for achieving the department’s goals, they must be free to employ their own staff, under their own pay scale, benefits and terms.

    The staff would be employed by the department and not the civil service. This will enable them to build up the experience, knowledge, and skills needed to function effectively.

    The Civil Service, as currently constituted covering all government departments, would no longer be needed.

    Policy, in terms of government departments, can be defined as those which are the prerogative of:
    – politicians. These affect the citizens of the country – welfare, public education, highways and public safety – and involve the spending of money
    – management. These affect the effective running of a department – improving system, for example, simplifying the collecting tax so it does not take 25,412 pages of Tolley’s Handbooks to explain.

    Management of an organisation accounts for 99 per cent of its effort and time and does not require impartiality.

    Redefining the roles and the structure of departments will change the civil service from reactive to dynamic. It should be looked at as a 5 year programme. To quote Peter Drucker ‘If you can turn a company around in a year, there was not much wrong with it to begin with’.

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