It is not very often that a technology comes along which promises to upend many of our assumptions about what government can and cannot achieve. But if you’ve been reading any news in the past few months, it has been difficult to avoid Artificial Intelligence (AI). It suddenly seems to be everywhere.
Three years ago every start-up had exactly one business model: “Uber for X” (“Uber for cat food”, “Uber for medical marijuana”, and “Uber for dog-walking”) – I promise, I only made up one of these three. Now, the model is different and it’s “X plus AI”.
No doubt, some of this is just hype. But the underlying development is real. And the speed at which it has been happening is staggering. Nick Bostrom, an academic at Oxford, is one of the most bullish people on AI. In 2014 he was convinced that it would take computers another 10 years before they would beat humans at Go, a famously complex board game.
In March last year, one of the world’s strongest Go players confidently agreed to play against an AI program called AlphaGo. AlphaGo didn’t just do well, it thrashed him, finding moves and strategies that were completely new to the humans who had spent their lives mastering the game. Algorithms are already outperforming humans on tasks that matter in a more immediate way. For instance, AI beats human pathologists at predicting patient survival times for certain kinds of cancerous tumours.
What does this mean for governments?
All of this of course raises many questions and fears. Much of the conversation in the public and also in policy circles is about AI’s impact on society. What does the future of work look like? And how should we regulate such things as self-driving cars or price-setting algorithms? These are important questions, to be sure. But surprisingly little effort has gone into understanding how AI will transform government itself.
You can think of any government as doing essentially three things: operations, service delivery and policymaking. In many ways a government has “operations” similar to any other organisation. This means that someone needs to take care of human resources, someone needs to make sure all the lights are on, make sure your office is neither too hot nor too cold, and all the rest of it.
Its “service delivery” function involves the provision of services such as unemployment counselling, benefits, social services, education, food safety inspections and street cleaning. And we also have some part of government that thinks about “policy” – the strategic questions of what a government’s priorities are and how it goes about achieving them.
For the “operations” piece it is relatively easy to predict the effect of AI. These functions naturally lend themselves to automation, and there is no difference between processing the payroll for a grocery chain and processing the payroll for a local school. Government will be able to benefit from the inevitable advances AI will deliver here.
Is service delivery any different? Much of it is based on humans doing their very best to assess a situation and act accordingly. Think of an unemployment counsellor. If you are unemployed and go to a job centre, you will meet a job counsellor who will use his or her well-honed professional judgment to help you find a job. When you walk in, the counsellor will probably do at least three things with you – check your eligibility for benefits, assess your profile and job history, and identify the best workshops or training that will help you find a job fast.
It turns out that AI systems are naturally good at doing all of these things. A machine can simply process more data and detect more subtle relationships than a human ever could. An AI system, or a counsellor working with an AI system, would outperform a human working alone. The same logic holds for an untold number of other government services.
This is not just neat, but it really matters. It really matters whether a job counsellor gives you good advice, or a physician detects your cancer early enough, or social workers can identify children in troubled families before they are harmed. If we have a new way to provide better services to the citizens that need them, then every government has a moral obligation to make full use of it.
Out of the three things that government does – operations, service delivery and policymaking – there are two that, so far, show a huge potential for AI. What about policymaking?
Take this interesting example. In Japan, as in many other countries, civil servants spend an enormous amount of time compiling answers to questions from elected representatives. Later this month, Japan’s Ministry for Economy, Trade and Industry will introduce an AI system which will help its civil servants draft answers to such questions.
Just yesterday I spoke to the finance director of a local district in London. On many days he spends 60% of his time not on managing the borough’s finances but on pulling together answers to exactly these kinds of questions. Imagine how liberating it would be if you had a machine to draft these for you.
It looks like AI can make a difference across all spheres of government.
Making full use of AI in government will have a number of consequences. I’ll highlight just three here.
Firstly, if we want to reap the benefits, we have to allow government to make full use of the data it already holds. Some countries are more worried about this than others. But they too may change their minds once other governments start mercilessly outperforming them – at a fraction of the tax burden.
Secondly, organising a government around distinct departments will become obsolete. Few of the difficult problems facing government align themselves with neat departmental boundaries, and AI systems will only be truly useful if we build them to solve problems rather than conform to arbitrary organisational units.
And finally, government’s interactions with citizens will become infinitely more personalised and tailored. Government will understand more about citizens than at any previous point in time.
This gives us new ways to govern ourselves and new ways to achieve our collective goals. But of course, it also gives governments terrifying new ways to coerce us.
The jury is out on which way this will go. The machine will not just figure this out for us, which is why we need to figure it out ourselves before it all ends in tears. But if we get this right, the amount of progress can be enormous. I’m hopeful that – in a few years from now – we will think of a government which refuses to use AI the same way we would think today of a government which insisted on using typewriters and clay tablets.
This blog is based on the keynote speech at the Pre Davos Summit 2017 of the WEF Global Shapers Community
The Centre for Public Impact is investigating the way in which artificial intelligence (AI) can improve outcomes for citizens.
Are you working in government and interested in how AI applies to your practice? Or are you are an AI practitioner who thinks your tools can have an application in government? If so, please get in touch.
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