GROWTH
The many shades of AI “Governments have been by far the greatest investors in AI - whether through military and intelligence agencies (particularly in the US and China), or less directly through universities…[ ]… The risk is that governments will oscillate between over enthusiasm as they buy into misleading hype and disillusion when the promised results don’t materialise. The answer is that they need more in-house capability to be smart customers and commissioners; more serious R&D and experiments; as well as more serious efforts to deal with public trust and legitimacy, like the UK’s promised new Centre for Data Ethics and Innovation.”
Ten major areas of likely change based on different types of AI technology relevant to governments:
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AUTOMATING EVERYDAY PROCESSES
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PATTERN RECOGNITION AND BETTER PREDICTION
Routine task automation may be the least exciting area for AI but offers the biggest early productivity gains, so long as whole processes are reengineered.
Predictive algorithms have been used for many years in public services, whether for predicting risks of hospital admissions or recidivism in criminal justice. Newer ones could predict exam results or job outcomes or help regulators predict patterns of infraction. These uses of AI have lots of challenges, not least of which is avoiding the bias embedded in past data sets.
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ENHANCING INTERACTIONS WITH CITIZENS
Governments are beginning to use Alexa and Siri and bots of various kinds to handle everyday interactions, from planning applications to school places. We’re already well down the road to a very different model of interaction between states and citizens.
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N E W WAY S O F S E E I N G
Computer vision is already obviously useful for security and surveillance. Combined with sensors, it could become much more integral to management of infrastructures.
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landscape of opinion; showing clusters of views or how different people’s views relate to each other.
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ROBOTICS
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TA R G E T I N G S O C I A L PROGRAMMES
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Robotics has been pioneered in the military and can be very useful for entering dangerous environments, such as after manmade or natural disasters. There are many other uses in and around public services, such as cleaning and maintenance.
With six, we’re looking at bigger projects that combine governments, foundations and business to interpret data on whole population patterns, using predictive algorithms to better target action. Saskatchewan in Canada and Allegheny in the US are leading examples that are trying to use a mix of big data, AI and smart social policy to better predict and prevent risks.
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A C C E L E R AT I N G E D U C AT I O N
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ENHANCING DEMOCRACY
There’s a flood of good ideas for AI in education, some of which Nesta has invested in (like Cogbooks). For maths, language teaching and a few other areas, the potential is big, though as with edtech more generally there’s been a shortage of good evidence and testbeds.
While currently controversial, some of the leading experiments in online democracy use AI tools like pol.is to help participants understand the balance and
NEW JOBS
Nesta’s detailed study of future jobs showed that the cruder forecasts in which AI simply replaces doctors or teachers is almost certainly wrong. Look in more detail at the cluster of skills in jobs and it becomes apparent that although some aspects are very amenable to automation others are not.
NEW FORMS OF R E G U L AT I O N A N D NEW GUIDING PRINCIPLES
There are big, and still unanswered, questions over transparency, ownership and responsibility. The working draft; ‘10 principles for public sector use of algorithmic decision making’ by Eddie Copeland, Director of Government Innovation, Nesta, is an important step forward in setting some new ground rules. One other pressure for new regulation is the potential for a crisis if AI is misused. AI promises more predictable and controlled public services. But a striking feature of complex systems is that they become opaque even to their creators. More complex and interconnected systems go wrong in ways that no one quite understands. ■
From the 26 February 2018 blog; ‘A roadmap for AI: 10 ways governments will change’ by Geoff Mulgan, CEO, Nesta.