Artificial intelligence (AI) is likely to prove the most transformative technology of the 21st century. Those of us who work in the field – whether in the public or private sector – are at a frontier that is advancing at an ever-accelerating rate. Yet my work on tech policy at the Government Digital Service and the Home Office often left me in despair. At a time when the possibilities created by AI are multiplying rapidly, the government isn’t really at the races.
The Government’s Digital Strategy, published yesterday, and the government’s Transformation Strategy, published a couple of weeks ago, are a case in point. It is fantastic that some more money is going into AI and robotics research in our universities, but treating AI as “one for the future” misses the opportunities of today.
At our own business, ASI, we work with organisations that are achieving radical improvements in efficiency from relatively simple applications of AI. A payments company that increases fraud detection by 93%. An airline that uses machine learning to predict demand for staff in real time, allowing them to cut the number of standby staff required by 33%. A train manufacturer that uses a predictive maintenance model to reduce the number of inspections an engineer needs to perform to find a fault in need of repair from 10,000 to two.
The opportunities are here and now. But the projects that could improve our public services and deliver value for money to the taxpayer were nowhere to be seen in the digital strategy. And government remains embarrassingly short of examples it can point to. In fact, at a conference on government data last week, the chief executive of the Civil Service resorted to praising a list of public toilets released as open data. We can do better than this.
The stakes are high. Even after seven years of austerity, the public sector spends more than 40% of GDP. Yet the services that we rely on are under ever greater pressure. The only way the government can continue to meet the expectations that people have of the NHS, transport or prisons is to find ways to radically improve efficiency.
The good news is that it is easy to imagine ways in which these services could benefit from AI with relatively little investment. It is encouraging that the justice secretary, Liz Truss, has made digital technology so central to her prisons and courts bill. Machine learning could play a big part in this. For example, Harvard researchers found that cell-sharing configurations can reduce reoffending rates by about 15% for drugs and theft offences in French prisons. It stands to reason that choices of cellmates matter, but even very experienced prison officers find it difficult to balance the bewildering array of factors that need to be taken into account. In contrast to humans, machine learning thrives in finding the patterns that matter in this kind of complexity. This could be done right now.
We’ve all read about supercomputers that are able to read a million medical journals an hour and spot tumours more accurately than experienced doctors. But there are significant wins to be had from the much more prosaic matter of allocating resources in hospitals more efficiently. Hospitals are complex organisations dealing with unpredictable demands. Machine learning can help them run more smoothly. Recent trials modelled how long particular consultations and operations were likely to take and booked theatre resources accordingly. This hugely increased the utilisation rates of these valuable resources, and reduced the number of over-runs caused by the fixed-time slots.
Transport is another area that could hugely benefit. AI can’t solve the Southern rail dispute, but it can help make services run more smoothly. A recent project by ASI built an adaptive scheduling system for a bus operator that modelled the complex ways in which traffic flows through a city. In just a few weeks this was able to make buses 38% more likely to show up at the right time. Cue happier passengers, less crowded busses, and big savings for the bus company.
These are just three easy examples that could be implemented today. There are dozens of others across the entire public sector. But to help kickstart this kind of revolution it is vital that ministers, civil servants and frontline professionals become more familiar with what is possible. To achieve this, government should create a £20m fund for officials to bid into for projects that could demonstrate the value of AI.
Another thing the government could do to move the needle is to provide much better access to the data that is used to train these predictive models. Data.gov.uk has become a dumping ground for nugatory and obscure data sets. Why not require each public body to publish details describing its top 20 data sets that it uses for its own operations? That might help to ferment a proper debate about the new applications that the public might benefit from.
In the next two decades, AI will transform the way we live and work. There is no reason whatsoever why the government shouldn’t be doing this too, but it is not. Adopting this technology is the most plausible way of delivering the public services people expect while making the savings we need.