We’ve all become used to the idea that local government can play a role as a placemaker in the physical world. But these days we live our lives as much in the digital world. It’s online that we connect with friends, manage fi nances and plan holidays.
It’s often assumed these digital connections and our links to physical places are distinct. But many of the digital tools we use daily are entwined with physical places. Our communities are shaped by neighbourhood websites, digital tools used by schools, online marketplaces, and meetups that connect businesses.
This means we’re seeing the emergence of a new role for government as a ‘digital placemaker’, pulling together data, information and knowledge to help the citizens and businesses they serve to make better choices.
This digital placemaker role goes beyond the necessary work local government is doing to automate and digitise transactions, from paying fines to managing bin collections. It is a sort of public sector equivalent of what we see in the likes of Amazon or Google: assembling many kinds of information, data and services to provide useful insight or products.
The first building blocks for these new local authority digital placemakers are being laid by a group of pioneering offices of data analytics that have emerged across the country in recent years. These have brought together multiple datasets to help local government solve practical problems.
There are an increasing number of excellent examples. Fire services are using data from multiple sources, including buildings, waste and electricity, to better predict which buildings are most at risk of fire. Meanwhile, Essex CC is using multiple datasets to better predict which buildings may have problematic activities going on inside them, such as modern slavery.
Data is being used to see how the availability of fried chicken outlets correlates with poor eating habits, and how the prevalence of betting shops relates to debt. In all these different ways the offices of data analytics are turning the data they have access to into a useful resource to help local authorities better understand and solve problems.
The next step is to link the data that has been gathered to artificial intelligence for analysis. AI is now beginning to be used in parts of government. For example, police are using PredPol, which uses past data to predict where a crime is most likely to occur and direct resources accordingly.
AI is also used in the Harm Assessment Risk Tool (Hart) algorithms, which attempt to predict which offenders are most at risk of reo ending to guide probation and bail decisions. In education, AI is behind learning tools which personalise teaching to cognitive styles and the attainment of individual pupils.
All of these applications bring their own challenges and controversies. In the US, for example, criminal justice AI has been shown to reflect the biases of years of past judgments.
Looking ahead, there is huge potential for AI used in healthcare and other public services. Some of those possibilities are documented in Nesta’s Confronting Dr Robot report from 2018. In our view, local authorities will see the biggest value from artifi cial intelligence when it is combined with intelligence of groups of people. ‘Collective intelligence’ is a new term to explain this idea, but it has a long history.
As far back as the very beginning of 20th century, the statistician Francis Galton observed a competition to guess the weight of a cow at a country fair. Answers varied widely, but he found the average answer was similar to the actual weight. This sort of mobilisation of large scale human intelligence is seen today in citizen science projects like Galaxy Zoo, where more than a million people work together to identify new stars.
There are many interesting ways these combined artificial and collective intelligence methods could be used in local government. Indeed, some cities around the world have already combined citizengenerated data on flooding with their own data to help guide control rooms and allocate public resources.
It should be much more normal for local authorities to harvest inputs from their residents, on fly-tipping or broken street lamps for example, as has been done by FixMyStreet and other services for well over a decade.
But, the biggest impact of combining AI and collective intelligence could come in crucial public services relating to skills and jobs. Over the past year at Nesta, we’ve been showing what this could mean for labour markets and been trying to show what a digital placemaking approach could mean in practice. To this end, we’ve been bringing together detailed data on 40 million job adverts to show in detail what skills are being looked for.
We’ve also been looking in detail at likely patterns of change in the labour market in the next 10 to 15 years, with one of the biggest studies of job shifts in both the US and the UK. We’ve shown there is likely to be more demand for skills of judgment, creativity and collaboration – information which could be used to direct curriculums and skills training.
The crucial point is that if you bring all this data together and link it to services targeted at those at risk losing their jobs, you can have a huge impact on the effect effciency of the labour market. This could ensure a fairer allocation of skills by aligning it with where jobs are likely to grow, rather than based on the needs of 10 years ago or even for the short-term present.
Similar tools could be used to help older people navigate their care choices in the same way we compare insurance and holidays. Here too there is a crucial role for local government in curating data to help older people and their families to make sense of their choices in residential care and in-home support, as well as the complex financial arrangements they may need to make.
All this highlights an institutional gap: we don’t yet have the right institutions taking responsibility for mobilising data and maximising its public value. Despite current budget pressures, it is crucial that local government begins thinking through the most pressing needs, the fields in which orchestration of data has the greatest value and how best to ensure governance and accountability.
Nesta believes in the next few years we will see the rise of new data trusts, sitting at arm’s length from local authorities, and bringing together other parts of civil society. These will act as trusted guardians of data, and ensure the public gets as much value from data as private companies like Google, LinkedIn and Facebook do already.
While the private sector will fill some gaps in socially benefi cial ways, as Google has already done with Google Maps, my fear is that if we leave it to the private sector, the public sector will find itself ever more dependent on commercial monopolies or quasi-monopolies that do not have public interest at heart.
If local government doesn’t rise to this new digital placemaking challenge, those private companies will.
So this is the emerging agenda of digital placemaking, and one which may become the core of what local government does in helping its place to thrive – the natural complement to the physical placemaking agenda.
Geoff Mulgan, chief executive, Nesta