Using Artificial Intelligence For Social Impact

By: Juan Mateos-García & George Richardson (Nesta)

There’s a flurry of excitement about modern developments in artificial intelligence (AI).

The arrival of powerful image generators, AI agents able to perform multiple tasks or seemingly (to some) sentient chatbots are an exciting prospect for data scientists that use machine learning to tackle big societal challenges in areas such as health, education and the environment.

One of the unofficial remits of AI is to “solve intelligence and then solve everything else”. We have to assume that “solving” would include reducing inequalities in education, tackling obesity and decarbonising our homes. Are we about to get AI systems that could help us solve these problems?

Industrialised AI

The dominant model for AI is an industrial one. It trains deep, artificial networks on large volumes of web and social media data. These networks learn predictive patterns and can be useful for perception jobs such as identifying a face in a photo. They are good for tasks that don’t have human input or where we are not interested in understanding why someone made a choice, such as liking a social media post.

The large technology companies developing these systems use them to predict relevant search engine results, what social media content is most engaging and to make recommendations that could result in a purchase. This helps these companies build more engaging and profitable websites and apps.

But when it