Data Science for Social Good Imperial College

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The potential of new technologies to tackle global issues remains largely unrealised. This summer, the Gandhi Centre will be working to change that

“Move fast and break things” is the motto of Facebook, a company that – in under two decades ­– has helped redefine how people interact. Founded by Harvard graduate Mark Zuckerberg, the social network has also become a poster child for the power of data in the 21st century.

Data has become our greatest tool and our most valuable resource; our society, economy, and even our personal relationships are being shaped by it. But in an era of fake newscyber threats, data leaks and increasingly intrusive algorithms, we have also become uneasy about the role of data science in our lives. This strained relationship forces us to ask who this technology is serving and whether its potential is being fully realised for the benefit of all.

Information technology is fantastic for business and for bottom lines, but its rise has exacerbated global inequality and helped concentrate resources into fewer hands. At the same time, the extent to which data has meaningfully tackled the big issues – poverty, climate change, homelessness and global inequality – is comparatively limited. The truth is 21st-century technologies such as data science, big dataartificial intelligence, and augmented and virtual reality have an immense capacity for enabling social good, but this capacity for social remains largely untapped.

Tackling the problems that matter

With PWC predicting AI technologies and data tools will create $15.7 trillion in global economic value by 2030, the opportunity to apply this for social good is huge. With the right tools, talent and knowledge, organisations have generated real human impact, whether it is: helping people save money, and water during droughtshelping the vulnerable access public benefits; or resettling refugees. The question is how these efforts can be encouraged, incubated and enabled.

The Rockefeller Foundation and the Mastercard Center for Inclusive Growth have been tackling these very issues. Through a joint $50 million investment, they are supporting projects that use data science for social impact. One organisation they have supported is DataKind, a non-profit that connects data science and AI talent with social enterprises for the good of humanity.

The Gandhi Centre for Inclusive Innovation, part of Imperial College Business School, is an institution committed to training the next generation of innovators, and developing sustainable solutions with a high social impact. The Centre is teaming up with the University of Chicago to host its Data Science for Social Good (DSSG) Fellowship, a 12-week education programme. The DSSG initiative as a whole is built around three themes:

  • Education: teaching data science through high-touch training programmes such as the summer fellowship.
  • Incubation: seeding and incubating ideas that could turn into scalable products and tools.
  • Collaboration: building a global community committed to using data science to tackle the problems that matter.

DSSG’s projects over the last three years have included: working with the World Economic Forum to use satellite and ocean data to predict illegal fishing; working with the El Salvador education system to identify the causes of school dropouts and improving the impact of social programs; and collaborating with UN Pulse Lab Jakarta to improve traffic safety in Indonesia through video analysis.

Coordination over cooperation

The aims of the fellowship fit well with the goals of the Gandhi Centre, which aims to develop thought leadership through research, technology and education, and to connect innovation and entrepreneurship with companies and institutions globally. Social impact and issues surrounding global resources require a greater level of cooperation and a shared interest beyond industry collaboration; there is a need for greater collaboration between sectors that don’t normally converge.

This way of thinking is evident in the Davos 2019 Manifesto of World Economic Forum executive chairman Klaus Schwab, who said: “In a world which has become more complex, multipolar, and multiconceptual, the ability to manage global collaboration may be increasingly based on coordination and less on cooperation. Coordination implies a means of achieving the same objectives while providing freedom for different national views, concepts, and value systems.”

The new way of thinking about technology and data science, in the context of social good, is that we have the ability to create new synergies between education, innovation, organisations and business that can generate real solutions using data. Only that way we can forge another motto for the information age that encompasses technology’s capacity for social good: “Move fast and fix things”.

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 Kieran Arasaratnam

About Kieran Arasaratnam

Professor of Practice
Kieran is a Professor-in-Practice at Imperial College Business School in London.