AI has been a subject of much speculation and debate since the 1950s, when Alan Turing asked if machines could think. However, the development and deployment of AI has proliferated only recently, enabled by access to vast amounts of data and a massive increase in computational power. From optimizing logistics to composing art, AI has the potential to radically transform society. The benefits could be vast – ranging from huge efficiency gains to solutions for complex problems.
Yet, unguided AI would also pose complex challenges related to the distribution of technology gains, the collection and use of personal data, and transparency and accountability of algorithmic decision-making. Risks associated with unintended consequences, misuse, and unpredictability also raise new and difficult governance challenges.
Much of the current conversation around AI is framed in the language of technological innovation and productivity gains. There is an urgent need to examine the social, ethical and governance challenges related to AI, and understand the ways in which society should shape these technologies. These challenges are likely to vary across social contexts, as technology trajectories intersect with local systems. The access to, and impact of, AI technologies on different social groups, for example needs to be understood, else AI risks entrenching existing socio-economic inequities.
Even with earlier technologies, the persistence of health problems, hunger, malnutrition, energy-poverty and low agricultural productivity illustrate that market signals and incentives alone are not sufficient to generate technological applications for social needs. Technology companies, particularly those that have the capital to make investments in AI capacities, are leading many current discussions on the principles and governance of AI; unsurprisingly, many are calling for self-regulation. Many more voices and perspectives are needed. Social steering of AI through policies is critical, to align technological trajectories with societal goals and development needs of the poor.
In partnership with FES we are hosting a series of six policy labs to map AI trajectories in India and identify key knowledge and policy needs. With our labs, we further seek to create a community of scholars and practitioners interested in understanding the social dimensions of technology trajectories.