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.
Much more social research is needed to understand and navigate the challenges posed by India’s unique and complex socio-economic landscape. Without proper outreach to expertise in the social, cultural, and political consequences of new technologies, AI trajectories are likely to widen the gap between technology applications and the public interest, and disconnect technical research from critical reflection
Data privacy and governance is already a growing concern, and current policy and legal frameworks seem unprepared or inadequate. Yet, many changes related to the application of AI technologies in India are still emergent, creating a critical and opportune moment to deliberate the knowledge and policy needed to steer future AI trajectories in India.
In partnership with FES, we are hosting a series of 6 policy labs on AI trajectories in India. The first lab, in August 2018, mapped the key actors, issues, institutions, and policies relevant to AI trajectories in India. Two more labs are scheduled for 2018 - AI and Environment on 5 October, and AI and Health on 4 December. Do get in touch if you are interested in participating!