AI systems, based on machine learning and automation, transform the governance spectrum via the regulatory approaches embedded in them, in particular by relying on hybrid public-private configurations and the blurring of boundaries between civilian and military applications. Recent ‘post-truth’ debates brought into sharper policy focus concerns that filter bubbles, mandated choices and in-built bias restructure the public sphere (and in particular the deliberation space) in ways previously unaccounted for. While algorithms have the potential to equalize access to information, they also have the power to limit exposure to diverse and reliable information. In this research theme, we explore issues of AI governance and AI bias.

AI Governance

AI Bias