Explaining the Principles to Practices Gap in AI

As artificial intelligence (AI) permeates across social and economic life, its ethical and governance implications have come to the forefront. Active debates surround AI's role in labor displacement, autonomous vehicles, military, misinformation, healthcare, education, and more. As societies collectively grapple with these challenges, new opportunities for AI to proactively contribute to social good (AI4SG) and equity (AI4Eq) have also been proposed [1], [2], such as Microsoft's AI for Earth program. These efforts highlight the potential of AI to address global challenges and help achieve targets like the United Nation's sustainable development goals (SDGs) [3]. Yet, whether AI efforts are directed explicitly at social good and equity or not, there are many barriers that stand between aspirations to be responsible and the translation of these aspirations into concrete practicalities.