2020/04/03 by Luciano Floridi, Josh Cowls, Thomas C. King +1 · 1 citation
Social Sciences · Medicine · Computer Science · Psychology · Engineering · #Ethics and Social Impacts of AI #Artificial Intelligence in Healthcare and Education #Explainable Artificial Intelligence (XAI) #Philosophy of science #Context (archaeology) #Subject (documents) #Engineering ethics #Management science #Computer science #Knowledge management #Epistemology #Sociology #Psychology #Engineering
paper · pdf · doi:10.1007/s11948-020-00213-5
openalex publication_date 2020/04/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
The idea of artificial intelligence for social good (henceforth AI4SG) is gaining traction within information societies in general and the AI community in particular. It has the potential to tackle social problems through the development of AI-based solutions. Yet, to date, there is only limited understanding of what makes AI socially good in theory, what counts as AI4SG in practice, and how to reproduce its initial successes in terms of policies. This article addresses this gap by identifying seven ethical factors that are essential for future AI4SG initiatives. The analysis is supported by 27 case examples of AI4SG projects. Some of these factors are almost entirely novel to AI, while the significance of other factors is heightened by the use of AI. From each of these factors, corresponding best practices are formulated which, subject to context and balance, may serve as preliminary guidelines to ensure that well-designed AI is more likely to serve the social good.