Ethics of Emerging Technologies: AI and Biotechnology

The rapid development of artificial intelligence and biotechnology since the 2010s has generated a distinct body of applied ethics addressing risks and questions that older frameworks, developed before these specific technologies existed, only partially anticipate. Algorithmic fairness has become a central concern following documented cases of biased automated decision-making, including the 2016 ProPublica investigation into the COMPAS recidivism-risk-assessment tool used in U.S. courts, which found the algorithm produced substantially higher false-positive rates for Black defendants than white defendants — a finding that sparked an extensive technical and philosophical literature on competing, and in some cases mathematically incompatible, formal definitions of algorithmic fairness, as demonstrated in a widely cited 2016 impossibility result by the computer scientists Jon Kleinberg, Sendhil Mullainathan, and Manish Raghavan showing that several intuitively plausible fairness criteria cannot generally be simultaneously satisfied.