AI Ethics: Managing Risks and Impacts under ISO/IEC 42001:2023

The growing interest in the use of artificial intelligence is transforming industrial processes, public services, and various sectors such as healthcare and finance. Recommendation tools, predictive algorithms, anomaly detection systems, and generative models are becoming the building blocks of information systems. These applications create opportunities, but they also introduce new challenges that go beyond traditional IT risks: bias and discrimination, privacy violations, opaque decision-making, data dependency, and model-specific vulnerabilities.

Several high-profile cases have highlighted these new risks. In 2016, a ProPublica investigation into the COMPAS algorithm—used by U.S. courts to assess the risk of recidivism—revealed that African American defendants were twice as likely to be incorrectly classified as high-risk compared to white defendants . In 2018, Amazon abandoned an automated recruitment tool after discovering that it systematically penalized female applicants . In 2019, Obermeyer et al. demonstrated that a commercial health management algorithm, deployed on a large scale in the U.S. healthcare system, systematically underestimated the care needs of Black patients compared to white patients with similar health conditions . The algorithm used historical healthcare costs as an indicator of future care needs, which led to an underestimation of Black patients’ needs due to their lower initial access to care. This is not an isolated case: in 2020, an...