AI for Diversity

AI for Diversity questions how AI technology can lead to inclusion or exclusion for diverse groups of society. It enables the reader to step back and see how AI is impacting diversity in humans impacted by AI and how diversity-awareness strategies can impact AI.

Artificial intelligence (AI) is increasingly impacting many aspects of people's lives across the globe, from relatively mundane technology to more advanced digital systems that can make their own decisions. While AI has great potential, it also holds great peril depending on how it is designed and used. AI for Diversity **questions how AI technology can lead to inclusion or exclusion for diverse groups in society. The way data is selected, trained, used, and embedded into societies can have unfortunate consequences unless we critically investigate the dangers of systems left unchecked, and can lead to misogynistic, homophobic, racist, ageist, transphobic, or ableist outcomes. This book encourages the reader to take a step back to see how AI is impacting diverse groups of people and how diversity-awareness strategies can impact AI.

Autorentext

Roger A. Søraa is an Associate Professor at the Department of Interdisciplinary Studies of Culture at the Norwegian University of Science and Technology (NTNU), in Trondheim, Norway. His main research interests are the digitalization and robotization of society and its ethical, gendered, and epistemological consequences. He leads the Digitalization and Robotization of Society research group and coordinates several research projects, including the Horizon Europe project "BIAS: Mitigating Diversity Biases in the Labor Market."

Zusammenfassung
AI for Diversity questions how AI technology can lead to inclusion or exclusion for diverse groups of society. It enables the reader to step back and see how AI is impacting diversity in humans impacted by AI and how diversity-awareness strategies can impact AI.

Inhalt

1.Opening the Black Box of AI. 2. Gendered AI: performativity, expectations, and sexism. 3. Queering AI: gender expression, identity, and binaries. 4. AI and Race: recognition, bias, and systemic issues. 5. Bodies and AI: Health, ageing, and disabilities. 6. AI and Class: socioeconomic issues reproduced by technology. 7. Intersectionality and Responsible AI.