Artículo

Mapping the landscape of ethical considerations in explainable AI research

Resumen

With its potential to contribute to the ethical governance of AI, eXplainable AI (XAI) research frequently asserts its relevance to ethical considerations. Yet, the substantiation of these claims with rigorous ethical analysis and reflection remains largely unexamined. This contribution endeavors to scrutinize the relationship between XAI and ethical considerations. By systematically reviewing research papers mentioning ethical terms in XAI frameworks and tools, we investigate the extent and depth of ethical discussions in scholarly research. We observe a limited and often superficial engagement with ethical theories, with a tendency to acknowledge the importance of ethics, yet treating it as a monolithic and not contextualized concept. Our findings suggest a pressing need for a more nuanced and comprehensive integration of ethics in XAI research and practice. To support this, we propose to critically reconsider transparency and explainability in regards to ethical considerations during XAI systems design while accounting for ethical complexity in practice. As future research directions, we point to the promotion of interdisciplinary collaborations and education, also for underrepresented ethical perspectives. Such ethical grounding can guide the design of ethically robust XAI systems, aligning technical advancements with ethical considerations.
Nannini, Luca (57804142000); Marchiori Manerba, Marta (59188279400); Beretta, Isacco (58484464500)
Mapping the landscape of ethical considerations in explainable AI research
2024
10.1007/s10676-024-09773-7
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196790433&doi=10.1007%2fs10676-024-09773-7&partnerID=40&md5=e26ae58caa235ed77a66c0ea3ef49987
Centro Singular de Investigación en Tecnoloxías Intelixentes, Universidade de Santiago de Compostela, Santiago de Compostela, Spain; Computer Science Department, Università di Pisa, Pisa, Italy; KDD Laboratory, ISTI, National Research Council, Pisa, Italy; Minsait, Indra Sistemas, Madrid, Spain
All Open Access; Hybrid Gold Open Access
Scopus
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