This book addresses the challenges posed by adopting and developing new AI technologies and how they impact people. Ethics, the scope, and the impact of technology on people are vital. The book starts with the ethical aspects of AI, presenting a socio-technical approach to integrating Ethics into AI projects, and outlines perspectives around feminism, sustainability, and labor transformation. Next, the concepts of fairness, accountability, and transparency are introduced, discussing their implications for developing information systems such as recommender systems, including aspects related to data privacy. Then the book covers the relevance of natural language processing systems, highlighting debias strategies and evaluation methodologies. The scopes of fairness-based approaches for ChatGPT and other generative text models are also introduced. Finally, advanced topics that include the relationship between AI and disinformation are addressed, including a discussion of the scope of news-generative models such as deep fakes. The book ends with a discussion of the perspectives and challenges in the area.
The book is meant for an audience of advanced undergraduate and graduate students from all disciplines related to information systems. It is also helpful for researchers and practitioners interested in the subject.
Gabriela Arriagada-Bruneau is an Assistant Professor with double appointment in the Applied Ethics (IEA) and Mathematical and Computational Engineering (IMC) Institutes at Pontificia Universidad Católica de Chile. She is a philosopher in the same university, and holds a Master of Science in Philosophy from The University of Edinburgh. She is a doctoral candidate with a specialization in Applied Ethics, particularly ethics of AI and data at the University of Leeds. She is a Young Researcher at the National Center of Artificial Intelligence in Chile (CENIA) and is the Latin American Lead for the World Ethical Data Foundation (WEDF). She has participated in expert consultations to develop the first Chilean regulation of Artificial Intelligence and UNESCO recommendations on neuroethics. Her current research interest is in Bias and Fairness in AI, Feminist Philosophy of Science, and Ethics of Disabilities.
Claudia López works as an assistant professor at Universidad Técnica Federico Santa María in Valparaíso, Chile. Additionally, she is a principal researcher at the National Center of Artificial Intelligence (CENIA) and the Millennium Nucleus on the Futures of Artificial Intelligence Research (FAIR) in the same country. She earned her PhD in Information Science and Technology from the University of Pittsburgh. Claudia, who has a background as an Informatics Engineer, focuses her research on human-centred artificial intelligence, social computing, and human-computer interaction (HCI). Her current projects focus on understanding how citizens perceive AI, making the use of AI more transparent, and incorporating ethical considerations in AI development. Claudia actively promotes a socio-technical perspective of AI in public discussions and is deeply involved in initiatives to strengthen the research in HCI in Latin America and increase women's participation in technology development.
Marcelo Mendoza is an associate professor in the Computer Science Department at Pontificia Universidad Católica de Chile. He received a Ph.D. in Computer Science from the Universidad de Chile. He did a postdoc in Yahoo Research. He is a founder and former President of the Chilean Association of Pattern Recognition and President of the Chilean Foundation for Transparency and Democracy. He is a principal researcher at the National Center of Artificial Intelligence (CENIA) and associate researcher at the Millennium Institute for Foundational Research on Data (IMFD). His research is focused on developing AI methods to measure and predict events and processes involving humans. His work includes the study of information dissemination, the spatial distribution of humans within cities, community formation, and the analysis of constructive and destructive interactions among individuals. His contributions are significant in advancing the understanding of how AI can address complex societal challenges, particularly those related to the dynamics of human behavior. He has published over 100 peer-reviewed papers in conference proceedings and top-tier journals. In 2021, he received the Seoul Test of Time award for co-authoring the paper Information Credibility on Twitter, a pioneering study in applying AI to the analysis of misinformation.
