🔬 Research summary by Sarah P. Grant, a freelance writer dedicated to covering the implications of AI and big data analytics. [Original paper by Gerald C. Kane, Amber Young, Ann Majchrzak, and Sam … [Read more...] about Avoiding an Oppressive Future of Machine Learning: A Design Theory for Emancipatory Assistants
Design
Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI
🔬 Research summary by Dr. Marianna Ganapini (@MariannaBergama), our Faculty Director. [Original paper by Juan Manuel Durán & Karin Rolanda Jongsma] Overview: The use of AI in medicine promises to advance … [Read more...] about Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI
Artificial Intelligence: the global landscape of ethics guidelines
🔬 Research Summary by Avantika Bhandari, SJD. Her research areas cover indigenous knowledge and its protection, human rights, and intellectual property rights. [Original paper by Anna Jobin, Marcello Ienca, Effy … [Read more...] about Artificial Intelligence: the global landscape of ethics guidelines
Public Strategies for Artificial Intelligence: Which Value Drivers?
🔬 Research summary by Connor Wright, our Partnerships Manager. [Original paper by Gianluigi Viscusi, Anca Rusu, and Marie-Valentine Florin] Overview: Different nations are now catching on to the need of … [Read more...] about Public Strategies for Artificial Intelligence: Which Value Drivers?
The Meaning of “Explainability Fosters Trust in AI”
🔬 Research summary by Dr. Andrea Pedeferri, instructional designer and leader in higher ed (Faculty at Union College), and founder at Logica, helping learners become more efficient thinkers. [Original paper by … [Read more...] about The Meaning of “Explainability Fosters Trust in AI”