1.8k citations · 2.9k across the 27 of their papers we have counts for
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Methodological reflections for AI alignment research using human feedback
Thilo Hagendorff, Sarah Fabi
The field of artificial intelligence (AI) alignment aims to investigate whether AI technologies align with human interests and values and function in a safe and ethical manner. AI…
Thinking Fast and Slow in Large Language Models
Thilo Hagendorff, Sarah Fabi, Michal Kosinski
Large language models (LLMs) are currently at the forefront of intertwining AI systems with human communication and everyday life. Therefore, it is of great importance to evaluate…
How to Assess Trustworthy AI in Practice
Roberto V. Zicari, Julia Amann, Frédérick Bruneault +17
This report is a methodological reflection on Z-Inspection. Z-Inspection is a holistic process used to evaluate the trustworthiness of A…
Why we need biased AI -- How including cognitive and ethical machine biases can enhance AI systems
Sarah Fabi, Thilo Hagendorff
This paper stresses the importance of biases in the field of artificial intelligence (AI) in two regards. First, in order to foster efficient algorithmic decision-making in complex…
Speciesist bias in AI -- How AI applications perpetuate discrimination and unfair outcomes against animals
Thilo Hagendorff, Leonie Bossert, Tse Yip Fai +1
Massive efforts are made to reduce biases in both data and algorithms in order to render AI applications fair. These efforts are propelled by various high-profile cases where biase…