Much of our everyday lives - from what we see in our social media feeds, to whether or not we get a bank loan - is governed by artificially intelligent systems. As the algorithms behind contemporary technology become more sophisticated they take over more and more of human decision-making. However, the ways in which these algorithms draw inferences are usually opaque and the conclusions they draw have often been found to be biased towards certain outcomes. Thus, the questions of the ethical ramifications regarding the use of such systems have become especially pertinent.
The course deals with ethics of artificial intelligence, focusing on issues related to machine learning (algorithmic bias, interpretability, fairness, responsibility in algorithmically assisted decision-making, privacy and surveillance, etc.), but other topics in the ethics of technology specific to artificial agents, human-robot interactions, and super intelligence will also be discussed. No previous technical knowledge of machine learning or ethics is presupposed, though general background in philosophy will be helpful.Course meetings will be divided into three parts, each dedicated to elucidating different aspects of the topic. These sections will roughly correspond to the ethical theory background behind debates in AI ethics, issues associated with the technical side of current AI systems, and specific, real world use cases and their ramifications.
Recommended readings:
https://plato.stanford.edu/entries/ethics-ai/Lo
Piano, S. (2020) Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward. Humanit Soc Sci Commun 7: 9. https://doi.org/10.1057/s41599-020-0501-9
The Oxford Handbook of Ethics of AI. (2020). Edited by Markus D. Dubber, Frank Pasquale, and Sunit Das, Oxford University Press.
- Kursleiter/in: Krzysztof Dolega