AI

Ethics Chat: AI Ethics and AI Ethics Lab
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AI and Data Ethics Group:

“The AI and Data Ethics Group provides faculty and students from all disciplines the opportunity to study and discuss emerging issues and current research related to information, data, computing and AI ethics. Topics, readings and speakers are decided upon by members of the group on an ongoing basis. Examples of topics include justice and fairness in machine learning, the form and extent of rights to information and technology access, the appropriate roles of institutions to prevent dissemination of misinformation, the responsible collection and sharing of data, AI research oversight models, and the moral status of artificial intelligences. The group also aims to encourage and develop information ethics research projects and collaborations by its members. Students and faculty from any discipline are encouraged to join. If you are interested in joining this group, or have any questions about it, inquiries should be directed to John Basl, Assistant Professor of Philosophy.”

In this workshop, we will watch and discuss the Black Mirror episode called the “White Christmas”.

The “White Christmas” episode weaves together several stories and two main technologies: the Z-Eye that allows blocking others (as well as taking pictures, zooming in, etc.) and cookies that are like an extreme form of personalized AI assistants. Both of these technologies raise a variety of philosophical questions. In this workshop, we will focus on the Z-Eye technology and specifically its function in blocking people.

When searching for “professor” or “CEO” on Google images, the results show overwhelmingly white male pictures. While these jobs are held by white male professionals more often, the image search results present an extreme bias against representing women and people of color. This has been pointed out as an ethical problem in various outlets; however the problem persists.
In this workshop, we use this case as an example on how to structure the ethical problem at hand and its underlying principles before moving on to try solving it. Through the game-like structure of the Mapping method, the workshop will engage participants and help them develop essential tools to decide on ethical solutions that are technically feasible.

Discussions on ethical AI often lead to questions regarding the responsibilities and obligations of tech companies. What was, for example, legally problematic in Facebook’s Cambridge Analytica scandal and what was ethically wrong? What does it mean for a company to be ethically wrong if it operates within the legal limits? What are the legal limits of corporations when it comes to systems that rely on user consent and/or that form a de facto monopoly? In this discussion session, we will focus on corporate law in relation to AI ethics. In a “coffee meet-up” style, AI Ethics Lab will host Professor Holger Spamann from Harvard Law School to discuss these questions.

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Often we access information that is presented to us through an AI system. Search engine results, Google Scholar pages, social media posts and tweets are prioritized and made available to us through an algorithm. Voice assistants respond to our inquiries. The world as we know it is at this point largely shaped by the AI systems that surround us and this trend will continue to increase. What does this entail about what we can know, what it means to know and how we know it?

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Searching for “professor” or “CEO” on Google images, the results show overwhelmingly white male pictures. While these jobs are held by white male professionals more often, the image search results present an extreme bias against representing women and people of color. This has been pointed out as an ethical problem in various outlets; however the problem persists. In this workshop, we use this case as an example on how to structure the ethical problem at hand and its underlying principles before moving on to try solving it.