Aileen Nielsen: Catalogue data in Autumn Semester 2021

Name	Ms Aileen Nielsen
Address	Professur für Recht und Ökonomie ETH Zürich, IFW E 49 Haldeneggsteig 4 8092 Zürich SWITZERLAND
E-mail	aileen.nielsen@gess.ethz.ch
Department	Humanities, Social and Political Sciences
Relationship	Lecturer

Number	Title	ECTS	Hours	Lecturers
851-0732-06L	Law & Tech Number of participants limited to 30.	3 credits	3S	A. Stremitzer, J. Merane, A. Nielsen
Abstract	This course introduces students to legal, economic, and social perspectives on the increasing economic and social importance of technology. We focus particularly on the challenges to current law posed by the increasing rate of tech innovation and adoption generally and also by case-specific features of prominent near-future technologies.
Learning objective	The course is intended for a wide range of engineering students, from machine learning to bioengineering to human computer interaction, as well as for law students interested in acquiring a better understanding of state-of-the-art technology. The course will combine both an overview of major areas of law that affect the regulation of technology and also guest lectures on the state-of-the art in a variety of important technologies, ranging from autonomous vehicles to fair artificial intelligence to consumer-facing DNA technologies. The course is open to ETH students through the Science in Perspective program of the Department of Humanities, Social and Political Sciences.
Content	The planned course outline is below 1. Overview of science, law, and technology a. Studies of law and technology b. Should science be regulated, and if so, how? c. Technology as a social problem 2. Designing technology for humans a. Attention fiduciaries and the digital environment b. Does technology weaponize known problems of bounded human rationality? c. Should technology be regulated as a psychotropic substance? An addictive substance? d. Can technology make life easier? e. Psychological effects of surveillance 3. Governing tech a. Can small governments regulate big tech? b. National and supranational legislation c. Enforcing the law with technology d. Can enforcement be baked into technology? 4. AI and fairness a. Discrimination b. Privacy c. Opacity d. AI and due process 5. Trade secret and technological litigation a. Trade secret is a long-standing tool for litigation but does it enjoy too much deference? b. Trade secrets and the rights of employes 6. Enforcement against tech a. Big tech and antitrust b. Consumer protection 7. The Digital Battlefield a. Technology for spying b. Spying on technology companies c. Race to be AI superpower d. Immigration policy 8. Contract law a. Smart contracts b. Modernizing contract law and practice c. Regulating cryptocurrencies 9. Tort law a. Applying existing tort law to new autonomous technologies b. Personhood and personal responsibility c. Victim entitlements 10. Self-driving cars and other autonomous robotics a. Legal regimes b. Diversity in morality judgements related to autonomous vehicles 11. Biometrics a. Widespread use of facial recognition b. Law enforcement c. Connecting biometrics to social data d. Solving crimes with biometrics 12. New Biology and Medicine a. Unregulated science (biohackers) b. Promising technology before it can be delivered c. Connecting medicine to social data d. Using technology to circumvent medical regulations
851-0746-00L	Algorithms and Fairness Any students enrolling in the course must complete a short writing assignment within two weeks of registering. Please contact the instructors via email (aileen.nielsen@gess.ethz.ch) for information about the assignment and for access to the course Slack workspace.	2 credits	1S	A. Stremitzer, A. Nielsen
Abstract	From a legal, social science, and applied mathematics perspective, we address the increasingly important question of what AI fairness means and how AI fairness can be addressed by legal, social science, and applied mathematical research to inform policy making.
Learning objective	Understand the history of fairness as defined in law, social science, and applied mathematics research Identify logical and mathematical conflicts between different definitions of fairness Explain why fairness and AI is a highly contested and unresolved problem in law.
Content	This block course will be broken into three components. Fair outcomes: the equality/equity debate -The proliferation of fairness definitions -Impossibility theorems -AI & fundamental rights Fair process -Appropriate use of AI in administrative or judicial roles -AI counterparties -Fair markets Fair distribution -Distributing scarce resources -Data markets and data labor -The future of work