Ethical behavior and artificial intelligence

Semester

Semester 2, 2024-2025

Type of course

Theory-oriented Workshops

Date

March 19, 2025

Location

TBA

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Duration

1 day

Maximum number of participants

24

ECTS

0.5 EC will be appointed for participation in the complete course

Staff

Margarita Leib (TiU), Nils Kobis (University of Duisburg-Essen & Max Planck Institute for Human Development, Center for Humans and Machines)

Content

This 1-day workshop introduces KLI PhD-students to the behavioral ethics literature, and recent work on behavioral ethics and Artificial intelligence. In the morning session the instructors will (1) present theory and discuss the experimental approach of behavioral ethics, and (2) cover recent work that examines ethical behavior in interaction with Artificial intelligence. In the afternoon session, students will work in teams of maximum 6 students (under the supervision of the teachers), to develop a research question and experimental design, inspired by work on ethical behavior and artificial intelligence. Groups will present their ideas to the class at the end of the day. There might be opportunities carry out the proposed research after the workshop, with the guidance of the supervisors.

Learning goals

After finishing this workshop students will be able to: 

(1) Explain key theoretical approaches to studying ethical behavior; 

(2) Describe and utilize the main tools and methods used to experimentally study ethical behavior

(3) Describe and utilize the machine behavior approach

(4) Describe recent work on ethical behavior and artificial intelligence 

(5) Collaborate in a group, formulating a research question and designing an experiment related to ethical behavior and artificial intelligence 

Preparation

In preparation for the workshop, students are asked to read the papers mentioned below. The papers aimed to familiarize students with the behavioral ethics and machine behavior approach (papers 1 & 2) and showcase two examples of how AI is used to study ethical consequences (papers 3 & 4). 

Literature: (1-3 compulsory, 4 is optional)

1. Shalvi, S., Gino, F., Barkan, R., & Ayal, S. (2015). Self-serving justifications: Doing wrong and feeling moral. Current Directions in Psychological Science, 24(2), 125-130.

2. Köbis, N., Bonnefon, J. F., & Rahwan, I. (2021). Bad machines corrupt good morals. Nature Human Behaviour, 5(6), 679-685.

3. Noy, S., & Zhang, W. (2023). Experimental evidence on the productivity effects of generative artificial intelligence. Science, 381(6654), 187-192.

4. Leib, M., Köbis, N., Rilke, R. M., Hagens, M., & Irlenbusch, B. (2024). Corrupted by algorithms? how ai-generated and human-written advice shape (dis) honesty. The Economic Journal, 134(658), 766-784.

 

 

If there are more PhDs interested in participating than available places, distribution will be based on seniority for this course. This means that we look at how long someone is a KLI member.