Hasso-Plattner-Institut25 Jahre HPI
Hasso-Plattner-Institut25 Jahre HPI
 

Ethical Questions in the Context of Data Engineering and Machine Learning (Wintersemester 2023/2024)

Lecturer: Dr. Thilo Hagendorff

General Information

  • Weekly Hours: 2
  • Credits: 3
  • Graded: yes
  • Enrolment Deadline: 01.10.2023 - 22.10.2023
  • Examination time §9 (4) BAMA-O: 31.03.2024
  • Teaching Form: Blockseminar
  • Enrolment Type: Compulsory Module
  • Course Language: English
  • Maximum number of participants: 30

Programs, Module Groups & Modules

Data Engineering MA
Software Systems Engineering MA
  • Software Systems Engineering
    • HPI-SSE-EL Ethics, Law and Compliance

Description

Description

The compact seminar deals with topics in the context of machine learning technologies, large language models and the associated (ethical and social) ramifications. The seminar will focus on different fields, ranging from behavioral ethics, AI governance, AI alignment, risks of generative AI systems, and many more. Importantly, the seminar focuses less on abstract ethical theories from philosophy, but rather on current, genuinely interdisciplinary research fields and papers, which deal directly with the intersection of ethics and computer science.

Learning

The purpose of the seminar is to become familiar with issues and methods from the field of ethics and its application to different AI systems.

Requirements

The provided references should be read before the start of the seminar so that the papers can be discussed during the seminar. The texts will be made available via Moodle.

Literature

References

Bartneck, Christoph; Lütge, Christoph; Wagner, Alan; Welsh, Sean (2021): What Is Ethics? In Christoph Bartneck, Christoph Lütge, Alan Wagner, Sean Welsh (Eds.): An Introduction to Ethics in Robotics and AI. Cham: Springer International Publishing, pp. 17–26.

Schwitzgebel, Eric (2014): The Moral Behavior of Ethicists and the Role of the Philosopher. In Christoph Luetge, Hannes Rusch, Matthias Uhl (Eds.): Experimental Ethics. London: Palgrave Macmillan UK, pp. 59–64.

Drumwright, Monette; Prentice, Robert; Biasucci, Cara (2015): Behavioral Ethics and Teaching Ethical Decision Making. In Decision Sciences Journal of Innovative Education 13 (3), pp. 431–458.

Brey, Philip (2010): Values in Technology and Disclosive Computer Ethics. In Luciano Floridi (Ed.): The Cambridge Handbook of Information and Computer Ethics. Cambridge, Massachusetts: Cambridge University Press, pp. 41–58.

Birhane, Abeba; Kalluri, Pratyusha; Card, Dallas; Agnew, William; Dotan, Ravit; Bao, Michelle (2021): The Values Encoded in Machine Learning Research. In arXiv: 2106.15590v1, pp. 1–28.

Jobin, Anna; Ienca, Marcello; Vayena, Effy (2019): The global landscape of AI ethics guidelines. In Nature Machine Intelligence 1 (9), pp. 389–399.

Morley, Jessica; Floridi, Luciano; Kinsey, Libby; Elhalal, Anat (2020): From What to How. An Overview of AI Ethics Tools, Methods and Research to Translate Principles into Practices. In Science and Engineering Ethics 26, pp. 2141–2168.

Munn, Luke (2023): The uselessness of AI ethics. In AI Ethics 3 (3), pp. 869–877.

Bommasani, Rishi; Hudson, Drew A.; Adeli, Ehsan; Altman, Russ; Arora, Simran; Arx, Sydney von et al. (2021): On the Opportunities and Risks of Foundation Models. In arXiv:2108.07258v2, pp. 1–212.

Hendrycks, Dan; Mazeika, Mantas; Woodside, Thomas (2023): An Overview of Catastrophic AI Risks. In arXiv:2306.12001, pp. 1–54.

Kenton, Zachary; Everitt, Tom; Weidinger, Laura; Gabriel, Iason; Mikulik, Vladimir; Irving, Geoffrey (2021): Alignment of Language Agents. In arXiv:2103.14659, pp. 1–18.

Weidinger, Laura; Uesato, Jonathan; Rauh, Maribeth; Griffin, Conor; Huang, Po-Sen; Mellor, John et al. (2022): Taxonomy of Risks posed by Language Models. In : 2022 ACM Conference on Fairness, Accountability, and Transparency. New York: ACM, pp. 214–229.

Zuboff, Shoshana (2015): Big other: surveillance capitalism and the prospects of an information civilization. In: Journal of Information Technology 30, pp. 75–89.

Learning

Compact seminar; group discussions; presentations if desired.

Examination

Grading is based on the quality of a term paper. The exact criteria according to which the paper will be graded will be discussed in the last session of the seminar.

Dates

time

January 25th, 2024

time

January 26th, 2024

January 27th, 2024

January 28th, 2024

 

 

09:15 to 10:45

Brey – Values in Technology and Disclosive Computer Ethics

Bommasani et al. – On the Opportunities and Risks of Foundation Models

Chapter “Inequity and fairness”, “Misuse” & “Environment”

Weidinger et al. – Taxonomy of Risks posed by Language Models

 

 

11:00 to 12:30

Birhane et al. – The Values Encoded in Machine Learning Research

Bommasani et al. – On the Opportunities and Risks of Foundation Models

Chapter “Legality”, “Economics” & “Ethics of scale”

Zuboff – Big other: surveillance capitalism and the prospects of an information civilization

14:00 to 15:30

Introduction

13:30 to 15:00

Jobin et al. – The global landscape of AI ethics guidelines

Hendrycks et al. – An Overview of Catastrophic AI Risks

Final discussions / seminar papers

15:45 to 17:15

Bartneck et al. – An Introduction to Ethics in Robotics and AI &

Schwitzgebel – The Moral Behavior of Ethicists and the Role of the Philosopher

15:15 to 16:45

Morely et al. – From What to How. An Overview of AI Ethics Tools, Methods and Research to Translate Principles into Practices

Kenton et al. – Alignment of Language Agents

 

17:30 to 19:00

Drumwright et al. – Behavioral Ethics and Teaching Ethical Decision Making

17:00 to 18:30

Munn – The uselessness of AI ethics

 

 

The seminar takes place online due to the strike. The dial-in details will be announced via Moodle.

Room: F-E.06 (if required, the room can be used on site)

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