AI and Data Ethics – Introduction for Data Scientists

Course Overview

Data scientists are pivotal in designing and implementing systems that impact society. This course provides a foundational understanding of ethics tailored to data scientists' specific challenges. Participants will explore how ethical principles intersect with technical processes, equipping them to create responsible and inclusive data-driven solutions.

Goal and Target Audience

• This course is designed specifically for data scientists who work with data and/or data-driven technologies and artificial intelligence systems.
• Understand the ethical dimensions of their work, including fairness, transparency, and accountability.
• Navigate complex ethical challenges in data collection, analysis, and application.
• Incorporate ethical principles into their daily workflows, whether building algorithms, analysing data, or collaborating within teams.
• Stay informed about European ethical standards, such as the ones underlying the GDPR and the AI Act, which directly impact their projects and responsibilities.

Course Aims

What this course is

An intensive, one-day workshop introducing participants to core concepts in AI and data ethics. The course includes both theoretical exploration and practical exercises to prepare participants for real-world ethical challenges in data science.

What this course is not

This course does not focus on specific programming or technical implementations. Instead, it emphasises critical thinking and decision-making skills in ethical contexts.

Course Objectives

Knowledge Objectives

• Understand fundamental ethical theories and their application to AI and data.
• Gain insight into European data ethics frameworks, such as the ones underlying the GDPR and the AI Act.

Skills Objectives

• Learn to identify and analyse ethical dilemmas in data science.
• Collaborate effectively with peers to propose ethical solutions.

Learning Objectives

• Apply ethical principles to professional challenges in data science.
• Build an ethical decision-making framework for team-based and individual projects.

Course Procedures

The workshop will include lectures, group discussions, and hands-on activities. Participants are expected to actively engage, particularly during group work and presentations.

Assessment

This course is assessed 100% through participation in group work and presentations. Participation in all sessions is mandatory.

How to join

Send an e-mail by 31 January 2025 with the following information:

• First and Last Name
• University (TUM / LMU) E-mail Address
• PhD Students:
  • Subject Area
  • School (TUM) / Faculty (LMU)
  • Name of the supervisor
• MSc Students:
  • MSc Program
  • School (TUM) / Faculty (LMU)

Successful applicants will be requested to identify one or more ethical considerations in their work they would like to discuss during the seminar, and send a one-pager explaining their project and its ethical challenges in relation to data and AI ethics where relevant by Feb. 20th, 2025.

Note: The course is open to relAI PhDs and MSc students. However, due to the limited number of available places, priority will be given to PhD students.