Course Description

The ongoing AI revolution calls for a responsible approach to AI development. This PhD course focuses on understanding the social consequences of AI-powered technologies. Participants will get familiar with approaches to AI development which put humans at the centre and are guided by ethical principles of respect for human autonomy, prevention of harm, fairness and explicability to improve individual and collective wellbeing. They will study how gender, racial, and social status biases encountered in datasets and algorithms aimed at making crucial decisions in our everyday lives lead to unfair discrimination, as well approaches to avoid data bias and algorithmic discrimination crucial to creating a more trustworthy and fair AI. They will reflect on the technical advances and research to account for inclusion and diversity. To better understand how we can develop more ethical and inclusive technologies in the future, this course also aims to reflect on AI development in compliance with legislation such as the EU AI Act.

Course Objectives

At the end of this course, the participants’ will be able to:

  • Understand principles of trustworthy AI.
  • Understand aspects of AI fairness, e.g., data bias, algorithm discrimination, fairness in synthetic data.
  • Identify and analyse challenges and harm deriving from the lack of inclusion, diversity, and AI ethics in embodied (e.g., social robots) and disembodied technologies.
  • Understand principles and approaches for research on responsible AI and AI policy.
  • Identify and analyse the ethical challenges when deploying technology in different scenarios, e.g., in education, healthcare.

Details

Timeline: February-April 2026

Teaching activities: Each lecture consists of a seminar (60 min + 30 min Q&A) and a workshop (45 min)

Tentative schedule

Lecture 1: Fredrik Heintz, Linköping University: Trustworthy AI (February 24th)

Lecture 2: Friederike Eyssel, Bielefeld University: Inclusive and accessible robotics (March 4th)

Lecture 3: Natalia Calvo Barajas, former Vi3 postdoc: AI fairness (March 12th)

Lecture 4: Jason Tucker, Institute for Future Studies and AI Policy Lab Umeå University: Researching Responsible AI Policy in a Disorderly Geopolitical Landscape (March 13th)

Lecture 5: Vicky Charisi, MIT Media Lab: Responsible designs of AI systems for children’s education that align with human rights (March 24th)

Assessment

Individual assignmentAttendance policy: to pass the course, it is mandatory to attend at least 3 out of 5 lectures. In addition, compensation assignments will be required for any missed lecture.

How to register

Send an email to ginevra.castellano@it.uu.se by February 9th.

Website: https://uppsala.instructure.com/courses/122729/pages/home

This course is funded by the Department of Information Technology’s Equal Opportunities Group.