91257 - Ethics in Artificial Intelligence

Academic Year 2022/2023

  • Moduli: Giovanni Sartor (Modulo 1) Francesca Lagioia (Modulo 2)
  • Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
  • Campus: Bologna
  • Corso: Second cycle degree programme (LM) in Artificial Intelligence (cod. 9063)

Learning outcomes

At the end of the course, the student understands the main ethical aspects related to the creation and use of artificial intelligence systems. The student is able to reason critically about the main machine ethics issues connected with the moral behavior of AI systems endowed with autonomous decision capabilities and is able to evaluate the impact of the ethical and legal aspects connected with AI systems.

Course contents

The course aims to provide a thorough overview of the many ethical and social issues raised by information and communication technologies (ICTs), with particular attention to Artificial Intelligence and its impact on society and individuals.

Students will learn about the most compelling social and ethical challenges posed by ICTs and how to approach them in a critical way. Conceptual analysis will be supported by discussion of practical case studies.

Erasmus students follow the same programme of regular students.

Course Contents:

  • Introduction to Ethics
  • Information technologies, purposeful behavior and intelligence;
  • Singularity and Superintelligence;
  • Artificial Agency, Free Will, Consciousness;
  • Artificial Agents and Responsibility;
  • Machine Ethics;
  • AI Ethics and Roboethics;
  • Machine Learning, Big Data and the issues of Bias and Discrimination;
  • Anthropomorphism, Human-Computer/Robot Interaction (HCI, HRI), and Human Dignity; AI and Trust;
  • Human in the loop, Security, and Accountability;
  • AI Explainability and Transparency;
  • Assessing AI use cases. Socio-Technical Scenarios
  • Assessing AI use cases. Ethical tensions, Trade offs.
  • Possible use cases:
    • Military robots and Autonomous Weapon Systems;
    • Self-driving cars;
    • Expert systems: COMPAS, Watson, …;
    • Aviation and Air Traffic Management;
    • Machine artistic creativity (TheNextRembrandt, Obvious Art, Shimon, …);
    • AI Ethics in Healthcare
  • Legal relevance of AI Ethics
  • Ethical Business
  • AI and privacy
  • Modelling of legal and ethical norms and reasoning (with exercises)

Readings/Bibliography

Slide and teaching materials (compulsory and supplementary) will be provided during the course, and will be made available on the course website on Insegnamenti online.

Teaching methods

Lectures are held by Prof. Sartor and by Prof. Lagioia.

We warmly invite the students to actively participate in the lectures and discuss with teachers and other students the news and events, related to the topics of the course

During the course the students will have a chance to attend different conferences held by professors and experts (in philosophy, law and computer science) on the topics of this course.

Assessment methods

The assessment includes two mandatory parts: an oral presentation on a given topic and a quiz on all the topics of the course.

The first part of the assessment consists of an oral presentation. Students will be invited in forming small groups and investigate more in-depth one of the proposed topics. The output of this work will be an oral presentation during which each member of each group should present some aspect of the research for a minimal amount of time.
The assessment of this part will concern:

  • consistence with the chosen subject
  • novelty
  • observance of timing
  • in-depth level

 

The second part of the assessment consists of an oral exam. Students who have passed the group activity (min 18/30) can take the oral test. The test will take place on Microsoft Teams.

The oral test consists of two or three questions that may cover the entire content of the course.

In the oral test, the student starts with the grade obtained in the group activity, to which a maximum of 3 points may be added, and it may also lead to reducing the grade from the group activity.

Teaching tools

Slides and supplementary teaching materials on the main topics, software (e.g. Rationale) to show the structure of the topics.

Expert interventions, viewing of specific films, readings and materials for individual study.

Students who for reasons of disability or specific learning disorders (DSA) need compensatory tools will be able to communicate their needs to the teacher in order to agree on the most appropriate measures.

All information related to the course and supplementary teaching materials will be available on the course website on Insegnamenti online.

Office hours

See the website of Giovanni Sartor

See the website of Francesca Lagioia