91257 - Ethics in Artificial Intelligence

Course Unit Page

  • Teacher Giovanni Sartor

  • Credits 6

  • SSD IUS/20

  • Language English

  • Campus of Bologna

  • Degree Programme Second cycle degree programme (LM) in Artificial Intelligence (cod. 9063)

Academic Year 2020/2021

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 with the support of collaborators.

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 exam includes a written part, which is mandatory, and an oral part, which is facultative.

In the written part, the student will have to answer open questions on the topics of the course. So as to answer the questions, the student will fill the appropriate fields on the exam module and eventually continue on the reverse side of it.

The written exam will last for 2 hours. No texts and/or codes can be used.

Approximately a week after the exam, we will publish the results.

Students obtaining a mark of at least 18 points in the written exam have the following choice:

  1. they can ask that the mark obtained in the written exam is registered as their final mark; or
  2. they can come to the oral exam and ask for an additional question in order to improve their mark. The oral exam is optional, and may also result in decreasing the mark obtained in the written exam.

In case 1), the student will send an email message to informaticagiuridicags.adm@gmail.com, including the following information:

  • name and surname
  • student number
  • date of the written exam
  • explicit acceptance of the mark as published in the website of the course

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