Scheda programma d'esame
SOCIAL AND ETHICAL ISSUES IN INFORMATION TECHNOLOGY
VINCENZO GERVASI
Academic year2020/21
CourseCOMPUTER SCIENCE
Code659AA
Credits6
PeriodSemester 2
LanguageItalian

ModulesAreaTypeHoursTeacher(s)
SOCIAL AND ETHICAL ISSUES IN INFORMATION TECHNOLOGYINF/01LEZIONI48
VINCENZO GERVASI unimap
Programma non disponibile nella lingua selezionata
Learning outcomes
Knowledge

The course aims to provide a thorough overview of the many ethical and social issues raised by computer technology, with particular attention to Artificial Intelligence and its multifarious impact on society and human existence. Students will learn about the most compelling social and ethical challenges posed by information technologies and how to approach them in a rigorous and critical fashion. Conceptual analysis will be supported by discussion of practical case studies.

Assessment criteria of knowledge

Students will be assessed on the basis of their participation to in-class debates. Furthermore, they will be asked to produce a written essay in which they will submit a critical analysis of a practical issue connected to the topics discussed during the course. The final evaluation will take into account both the knowledge of the course material and the critical skills developed.

Skills

Students will develop or improve both the ability to think critically about social and ethical issues connected to the use of information technologies and the analytical skills that are necessary to approach such problems thoroughly.

Assessment criteria of skills

Skills will be assessed during in-class debate, practical exercises, oral presentations, and by assessment of written essays.

Behaviors

Students will be encouraged to develop critical awareness of the ethical and social impact of information technologies. They will be spurred to express their opinions with clarity and to defend them from objections or counterarguments. Students will engage in debate with their pairs and learn how to weigh different stances in an open, inclusive, and challenging learning environment.

Assessment criteria of behaviors

Readiness to participate, clarity of expression, communicative attitudes and analytical insight will be assessed during in-class debate, practical exercises, and oral presentations.

Teaching methods

Teaching methods will include traditional lectures with the aids of slides, in-class debate, practical activities, student presentations, and talks delivered by experts. The course is organized as a series of seminars, so the active participation of students will be essential. The course will be held in English.

Syllabus

The purpose of this course is to offer a thorough overview of the most debated issues in the fields generally known as Ethics of Information Technologies and AI Ethics. The lectures will cover the following topics, not necessarily in the listed order:
• 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 Bias;
• Anthropomorphism, Human-Computer/Robot Interaction (HCI, HRI), and Human Dignity;
• Automation, AI, and Labour;
• Automation, AI, and Social Equity;
• Possible practical cases for students’ presentations:

  • ◦ Sex robots; 
  • ◦ Military robots; 
  • ◦ Self-driving cars; 
  • ◦ Expert systems: COMPAS, Watson, …; 
  • ◦ Anthropomorphic emotional/social robots: Hanson’s Sophia, MIT’s Kismet, …;
  • ◦ Microsoft Tay’s Twitter misadventure, …; 
  • ◦ Machine artistic creativity (TheNextRembrandt, Obvious Art, Shimon, …), 
  • and so on.
Bibliography

Students will be asked to read at least 6 papers from the following list:
• Nick Bostrom – Ethical Issues in Advanced Artificial Intelligence.
• John Searle – Minds, Brains, and Programs.
• Andreas Matthias – The Responsibility Gap.
• James Gips – Towards the Ethical Robot.
• Nick Bostrom and Eliezier Yudkowsky – The Ethics of Artificial Intelligence.
• AI4People – Ethical Frameworks for a Good AI Society.
• Joanna Bryson – Semantics Derived Entirely From Language Corpora Contain Biases.
• Helen Nissenbaum – How Computer Systems Embody Values.
• Reuben Binns – Algorithmic Accountability and Public Reason.
• A. Sharkey – Robots and Human Dignity.
• Carl Benedict Frey et al. – The Future of Employment: How Susceptible Are Jobs to Computerization?
• J. Kaplan – Impact of AI on Social Equity.

For a general introduction to the topics that will be discussed in class, the following title is strongly recommended (but not compulsory):

Jerry Kaplan, Artificial Intelligence: What Everyone Needs to Know, Oxford, Oxford University Press (2016).

Further materials will be provided in class and made available through a dedicated page on Google Classroom.

Indications concerning material for oral presentations will be given in class.

Non-attending students info

Please contact the lecturers.

Assessment methods

Written essay: students will be required to produce a ~6000 words essay related to the topics of the course. The outcome of the exam will be successful if the students will be able to:
• analyze the technologies involved from an ethical and social point of view,
• interpret a practical case in a critical light,
• elaborate claims in a clear and thorough fashion,
• consider counterarguments or possible objections, and
• engage in a debate with their pairs.
The active participation of the candidate to in-class debates will also play its part in the final evaluation.

Updated: 28/06/2021 11:38