University of West Attica

Artificial Intelligence and Data Science

Ethical, Policy And Legal Issues In Artificial Intelligence

Course info:

Semester: 7

General Foundation

ECTS: 6

Hours per week: 2

Professor: T.B.D.

Teaching style: Face to face, distance learning

Grading: Written exam (50%), exercises (50%)

Activity Workload
Lectures 26
Tutorials
Laboratory work
Project development 56
Autonomous learning 68
Course total 150

Learning Results

Upon successful completion of the course, students will be able to:

  • Demonstrate a basic understanding of the AI bias phenomenon and the role of AI in surveillance,
  • Demonstrate a basic understanding of the importance of democracy in relation to AI and acquaintance with common issues with democracy in relation to AI,
  • Demonstrate an understanding of the complexity of the concepts ‘intelligence’ and ‘consciousness’ and acquaintance with common approaches to creating artificial consciousness,
  • Demonstrate a basic understanding of the concepts of ‘forward-looking’ and ‘backward-looking responsibility’ and an acquaintance with problems connected to applying these concepts on AI,
  • Demonstrate a basic understanding of the control problem in AI and acquaintance with commonly discussed solutions to this problem,
  • Discuss the ethical and societal aspects of these issues.

Skills acquired

Retrieve, analyse and synthesise data and information, with the use of necessary technologies, Work in teams, Work in an interdisciplinary team, Promote free, creative and causative thinking

  • Algorithmic transparency
  • Cybersecurity vulnerabilities.
  • Unfairness, bias and discrimination
  • Lack of contestability.
  • Legal personhood issues.
  • Intellectual property issues.
  • Adverse effects on workers.
  • Privacy, security and data protection issues/problems.
  • Liability for damage and lack of accountability.
  • “Awakening” of AI.
  • General Data Protection Regulation.
  1. John Havens, Heartificial Intelligence: Embracing Our Humanity to Maximize Machines, Tarcher, 2016.
  2. James X. Dempsey, Artificial Intelligence: An Introduction to the Legal, Policy and Ethical Issues, Berkeley Center for Law & Technology, 2020.
Learning Results - Skills acquired

Learning Results

Upon successful completion of the course, students will be able to:

  • Demonstrate a basic understanding of the AI bias phenomenon and the role of AI in surveillance,
  • Demonstrate a basic understanding of the importance of democracy in relation to AI and acquaintance with common issues with democracy in relation to AI,
  • Demonstrate an understanding of the complexity of the concepts ‘intelligence’ and ‘consciousness’ and acquaintance with common approaches to creating artificial consciousness,
  • Demonstrate a basic understanding of the concepts of ‘forward-looking’ and ‘backward-looking responsibility’ and an acquaintance with problems connected to applying these concepts on AI,
  • Demonstrate a basic understanding of the control problem in AI and acquaintance with commonly discussed solutions to this problem,
  • Discuss the ethical and societal aspects of these issues.

Skills acquired

Retrieve, analyse and synthesise data and information, with the use of necessary technologies, Work in teams, Work in an interdisciplinary team, Promote free, creative and causative thinking

Course content
  • Algorithmic transparency
  • Cybersecurity vulnerabilities.
  • Unfairness, bias and discrimination
  • Lack of contestability.
  • Legal personhood issues.
  • Intellectual property issues.
  • Adverse effects on workers.
  • Privacy, security and data protection issues/problems.
  • Liability for damage and lack of accountability.
  • “Awakening” of AI.
  • General Data Protection Regulation.
Recommended bibliography
  1. John Havens, Heartificial Intelligence: Embracing Our Humanity to Maximize Machines, Tarcher, 2016.
  2. James X. Dempsey, Artificial Intelligence: An Introduction to the Legal, Policy and Ethical Issues, Berkeley Center for Law & Technology, 2020.