Ethics in Artificial Intelligence

Universidad Autónoma de Barcelona

Course Description

  • Course Name

    Ethics in Artificial Intelligence

  • Host University

    Universidad Autónoma de Barcelona

  • Location

    Barcelona, Spain

  • Area of Study

    Business Administration, Ethics, Philosophy

  • Language Level

    Taught In English

    Hours & Credits

  • Contact Hours

  • Recommended U.S. Semester Credits
  • Recommended U.S. Quarter Units
  • Overview

    Objectives and Contextualization
    As an example of a general-purpose technology, artificial intelligence (AI) is present in more and more facets of our lives, creating concerns about its proper use as it evolves.
    This course explores the ethical issues surrounding developing and deploying artificial intelligence (AI) technologies. Students will learn about the philosophical, social, and legal considerations related to AI and create an understanding of the potential impacts of these technologies on society. Topics may include bias and fairness in algorithmic decision-making, privacy and surveillance, responsibility and accountability for AI systems, and the ethical implications of automation and job displacement. Through readings, discussions, and case studies, students will develop critical thinking skills and ethical frameworks to analyse and evaluate AI technologies and their impacts. 
    Some possible sources of inspiration are: How do we prevent algorithms' ethical biases? How best to embed AI systems in our professional and social relations? Is surveillance capitalism ethical? What ethical codes should guide AI applications like self-driving cars? Are AI systems moral agents? How is our brain considering trust in AI? Do AI systems need to pay taxes? Is the future of AI a threat to our existence? Is it ethical to fall in love with a robot? Can a robot express real feelings?

    At the end of the course, students will develop the following generic competencies: 
    • Critical thinking and analysis.
    • Creative thinking for problem solving.
    • Capacity to learn autonomously.
    • Capacity for generating new ideas.
    • Ethical commitment.
    • Basic knowledge of the field of study.
    • Ability to work in a team.

    Learning Outcomes
    After completing this course, students will be able to:
    1. Identify the ethical challenges of AI development and implementation.
    2. Analyze real-life scenarios where AI is involved. 
    3. Apply adequate philosophical and ethical frameworks to different case studies.
    4. Read news about AI development in a critical way. 
    5. Deconstruct ethical problems related to the use of AI. 
    6. Produce written ethical guidelines in a business context.
    7. Judge actions associated with the performance of AI in socioeconomic environments. 
    8. Generate opinions and recommendations to deal with AI in business. 
    9. Carry out their research in the field of study.
    10. Demonstrate their ability to reason logically. 

    Part One: Introduction
    Chapter 1: What is ethics? 
    Chapter 2: Why AI ethics?

    Part Two: Applied ethics
    Chapter 3: AI and philosophy of technology.
    Chapter 4: Applied ethics and AI.
    Chapter 5: AI and transhumanism.
    Chapter 6: The moral status of AI.

    Part Three: AI in business
    Chapter 7: AI in the workplace: Application areas and ethical concerns.
    Chapter 8: AI challenges.

    Part Four: Topics of interest 
    Chapter 9: AI and gender bias.
    Chapter 10: AI and political theory.
    Chapter 11: Ethics of AI for sustainable development goals.

Course Disclaimer

Credits earned vary according to the policies of the students' home institutions. According to ISA policy and possible visa requirements, students must maintain full-time enrollment status, as determined by their home institutions, for the duration of the program.

ECTS (European Credit Transfer and Accumulation System) credits are converted to semester credits/quarter units differently among U.S. universities. Students should confirm the conversion scale used at their home university when determining credit transfer.

Please reference fall and spring course lists as not all courses are taught during both semesters.

Availability of courses is based on enrollment numbers. All students should seek pre-approval for alternate courses in the event of last minute class cancellations


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