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ME102: The Ethics of Data and Artificial Intelligence

Subject Area: Research Methods, Data Science, and Mathematics

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Course details

  • Department
    Department of Philosophy, Logic and Scientific Method
  • Application code
    SS-ME102
Dates
Session oneOpen - 17 Jun 2024 - 5 Jul 2024
Session twoNot running in 2024
Session threeNot running in 2024

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We are accepting applications. Apply early to avoid disappointment.

Overview

AI is now embedded in our day-to-day lives, influencing who we date, the new stories we read on our social media feed, how we invest in financial assets, our community’s exposure to the police, the goods we consume online, and the tasks we do at work.

Ethics has often been the last step in the design and deployment of AI technologies. But, new and pending regulation, activism by civil society, and self-governance efforts by companies have sought to integrate values like fairness, safety, and privacy throughout the product development process or decision support system design.

This course introduces you to the core ethics concepts needed to build better technology and reason about its impact on the economy, civil society, and government. In the first half of the course, we consider ethical questions raised by different steps in the data science pipeline, such as:

  • What is data, and how can we design better (ethical?) data governance regimes?
  • Can technology discriminate? If so, what are promising strategies for promoting fairness and mitigating algorithmic bias?
  • Can we understand black-box AI systems and explain their decisions? Why is it morally important that we do so?

In the second half of the class, we consider ethical questions raised by the use of AI systems to manage our work, political, and social lives, such as:

  • How does automation impact economic inequality?
  • Do employees have a right to privacy at work?
  • How does AI concentrate power, and when is this concentration of power objectionable?
  • How can we embed human values into AI systems?
  • How does AI art challenge authorship and intellectual property rights?

 

Students who receive an offer for this course are also eligible to apply for the Academic Director's Scholarship.

Key information

Prerequisites: There are no prerequisites for this course. No prior study in philosophy or computer science is assumed, and students from all disciplines - from law to engineering to business - are welcome.

Level: 100 level. Read more information on levels in our FAQs

Fees: Please see Fees and payments

Lectures: 36 hours

Classes: 18 hours

Assessment: A mid-session essay (50%) and a final exam (50%)

Typical credit: 3-4 credits (US) 7.5 ECTS points (EU)

Please note: Assessment is optional but may be required for credit by your home institution. Your home institution will be able to advise how you can meet their credit requirements. For more information on exams and credit, read Teaching and assessment

Is this course right for you?

This course is ideal if you’re seeking a practical understanding of the ethical challenges and potential solutions posed by real-world AI systems.

This course is especially beneficial to those targeting a career in data science or computational social science, product management, managerial positions, AI policy, information technology law, or an academic career in a field related to the ethics of AI.

Outcomes

  • Understand core ethics concepts and how those concepts apply to AI systems
  • Analyse the ethical issues raised by a particular technology by applying core ethical reasoning techniques to real-world case
  • Show how to apply cutting-edge ethics research within the development process to build more ethical AI systems
  • Communicate your own ethical viewpoint clearly and persuasively by reconstructing others’ arguments, objecting to them, and providing your own solution

Content

Treyana Reed, USA

I have learnt new coding language and principles of my subject that will help me later in my career.

Faculty

The design of this course is guided by LSE faculty, as well as industry experts, who will share their experience and in-depth knowledge with you throughout the course.

Kate Vredenburgh

Dr Kate Vredenburgh

Assistant Professor

Ali Boyle

Dr Ali Boyle

Assistant Professor in Philosophy

Alex Voorhoeve

Professor Alex Voorhoeve

Professor

Paola Romero

Dr Paola Romero

Guest Teacher

Department

The Department of Philosophy, Logic and Scientific Method was founded in 1946 by Sir Karl Popper and is renowned for doing philosophy in a manner that is both continuous with the sciences and socially relevant. It is widely recognized as a world-leading place for teaching and research in philosophy of the natural and social sciences, logic, moral and political philosophy, epistemology, decision and game theory, and social choice. The department was ranked #3 in the world for Philosophy in the 2023 QS World University Rankings.

The Department embodies LSE’s long tradition of analytic, interdisciplinary, and socially engaged philosophy. This tradition, and the fact that to become part of it, all you need is a critical, independent mind-set and a desire to do empirically informed philosophy, is exemplified by some of the world’s leading thinkers and social reformers from diverse backgrounds who have worked or studied at LSE.

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Applications are open

We are accepting applications. Apply early to avoid disappointment.