Overview

This module, AI Ethics, will give students the conceptual tools to understand the centrality of AI to modern society, and the political, ethical and governance issues it raises. It will involve assessing technologies and their impact on society. By means of case studies, consideration of technologies, and policy challenges, students will learn to offer expert opinion on how to resolve ethical conundrums that deny easy answers. It will be assessed by a group-led seminar and a report.

Students will be exposed to contemporary thinkers from data ethics, media, politics of technology, law and governance, cultural and communications theory, digital sociology, and science and technology studies.

Main themes and indicate syllabus contents include:

1. Understanding meta, normative, applied, and technology ethics
2. Technology ethics in depth: hybridity and post-phenomenology
3. Sifting AI hype from real-world AI
4. Algorithms and society: gauging racial bias
5. Education: what role should AI play?
6. Politics, social media and society: how is AI affecting political discourse and freedom of thought?
7. Automating empathy: how deeply may technologies understand us?
8. Automobility: biometric profiling and decision-making by self-driving cars
9. Transhumanism and longtermism: protecting tomorrow's simulations from today's physical people
10. "Just" machines and moral patiency: should robots have rights?
11. Cross-cultural ethics: who has the "right" answer?
12. Value-sensitive design: how should ethicists and technologists get along?

Assessment Strategy

By means of a group-led seminar and a final report.

Excellent (Grade A) Work at this level displays comprehensive knowledge and detailed understanding, reflecting extensive background study of AI ethics, likely derived from relevant academic journals . The work is highly focussed, well structured, logically presented and with defended arguments. The work contains original interpretation (or application) and new links between topics are developed. The work distills complex ideas and is presented to a high standard with accurate communication and no factual or computational errors.

Good (Grade B) Work at this level displays sound knowledge and understanding but with some limitations. There is evidence of background study and wider reading of AI ethics, with some of this drawing on academic journals. The work had a defined and logical structure but with some weaknesses in the way in which ideas and/or arguments are presented. There is some original interpretation, application and demonstration of links between topics. The work is presented carefully with accurate communication and few factual or computational errors.

Pass (Grade C or D at Level 4-6: Grade C at Level 7) Work at this level only demonstrates knowledge of key areas/principles and there is limited evidence of originality or of background study of Ai ethics. The work contains some irrelevant material and weaknesses in structure, likely from over-usage of non-academic sources. Arguments and ethical insights are presented but they lack coherence or depth. The work contains factual/computational errors with little evidence of problem solving. There are weaknesses in the standard of the presentation and its accuracy.

Learning Outcomes

• Analyse the complexity of AI ethics and AI technologies

• Critically analyse AI ethics problems to advise diverse stakeholders

• Critically evaluate ethical frameworks that guide development of AI technologies

• Differentiate technical factors and design considerations behind AI technologies