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DHUM403 When Machines Decide

Analysis of social, ethical, and legal issues arising from artificial intelligence and data science. Topics include bias, transparency, control, data sovereignty, employment and regulation. No knowledge of data science is assumed.

Artificial Intelligence is increasingly important in government, commerce, and daily life. This interdisciplinary course examines how we might best develop, deploy, regulate, and work alongside AI. It addresses issues such as bias, control, transparency, data sovereignty, liability, and the likely social and economic effects of AI. No expertise in computing or data science is required.

Paper title When Machines Decide
Paper code DHUM403
Subject Digital Humanities
EFTS 0.1667
Points 20 points
Teaching period Semester 2 (On campus)
Domestic Tuition Fees (NZD) $1,206.91
International Tuition Fees Tuition Fees for international students are elsewhere on this website.

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36 300-level points

No expertise in computing or data science is required.


Teaching staff

Course co-ordinator: Professor James Maclaurin

This course is taught by a selection of academics from programmes including: Computer Science, Data Science, Information Science, Law, Philosophy, Sociology, Social work and Statistics.

Teaching Arrangements

Teaching will consist of one lecture (50 minutes) and one seminar (1hr 50 minutes each) each week. The seminars will include a mix of lecture material and small group teaching. They will also be used for student presentations. Lectures and seminars will be common to students in 303 and 403.


Zerilli, J., Danaher, J., Maclaurin, J., Gavaghan, C., Knott, A., Liddicoat, J., and Noorman, M. E. (2021) A Citizen's Guide to Artificial Intelligence, Cambridge Massachusetts, MIT Press. For more information see

Graduate Attributes Emphasised

Information literacy, communication, critical thinking, ethics, global perspective
View more information about Otago's graduate attributes.

Learning Outcomes

Students who successfully complete the paper will:

  • Have enhanced understanding and communication of the development, use, and commercialisation of data science and artificial intelligence (Lifelong Learning; Critical Thinking)
  • Have enhanced understanding of common impacts and drivers of the use of data science and artificial intelligence.
  • Analyse ethical, regulatory, and public policy debates in light of practical considerations for those provisioning and developing data science and artificial intelligence (Critical Thinking; Interdisciplinary Perspective)
  • Debate and communicate the risks associated with data science and artificial intelligence in scientific, government and business contexts (Critical Thinking; Communication; Information Literacy; Teamwork)
  • Develop detailed analysis of a practical application of data science and artificial intelligence, including design considerations, risk factors and social impact (Critical Thinking; Interdisciplinary Perspective; Information Literacy)
  • Understand key debates relating to the ownership, control and use of data, including an ability to critically analyse the differential impacts of AI for different populations.
  • Have enhanced understanding of the application of selected software industry guidelines and tools for identifying and reducing societal risks in the development and deployment of AI systems.
  • Demonstrate cultural awareness and describe how the concepts of data sovereignty and equity apply to the use of artificial intelligence and indigenous data (Cultural Understanding)

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Semester 2

Teaching method
This paper is taught On Campus
Learning management system


Stream Days Times Weeks
A1 Monday 15:00-16:50 28-34, 36-41
Thursday 09:00-09:50 28-34, 36-41