FIT1110 · Human-centred artificial intelligence

Overview

This unit will explore how AI technologies are integrated into — and deeply influenced by — human values and social systems. It will explain the foundations of human-centred design and illustrate the application of design frameworks to designing socio-technical AI systems. In addition to gaining basic technical experience on how AI is constructed and used in software development, you will also develop your skills in critical analysis of AI technologies by engaging with their social dimensions and ethical challenges across a wide-range of case studies. These include studying how AI can reinforce old (or create new) forms of social discrimination, how to assess the authority and trustworthiness of AI outputs, and how AI is developed in a broader political and financial context. You will use your critical skills to evaluate existing AI technologies and propose new ways to redesign AI systems so they align with the principles, frameworks, and goals of human-centred design.

Offerings

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

The Handbook lists no prerequisite, corequisite or prohibition for this unit.

Learning outcomes

1. Describe the principles of human-centred design in their application to AI
2. Critically analyse AI systems in terms of their motivations, processes, and outcomes
3. Analyse different social, ethical, legal, and environmental challenges and problems with AI systems, and identify possibilities for appropriate solutions
4. Evaluate the broader social and technical implications of how AI is constructed and used in software development
5. Apply socio-technical knowledge to propose a detailed plan for (re)designing human-centred AI systems

Workload

This unit has a requirement of 1-2 hours per week of asynchronous learning. Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled online and face to face learning activities and independent study. Independent study may include associated reading and preparation for scheduled teaching activities.

Student experience, not official rules. Nothing here changes what the Handbook says.