FIT1060 · Human understanding and AI navigation

Overview

Human Understanding & AI Navigation introduces you to the foundations of human‑centred computing, and the skills and knowledge needed to design and work effectively in an AI-integrated world. You will learn how humans experience technology, how human needs shape digital systems, and why approaches centering the human are essential for creating solutions that genuinely work for diverse communities. You will also build confidence in working with AI as a tool while maintaining strong human agency. Through hands‑on, collaborative activities and design‑thinking approaches, you will strengthen complex problem‑solving capabilities and develop an innovation mindset required to work effectively in diverse, multidisciplinary teams. Building these capabilities will prepare you to thrive in tech roles where problems are complex, teams are diverse, and solutions must be grounded in real human contexts.

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. Identify how digital technologies and AI-enabled systems can affect people, communities and society, recognising opportunities to support inclusion, accessibility, sustainability and social good;
2. Communicate human needs, design ideas, evidence and AI-assisted work clearly using appropriate written, verbal and visual forms for peers and project stakeholders;
3. Collaborate effectively in diverse teams by contributing to shared activities, coordinating simple tasks, listening to others and responding constructively to feedback;
4. Apply introductory human-centred design practices to explore user needs, generate design ideas, document design choices and develop simple design artefacts for digital or AI-integrated systems;
5. Observe how people interact with digital or AI-enabled technologies, identifying basic usability issues and opportunities to improve user experience;
6. Gather and interpret feedback on simple digital or AI-enabled designs, using human-centred evaluation methods to explain how evidence can inform improvement.

Workload

Minimum expected workload to achieve the learning outcomes of this unit is 144 hours per semester comprising a mixture of scheduled face to face learning activities (2 hours workshop and 2 hours applied classes per week) 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.