UnitLevel 2Undergraduate

FIT2118 Artificial intelligence futures: Research directions, drivers and dangers

Faculty of Information Technology

FIT2118 Artificial intelligence futures: Research directions, drivers and dangers is a level 2, 6-credit-point, undergraduate unit from the Faculty of Information Technology. It isn't offered in 2027. It needs FIT1059 or FIT1066 and unlocks 2 units.

Credit points
6
Offered in 2027
Not offered
Workload
144 hours
per semester

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Requisites

Overview

In this unit, you will learn how AI research is shaped, communicated, and practiced. You will investigate who and why governments, militaries, corporations, and public-interest bodies fund AI research and how their agendas may influence priorities. You will explore the implications of this for society and the environment. You will cover major AI sub-fields, including language, vision, speech, time-series, and robotics, and investigate how people interact with these systems. You will also practise locating, assessing, and synthesising research using scholarly databases and AI-enabled tools with transparent, reproducible methods and responsible judgement.

Offerings in 2027

The 2027 handbook lists no offerings for FIT2118.

Learning outcomes

When you finish this unit, you should be able to:

  1. 1

    Analyse how funding sources, incentives, and institutional agendas influence AI research priorities, and explain implications for equity, safety, governance, and public benefit;

  2. 2

    Describe major AI research sub-fields and typical application contexts, including how humans interact with AI systems and how these interactions shape design and deployment choices;

  3. 3

    Evaluate open problems in selected AI sub-fields by applying structured reasoning to compare approaches, identify limitations, and anticipate plausible future implications if key challenges are solved;

  4. 4

    Communicate a well-structured research and futures brief that synthesises evidence, articulates uncertainty, and recommends informed next steps for a specified audience, including disclosure of any AI-enabled tools used;

  5. 5

    Use advanced AI‑assisted research workflows—such as semantic search, automated summarisation and critical reasoning tools—responsibly, verifying outputs and documenting AI contributions with clarity and judgement.

Workload and teaching

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.

Where it fits

FIT2118 is part of 1 area of study in the 2027 handbook.

Common questions

What are the prerequisites for FIT2118?

You need FIT1059 or FIT1066 before you enrol.

What can I take after FIT2118?

FIT2118 is a prerequisite or corequisite for 2 units, including FIT3205 and FIT3206.

When is FIT2118 offered?

FIT2118 has no offerings listed in the 2027 handbook.

How much work is FIT2118?

The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.

Which majors and minors include FIT2118?

FIT2118 is part of Applied artificial intelligence.

More details

Credit points
6
Level
2
Study level
Undergraduate
Faculty
Faculty of Information Technology
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 2
Study abroad
Available
Handbook years
2027