UnitLevel 3Undergraduate

ATS3187 Artificial Intelligence and algorithmic decision-making in the criminal justice system

Faculty of Arts

ATS3187 Artificial Intelligence and algorithmic decision-making in the criminal justice system is a level 3, 6-credit-point, undergraduate unit from the Faculty of Arts, offered in 2027 in Semester 2 at Clayton. It has no prerequisites.

Credit points
6
Offered in 2027
Semester 2
Clayton
Assessment
No exam
4 tasks
Workload
144 hours
per semester

Reviews

No reviews yet

No reviews yet. Be the first to review ATS3187.

Requisites

Before ATS3187

No prerequisites or corequisites besides the enrolment rules below.

After ATS3187

No unit lists ATS3187 as a prerequisite in the 2027 handbook.

Enrolment rules

Prerequisite: Must have passed 12 credit points of level two Arts units.

Overview

In this unit, you will critically examine how artificial intelligence and advanced technologies are transforming criminal justice systems in Australia and internationally. You will explore key applications including predictive policing, facial recognition, algorithmic risk assessment, AI-generated police reports, and surveillance technologies, and analyse the ethical, legal, human rights, and social justice implications of their deployment in policing, courts, and corrections.

Through Australian and International case studies you will assess how algorithmic decision-making tools can entrench existing inequalities, with particular attention to the disproportionate impacts on First Nations peoples and other marginalised communities. You will engage with regulatory and policy frameworks.

A distinctive feature of this unit is a hands-on prototype project in which you will use AI tools to develop a transparent complaint triage system, giving you practical experience in critically evaluating the technologies you study. You will also collaborate on a professional policy brief and oral presentation, building skills in evidence-based policy analysis and communication.

Whether you are pursuing a career in policing, law, policy, journalism, human rights, or technology, the ability to critically evaluate AI systems that make high-stakes decisions about people is fast becoming an essential skill. You will build on your existing knowledge to develop the kind of informed, evidence-based perspective that employers, government agencies, and advocacy organisations increasingly seek from graduates.

Offerings in 2027

Teaching periodCampusMode
Second semesterClaytonOn campus

Assessment

  • Design ProjectProject
    30%
  • Critical investigationProject
    20%
  • In-Class testQuiz / Test
    40%
  • In-Class Participation ActivityExercise
    10%

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

Learning outcomes

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

  1. 1

    Critically evaluate the major categories of AI and advanced technologies deployed across criminal justice systems in Australia and internationally, including predictive policing, facial recognition, risk assessment instruments, and AI-generated police reports.

  2. 2

    Analyse the ethical, legal, human rights, and social justice implications of deploying algorithmic decision-making tools in policing, courts, and corrections, with particular attention to impacts on First Nations peoples and other marginalised communities.

  3. 3

    Assess the accuracy, reliability, and validity of AI-based tools used in criminal justice by engaging with empirical research, case studies, and audit findings.

  4. 4

    Apply relevant regulatory and policy frameworks to evaluate AI governance in criminal justice contexts.

  5. 5

    Communicate complex arguments about technology, ethics, and justice effectively through written analysis, oral presentations, and policy briefs.

Workload and teaching

  • Tutorials24 hours
  • Lectures12 hours
  • Teaching approachActive learning
  • Teaching approachCase-based teaching

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours typically comprising a mixture of scheduled learning activities and independent study. Scheduled activities may include a combination of teacher directed learning, peer directed learning and online engagement.

This unit engages students in actively applying their knowledge, skills and attributes in interactive, collaborative and reflective activities including data analysis exercises, moot courts, policy debates, and community consultation simulations.

This unit includes case-based teaching, where students apply their knowledge and engage in analytical and reflective thinking to examine real-world AI deployments in criminal justice, including the Robodebt scheme, NSW Police STMP, and international case studies such as COMPAS and facial recognition controversies.

Contacts

Chief Examiners
Dr Zarina Vakhitova
Unit Coordinators
Dr Zarina Vakhitova

Common questions

What are the prerequisites for ATS3187?

ATS3187 has no prerequisites, but enrolment rules apply.

When is ATS3187 offered?

In 2027, ATS3187 runs in Semester 2 at Clayton.

How much work is ATS3187?

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

Does ATS3187 have an exam?

No. ATS3187 has 4 assessment tasks and no exam.

More details

Credit points
6
Level
3
Study level
Undergraduate
Faculty
Faculty of Arts
Organisational unit
School of Social Sciences
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 4
Study abroad
Available
Handbook years
2027