AI Challenge

Theme: “How might we…”

Challenge Day: Thursday 15th October 2026

Overview

“How Might We…” prompts for the Trusted AI decision-support challenge pick one and run with it. Each is framed as an open “How Might We” question so you can shape your own solution, but comes with a real user, a decision to support, and the trust twist that makes it worth doing. Whatever you choose, scope it to one decision, one user, synthetic or public data — and remember the AI assists, a human decides

Tasks

1. Housing maintenance triage HMW: How might we help a housing maintenance coordinator prioritise urgent repairs across remote NT communities without “efficiency” quietly pushing remote tenants to the back of the queue?

2. Grant eligibility assessment HMW: How might we help a grants officer assess applications consistently and produce reasons a rejected applicant could actually understand and challenge?

3. Information‑access (FOI) request triage HMW: How might we help an information officer find the records relevant to a request while guaranteeing a human reviews anything sensitive before it’s released?

4. Risk‑based inspection prioritisation HMW: How might we help a regulator decide where to send limited inspectors first, without the model just re‑checking wherever it looked last time?

5. Getting urgent messages to a human, fast HMW: How might we make sure a vulnerable person’s urgent message never gets buried in a high‑volume government inbox and reaches a human quickly?

6. Making sense of long documents without over‑trusting the AI HMW: How might we help a caseworker get through a backlog of long policy or case documents faster, without nudging them into trusting a summary they haven’t verified?

Eligibility

Teams of 2–4 enrolled CDU IT coursework students (undergraduate, postgraduate, TAFE & short courses). Higher Degree by Research students are not eligible.

Evaluation

Judging Criteria

Submissions will be judged according to the following criteria: datasets, overall creativity and originality, technical sophistication, contextual relevance and practicality, ethical considerations and presentation.

First winner and runner up will be selected.

Panel of Judges

Sarah Strzelecki

Senior Manager AI Advisory, Department of Corporate and Digital Development (NTG)

Brett Riley

Data Warehouse Manager, Department of Corporate and Digital Development (NTG)

Dr Cat Kutay

Charles Darwin University, Australia

Rushi Vyas

What’s On, Australia

1. Team Up

Teams of 2–4 enrolled CDU IT coursework students (undergraduate, postgraduate, TAFE & short courses). Higher Degree by Research students are not eligible.

2. Submission

Submission items:
1. Project report (Requirement Link)
2. Source code (Python with remarks for the key steps) with a README file containing reproducing instructions.

Submission Deadline and Test Run: 08 October, 2026

Please send your progress with all necessary files and markdowns in a zip file to itcodefair@cdu.edu.au.

Email instructions:
i. Use a proper subject line. E.g. AI Challenge Submission – [Group] – IT Code Fair 2026
ii. Please mention your group details properly and include all necessary files in the zip folder.

3. Presentation on Challenge Day

10-minute pitching + 5-minute Q&A per team, present your project face-to-face with industry judges.

4. Award

First winner and Runner up will be announced on 5 November.

Important Dates

Registration Closing 18 September (5pm), 2026 To participate please REGISTER HERE.

Submission Deadline and Test Run: 08 October, 2026

Workshop 1: Discover and Define, 22-Sept-2026 at 16:30 ACST for 120 mins Workshop 2: Develop and Deliver, 02-Oct-2026 at 16:30 ACST for 120 mins

Workshop conducted by Rushi Vyas (Partner ANZ, OpenAI)
Workshops will be conducted on Microsoft Teams. Registered Participants will be sent an invitation link.

Challenge Day Thursday 15th October 2026