Program

Keynote address

From Data to Discovery: Developing AI Tools for Economic and Social Policy
Associate Professor Jan Kabátek 
Melbourne Institute

Session 1: AI Adoption, Work, and Society
How are workers, managers, consumers, and institutions responding to AI and its consequences.

Chair: Maxim Ananyev (Melbourne Institute)

AI adoption and subscription dynamics in Australian transaction data
Hamish Thomas (e61 Institute)

Managers as gatekeepers in the age of AI
Jacob Dominski (University of Notre Dame)
Christopher Hoy (Melbourne Institute)
Yong Suk Lee (University of Notre Dame)
Cassandra Merritt (University of Notre Dame)

GenAI and job quality in Australia’s ageing and gender-segregated workforce
Anya Bedi (The University of Sydney)
Isabella Dabaja (The University of Sydney)
Elsie Foeken (The University of Sydney)
Laura Good (The University of Sydney)
Suneha Seetahul (The University of Sydney)

Human–AI collaboration in finance education: Developing and evaluating AI-assisted interactive finance simulators
Assaf Dekel (The University of Melbourne)
Natalie Le (The University of Melbourne)

Session 2: Building AI-Enabled Research and Learning Infrastructure
What are the practical systems and tools that support economists, government researchers, analysts, and students.

Chair: Ujjwal KC (Melbourne Institute)

Ask ABARES: Building an agentic retrieval-augmented generation system for a government economic research agency
Neal Hughes (Department of Agriculture Fisheries and Forestry)

Machine-readable economics papers for agentic research
Patrick Healy (Monash University) 

Safeguarding knowledge: A systematic review of AI-content detection tools, algorithms, and institutional challenges.
Igor Poluboiartsev (Asia Pacific University of Technology and Innovation, Malaysia)
Ankit Kumar Bhardwaj (Asia Pacific University of Technology and Innovation, Malaysia)
Ekaterina Balkanova (Monash University Malaysia)

Comparison as Insight: Iteratively Designing a Human-AI Collaborative Agent for Public Opinion Research
Erin Kelly (Advanced Symbolics)
Kenton White (Advanced Symbolics) 

Panel session
Universities in the age of AI

Eduard Hovy, Executive Director, Melbourne Connect, The University of Melbourne
Greg Nyilasy, Director, BehavAI Research Lab, The University of Melbourne 
Leah Schwartz, Director, AI and Education, The University of Melbourne
Matthew Greenwood-Nimmo, Head of Macroeconomics, Melbourne Institute (moderator)

Keynote address

Session 3:  AI for Text, Classification, and Evidence Synthesis
How we can use AI to convert complex or unstructured information into reliable research data.

Chair: Taylor Ey (Melbourne Institute)

Interpretable textual classifiers for complex economic questions
Joel Fernando (Reserve Bank of Australia)
Nicholas Gray (Reserve Bank of Australia)
Dominic Zaun Eu Jones (Reserve Bank of Australia)
Tamika Stasiuk (Reserve Bank of Australia)
Max Zang (Reserve Bank of Australia)

Evaluation of AI-based coding of occupation responses in the HILDA Survey
Taylor Ey (Melbourne Institute)
Michelle Summerfield (Melbourne Institute) 
Nicole Watson (Melbourne Institute)

Using AI to combine qualitative and quantitative economic data: Application to life-history data of urban job-seekers
Simon Franklin (Queen Mary University of London)

Trends in the use of preference-weighted health-related quality of life instruments in clinical trials over the past 50 years: a protocol for a meta-research study using AI models. 
Sarun Srikhom (The University of Melbourne) 

Session 4: AI for Financial, Strategic, and Trusted Decision-Making
Deploying and evaluating AI in high-stakes analytical and decision environments.

Chair: Filippo Dell'Andrea (The University of Melbourne)

Pivotal: A new language for interactive data workflows
Neal Hughes (Department of Agriculture Fisheries and Forestry)

Imag(in)ing the bull and bear markets
Yong Song (The University of Melbourne)

Climate risk through the eyes of insurers: Earnings calls and the cross-section of stock returns
Hong Li (Monash University)
Yufan Lu (The University of Melbourne)
David Pitt (The University of Melbourne)
Rui Zhou (The University of Melbourne)

AI-assisted strategic decision-making for vehicle-to-grid energy management: A constraint-aware deep reinforcement learning and stackelberg framework
Muhammad Adil (Polytechnic Institute Australia)
Muhammad Usman Ali Khan (Polytechnic Institute Australia)
Torikul Islam Badal (Polytechnic Institute Australia)
Mahwish Ramzan (Polytechnic Institute Australia)
Muhammad Wajahat (Polytechnic Institute Australia)

Panel session
Making AI work: Opportunities and challenges for business and government