In this unit, you will learn how to design and evaluate intelligent decision-making solutions that support high-stakes choices in complex, uncertain and data-rich environments. Intelligent decision making combines data, models and human judgement to produce recommendations that are not only accurate, but also explainable, defensible and fit for purpose in real organisations.
You will develop the capability to frame decision problems, identify what evidence is needed, and select appropriate AI-enabled approaches to generate and justify recommendations. You will also learn how to evaluate decision quality, manage uncertainty and risk, and communicate decisions clearly to technical and non-technical stakeholders. Responsible practice is embedded throughout, including consideration of fairness, privacy, safety and accountability when decisions affect people and communities.
Responsible practice is embedded throughout, including consideration of fairness, privacy, safety, accountability, cultural context and the impacts of AI-supported decisions on people and communities. Students will be required to consider Aboriginal and Torres Strait Islander data sovereignty and Indigenous data governance where decision systems may affect First Nations peoples, communities, knowledges, cultural heritage, Country or community-controlled data.
Learning is applied and scenario-driven. You will work through realistic decision contexts using practical tools, guided workshops and iterative feedback, building from individual skill development to collaborative analysis and presentation. By the end of the unit, you will be able to produce and defend an intelligent decision-making solution that demonstrates professional judgement and measurable value.
On successful completion of this unit, students will be able to:
Selected readings will be available in VU Collaborate.
This unit is studied as part of the following course(s):