DATA3406: Human-in-the-Loop Data Analytics

University of Sydney•2026 S2
In Progress
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Human-Centred Data
Ethics
Bias & Uncertainty
Stakeholders
Visualisation
Literate Programming

Human-centred data science across the full analytical loop: stakeholder requirements, data gathered from people, uncertainty and bias, ethics, communication and evaluation.

Learning Outcomes

Official unit information
  • Ethical and legal reasoning: Identify ethical and legal issues arising in data analytics and connect them to the driving questions of an analysis.
  • People in the loop: Analyse how people act as data sources, analysts, decision makers and subjects affected by analytical outcomes.
  • Stakeholder requirements: Identify explicit and implicit requirements while accounting for the perspectives of different stakeholders.
  • Bias and uncertainty: Select and justify analytical techniques suited to unreliable, biased or uncertain human-generated data.
  • End-to-end pipeline: Design, implement, document and evaluate a human-in-the-loop analysis pipeline using literate programming.
  • Responsible communication: Communicate methods and results through appropriate text, tables and visualisations for the intended audience.

Current Focus

This unit is especially relevant to my interest in real-world sensing systems: measurements involving people are never purely technical. I am focusing on how study design, consent, uncertainty, stakeholder interpretation and evaluation shape whether a data product is genuinely trustworthy.