Filter bubbles, bias, rabbit holes and nudging
This lesson focuses on the AI systems that recommend content in various applications that students use on a day-to-day basis. It draws on students’ ethical understandings during analysis of these systems. This lesson was developed by the Digital Technologies Institute in collaboration with the Digital Technologies Hub.
Additional details
| Year band(s) | 9-10 |
|---|---|
| Content type | Lesson ideas |
| Format | Web page |
| Core and overarching concepts | Privacy and security, Systems thinking, Impact and interactions |
| Australian Curriculum Digital Technologies code(s) |
AC9TDI10P01
Develop techniques to acquire, store and validate data from a range of sources using software, including spreadsheets and databases
AC9TDI10P14
Apply the Australian Privacy Principles to critique and manage the digital footprint that existing systems and student solutions collect
AC9TDI10P02
Analyse and visualise data interactively using a range of software, including spreadsheets and databases, to draw conclusions and make predictions by identifying trends and outliers
AC9TDI10P10
Evaluate existing and student solutions against the design criteria, user stories, possible future impact and opportunities for enterprise |
| Technologies & Programming Languages | Artificial Intelligence |
| Keywords | Artificial Intelligence, AI, artificial, intelligence, problem solving, my computer brain, Recommender system, ethics, ethical issue, ethical behaviour |
| Integrated, cross-curriculum, special needs | Digital Literacy |
| Organisation | ESA |
| Copyright | Creative Commons Attribution 4.0, unless otherwise indicated. |
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