Administrative Information
| Title | Consumer Issues - Filter Bubbles, Data Storage, AI monitoring, fair practices |
| Duration | 45-60 min |
| Module | C |
| Lesson Type | Lecture |
| Focus | Practical - Socially Responsible AI |
| Topic | Corporate Social Responsibility (ISO 26000) - when using HCAI systems |
Keywords
Consumer Issues, Filter Bubbles, Fair Practices, AI monitoring,
Learning Goals
- Identify and define key consumer issues
- Analyse the implications of filter bubbles and AI monitoring on consumer issues.
- Explore the fair practices used when dealing with AI consumers
Expected Preparation
Learning Events to be Completed Before
Obligatory for Students
- Review the lecture notes on Consumer Issues and Research on case studies related to Consumer rights
Optional for Students
References and background for students
- The Filter Bubble: What The Internet Is Hiding From
- Tufekci, Z. (2014). Engineering the public: Big data, surveillance, and computational politics. First Monday, 19(7).
- Zarsky, T. Z. (2016). Transparent predictions. Washington Law Review, 91, 521-592.
Recommended for Teachers
- Binns, R., et al. (2018). Fairness in precision medicine. Proceedings of Machine Learning Research, 81, 1-15.
Lesson materials
Instructions for Teachers
Students should research companies regarding their efforts to comply with GDPR and the EU AI Act over the past year after the completion of this lecture.
Outline
| Duration | Description |
|---|---|
| 5 min | Introduction - Consumer Issues |
| 25 min | Consumer Issues due to Filter Bubble, AI monitoring |
| 20 min | Other Factors - Data Storage, Fair Practices |
| 5 min | Summary and Research Task |
Acknowledgements
The Human-Centered AI Masters programme was Co-Financed by the Connecting Europe Facility of the European Union Under Grant №CEF-TC-2020-1 Digital Skills 2020-EU-IA-0068.