Administrative Information
| Title | Consumer Issues - Filter Bubbles, Data Storage, AI monitoring, fair practices |
| Duration | 50-55 min |
| Module | C |
| Lesson Type | Interactive Session |
| Focus | Practical - Socially Responsible AI |
| Topic | Corporate Social Responsibility (ISO 26000) - when using HCAI systems |
Keywords
Filter Bubbles, Data Storage, AI monitoring, AI landscapes,
Learning Goals
- Understand the implications of filter bubbles on consumer access to information.
- Explore the ethical considerations surrounding data storage and privacy.
- Discuss the impact of AI monitoring and fair practices on consumer rights.
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
None.
References and background for students
- Metaxas, P. T., & Mustafaraj, E. (2012). Social media and the elections. Science, 338(6106), 472-473.
- 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
The class can be divided into two groups, Each group will be assigned two case study scenarios listed in the slides.
Outline
| Duration (min) | Description | Concepts | Activity |
|---|---|---|---|
| 5 | Case Study - Consumer Issues 4 scenarios | Navigating the AI landscape | |
| 10 | Scenarios - Filter Bubbles, Data Storage, AI monitoring, Fair practices | Student driven Discussion | |
| 25 | Guided Discussion- Research Questions | Student driven Discussion | |
| 10 | Discussion of results and some additional points of discussion | Result discussion | |
| 5 | Conclusion and some open-ended questions | Food for thought |
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.