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

Lecture: Consumer Issues - Filter Bubbles, Data Storage, AI monitoring, fair practices
Lecture: Fair Operating Practices - AI Recruitment and Malpractices of AI Monitoring

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

Consumer Issues - Case study slides

The materials of this learning event are available under CC BY-NC-SA 4.0.

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

More information

Click here for an overview of all lesson plans of the master human centred AI

Please visit the home page of the consortium HCAIM

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.

The materials of this learning event are available under CC BY-NC-SA 4.0

The HCAIM consortium consists of three excellence centres, three SMEs and four Universities