Administrative Information
| Title | Perspectives on Privacy |
| Duration | 60 mins |
| Module | B |
| Lesson Type | Interactive Session |
| Focus | Ethical - Trustworthy AI |
| Topic | Privacy |
Keywords
Privacy, Privacy in AI, AI Risk, Risk Management, Resilience Management, Explainable AI, Interpretable AI, Security, Resilience, Transparency, Accountability, Industry-Specific AI Risk Management,
Learning Goals
- Understand, analyze and elaborate upon the importance of AI privacy and risk management in the various application sectors.
- Discern, investigate and discuss key risks which AI and Machine Learning models introduce and how experts from specific fields and sectors have chosen to address them.
- How to create a governance framework in your organization to enable AI risk management Summarize and understand the working principles, privacy and risks which AI systems introduce and how to address them.
- Expand on possible applications of privacy and security controls at each phase of the Artificial Intelligence lifecycle, based on sector-specific applications of AI.
- Open the discussion towards Privacy-Preserving Machine Learning and Privacy-Preserving Techniques.
Expected Preparation
Learning Events to be Completed Before
None.
Obligatory for Students
- High-Level Expert Group on Artificial Intelligence (AI HLEG). (Apr. 8, 2019). European Commission. “Ethics Guidelines for Trustworthy AI.
- HCAIM Lecture on Risk and Risk Mitigation
- HCAIM Interactive Session on AI Risks and Risk Management
Optional for Students
None.
References and background for students
- High-Level Expert Group on Artificial Intelligence (AI HLEG). (Apr. 8, 2019). European Commission. “Ethics Guidelines for Trustworthy AI.
- HCAIM Webinar on the European Approach Towards Reliable, Safe, and Trustworthy AI (Available on YouTube)
- HCAIM Webinar on the Role of Security and Privacy in Machine Learning (Available on YouTube)
Recommended for Teachers
- European Commission: Proposal for a Regulation of the European Parliament and of the Council Laying Down Harmonized Rules on Artificial Intelligence (Artificial Intelligence Act), 2021
- European Union Agency for Cybersecurity, Malatras, A., Dede, G., AI cybersecurity challenges: threat landscape for artificial intelligence, European Network and Information Security Agency, 2020
- High-Level Expert Group on Artificial Intelligence (AI HLEG). (Apr. 8, 2019). European Commission. “Ethics Guidelines for Trustworthy AI.”
- Malicious Uses and Abuses of Artificial Intelligence 2020, Europol Publication
Lesson materials
None.
Instructions for Teachers
This interactive session is a guest-led discussion on industry-specific perspectives on AI from sectors, such as maritime, energy, healthcare, finance, insurance, education, advertising, and human resources, to name a few.
The goal of this interactive session is to offer students a unique and relevant perspective on AI risk, risk management, and privacy AI.
To achieve this, the guest lecturer might choose to discuss specific use cases from their practice, or introduce specific problems that are being faced by the sector in general.
Two HCAIM Webinars are particularly relevant to this interactive session. Those could be shown prior to the discussion or parts of them could be played to facilitate topics and manage silence.
- HCAIM Webinar on the European Approach Towards Reliable, Safe, and Trustworthy AI (Available on YouTube)
- HCAIM Webinar on the Role of Security and Privacy in Machine Learning (Available on YouTube)
Outline
The materials provided, as well as the overall outline and schedule of the interactive session are indicative and presented in order to better guide a discussion with the students. As long as the learning goals are met, the guest lecturers and the facilitators/moderators of the interactive session are encouraged to follow the natural flow of the discussion.
| Duration | Topic | Description |
|---|---|---|
| 10 mins | Introduction | Introduction of the guest lecturer, their company, their work and the AI applications within their company or sector. Specific use cases of AI are introduced through the prism of privacy. |
| 40 mins | Privacy in AI | Approaching the topic of privacy in AI using sector-specific use cases. Discussion. |
| 10 mins | Closing Remarks | Discussion with Students. Questions and Answers. Introducing the topic of Privacy-Preserving Machine Learning. |
Guest lecturers create their own presentations and materials, using the templates provided by the HCAIM consortium. Specifically, for presentations, they use the following template.
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.