Administrative Information
| Title | Investigate data lineage, challenges and potential impact of the AI teams |
| Duration | 90 min |
| Module | C |
| Lesson Type | Practical |
| Focus | Ethical - Compliance, Legality and Humanity |
| Topic | Data Management, Audit and Assessment |
Keywords
Data Lineage, Data Provenence, Differential Privacy, Data Pipeline,
Learning Goals
- To understand the concept and importance of data provenence for AI teams
- Impact of bias in datasets
- Methods for tracing Data Lineage
Expected Preparation
Learning Events to be Completed Before
Obligatory for Students
- Knowledge of GDPR and database concepts
Optional for Students
- N/A
References and background for students
- High level knowledge of GDPR and database concepts
Recommended for Teachers
- Provide background on GDPR
- Give examples of significant GDPR cases
Lesson materials
Instructions for Teachers
Try to stick to the time table. If possible provide more time to the question and answer session if needed.
Outline of lecture
| Duration (min) | Description | Concepts | Activity | Material |
|---|---|---|---|---|
| 0 - 5 min | Brief of the tasks to be conducted | |||
| 5 - 30 min | Task #1 - Provenance | Provenance | Guided Discussion | - |
| 30 - 55 min | Task #2 - Compliance | Compliance | Guided Discussion | - |
| 55 - 80 min | Task #3 - In Practice | In Practice | Guided Discussion | - |
| 80 - 90 min | Summary of the practical | Q&A | - |
Acknowledgements
Each author of the sources cited within the slides
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.