Applied Data Science

Class semester
2nd semester
Class type
Mandatory
Instructors
Alexandros Nousias

Topics per week

1. Introduction to Digital Ethics: An introductory session focusing on the ‘what is digital ethics’ and the ‘why ethics’

2. Values Perception Workshop: An interactive group exercise on value perception based on moral dilemmas encountered in ancient Greek tragedies (based on the methodology of VAST, EU H2020 research and innovation action)

3. Contextualising Information & Data: A conceptual analysis of the logic and the ethics of information including hands on applications

4. Data Governance: A description of the data governance framework and models

5. AI Systems & The Alignment Problem: How to ensure that the systems we develop will do what we truly want in a trustworthy fashion. Basic ethics principles

6. Transparency: What is transparency, why is needed and how can be implemented (with practical examples and hands on methodologies)

7. Representation & Fairness: Identifying the risks of knowledge representation & applying fairness (with practical examples and hands on methodologies)

8. Bias: Identifying different types of bias and why is it a problem (with practical examples and hands on methodologies)

9. Moral theories & dilemmas in complex systems: Idenitifying ethics as a complex system and navigating in complexity using moral theories

10. The Regulation taxonomy of the digital: Introducing the regulatory framework and its interplay with technology

11.  Assessing Risk & Impact: A list of practical assessment tools for different type of risk

12.  Use case 1: workshop

13.  Use case 2: workshop