Ethical and Legal Challenges of AI and Data Science

Practical Seminar Block Course: 14.-25. September

(For our virtual seminar we use Webex Meetings. In case you want to join a meeting please drop us an email.)


Further contributors:

  • PD Dr. Jürgen Altmann (Universität Dortmund, Dep. of Physics): Expert reporting on the current state and trends of military AI applications 
  • Prof. Dr. Sabine Ammon (TU Berlin, Dep. of Philosophy): Expert on ethics of technology and technology assessment
  • Dr. Vaishak Belle (University of Edinburgh, UK, School of Informatics, Partner in the UNA Europa University Alliance): Expert on explainability & ethics in AI, fairness in machine learning
  • Dr. Huimin Dong (Zheijang University, China, School of Humanities): Expertise in logic for law and ethics, logic for social networks
  • Prof. Dr. Philipp Hacker (HU Berlin, Dep. of Law): Legal expert reporting on discriminating algorithms
  • Prof. Dr. Volker Roth (FU Berlin, Dep. of Mathematics and Computer Science): Expert on secure identity 
  • Marcus Soll (Universität Hamburg): Expertise on adversial atttacks

Course poster: see here

Target group: Master’s students (Bachelor’s students from the fifth semester onwards)

Prerequisites: None

Block course format: The main part pf the seminar will be held in the form of a two week intensive block course (9:00-12:00 and 13:30--15:00) to be held from 14.-25. September. A mixture of lectures (including invited lectures by experts), student presentations and student projects/group work will be offered. The seminar includes an intensive preparation and postprocessing phase.

Student deliverables: Presentation (30 + 15 min), report (about 10 pages), further contributions depending on selected topic (surveys, programming, modeling, empirical studies), active participation in discussions

Description: Ethical and legal challenges in AI and Data science will be identified and options to resolve or control them will explored and discussed. The list of topics that will be addressed include:

  • Introduction, survey and delineation on core notions, including "AI", "Data Science", "Machine Learning", "Ethics and Law in AI and Data Science"
  • Survey and discussion of international positions and recommendations on ethical and legal regulation of AI and data science applications
  • Clarification and discussion of relevant notions, including "Trustworthy AI", "Explainable AI", "Transparent AI"
  • Elaboration of a spectrum of critical and non-critical applications of AI and data science technology
  • Exemplary discussion of selected, critical application areas, including e.g. military applications, automated financial markets, criminal profiling, etc.
  • Adversial attacks, and potential countermeasures
  • Bias in data science and machine learning, and potential countermeasures
  • Means to explain and assess decision making in data science and AI
  • Means to enforce ethical and legal control in data science and machine learning
  • Means to enforce ethical and legal control in large, integrated AI systems 
  • Ethics and security


Preliminary Schedule (changes my still apply)

Day 1 (14.9. Monday) 

Day 2 (15.9. Tuesday)

Day 3 (16.9. Wednesday)

Day 4 (17.9. Thursday)

  • Morning (starting at 9:00):
    • Adversial attacks (Marcus Soll)
    • Reading:  
      • Marcus Soll: InformatiCup Competition 2019: Fooling Traffic Sign Recognition. KI 2019: 325-332, 2019.
      • Marcus Soll, Tobias HinzSven MaggStefan Wermter:
        Evaluating Defensive Distillation for Defending Text Processing Neural Networks Against Adversarial Examples. ICANN (3) 2019: 685-696, 2020.
  • Afternoon (starting at 13:00): Group exercises on adversial attacks (these could extend over the WE into the next week)

Day 5 (18.9. Friday)

Day 6 (21.9. Monday)

Day 7 (22.9. Tuesday)

  • Morning (starting at 9:00):
  • Afternoon: Designing normative theories for ethical and legal reasoning: LogiKEy framework, methodology, and tool support (Christoph Benzmüller)
    • Reading:  
      • Designing Normative Theories for Ethical and Legal Reasoning: LogiKEy Framework, Methodology, and Tool Support. Artificial Intelligence, 237, pp. 103348, 2020. Preprint
      • LogiKEy Workbench: Deontic Logics, Logic Combinations and Expressive Ethical and Legal Reasoning (Isabelle/HOL Dataset), 2020.
      • Encoding Legal Balancing: Automating an Abstract Ethico-Legal Value Ontology in Preference Logic, 2020. Preprint

Day 8 (23.9. Wednesday)

  • Morning (starting at 9:00):
    • PhD projects on ethical reasoning (David Fuenmayor,  Sarah Hiller, etc.)
  • Afternoon (starting at 13:00):
    • Exercises/group work/student presentations

Day 9 (24.9. Thursday)

  • Morning (starting at 9:00):
    • Exercises/group work/student presentations
  • Afternoon (starting at 13:00):
    • Exercises/group work/student presentations

Day 10 (25.9. Friday)

  • Morning (starting at 9:00):
  • Afternoon (starting at 13:00):
    • (not part of the official seminar) Meet for a drink in the real world?


Exercise Topics as discussed on 14.9.:

TOPIC 1: AI Definition and Superintelligence

TOPIC 2: AI Ethics Principles (Guidelines)

TOPIC 3: Moral Machines (Ethical AI decisions)

TOPIC 4: AI Fairness, Discrimination & Biases

TOPIC 5: ML Security (Adversial Attacks, secure identity)

TOPIC 6: Law & Formal Logic (Symbolic AI)