Algorithms in digital economy

elective courses

Remote learning

The conversatory is focused on the topic of the algorithms and the role they play in the contemporary economy and society. The aim of this class is to discuss the regulatory challenges raised by the algorithms and the solutions which are adopted in law (with the special focus on European Union law) in order to face these challenges. The topics discussed in the class include, e.g., algorithmic bias, the provisions concerning automated decision-making in the area of data protection law, and consumers’ rights referring to price differentiation. The regulatory aspects will be discussed in relation to the particular examples of the implementation of algorithms in the economic context (e.g. content filtering in social media) and in the public sector (e.g. algorithms implemented in the judiciary and in law enforcement). This course is important for better understanding of business transactions in dynamically changing digital economy.

The conversatory is focused on the topic of the algorithms and the role they play in the contemporary economy and society. The aim of this class is to discuss the regulatory challenges raised by the algorithms and the solutions which are adopted in law (with the special focus on European Union law) in order to face these challenges. Each of the seven meetings will be focused on specific topic related to the algorithms’ regulation, mostly – but not only – in EU law.

1. Introduction: Regulatory challenges raised by algorithms

- the introduction to the types of legal sources which will be analysed during the classes (mostly EU law);

- the examples of the algorithms’ implementation in public and private sector;

- the catalogue of the regulatory challenges related to the algorithms, e.g. lack of transparency, potential discrimination;

- the challenges raised by the algorithms to law.

2. Data protection law and automated decision making

- the analysis of arts 13-15 and 22 of the General Data Protection Regulation;

- the obligation to conduct data protection impact assessment (examples: the EU and the US).

3. Algorithms and citizens: algorithm as public information

- approaching algorithms as public information on the examples drawn from Polish case law and in the context of European law;

- problems related to approaching algorithms as public information – analysis of the examples drawn from the US’s case law.

4. Algorithms and copyrights protection: content moderation and content filtering

- the analysis of art 17 of directive 2019/790 in the context of the CJEU’s case law on content filtering;

- the role of algorithmic solutions and platforms’ role in shaping of the public debate.

5. Algorithms and consumers: consumer rights and competition law

- geoblocking and price differentiation;

- the unique position of the internet platforms from the perspective of competition law (gatekeepers) due to their role in data collection and algorithms’ development.

6. Algorithms’ regulation in international trade agreements

- the analysis of selected provisions of regional trade agreements concerning source code and algorithms and of the negotiated text of multilateral agreement on e-commerce negotiated under World Trade Organisation;

- the challenges raised by the source code protection as trade secrecy.

7. AI: regulatory challenges and solutions

- the specific character of the challenges raised by the development of aritficial intelligence;

- the analysis of selected provisions of the legislative proposal Act on AI.

This class provides an opportunity not only to gain certain knowledge on the regulation of algorithms, but also to discuss important problems of the contemporary social and economic world.

Amount of work required from the student:

- presence and active participation in classes (7 x 1,5 hours);

- reading the materials provided by the lecturer (6 x 1 hour).

Bibliography (basic):

- Wachter S., Mittelstadt B., Floridi L. (2017) Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation, “International Data Privacy Law”, vol. 7, issue 2, pp. 76-99;

- Bloch-Wehba H., Access to Algorithms (2020) “Fordham Law Review”, vol. 88, pp. 1265-1314;

- Ferri F. (2020) The dark side(s) of the EU Directive on copyright and related rights in the Digital Single Market. China-EU Law J. https://doi.org/10.1007/s12689-020-00089-5;

- Capobianco A., Nyeso A.(2017) Challenges for Competition Law Enforcement and Policy in the Digital Economy. Journal of European Competition Law & Practice, pp. 1–9, doi:10.1093/jeclap/lpx082;

Bibliography (facultative and for exercised taking place during classes):

- AlgorithmWatch, Bertelsmann Stiftung, Open Society Foundations, (2019) Automating Society. Taking Stock of Automated Decision-Making in the EU;

- Panoptykon Foundation (J. Niklas, K. Sztandar-Sztanderska, K. Szymielewicz) (2015) Profiling the Unemployed in Poland: Social and Political Implications of Algorithmic Decision Making, Warsaw;

- Lessig L. (2006) Code. Version 2.0, Basic Books, New York (selected chapters);

- Neeraj R. S. (2017) Trade rules on source code: Deepening the digital inequities by locking up the software fortress. Centre for WTO Studies Indian Institute of Foreign Trade;

- Irion K., Williams J. (2019) Prospective Policy Study on Artificial Intelligence and EU Trade Policy. The Institute for Information Law.

Other sources:

- scenes from the movie „Coded Bias” (2020) which illustrate the challenges related to the implementation of automated solutions;

- press articles on the issues discussed during the classes.

K_U04 (Uses a foreign language at the B2+ level of the Common European Framework of Reference for Languages and specialist terminology in the field of science of management and quality)

K_W04 (Has knowledge and in-depth understanding of legal regulations regarding the functioning of the organization and the entire economy)

K_U02 (Is able to correctly interpret complex technological, social, political, legal, economic, and ecological processes and phenomena and their impact on the functioning of the organization and the entire economy, using the appropriate selection of sources.)

Assessment methods and criteria include:

- students’ presence in the classes (40%);

- active participation in the classes (60%).

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