(in Polish) Prawne aspekty HR: podstawy administracji kadrami i wyceny pracy 2600-ZLAIz1PAHR
The aim of the course is to familiarize participants with the legal requirements relating to personnel administration and recruitment, with particular emphasis on personal data protection (GDPR) and the use of AI tools. Participants will also acquire knowledge of the legal protection of remuneration, the drafting of internal regulations, and job evaluation methodology in light of the latest EU directives.
The course combines knowledge of labour law with the practical challenges of the modern labour market, including the use of artificial intelligence (AI), personal data protection (GDPR), and EU requirements concerning pay transparency. During the course, participants will examine the entire employee lifecycle within an organization from the perspective of applicable legal regulations. The course “Legal Aspects of HR: Fundamentals of Personnel Administration, Job Evaluation and New Technologies” (30 hours) comprehensively combines traditional labour law knowledge with the practical challenges of the modern labour market, including the use of artificial intelligence (AI), personal data protection (GDPR), and EU pay transparency requirements. Participants will examine the entire employee lifecycle within an organization from the perspective of applicable legal regulations.
1. Legal Aspects of Recruitment and the Use of Artificial Intelligence
The employee recruitment process in light of labour law, the GDPR and the AI Act; the limits of employers’ powers at the recruitment stage, the principles governing the processing of candidates’ data, and the legal and ethical risks associated with the automation of application screening, including:
● limitations on recruitment questions;
● AI tools and Applicant Tracking Systems (ATS) in recruitment;
● legal and ethical risks associated with AI in recruitment;
● algorithmic bias and discrimination;
● automated decision-making (Article 22 GDPR);
● the EU AI Act and HR.
2. GDPR in HR and Data Protection When Using AI Tools
Analysis of the employee data lifecycle, from hiring to archiving, with particular emphasis on the secure implementation of AI solutions (e.g. ChatGPT, internal LLMs, predictive HR analytics) in the day-to-day work of HR departments, including:
● legal bases for data processing in HR;
● maintaining personnel files and digitalization;
● GDPR principles when implementing AI tools in HR;
● the principles of data minimization and purpose limitation;
● confidentiality and data leakage;
● Data Protection Impact Assessment (DPIA);
● employee monitoring and AI.
3. Employment Relationship, Working Time and Personnel Records
Practical aspects of concluding and terminating employment contracts, organizing working time, and maintaining the necessary personnel documentation in accordance with labour law, including:
● forms of employment;
● flexible forms of work;
● working time in practice;
● employee rights and entitlements;
● remuneration;
● social insurance.
4. Legal Framework for Job Evaluation, Equal Treatment and Job Grading Structures
Job evaluation methodology, the development of fair remuneration systems, and compliance with legal requirements concerning equal pay and pay transparency, including:
● the principle of equal treatment in employment (Article 18³c of the Labour Code);
● the EU Pay Transparency Directive;
● the obligation to disclose salary ranges in job advertisements;
● the prohibition on asking candidates about their previous remuneration;
● mandatory Gender Pay Gap reporting and employees’ right to information on average remuneration for comparable positions;
● job evaluation as a legal tool;
● job evaluation methods, with particular emphasis on analytical point-factor methods;
● job evaluation criteria, including responsibility, qualifications, effort, and working conditions;
● drafting internal legal instruments, including remuneration regulations, pay scales, job grading structures, and job classification tables compliant with applicable law.
The course is conducted in a seminar format and is focused on developing practical skills necessary for the safe management of HR processes in a digital business environment.
Course coordinators
Type of course
Learning outcomes
After finishing the course, the student:
KNOWLEDGE: THE GRADUATE KNOWS AND UNDERSTANDS: K_W02, K_W04
- at an advanced level, complex processes and phenomena occurring in different types of organizations and in their surrounding environment, and applies management theory, in particular theories related to people management, drawing on complementary disciplines such as economics and finance, legal sciences and social sciences, to identify, diagnose and solve problems related to people management in organizations, using an appropriate selection of sources, adapting existing methods or developing new ones, and integrating them within the organization’s strategy;
- at an advanced level, legal regulations concerning the functioning of organizations, in particular those relating to people management in organizations.
SKILLS: THE GRADUATE IS ABLE TO: K_U01, K_U02, K_U09
- apply theories from the discipline of management and quality sciences, in particular in the area of people management using AI, as well as from complementary disciplines (legal sciences), to identify, diagnose and solve complex and non-standard problems related to people management in the internal and external environment of an organization;
- correctly interpret complex processes and phenomena, e.g. social, technological, legal, economic and environmental, and their impact on the functioning of organizations and the economy as a whole;
- enhance acquired qualifications, support others in doing so, and engage in self-directed learning.
SOCIAL COMPETENCES: THE GRADUATE IS PREPARED TO:
K_K01, K_K02, K_K05
- assess and adopt a critical approach to complex situations and phenomena related to the functioning of organizations, in particular the labour market and people management processes involving the use of AI;
- recognize the importance and value of scientific knowledge in solving complex problems in the field of people management, including those involving the use of AI, as well as seek expert opinions in this process;
- comply with, enforce and contribute to the development of professional ethical standards in business relations, and uphold the professional ethos.
Assessment criteria
Active participation in classes – up to 70 points; ongoing assessment – 70 points; test – up to 30 points; practical project on an assigned topic – up to 30 points; other activities – up to 20 points.
Passing threshold: 120 points.
Bibliography
Examples of recommended literature:
1. Kodeks pracy – legal status as of 5 November 2026.
2. Commentaries on the Labour Code, GDPR and the AI Act – current editions available in legal databases.
3. Labour law textbooks – editions no older than 2025, preferably published in 2026, due to the considerable number of recent changes.
4. Regulation (EU) 2016/679 of the European Parliament and of the Council (GDPR) – with regard to the processing of employee data (Articles 6, 9 and 22).
5. Regulation of the European Parliament and of the Council laying down harmonised rules on artificial intelligence (EU AI Act) – provisions concerning high-risk systems in the field of employment.
6. Directive (EU) 2023/970 of the European Parliament and of the Council on strengthening the application of the principle of equal pay for equal work or work of equal value between men and women through pay transparency.
7. Otto, M. (2022). Dyskryminacja algorytmiczna w zatrudnieniu. Zarys problemu. Studia z Zakresu Prawa Pracy i Polityki Społecznej, 29(2), 145–159.
8. Bąba, M. (2020). Algorytmy – nowy wymiar nadzoru i kontroli nad świadczącym pracę. Praca i Zabezpieczenie Społeczne, 3.
9. O’Neil, C. (2017). Broń matematycznej zagłady. Jak algorytmy nasilają nierówności i zagrażają demokracji. Wydawnictwo Naukowe PWN.
10. Szostek, D. (2020). Sztuczna inteligencja a prawo. C.H. Beck.
11. Adams-Prassl, J. (2019). What if Your Boss Was an Algorithm? The Economic Agency and the Future of Work. Comparative Labor Law & Policy Journal, 41(1), 123–146.
12. Żołyński, J., & Brzostek, K. (2024). Blockchain jako nowoczesne narzędzie prawa pracy i zarządzania pracą: wymiar ogólnoteoretyczny i praktyczny.
13. Karczewska, A., & Kukowska, K. (2025). MOŻLIWOŚCI I WYZWANIA ZASTOSOWANIA NARZĘDZI AI W PROCESACH REKRUTACJI I SELEKCJI NA RYNKU PRACY. Management & Quality/Zarządzanie i Jakość, 7(4), 375.
14. Strożek-Kucharska, M., Mółka, M., Adamowski, J. W., & Borski, M. (2026). Przyszłość pracy w administracji publicznej w erze AI: jak sztuczna inteligencja może zmienić struktury zatrudnienia i kompetencje pracowników organów administracji publicznej? The Future of Work in Public Administration. In Sztuczna inteligencja w ekosystemie medialnym: algorytmy, automatyzacja, społeczne konsekwencje (pp. 349–361). Akademia Humanitas. Oficyna Wydawnicza Humanitas.
15. Drobot, J. (2025). Osobiste świadczenie pracy w dobie sztucznej inteligencji. Radca Prawny. Zeszyty Naukowe, (3), 53–68.
16. Striker, M., & Grzesiak, L. (2025). Analityka HR i controlling personalny w organizacji: struktura, kompetencje, narzędzia. Wydawnictwo Uniwersytetu Łódzkiego.
17. Sztandar-Sztanderska, K. (2026). How context matters: Human oversight of automated decision-making systems in welfare administration. Journal of European Social Policy, 36(3), 255–269.
18. Sztandar-Sztanderska, K., Kotnarowski, M., & Zieleńska, M. (2021). Czy algorytmy wprowadzają w błąd? Metaanaliza algorytmu profilowania bezrobotnych stosowanego w Polsce. Studia Socjologiczne, 89–115.
Additional readings will be provided on an ongoing basis.