Fairness and Bias in Data
Data Science · University of Applied Sciences · Data Ethics and Privacy
This unit examines the ethical implications of fairness and bias in data, exploring how they can impact decision-making. Students will gain an understanding of the importance of addressing fairness and bias in data science practices.
Zum Üben gibt es 50 Aufgaben. Jede Antwort bekommt sofort eine Rückmeldung, kostenlos und ohne Anmeldung.
Das gehört dazu
- Definitions of fairness and bias
- Ethical implications of fairness and bias
- Types of bias in data
- Techniques for identifying and mitigating bias
- Case studies of fairness and bias in data
Stichworte
- Fairness
- Bias
- Data Ethics
- Decision-Making
- Data Science