Students will be introduced to ethical and legal challenges when dealing with real data. Specifically, the topics of the course are structured into four parts, two on ethical issues and two on legal issues.

The first part will cover the following ethical issues by means of lectures with discussion:
* Introduction to ethics of AI & data science + narratives about AI
* Privacy and digital labor + future of work
* Responsibility and explainability + Bias/fairness
* Climate and environment: Opportunities and ethical problems

The second part will bridge to the more practical/empirical and political-social aspects and include the following topics:
* Critical Data and Algorithm Studies, how to reflect data practices, abrief introduction to Science and Technology Studies (STS)
* Everyday surveillance, human sensors
* Hands-on project: experimenting with data / ML: Training ML, data sets, open data (for DH Students, we can tailor this to specific interests)
* Presentation of project findings and discussion

The third part will cover legal issues on:
* Introduction into the legal system in Europe and Austria / legal resources
* Introduction to European data protection and data security law
IP, in particular copyright, licenses
* Recent trends, in particular digital services act

In the fourth part, we will be building on the introduction to legal basics outlined above. The course will provide a detailed overview of the most commonly encountered legal issues in DH projects.
* Example case studies - legal issues with source material:
- Copyright on primary texts
- Copyright on images (works of art)
- Data privacy issues with photographs
- Data privacy issues with diaries & letters
- Orphan works
* Example case studies - legal issues with research data:
- Ownership of scans
- Ownership of raw data; ownership of processed data
- Copyright on (scholarly) editions
- Ownership of scans
- Ownership of research output (e.g. papers)
- Ownership of code
- Research data about living persons and data privacy
- Non-research data about living persons and data privacy

In addition, the course will introduce a number of tools developed and infrastructure maintained by the DH community to tackle these issues (e.g. License Selector, Consent Form Wizard). Students will learn about the most important research infrastructures in the field of DH (CLARIN, DARIAH) and their working groups on legal and ethical issues (CLIC, ELDAH). Additionally, the relevance of the legal framework in which we conduct our research and its consequences for the implementation of Open Science approaches will be discussed.