Data, Ethics and Law
Course, Master's level, 1DL002
Autumn 2023 Autumn 2023, Uppsala, 33%, On-campus, English
- Location
- Uppsala
- Pace of study
- 33%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 28 August 2023–30 October 2023
- Language of instruction
- English
- Entry requirements
-
140 credits including 75 credits in mathematics and computer science of which at least 15 credits in computer science. Alternatively 45hp in the Master's Programme in Language Technology (HSP2M). Proficiency in English equivalent to the Swedish upper secondary course English 6.
- Selection
-
Higher education credits in science and engineering (maximum 240 credits)
- Fees
-
If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees.
- Application fee: SEK 900
- First tuition fee instalment: SEK 12,083
- Total tuition fee: SEK 12,083
- Application deadline
- 17 April 2023
- Application code
- UU-11011
Admitted or on the waiting list?
- Registration period
- 28 July 2023–4 September 2023
- Information on registration
Autumn 2023 Autumn 2023, Uppsala, 33%, On-campus, English For exchange students
- Location
- Uppsala
- Pace of study
- 33%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 28 August 2023–30 October 2023
- Language of instruction
- English
- Entry requirements
-
140 credits including 75 credits in mathematics and computer science of which at least 15 credits in computer science. Alternatively 45hp in the Master's Programme in Language Technology (HSP2M). Proficiency in English equivalent to the Swedish upper secondary course English 6.
Admitted or on the waiting list?
- Registration period
- 28 July 2023–4 September 2023
- Information on registration
Autumn 2024 Autumn 2024, Uppsala, 33%, On-campus, English
- Location
- Uppsala
- Pace of study
- 33%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 2 September 2024–3 November 2024
- Language of instruction
- English
- Entry requirements
-
140 credits including 75 credits in mathematics and computer science of which at least 15 credits in computer science. Alternatively 45hp in the Master's Programme in Language Technology (HSP2M). Proficiency in English equivalent to the Swedish upper secondary course English 6.
- Selection
-
Higher education credits in science and engineering (maximum 240 credits)
- Fees
-
If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees.
- Application fee: SEK 900
- First tuition fee instalment: SEK 12,083
- Total tuition fee: SEK 12,083
- Application deadline
- 15 April 2024
- Application code
- UU-11011
Admitted or on the waiting list?
- Registration period
- 26 July 2024–9 September 2024
- Information on registration
Autumn 2024 Autumn 2024, Uppsala, 33%, On-campus, English For exchange students
- Location
- Uppsala
- Pace of study
- 33%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 2 September 2024–3 November 2024
- Language of instruction
- English
- Entry requirements
-
140 credits including 75 credits in mathematics and computer science of which at least 15 credits in computer science. Alternatively 45hp in the Master's Programme in Language Technology (HSP2M). Proficiency in English equivalent to the Swedish upper secondary course English 6.
Admitted or on the waiting list?
- Registration period
- 26 July 2024–9 September 2024
- Information on registration
About the course
The widespread use of digital data in society in combination with very powerful tools for its analysis leads to a number of ethical issues. The discipline of data science also raises several legal issues. You should develop the skill of identifying the relevant legal regulations.
How can we make a legal analysis about whether different tools in data science comply with the legislation? What are the differences and overlapping between the protection of personal data and the protection of personal privacy? How is intellectual property protected, e.g. how do you legally protect a machine learning tool? How has data science as a whole affected the development of legislation and why, namely, what interests have become important to protect because of the new possibilities to process data? How do you balance the interests of the different actors? And, how do you solve liability issues?
The course introduces relevant ethical theories and provides a background in legal aspects.
Reading list
No reading list found.