053620 VU Data Ethics and Legal Issues (2022S)
Continuous assessment of course work
Labels
REMOTE
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 14.02.2022 09:00 to Th 24.02.2022 10:00
- Deregistration possible until Mo 14.03.2022 23:59
Details
max. 25 participants
Language: English
Lecturers
- Vanessa Hannesschläger
- Catherine Altobelli
- Paul Eberstaller
- Nikolaus Forgó
- Erich Prem
- Mariana Alicia Rissetto
- Eugenia Stamboliev
- Elisabeth Steindl
Classes (iCal) - next class is marked with N
regular course time: Monday, 2 pm - 5 pm
ATTENTION: on 4 April and 2 May, the course takes place 3pm - 6 pm!
Monday
07.03.
14:00 - 17:00
Digital
Monday
14.03.
14:00 - 17:00
Digital
Monday
21.03.
14:00 - 17:00
Digital
Monday
28.03.
14:00 - 17:00
Digital
Monday
04.04.
15:00 - 18:00
Digital
Monday
25.04.
14:00 - 17:00
Digital
Monday
02.05.
15:00 - 18:00
Digital
Monday
09.05.
14:00 - 17:00
Digital
Monday
16.05.
14:00 - 17:00
Digital
Monday
23.05.
14:00 - 17:00
Digital
Monday
30.05.
14:00 - 17:00
Digital
Monday
13.06.
14:00 - 17:00
Digital
Monday
20.06.
14:00 - 17:00
Digital
Monday
27.06.
14:00 - 17:00
Digital
Information
Aims, contents and method of the course
Assessment and permitted materials
50% group work & presentations
20% short essay
30% final
20% short essay
30% final
Minimum requirements and assessment criteria
There is no mandatory prerequisite for this class.The grading scale for the course will be:
1: at least 87.5%
2: at least 75.0%
3: at least 62.5%
4: at least 50.0%In order to pass the course successfully, you will need to reach a minimum of 30% on each of the assessments.
1: at least 87.5%
2: at least 75.0%
3: at least 62.5%
4: at least 50.0%In order to pass the course successfully, you will need to reach a minimum of 30% on each of the assessments.
Examination topics
* Ethical issues raised by AI and data science
* Societal challenges
* Legal Basics
* Data protection and intellectual property law
* Current legal developments
* DH tools for legal issues in practice
* DH research infrastructures
* Open Science
* Legal issues with source material
* Legal issues with research data
* Societal challenges
* Legal Basics
* Data protection and intellectual property law
* Current legal developments
* DH tools for legal issues in practice
* DH research infrastructures
* Open Science
* Legal issues with source material
* Legal issues with research data
Reading list
* Coeckelbergh, Mark. 2020. AI Ethics. MIT Press.
* Coeckelbergh, Mark. 2019. Artificial Intelligence, Responsibility Attribution, and a Relational Justification of Explainability. Science and Engineering Ethics, https://link.springer.com/article/10.1007/s11948-019-00146-8
* Crawford, Kate. 2021. Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. New Haven: Yale University Press.
* Perez, Caroline Criado. 2019. Invisible Women: Data Bias in a World Designed for Men. New York: Abrams.
* Dignum, Virginia. 2020. “Responsibility and Artificial Intelligence.” In The Oxford Handbook of Ethics of AI, edited by Marcus Dubber, Frank Pasquale, and Sunit Das, 215–33. University of Oxford Press.
* Fuchs, Christian & Sevignani 2013 What is Digital Labour? https://www.triple-c.at/index.php/tripleC/article/view/461
* House of Commons 2018 report “Algorithms in Decision-Making https://publications.parliament.uk/pa/cm201719/cmselect/cmsctech/351/35104.htm
* Mittelstadt, Brent, et al. 2016. The ethics of algorithms: Mapping the Debate. Big Data & Society https://journals.sagepub.com/doi/full/10.1177/2053951716679679
* Zou, James & Schibinger, Londa. AI can be sexist and racist - it’s time to make it fair. Nature https://www.nature.com/articles/d41586-018-05707-8
* OANA: Vienna Principles. A Vision for Scholarly Communication, 2015/16. https://viennaprinciples.org/
* Wilkinson, Mark D.; Dumontier, Michel; Aalbersberg, IJsbrand Jan; Appleton, Gabrielle; et al. (15 March 2016). "The FAIR Guiding Principles for scientific data management and stewardship". Scientific Data 3: 160018. doi:10.1038/sdata.2016.18. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4792175/
* Open Science Network Austria OANA. https://www.oana.at/
* DARIAH-EU. https://www.dariah.eu/
* DARIAH working group Ethics & Legality in Digital Arts & Humanities ELDAH. https://eldah.hypotheses.org/
* CLARIN ERIC. https://www.clarin.eu/
* CLARIN Legal and Ethical Issues Committee CLIC: Copyright Law Overview. https://www.clarin.eu/content/clic-overview-copyright-law
* CLARIN Legal and Ethical Issues Committee CLIC: Introduction to Copyright and Related Rights. Orphan works. https://www.clarin.eu/content/clic-orphan-works
* Vanessa Hannesschläger. Common Creativity international. CC-licensing and other options for TEI-based digital editions in an international context. In Journal of the Text Encoding Initiative, Issue 11 (2016 Conference Issue), July 2019 -, Online since 17 November 2019. DOI: https://doi.org/10.4000/jtei.2610
* DARIAH ELDAH Consent Form Wizard (CFW). https://consent.dariah.eu/
* Bates, Jo, Yu-Wei Lin, and Paula Goodale. 2016. ‘Data Journeys: Capturing the Socio-Material Constitution of Data Objects and Flows’. Big Data & Society 3(2):205395171665450. doi: 10.1177/2053951716654502.
* Ienca, Marcello, and Effy Vayena. 2020. ‘On the Responsible Use of Digital Data to Tackle the COVID-19 Pandemic’. Nature Medicine 26(4):463–64. doi: 10.1038/s41591-020-0832-5.
* Kitchin, Rob. 2014. ‘Big Data, New Epistemologies and Paradigm Shifts’. Big Data & Society 1(1):205395171452848. doi: 10.1177/2053951714528481.
* Olteanu, Alexandra, Carlos Castillo, Fernando Diaz, and Emre Kıcıman. 2019. ‘Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries’. Frontiers in Big Data 2:13. doi: 10.3389/fdata.2019.00013.
* European IPR Helpdesk, Copyright Essentials (2017). https://www.iprhelpdesk.eu/sites/default/files/newsdocuments/Fact-Sheet-copyright_essentials.pdf
* Kohl, U., & Charlesworth, A. (2016). Information Technology Law https://doi-org.uaccess.univie.ac.at/10.4324/9780203798522
* EU, Handbook on European data protection law (2018) https://op.europa.eu/en/publication-detail/-/publication/5b0cfa83-63f3-11e8-ab9c-01aa75ed71a1 (Sections 2, 3, 4, 6.1, 9.4, 10.1)
* Coeckelbergh, Mark. 2019. Artificial Intelligence, Responsibility Attribution, and a Relational Justification of Explainability. Science and Engineering Ethics, https://link.springer.com/article/10.1007/s11948-019-00146-8
* Crawford, Kate. 2021. Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. New Haven: Yale University Press.
* Perez, Caroline Criado. 2019. Invisible Women: Data Bias in a World Designed for Men. New York: Abrams.
* Dignum, Virginia. 2020. “Responsibility and Artificial Intelligence.” In The Oxford Handbook of Ethics of AI, edited by Marcus Dubber, Frank Pasquale, and Sunit Das, 215–33. University of Oxford Press.
* Fuchs, Christian & Sevignani 2013 What is Digital Labour? https://www.triple-c.at/index.php/tripleC/article/view/461
* House of Commons 2018 report “Algorithms in Decision-Making https://publications.parliament.uk/pa/cm201719/cmselect/cmsctech/351/35104.htm
* Mittelstadt, Brent, et al. 2016. The ethics of algorithms: Mapping the Debate. Big Data & Society https://journals.sagepub.com/doi/full/10.1177/2053951716679679
* Zou, James & Schibinger, Londa. AI can be sexist and racist - it’s time to make it fair. Nature https://www.nature.com/articles/d41586-018-05707-8
* OANA: Vienna Principles. A Vision for Scholarly Communication, 2015/16. https://viennaprinciples.org/
* Wilkinson, Mark D.; Dumontier, Michel; Aalbersberg, IJsbrand Jan; Appleton, Gabrielle; et al. (15 March 2016). "The FAIR Guiding Principles for scientific data management and stewardship". Scientific Data 3: 160018. doi:10.1038/sdata.2016.18. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4792175/
* Open Science Network Austria OANA. https://www.oana.at/
* DARIAH-EU. https://www.dariah.eu/
* DARIAH working group Ethics & Legality in Digital Arts & Humanities ELDAH. https://eldah.hypotheses.org/
* CLARIN ERIC. https://www.clarin.eu/
* CLARIN Legal and Ethical Issues Committee CLIC: Copyright Law Overview. https://www.clarin.eu/content/clic-overview-copyright-law
* CLARIN Legal and Ethical Issues Committee CLIC: Introduction to Copyright and Related Rights. Orphan works. https://www.clarin.eu/content/clic-orphan-works
* Vanessa Hannesschläger. Common Creativity international. CC-licensing and other options for TEI-based digital editions in an international context. In Journal of the Text Encoding Initiative, Issue 11 (2016 Conference Issue), July 2019 -, Online since 17 November 2019. DOI: https://doi.org/10.4000/jtei.2610
* DARIAH ELDAH Consent Form Wizard (CFW). https://consent.dariah.eu/
* Bates, Jo, Yu-Wei Lin, and Paula Goodale. 2016. ‘Data Journeys: Capturing the Socio-Material Constitution of Data Objects and Flows’. Big Data & Society 3(2):205395171665450. doi: 10.1177/2053951716654502.
* Ienca, Marcello, and Effy Vayena. 2020. ‘On the Responsible Use of Digital Data to Tackle the COVID-19 Pandemic’. Nature Medicine 26(4):463–64. doi: 10.1038/s41591-020-0832-5.
* Kitchin, Rob. 2014. ‘Big Data, New Epistemologies and Paradigm Shifts’. Big Data & Society 1(1):205395171452848. doi: 10.1177/2053951714528481.
* Olteanu, Alexandra, Carlos Castillo, Fernando Diaz, and Emre Kıcıman. 2019. ‘Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries’. Frontiers in Big Data 2:13. doi: 10.3389/fdata.2019.00013.
* European IPR Helpdesk, Copyright Essentials (2017). https://www.iprhelpdesk.eu/sites/default/files/newsdocuments/Fact-Sheet-copyright_essentials.pdf
* Kohl, U., & Charlesworth, A. (2016). Information Technology Law https://doi-org.uaccess.univie.ac.at/10.4324/9780203798522
* EU, Handbook on European data protection law (2018) https://op.europa.eu/en/publication-detail/-/publication/5b0cfa83-63f3-11e8-ab9c-01aa75ed71a1 (Sections 2, 3, 4, 6.1, 9.4, 10.1)
Association in the course directory
Modul: DEL
Last modified: Th 11.05.2023 11:27
* 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 problemsThe 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 discussionThe 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 actIn 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 privacyIn 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.