Publications - Page 18 of 267

The paradox of lawful text and data mining? Some experiences from the research sector and where we (should) go from here external link

GRUR International, vol. 74, iss. : 4, pp: 307-319, 2025

Abstract

Scientific research can be tricky business. This paper critically explores the 'lawful access' requirement in European copyright law which applies to text and data mining (TDM) carried out for the purpose of scientific research. Whereas TDM is essential for data analysis, artificial intelligence (AI) and innovation, the paper argues that the 'lawful access' requirement in Article 3 CDSM Directive may actually restrict research by complicating the applicability of the TDM provision or even rendering it inoperable. Although the requirement is intended to ensure that researchers act in good faith before deploying TMD tools for purposes such as machine learning, it forces them to ask for permission to access data, for example by taking out a subscription to a service, and for that reason provides the opportunity for copyright holders to apply all sorts of commercial strategies to set the legal and technological parameters of access and potentially even circumvent the mandatory character of the provision. The paper concludes by drawing on insights from the recent European Commission study 'Improving access to and reuse of research results, publications and data for scientific purposes' that offer essential perspectives for the future of TDM, and by suggesting a number of paths forward that EU Member States can take already now in order to support a more predictable and reliable legal regime for scientific TDM and potentially code mining to foster innovation.

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Artificial intelligence, CDSM Directive, Copyright, Text and Data Mining (TDM)

RIS

TY  - JOUR
AU  - Szkalej, K.
PY  - 2025
DA  - 2025-03-10
T1  - The paradox of lawful text and data mining? Some experiences from the research sector and where we (should) go from here
JO  - GRUR International
VL  - 74
IS  - 4
SP  - 307-319
UR  - https://ssrn.com/abstract=5000116
DO  - https://doi.org/10.1093/grurint/ikaf029
AB  - Scientific research can be tricky business. This paper critically explores the \'lawful access\' requirement in European copyright law which applies to text and data mining (TDM) carried out for the purpose of scientific research. Whereas TDM is essential for data analysis, artificial intelligence (AI) and innovation, the paper argues that the \'lawful access\' requirement in Article 3 CDSM Directive may actually restrict research by complicating the applicability of the TDM provision or even rendering it inoperable. Although the requirement is intended to ensure that researchers act in good faith before deploying TMD tools for purposes such as machine learning, it forces them to ask for permission to access data, for example by taking out a subscription to a service, and for that reason provides the opportunity for copyright holders to apply all sorts of commercial strategies to set the legal and technological parameters of access and potentially even circumvent the mandatory character of the provision. The paper concludes by drawing on insights from the recent European Commission study \'Improving access to and reuse of research results, publications and data for scientific purposes\' that offer essential perspectives for the future of TDM, and by suggesting a number of paths forward that EU Member States can take already now in order to support a more predictable and reliable legal regime for scientific TDM and potentially code mining to foster innovation.
K1  - Artificial intelligence
K1  - CDSM Directive
K1  - Copyright
K1  - Text and Data Mining (TDM)
ER  -

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Bibtex

Article{nokey,
	title = {The paradox of lawful text and data mining? Some experiences from the research sector and where we (should) go from here},
	author = {Szkalej, K.},
	url = {https://www.ivir.nl/publications/the-paradox-of-lawful-text-and-data-mining-some-experiences-from-the-research-sector-and-where-we-should-go-from-here/grurint_2025_4/},
	doi = {https://doi.org/10.1093/grurint/ikaf029},
	year = {2025},
	date = {2025-03-10},
	journal = {GRUR International},
	volume = {74},
	issue = {4},
	pages = {307-319},
	abstract = {Scientific research can be tricky business. This paper critically explores the \'lawful access\' requirement in European copyright law which applies to text and data mining (TDM) carried out for the purpose of scientific research. Whereas TDM is essential for data analysis, artificial intelligence (AI) and innovation, the paper argues that the \'lawful access\' requirement in Article 3 CDSM Directive may actually restrict research by complicating the applicability of the TDM provision or even rendering it inoperable. Although the requirement is intended to ensure that researchers act in good faith before deploying TMD tools for purposes such as machine learning, it forces them to ask for permission to access data, for example by taking out a subscription to a service, and for that reason provides the opportunity for copyright holders to apply all sorts of commercial strategies to set the legal and technological parameters of access and potentially even circumvent the mandatory character of the provision. The paper concludes by drawing on insights from the recent European Commission study \'Improving access to and reuse of research results, publications and data for scientific purposes\' that offer essential perspectives for the future of TDM, and by suggesting a number of paths forward that EU Member States can take already now in order to support a more predictable and reliable legal regime for scientific TDM and potentially code mining to foster innovation.},
	keywords = {Artificial intelligence, CDSM Directive, Copyright, Text and Data Mining (TDM)},
}

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Designing algorithms against corruption: a conjoint study on communicative features to encourage intentions for collective action external link

Starke, C., Kieslich, K., Reichert, M. & Köbis, N.

Journal of Information Technology & Politics, 2025

Abstract

Algorithmic tools are increasingly used to automate corruption reporting on social media platforms. Based on the use case of an existing bot, this study investigates how to design the communication of a bot to effectively and responsibly mobilize people for collective action against corruption. In a pre-registered choice-based conjoint survey (n = 1,331), we test six message design features: type of injustice, degree of injustice, anger, political partisanship, gender, and efficacy cues. Our results show that calling out cases of severe corruption increased people’s intention to engage in collective action against corruption. We find no empirical support for in-group favoritism based on political affiliation and gender. Yet, some commonly used design features can have contrasting effects on different audiences. We call for more social science research accompanying the technical development of algorithmic tools to fight corruption.

Links

DOI: https://doi.org/10.1080/19331681.2025.2465326

RIS

TY  - JOUR
AU  - Starke, C.
AU  - Kieslich, K.
AU  - Reichert, M.
AU  - Köbis, N.
PY  - 2025
DA  - 2025-02-26
T1  - Designing algorithms against corruption: a conjoint study on communicative features to encourage intentions for collective action
JO  - Journal of Information Technology & Politics
UR  - https://www.tandfonline.com/doi/full/10.1080/19331681.2025.2465326
DO  - https://doi.org/10.1080/19331681.2025.2465326
AB  - Algorithmic tools are increasingly used to automate corruption reporting on social media platforms. Based on the use case of an existing bot, this study investigates how to design the communication of a bot to effectively and responsibly mobilize people for collective action against corruption. In a pre-registered choice-based conjoint survey (n = 1,331), we test six message design features: type of injustice, degree of injustice, anger, political partisanship, gender, and efficacy cues. Our results show that calling out cases of severe corruption increased people’s intention to engage in collective action against corruption. We find no empirical support for in-group favoritism based on political affiliation and gender. Yet, some commonly used design features can have contrasting effects on different audiences. We call for more social science research accompanying the technical development of algorithmic tools to fight corruption.
ER  -

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Article{nokey,
	title = {Designing algorithms against corruption: a conjoint study on communicative features to encourage intentions for collective action},
	author = {Starke, C. and Kieslich, K. and Reichert, M. and Köbis, N.},
	doi = {https://doi.org/10.1080/19331681.2025.2465326},
	year = {2025},
	date = {2025-02-26},
	journal = {Journal of Information Technology & Politics},
	abstract = {Algorithmic tools are increasingly used to automate corruption reporting on social media platforms. Based on the use case of an existing bot, this study investigates how to design the communication of a bot to effectively and responsibly mobilize people for collective action against corruption. In a pre-registered choice-based conjoint survey (n = 1,331), we test six message design features: type of injustice, degree of injustice, anger, political partisanship, gender, and efficacy cues. Our results show that calling out cases of severe corruption increased people’s intention to engage in collective action against corruption. We find no empirical support for in-group favoritism based on political affiliation and gender. Yet, some commonly used design features can have contrasting effects on different audiences. We call for more social science research accompanying the technical development of algorithmic tools to fight corruption.},
}

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Cybersecurity in the financial sector and the quantum-safe cryptography transition: in search of a precautionary approach in the EU Digital Operational Resilience Act framework

Jančiūtė, L.

International Cybersecurity Law Review, vol. 6, pp: 145-154, 2025

Abstract

An ever more digitalised financial sector is exposed to a growing number of cyberattacks. Given the criticality and interconnectedness of this sector, cyber threats here represent not only operational risks, but also systemic risks. In the long run, the emerging cyber risks include developments in quantum computing threatening widely used encryption safeguarding digital networks. Globally in the financial sector, some initiatives have already been taking place to explore the possible mitigating measures. This paper argues that for an industry-wide transition to quantum-safe cryptography the precautionary principle is relevant. In the EU, financial entities now have to be compliant with the Digital Operational Resilience Act strengthening ICT security requirements. This research traces the obligation to adopt quantum-resistant precautionary measures under its framework.

Links

DOI: https://doi.org/10.1365/s43439-025-00135-7

Cybersecurity, quantum technologies

RIS

TY  - NEWS
AU  - Jančiūtė, L.
PY  - 2025
DA  - 2025-03-05
T1  - Cybersecurity in the financial sector and the quantum-safe cryptography transition: in search of a precautionary approach in the EU Digital Operational Resilience Act framework
JO  - International Cybersecurity Law Review
VL  - 6
SP  - 145-154
DO  - https://doi.org/10.1365/s43439-025-00135-7
AB  - An ever more digitalised financial sector is exposed to a growing number of cyberattacks. Given the criticality and interconnectedness of this sector, cyber threats here represent not only operational risks, but also systemic risks. In the long run, the emerging cyber risks include developments in quantum computing threatening widely used encryption safeguarding digital networks. Globally in the financial sector, some initiatives have already been taking place to explore the possible mitigating measures. This paper argues that for an industry-wide transition to quantum-safe cryptography the precautionary principle is relevant. In the EU, financial entities now have to be compliant with the Digital Operational Resilience Act strengthening ICT security requirements. This research traces the obligation to adopt quantum-resistant precautionary measures under its framework.
K1  - Cybersecurity
K1  - quantum technologies
ER  -

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Bibtex

Newspaper article{nokey,
	title = {Cybersecurity in the financial sector and the quantum-safe cryptography transition: in search of a precautionary approach in the EU Digital Operational Resilience Act framework},
	author = {Jančiūtė, L.},
	doi = {https://doi.org/10.1365/s43439-025-00135-7},
	year = {2025},
	date = {2025-03-05},
	journal = {International Cybersecurity Law Review},
	volume = {6},
	pages = {145-154},
	abstract = {An ever more digitalised financial sector is exposed to a growing number of cyberattacks. Given the criticality and interconnectedness of this sector, cyber threats here represent not only operational risks, but also systemic risks. In the long run, the emerging cyber risks include developments in quantum computing threatening widely used encryption safeguarding digital networks. Globally in the financial sector, some initiatives have already been taking place to explore the possible mitigating measures. This paper argues that for an industry-wide transition to quantum-safe cryptography the precautionary principle is relevant. In the EU, financial entities now have to be compliant with the Digital Operational Resilience Act strengthening ICT security requirements. This research traces the obligation to adopt quantum-resistant precautionary measures under its framework.},
	keywords = {Cybersecurity, quantum technologies},
}

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The concept of “research organisation” and its implications for text and data mining and AI research external link

Quintais, J.

2025

Abstract

The concept of a “research organization” has significant implications across various domains of EU information law, including copyright, artificial intelligence (AI), and even platform regulation. Defined in the Copyright in the Digital Single Market Directive (CDSMD), this concept plays a crucial role in determining the legal obligations and rights of entities engaging in activities such as text and data mining (TDM) and AI research, or data access for research purposes. By examining how this definition interacts with legislative frameworks like the CDSMD and the AI Act, this short contribution examines its critical role in EU digital regulation of research and highlights areas of legal uncertainty.

Links

DOI: https://doi.org/10.2139/ssrn.5155685

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DeepSeek-paniek download

Alberdingk Thijm, Chr. A.

Nederlands Juristenblad (NJB), iss. : 6, num: 300, pp: 401, 2025

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Co-creating research at The AI, media, and democracy lab: Reflections on the role of academia in collaborations with media partners external link

Cools, H., Helberger, N. & Vreese, C.H. de

Journalism, 2025

Abstract

This commentary explores academia’s role in co-creating research with media partners, focusing on the distinct roles and challenges that each stakeholder brings to such partnerships. Starting from the perspective of the AI, Media, and Democracy Lab, and building on the Ethical, Legal, and Societal Aspects (ELSA) approach, we share key learnings from 3 years of collaborations with (media) partners. We conclude that navigating dual roles, expectations, output alignment, and a process of knowledge sharing are important requirements for academics and (media) partners to adequately co-create research and insights. We also argue that these key lessons do not always square with how academic research is organized and funded. We underscore that changes in funding structures and the way academic research is assessed can further facilitate the co-creation of research between academic research and projects in the media sector.

Links

DOI: https://doi.org/10.1177/14648849251318622

RIS

TY  - JOUR
AU  - Cools, H.
AU  - Helberger, N.
AU  - Vreese, C.H. de
PY  - 2025
DA  - 2025-02-04
T1  - Co-creating research at The AI, media, and democracy lab: Reflections on the role of academia in collaborations with media partners
JO  - Journalism
UR  - https://journals.sagepub.com/doi/10.1177/14648849251318622
DO  - https://doi.org/10.1177/14648849251318622
AB  - This commentary explores academia’s role in co-creating research with media partners, focusing on the distinct roles and challenges that each stakeholder brings to such partnerships. Starting from the perspective of the AI, Media, and Democracy Lab, and building on the Ethical, Legal, and Societal Aspects (ELSA) approach, we share key learnings from 3 years of collaborations with (media) partners. We conclude that navigating dual roles, expectations, output alignment, and a process of knowledge sharing are important requirements for academics and (media) partners to adequately co-create research and insights. We also argue that these key lessons do not always square with how academic research is organized and funded. We underscore that changes in funding structures and the way academic research is assessed can further facilitate the co-creation of research between academic research and projects in the media sector.
ER  -

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Article{nokey,
	title = {Co-creating research at The AI, media, and democracy lab: Reflections on the role of academia in collaborations with media partners},
	author = {Cools, H. and Helberger, N. and Vreese, C.H. de},
	doi = {https://doi.org/10.1177/14648849251318622},
	year = {2025},
	date = {2025-02-04},
	journal = {Journalism},
	abstract = {This commentary explores academia’s role in co-creating research with media partners, focusing on the distinct roles and challenges that each stakeholder brings to such partnerships. Starting from the perspective of the AI, Media, and Democracy Lab, and building on the Ethical, Legal, and Societal Aspects (ELSA) approach, we share key learnings from 3 years of collaborations with (media) partners. We conclude that navigating dual roles, expectations, output alignment, and a process of knowledge sharing are important requirements for academics and (media) partners to adequately co-create research and insights. We also argue that these key lessons do not always square with how academic research is organized and funded. We underscore that changes in funding structures and the way academic research is assessed can further facilitate the co-creation of research between academic research and projects in the media sector.},
}

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European Copyright Society Opinion on Copyright and Generative AI external link

Dusollier, S., Kretschmer, M., Margoni, T., Mezei, P., Quintais, J. & Rognstad, O.A.

Kluwer Copyright Blog, 2025

Copyright, Generative AI

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Judicial Automation: Balancing Rights Protection and Capacity-Building external link

Qiao, C. & Metikoš, L.

2025

Abstract

This entry explores the global rise of judicial automation and its implications through two dominant frameworks: rights protection and capacity-building. The rights protection framework aims to safeguard individual rights against opaque judicial automation by advocating for the use of explainable and contestable AI tools in courts. In contrast, the capacity-building framework prioritises judicial efficiency and consistency by automating court proceedings. Although these frameworks offer contrasting approaches, they are not mutually exclusive. A balance needs to be struck, where judicial automation enhances judicial capacities while maintaining transparency and accountability.

individual rights, judicial automation, judicial capacity, right to explanation

RIS

TY  - BLOG
AU  - Qiao, C.
AU  - Metikoš, L.
PY  - 2025
DA  - 2025-02-11
T1  - Judicial Automation: Balancing Rights Protection and Capacity-Building
UR  - https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5125645
AB  - This entry explores the global rise of judicial automation and its implications through two dominant frameworks: rights protection and capacity-building. The rights protection framework aims to safeguard individual rights against opaque judicial automation by advocating for the use of explainable and contestable AI tools in courts. In contrast, the capacity-building framework prioritises judicial efficiency and consistency by automating court proceedings. Although these frameworks offer contrasting approaches, they are not mutually exclusive. A balance needs to be struck, where judicial automation enhances judicial capacities while maintaining transparency and accountability.
K1  - individual rights
K1  - judicial automation
K1  - judicial capacity
K1  - right to explanation
ER  -

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Copyright and Generative AI: Opinion of the European Copyright Society external link

Dusollier, S., Kretschmer, M., Margoni, T., Mezei, P., Quintais, J. & Rognstad, O.A.

2025

Links

https://zenodo.org/records/14809287

Copyright

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Research Workshop Report: “The (Evolving) Human Right to a Healthy Environment: What Impact on Intellectual Property Laws?” external link

Meyermans-Spelmans, E. & Izyumenko, E.

Human Rights Here, 2025

Human rights, Intellectual property

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