Considerations About Integration of GenAI into Products and Services from an Ethical and Legal Perspective
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Using the 4P creativity framework and the tetrad does not directly encourage consideration of the ethical, legal, and sustainability issues increasingly associated with GenAI.
“Secondly, using the 4P creativity framework and the tetrad with its focus on how a technology can enhance, obsolesce, retrieve, and reverse into phenomena does not directly encourage consideration of the ethical, legal, and sustainability issues increasingly associated with GenAI (e.g., [10, 100, 106, 120]).”
From The Impact of Generative AI on Creativity in Software Development: A Research Agenda (2025) · cites this paper as [106]
Cites
Barredo Arrieta, A., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., Garcia, S., Gil-Lopez, S., Molina, D., Benjamins, R., et al. (2020) · Information Fusion · doi:10.1016/j.inffus.2019.12.012 · Cited by 10,423 · see citing works
Scenario types and techniques: Towards a user's guide
Börjeson, L., Höjer, M., Dreborg, K.-H., Ekvall, T., & Finnveden, G. (2006) · Futures · doi:10.1016/j.futures.2005.12.002 · Cited by 1,421 · see citing works
Why We Boycott: Consumer Motivations for Boycott Participation
Klein, J. G., Smith, N. C., & John, A. (2004) · Journal of Marketing · doi:10.1509/jmkg.68.3.92.34770 · Cited by 943 · see citing works
The current state of scenario development: an overview of techniques
Bishop, P. C., Hines, A., & Collins, T. (2007) · foresight · doi:10.1108/14636680710727516 · Cited by 815 · see citing works
Critical Theory of Technology.
Liu, A. Y., & Feenberg, A. (1992) · MLN · doi:10.2307/2904830 · Cited by 652 · see citing works
SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models
Manakul, P., Liusie, A., & Gales, M. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/2023.emnlp-main.557 · Cited by 557 · see citing works
Biases in Large Language Models: Origins, Inventory, and Discussion
Navigli, R., Conia, S., & Ross, B. (2023) · Journal of Data and Information Quality · doi:10.1145/3597307 · Cited by 364 · see citing works
García‐Peñalvo, F. J., & Vázquez‐Ingelmo, A. (2023) · International Journal of Interactive Multimedia and Artificial Intelligence · doi:10.9781/ijimai.2023.07.006 · Cited by 236 · see citing works
Ethics and law for the health professions
Braunack‐Mayer, A., Elkin, S., Norris, P., & Wilson, H. J. (2005) · Journal of Bioethical Inquiry · doi:10.1007/bf02448598 · Cited by 199 · see citing works
Muchlinski, P. (2012) · Business Ethics Quarterly · doi:10.5840/beq20122218 · Cited by 163 · see citing works
Stahl, B. C. (2021) · SpringerBriefs in research and innovation governance · doi:10.1007/978-3-030-69978-9_4 · Cited by 158 · see citing works
Towards Understanding and Mitigating Social Biases in Language Models
Liang, P. P., Wu, C., Morency, L.-P., & Salakhutdinov, R. (2021) · arXiv · doi:10.48550/arxiv.2106.13219 · Cited by 153 · see citing works
Technology Assessment: Concepts and Methods
Grünwald, A. (2009) · Elsevier eBooks · doi:10.1016/b978-0-444-51667-1.50044-6 · Cited by 130 · see citing works
Quantitative and qualitative decision‐making methods in simulation modelling
Eldabi, T., Irani, Z., Paul, R. J., & Love, P. E. D. (2002) · Management Decision · doi:10.1108/00251740210413370 · Cited by 111 · see citing works
A Global Ethic in an Age of Globalization
Küng, H. (1997) · Business Ethics Quarterly · doi:10.2307/3857310 · Cited by 56 · see citing works
The Ethics of Artificial Intelligence in the Era of Generative AI
Kirova, V. D., Ku, C. S., Laracy, J. R., & Marlowe, T. J. (2023) · Journal of systemics, cybernetics, and informatics/Journal of systemics cybernetics and informatics · doi:10.54808/jsci.21.04.42 · Cited by 54 · see citing works
Ethical Aspects of the Impact of AI: the Status of Humans in the Era of Artificial Intelligence
Rakowski, R., Polak, P., & Kowalikova, P. (2021) · Society · doi:10.1007/s12115-021-00586-8 · Cited by 45 · see citing works
How to Innovate Software Quality Assurance and Testing in Large Enterprises?
Poth, A., & Heimann, C. (2018) · Communications in computer and information science · doi:10.1007/978-3-319-97925-0_37 · Cited by 21 · see citing works
Self-citationDesigning simulation experiments
Barton, R. R. (2013) · Winter Simulation Conference · doi:10.1109/wsc.2013.6721432 · Cited by 17 · see citing works
Integration- and System-Testing Aligned with Cloud-Native Approaches for DevOps
Poth, A., Rrjolli, O., & Riel, A. (2022) · IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C) · doi:10.1109/qrs-c57518.2022.00038 · Cited by 16 · see citing works
Self-citationSocial construction of XAI: Do we need one definition to rule them all?
Ehsan, U., & Riedl, M. (2024) · Patterns · doi:10.1016/j.patter.2024.100926 · Cited by 10 · see citing works
Saariluoma, P. O. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-50267-6_10 · Cited by 2 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
The Impact of Generative AI on Creativity in Software Development: A Research Agenda
Jackson, V., Vasilescu, B., Russo, D., Ralph, P., Prikladnicki, R., Izadi, M., D’Angelo, S., Inman, S., Andrade, A., & van der Hoek, A. (2025) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3708523 · Cited by 23 · see citing works
- Authors
- Poth, A., Wildegger, A., & Levien, D.-A.
- Affiliations
- Volkswagen Group (Germany) (DE)
- Audi (Germany) (DE)
- Corresponding author
- Poth, Alexander
- ORCID
- Poth, Alexander
- Venue
- Communications in Computer and Information Science
- Publisher
- Springer Nature Switzerland
- Published
- 2024
- Pages
- 155-171
- ISSN
- 1865-0929 (ISSN-L)
- 1865-0937
- OpenAlex
- W4402321021
- Semantic Scholar
- 9a45124b247074343cd5415ac0426ea8e789939b
- Cited by
- 8
- References
- 22
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 2
- FWCI
- 32.53
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- Communications in computer and information science (publishedVersion)
- Topics
- Social Sciences › Law › Digitalization, Law, and Regulation
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Law, AI, and Intellectual Property
- Keywords
- generative AI, large language models, test case generation, AI ethics, AI law, German law, AI licensing, training data selection, chatbots, product and service development
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
