Künstliche Intelligenz als Herausforderung für die wissenschaftliche Kommunikation

Zusammenfassung

Die Entwicklung der sog. künstlichen Intelligenz hat in den letzten Jahren beeindruckende Fortschritte gemacht. Neben KI-gestützten Suchsystemen und generativen KI-Systemen zur Herstellung von Texten, Bildern, Videos oder musikalischen Kompositionen gibt es inzwischen eine Vielzahl spezialisierter Systeme, die Aufgaben im Bereich der wissenschaftlichen Recherche, Datenanalyse, Textproduktion, Textgestaltung, Grammatikprüfung, stilistischen Überarbeitung, Übersetzung, Plagiatskontrolle und des wissenschaftlichen Reviewprozesses übernehmen oder bei der Erfüllung dieser Aufgaben unterstützen sollen. Der Einsatz solcher Systeme verspricht in vielerlei Hinsicht tatsächlich sinnvolle Arbeitserleichterungen und Vereinfachungen. Da KI-Systeme jedoch über kein genuines Verständnis der von ihnen bearbeiteten oder generierten Inhalte verfügen, sondern ein solches Verständnis nur simulieren, indem sie statistische Muster reproduzieren, die sie aus den jeweiligen Trainingsdaten extrahiert haben, wäre es gefährlich, ihnen blind zu vertrauen oder sie unkritisch und nachlässig einzusetzen. In diesem Beitrag werden sowohl die Potenziale als auch die Gefahren des Einsatzes von KI im Kontext der wissenschaftlichen Kommunikation diskutiert und dabei auch mögliche systemische Folgen einer breiten Durchsetzung von KI-Systemen in diesem Kontext in den Blick genommen.

Schlüsselwörter

künstliche Intelligenz - wissenschaftliche Kommunikation - Publikationsethik

Publication History

Received: 22 July 2024

Accepted: 05 September 2024

Article published online:
05 December 2024

• References/Literatur

• 1 Jonas H. Erinnerungen: Nach Gesprächen mit Rachel Salamander. Frankfurt a. M.: Suhrkamp; 2005
• 2 Treml M. Eschatology as Occidental Lebensform: The Case of Jacob Taubes. In: Wieser V, Eltschinger V, Heiss J. Hrsg. Cultures of Eschatology. Berlin/Boston: De Gruyter Oldenbourg; 2020: 759-782
• 3 Muller JZ. Professor der Apokalypse: Die vielen Leben des Jacob Taubes. Berlin: Suhrkamp; 2022
• 4 Bolz N. Stop Making Sense!. Würzburg: Königshausen und Neumann; 1989
• 5 Vaswani A, Shazeer N, Parmar N. et al. Attention is All you Need. Long Beach; 2017. Im Internet (Stand: 23.09.2024): https://arxiv.org/abs/1706.03762
• 6 Kharlamova G. The Use of Artificial Intelligence in Academic Publishing: Preliminary Remarks and Perspectives. Access Justice East Eur 2023; 6: 1-12
• 7 Golan R, Reddy R, Muthigi A. et al. Artificial intelligence in academic writing: a paradigm-shifting technological advance. Nat Rev Urol 2023; 20: 327-328
• 8 Currie G, Singh C, Nelson T. et al. ChatGPT in medical imaging higher education. Radiography 2023; 29: 792-799
• 9 Bender EM, Gebru T, McMillan-Major A. et al. On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?. In: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. New York, NY, USA: Association for Computing Machinery; 2021: 610-623
• 10 Gartner. Gartner Hype Cycle. Interpreting technology hype. Im Internet (Stand: 28.06.2024): https://www.gartner.com/en/research/methodologies/gartner-hype-cycle
• 11 Khalifa M, Albadawy M. Using artificial intelligence in academic writing and research: An essential productivity tool. Comput Methods Programs Biomed Update 2024; 5: 100145
• 12 Nezhurina M, Cipolina-Kun L, Cherti M. et al. Alice in Wonderland: Simple Tasks Showing Complete Reasoning Breakdown in State-Of-the-Art Large Language Models. 2024. Im Internet (Stand: 23.09.2024): https://arxiv.org/abs/2406.02061
• 13 Giray L. Prompt Engineering with ChatGPT: A Guide for Academic Writers. Ann Biomed Eng 2023; 51: 2629-2633
• 14 Semrl N, Feigl S, Taumberger N. et al. AI language models in human reproduction research: exploring ChatGPTʼs potential to assist academic writing. Hum Reprod 2023; 38: 2281-2288
• 15 Swift J. Gulliverʼs travels. Arlington, VA: Great Ocean; 1980
• 16 Thorp HH. ChatGPT is fun, but not an author. Science 2023; 379: 313
• 17 American Association for the Advancement of Science (AAAS). Science Journals: Editorial Policies. Im Internet (Stand: 04.07.2024): https://www.science.org/content/page/science-journals-editorial-policies
• 18 Salimi A, Saheb H. Large Language Models in Ophthalmology Scientific Writing: Ethical Considerations Blurred Lines or Not at All?. Am J Ophthalmol 2023; 254: 177-181
• 19 Checco A, Bracciale L, Loreti P. et al. AI-assisted peer review. Humanit Soc Sci Commun 2021; 8: 1-11
• 20 OpenAI. ChatGPT. Im Internet (Stand: 21.05.2024): https://openai.com/chatgpt/
• 21 Memon SA, West JD. Search Engines Post-ChatGPT: How Generative Artificial Intelligence Could Make Search Less Reliable. 2024. Im Internet (Stand: 08.05.2024): http://arxiv.org/abs/2402.11707
• 22 Sarraju A, Bruemmer D, Van Iterson E. et al. Appropriateness of Cardiovascular Disease Prevention Recommendations Obtained From a Popular Online Chat-Based Artificial Intelligence Model. JAMA 2023; 329: 842-844
• 23 Howard A, Hope W, Gerada A. ChatGPT and antimicrobial advice: the end of the consulting infection doctor?. Lancet Infect Dis 2023; 23: 405-406
• 24 Whiles BB, Bird VG, Canales BK. et al. Caution! AI Bot Has Entered the Patient Chat: ChatGPT Has Limitations in Providing Accurate Urologic Healthcare Advice. Urology 2023; 180: 278-284
• 25 Walker HL, Ghani S, Kuemmerli C. et al. Reliability of Medical Information Provided by ChatGPT: Assessment Against Clinical Guidelines and Patient Information Quality Instrument. J Med Internet Res 2023; 25: e47479
• 26 Jeblick K, Schachtner B, Dexl J. et al. ChatGPT makes medicine easy to swallow: an exploratory case study on simplified radiology reports. Eur Radiol 2024; 34: 2817-2825
• 27 Tyler C, Akerlof KL, Allegra A. et al. AI tools as science policy advisers? The potential and the pitfalls. Nature 2023; 622: 27-30
• 28 Frank J, Herbert F, Ricker J. et al. A Representative Study on Human Detection of Artificially Generated Media Across Countries. 2023 doi:10.48550/arXiv.2312.05976
• 29 Lin Z. Why and how to embrace AI such as ChatGPT in your academic life. R Soc Open Sci 2023; 10: 230658
• 30 Wang K. Opportunities in Open Science With AI. Front Big Data 2019; 2: 26
• 31 Deutsche Forschungsgemeinschaft (DFG). Guidelines for Safeguarding Good Research Practice. Code of Conduct 2022;
• 32 Graff G, Birkenstein C. They Say/I Say: The Moves That Matter in Academic Writing. 6th ed. New York: Norton; 2024
• 33 Conroy G. How ChatGPT and other AI tools could disrupt scientific publishing. Nature 2023; 622: 234-236
• 34 Gordijn B, Have HT. ChatGPT: evolution or revolution?. Med Health Care Philos 2023; 26: 1-2
• 35 Jarrah AM, Wardat Y, Fidalgo P. Using ChatGPT in academic writing is (not) a form of plagiarism: What does the literature say?. Online J Commun Media Technol 2023; 13: e202346
• 36 Deutsche Forschungsgemeinschaft (DFG). Leitlinien zur Sicherung guter wissenschaftlicher Praxis: Kodex. Bonn: 2022
• 37 OʼConnor S. Open artificial intelligence platforms in nursing education: Tools for academic progress or abuse?. Nurse Educ Pract 2023; 66: 103537
• 38 Curtis N. To ChatGPT or not to ChatGPT? The Impact of Artificial Intelligence on Academic Publishing. Pediatr Infect Dis J 2023; 42: 275
• 39 International Committe of Medical Journal Editors (ICMJE). Defining the Role of Authors and Contributors. Im Internet (Stand: 24.06.2024): https://www.icmje.org/recommendations/browse/roles-and-responsibilities/defining-the-role-of-authors-and-contributors.html
• 40 Teixeira da Silva JA. Is ChatGPT a valid author?. Nurse Educ Pract 2023; 68: 103600
• 41 Conroy G. Scientific sleuths spot dishonest ChatGPT use in papers. Nature 2023;
• 42 Guo X, Dong L, Hao D. RETRACTED: Cellular functions of spermatogonial stem cells in relation to JAK/STAT signaling pathway. Front Cell Dev Biol 2024; 11: 1339390
• 43 Kidd C, Birhane A. How AI can distort human beliefs. Science 2023; 380: 1222-1223
• 44 Barrow N. Anthropomorphism and AI hype. AI Ethics 2024; 4: 707-711
• 45 Birhane A, van Dijk J. Robot Rights? Letʼs Talk about Human Welfare Instead. In: Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society. New York, NY, USA: Association for Computing Machinery; 2020: 207-213
• 46 Monteith S, Glenn T, Geddes JR. et al. Artificial intelligence and increasing misinformation. Br J Psychiatry 2024; 224: 33-35
• 47 Şendur HN, Şendur AB, Cerit MN. ChatGPT from radiologistsʼ perspective. Br J Radiol 2023; 96: 20230203
• 48 Srinivasan R, Chander A. Biases in AI systems. Commun ACM 2021; 64: 44-49
• 49 Ntoutsi E, Fafalios P, Gadiraju U. et al. Bias in data‐driven artificial intelligence systems – An introductory survey. WIREs Data Min Knowl Discov 2020; 10: e1356
• 50 Leavy S, OʼSullivan B, Siapera E. Data, Power and Bias in Artificial Intelligence. 2020. Im Internet (Stand: 23.09.2024): https://arxiv.org/abs/2008.07341
• 51 Challen R, Denny J, Pitt M. et al. Artificial intelligence, bias and clinical safety. BMJ Qual Saf 2019; 28: 231-237
• 52 Delgado J, de Manuel A, Parra I. et al. Bias in algorithms of AI systems developed for COVID-19: A scoping review. J Bioeth Inq 2022; 19: 407-419
• 53 Parikh RB, Teeple S, Navathe AS. Addressing Bias in Artificial Intelligence in Health Care. JAMA 2019; 322: 2377
• 54 Chen Y, Clayton EW, Novak LL. et al. Human-Centered Design to Address Biases in Artificial Intelligence. J Med Internet Res 2023; 25: e43251
• 55 Barbaro M, Roose K, Tan S. et al. The Miseducation of Googleʼs A. I. N Y Times 03-07-2024. Im Internet (Stand: 24.09.2024): https://www.nytimes.com/2024/03/07/podcasts/the-daily/gemini-google-ai.html
• 56 Chowdhury T, Oredo J. AI ethical biases: normative and information systems development conceptual framework. J Decis Syst 2023; 32: 617-633
• 57 Van Leeuwen TN, Moed HF, Tijssen RJW. et al. Language biases in the coverage of the Science Citation Index and its consequences for international comparisons of national research performance. Scientometrics 2001; 51: 335-346
• 58 Herrera AJ. Language bias discredits the peer-review system. Nature 1999; 397: 467
• 59 Clarivate. Journal Citation Reports – Home. Im Internet (Stand: 02.07.2024): https://jcr.clarivate.com/jcr/home
• 60 Giglio AD, Costa MUPD. The use of artificial intelligence to improve the scientific writing of non-native English speakers. Rev Assoc Med Bras (1992) 2023; 69: e20230560
• 61 Ingley SJ, Pack A. Leveraging AI tools to develop the writer rather than the writing. Trends Ecol Evol 2023; 38: 785-787
• 62 Bertolo R, Antonelli A. Generative AI in scientific publishing: disruptive or destructive?. Nat Rev Urol 2024; 21: 1-2
• 63 Kendall G, Teixeira da Silva JA. Risks of abuse of large language models, like ChatGPT, in scientific publishing: Authorship, predatory publishing, and paper mills. Learn Publ 2024; 37: 55-62
• 64 Pérez-Neri I, Pineda C, Sandoval H. Threats to scholarly research integrity arising from paper mills: a rapid scoping review. Clin Rheumatol 2022; 41: 2241-2248
• 65 Avital M. Copenhagen Business School. Digital Transformation of Academic Publishing: A Call for the Decentralization and Democratization of Academic Journals. J Assoc Inf Syst 2024; 25: 172-181
• 66 Werner MH. Redefreiheit, Digitalisierung und die Rolle der Philosophie. In: Adlophi R, Alpsancar S, Hahn S, Kettner M. Hrsg. Philosophische Digitalisierungsforschung: Verantwortung, Verständigung, Vernunft, Macht. Bielefeld: transcript; 2024: 155-196
• 67 Shumailov I, Shumaylov Z, Zhao Y. et al. The Curse of Recursion: Training on Generated Data Makes Models Forget. 2023. Im Internet (Stand: 13.07.2023): https://arxiv.org/abs/2305.17493