Artifcial intelligence-friend or foe in fake news campaigns

• Authors: Krzysztof Węcel , Marcin Sawiński , Milena Stróżyna , Włodzimierz Lewoniewski , Piotr Stolarski , Ewelina Księżniak , Witold Abramowicz

Abstracts

EN

In this paper the impact of large language models (LLM) on the fake news phenomenon is analysed. On the one hand decent text‐generaotin capabilietis can be misused for mass fake news production. On the other, LLMs trained on huge volumes of text have already accumulated information on many facts thus one may assume they could be used for fact‐checking. Experiments were designed and conducted to verify how much LLM responses are aligned with actual fact‐checking verdicts. The research methodology consists of an experimental dataset preparation and a protocol for interacting with ChatGPT, currently the most sophisticated

• Publisher: Uniwersytet Ekonomiczny w Poznaniu
• Journal: Economics and Business Review
• Year: 2023
• Volume: 9
• Issue: 2
• Pages: 41-70

Dates

published

2023

Contributors

author

Krzysztof Węcel

• Department of Information Systems, Poznań University of Economics and Business, al. Niepodległości 10, 61‐875 Poznań, Poland

author

Marcin Sawiński

• Department of Information Systems, Poznań University of Economics and Business, al. Niepodległości 10, 61‐875 Poznań, Poland

author

Milena Stróżyna

• Department of Information Systems, Poznań University of Economics and Business, al. Niepodległości 10, 61‐875 Poznań, Poland

author

Włodzimierz Lewoniewski

• Department of Information Systems, Poznań University of Economics and Business, al. Niepodległości 10, 61‐875 Poznań, Poland

author

Piotr Stolarski

• Department of Information Systems, Poznań University of Economics and Business, al. Niepodległości 10, 61‐875 Poznań, Poland

author

Ewelina Księżniak

• Department of Information Systems, Poznań University of Economics and Business, al. Niepodległości 10, 61‐875 Poznań, Poland

author

Witold Abramowicz

• Department of Information Systems, Poznań University of Economics and Business, al. Niepodległości 10, 61‐875 Poznań, Poland

References

• Agres,ti S. Hashemian, S. A., & Carman, M. J. (2022). PoliMi‐FlatEarthers at CheckThat! 2022: GPT‐3 applied to claim detection. In. G. Faggioli, N. Ferro, A. Harbury & M. Pothast (Eds.), Proceedings of the working notes of CLEF 2022-Conference and labs of the evaluation forum . Bologna, Italy. CEUR Workshop Proceedings, 3180, pp. 422-427. htps://ceur ‐ws.org/Vol‐3180/paper‐31.pdf
• Alkaissi, H., & McFarlane, S. I. (2023). Arcftiial hallucinaotins in ChatGPT: Implicaotins in sciencfti wrintig. Cureus, 15(2), e35179. hpts://doi.org/10.7759/cureus.35179
• Bahdanau, D., Cho, K., & Bengio, Y. (2014). Neural machine translation by jointly lear - ning to align and translate. htps://doi.org/10.48550/arXiv.1409.0473
• Bang, Y., Cahyawijaya, S., Lee, N., Dai, W., Su, D., Wilie, B., Lovenia, H., Ji, Z., Yu, T., Chung, W., Do, Q. V., Xu, Y., & Fung, P. (2023). A multitask, multilingual, multimo ‐ dal evaluation of ChatGPT on reasoning, hallucination, and interactivity. htps:// doi.org/10.48550/arXiv.2302.04023
• Bouie, J. (2023, March 11). Disinformation is not the real problem with democracy. The New York Times.
• Buchholz, K. (2023, January 24). ChatGPT sprints to one million users. Stastita . hpts:// www.statista.com/chart/29174/time‐to‐one‐million‐users/
• Candelon, F., di Carlo, R.C., De Bondt, M.,& Evgeniou, T. (2021, September‐October). AI regulation is coming. Harvard Business Review. htps://hbr.org/2021/09/airegulation‐is‐coming
• Corfield, G. (2023, February 8). $120bn wiped of google aeftr bard AI chatbot gives wrong answer. htps://www.telegraph.co.uk/technology/2023/02/08/googlesbard‐ai‐chatbot‐gives‐wrong‐answer‐launch‐event/
• Dale, R. (2021). GPT‐3: What's it good for? Natural Language Engineering, 27(1), 113-118. htps://doi.org/10.1017/S1351324920000601
• Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2019). BERT: Pre‐training of deep bidirecotinal transformers for language understanding . hpts://doi.org/10.48550/ arXiv.1810.04805
• Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi M., Al‐Busaidi, A., Balakrishman, J., Barleet, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., ..., Carter, L. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on oppor ‐ tunities, challenges and implications of generative conversational AI for research, pracctie and policy. Internaotinal Journal of Informaotin Management , 71, 102642.
• Faggioli, G., Ferro, N., Hanbury, A., Pothast, M. (2022). Proceedings of the working notes of CLEF 2022-Conference and labs of the evaluation forum . Bologna, Italy. CEUR Workshop Proceedings, 3180. htps://ceur ‐ws.org/Vol‐3180/
• Floridi, L., & Chiriati, M. (2020). GPT‐3: Its nature, scope, limits, and consequences. Minds and Machines, 30, 681-694.
• Frieder, S., Pincheti, L., Grifiths, R.‐R., Salvatori, T., Lukasiewicz, T., Petersen, P. C., Chevalier, A., & Berner, J. (2023). Mathematical capabilities of ChatGPT . htps:// doi.org/10.48550/arXiv.2301.13867
• George, A. S., & George, A. H. (2023). A review of ChatGPT AI's impact on several business sectors. Partners Universal International Innovation Journal , 1(1), 9-23. htps://doi.org/10.5281/zenodo.7644359
• Gibbs, S. (2017, July 17). Elon Musk: Regulate AI to combat 'existential threat' befo ‐ re it's too late. The Guardian. htps://www.theguardian.com/technology/2017/ jul/17/elon‐musk‐regulation‐ai‐combat ‐existential‐threat ‐tesla‐spacex‐ceo
• Goldstein, J. A., Sastry, G., Musser, M., DiResta, R., Gentzel, M., & Sedova, K. (2023). Generavtie language models and automated inuflence operaotins: Emerging thre - ats and potential mitigations . htps://doi.org/10.48550/arXiv.2301.04246
• Haleem, A., Javaid, M., & Singh, R. P. (2022). An era of ChatGPT as a significant fu ‐ turistic support tool: A study on features, abilities, and challenges. BenchCouncil Transactions on Benchmarks, Standards and Evaluations , 2(4), 100089.
• Hosseini, M., Gao, C. A., Liebovitz, D. M., Carvalho, A. M., Ahmad, F. S., Luo, Y., MacDonald, N., Holmes, K. L., & Kho, A. (2023, April 3). An exploratory survey about using ChatGPT in education, healthcare, and research. medRxiv, 3.
• Ji, Z., Lee, N., Frieske, R., Yu, T., Su, D., Xu, Y., Ishii, E., Bang, Y., Madoot, A., & Fung, P. (2022). Survey of hallucination in natural language generation . htps:// doi.org/10.48550/arXiv.2202.03629
• King, M. R., ChatGPT (2023). A conversation on artifcial intelligence, chatbots, and plagiarism in higher educaotin. Cellular and Molecular Bioengineering, 16(1), 1-2.
• Kirmani, A. R. (2022). Artifcial intelligence-enabled science poetry. ACS Energy Leetrs , 8, 574- 576.
• Launchbury, J. (2016, December 6). A DARPA perspective on artifcial intelligence . DARPA. htps://www.darpa.mil/aatchments/AIFull.pdf
• LMSYS. (2023, May 25). Chatbot arena leaderboard updates. htps://lmsys.org/ blog/2023‐05‐25‐leaderboard/
• Lopez‐Lira, A., & Tang, Y. (2023). Can ChatGPT forecast stock price movements? Return predictability and large language models. htps://doi.org/10.48550/ arXiv.2304.07619
• Lund, B. D., & Wang, T. (2023). Chating about ChatGPT: How may AI and GPT impact academia and libraries? Library Hi Tech News.
• Malone, T. W. (2018). Superminds: The surprising power of people and computers thinking together. Litle, Brown Spark.
• Mayor, T. (2019). Ethics and automation: What to do when workers are displaced . MIT Management Sloan School. hpts://mitsloan.mit.edu/ideas‐made ‐to‐maetr/ ethics‐and‐automation‐what ‐to‐do‐when‐workers‐are‐displaced
• McGee, R. W. (2023, April 8). Using artifcial intelligence (AI) to compose a musical score for a taekwondo tournament rountie: A ChatGPT experiment . Working Paper. htps://doi.org/10.13140/RG.2.2.11235.22569
• Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013). Eficient estimation of word re - presentations in vector space . htps://doi.org/10.48550/arXiv.1301.3781
• Mikolov, T., Sutskever, I., Chen, K., Corrado, G., & Dean, J. (2013). Distributed representaotins of words and phrases and their composiotinality . hpts://doi.org/10.48550/ arXiv.1310.4546
• Motoki, F., Pinho Neto, V., & Rodrigues, V. (2023).More human than human: Measuring ChatGPT political bias . htps://doi.org/10.2139/ssrn.4372349
• OpenAI & Pilipiszyn, A. (2021, March 25). GPT‐3 powers the next generation of apps . htps://openai.com/blog/gpt ‐3‐apps
• Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C. L., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., Ray, A., Schulman, J., Hilton, J., Kelton, F., Miller, L., Simens, M., Askell, A., & Welinder, P. (2022). Training language models to follow instructions with human feedback. arXiv preprint arXiv:2203.02155.
• Patel, S. B., & Lam, K. (2023). ChatGPT: The future of discharge summaries? The Lancet Digital Health, 5(3), e107-e108.
• Paul, J., Ueno, A., & Dennis, C. (2023). ChatGPT and consumers: Benefits, piatflls and future research agenda. International Journal of Consumer Studies , 47( 4), 1213- 1225. htps://doi.org/10.1111/ijcs.12928
• Pennington, J., Socher, R., & Manning, C. D. (2014). Glove: Global vectors for word representation . Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), 1532-1543.
• Rivas, P., & Zhao, L. (2023). Marketing with ChatGPT: Navigating the ethical terra ‐ in of GPT‐based chatbot technology. AI, 4(2), 375-384. htps://doi.org/10.3390/ ai4020019
• Romero, A. (2021, June 21). Understanding GPT‐3 in 5 minutes. htps://towardsdata ‐ science.com/understanding‐gpt‐3‐in‐5‐minutes‐7fe35c3a1e52
• Rudolph, J., Tan, S., & Tan, S. (2023, January 24). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education? Journal of Applied Learning and Teaching, 6(1). htps://doi.org/10.37074/jalt.2023.6.1.9
• Shen, Y., Heacock, L., Elias, J., Hentel, K. D., Reig, B., Shih, G., & Moy, L. (2023). ChatGPT and other large language models are double‐edged swords. Radiology, 307(2). htps://doi.org/10.1148/radiol.230163
• Thurzo, A., Strunga, M., Urban, R., Surovková, J., & Afrashtehfar, K. I. (2023). Impact of artifcial intelligence on dental education: A review and guide for curriculum update. Education Sciences , 13(2), 150.
• Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017).Aetnotin is all you need . hpts://doi.org/10.48550/ arXiv.1706.03762
• Weizenbaum, J. (1966). Eliza-a computer program for the study of natural language communication between man and machine. Communications of the ACM , 9(1), 36-45. htps://doi.org/10.1145/365153.365168
• Westerlund, M. (2019, November). The emergence of deepfake technology: A review. Technology Innovation Management Review , 9(11), 39-52. htps://doi. org/10.22215/timreview/1282
• Yang, Z., Li, L., Wang, J., Lin, K., Azarnasab, E., Ahmed, F., Liu, Z., Liu, C., Zeng, M., & Wang, L. (2023). MM‐react: Prompting ChatGPT for multimodal reasoning and action . htps://doi.org/10.48550/arXiv.2303.11381

Identifiers

DOI

10.18559/ebr.2023.2.736

Biblioteka Nauki

2231663