ChatGpt and political discourse: A review
DOI:
https://doi.org/10.31637/epsir-2024-841Keywords:
Chat GPT, chatbot, Artificial Intelligence, Natural Language Processing, Machine Learning, Technology, Public politics, Human rightsAbstract
Introduction: ChatGPT is already being used by members of congress, politicians, journalists, students, scientists, and public administrations around the world. In politics it has deployed numerous uses: for the generation of essays or speeches; to understand emerging political trends; to simulate debates and discussions on issues of importance to voters; to design public policies that are more in line with majority public opinion or that satisfy the aspirations of a greater number of people; identify who has a significant influence on the public agenda, etc. Methodology: This study uses the PRISMA methodology and analyzes data obtained from the Web of Science and Google Scholar. Discussion: However, some problems inherent to its operation (such as errors, biases, political bias, lack of data protection, violation of rights such as those related to data protection or intellectual property, environmental impact) have conditioned its use in several countries. Conclusions: This paper aims to make these aspects visible in relation to politics, the construction of discourses for electoral purposes, focusing the debate on their ethical use, respect for fundamental rights and the impact on our democracies.
Downloads
References
Ahmed, T. N. y Mahmood, K. A. (2024). A Critical Discourse Analysis of ChatGPT's Role in Knowledge and Power Production. Arab World English Journ. https://dx.doi.org/10.24093/awej/ChatGPT.12
Algolia (2023). Index your world, put it in motion with our powerful search API. https://www.algolia.com/
Allport, G. W. y Postman, L. (1947). The Psychology of Rumor. Henry Holt.
Amoore, L., Campolo, A., Jacobsen, B. y Rella, L. (2024). A world model: On the political logics of generative AI. Political Geography, 113, 103134. https://doi.org/10.1016/j.polgeo.2024.103134
Aseeva, A. (2023). Liable and Sustainable by Design: A Toolbox for a Regulatory Compliant and Sustainable Tech. Sustainability, 16(1), 228. https://doi.org/10.3390/su16010228
Avetisyan, A. y Silaev, N. (2023). Russia Is a Serious Player in the AI Race. https://open.mgimo.ru/handle/123456789/4823
Aydın, Ö. y Karaarslan, E. (2023). Is ChatGPT leading generative AI? What is beyond expectations?. Academic Platform Journal of Engineering and Smart Systems, 11(3), 118-134. https://doi.org/10.21541/apjess.1293702
Bang, Y., Lee, N., Ishii, E., Madotto, A. y Fung, P. (2021). Assessing political prudence of open-domain chatbots. https://arxiv.org/pdf/2106.06157.pdf
Barščevski, T. (2024). The Church in the Face of Ethical Challenges of Artificial Intelligence. Bogoslovska smotra, 94(1), 31-51. https://doi.org/10.53745/bs.94.1.5
Bass, D. (2023a). Buzzy ChatGPT chatbot is so error-prone that its maker just publicly promised to fix the tech’s ‘glaring and subtle biases.’ Fortune. bit.ly/3Y2mFjP
Bass, D. (2023b). ChatGPT maker OpenAI says it’s working to reduce bias, bad behavior. Bloomberg. bloom.bg/4eYyei7
Berry, D. M. y Stockman, J. (2024). Schumacher in the age of generative AI: Towards a new critique of technology. European Journal of Social Theory, 13684310241234028. https://doi.org/10.1177/13684310241234028
Blodgett, S. L., Barocas, S., Daumé III, H. y Wallach, H. (2020). Language (technology) is power: A critical survey of" bias". Proceed. of the 58th Annual Meeting of the Association for Computat. Linguistics, 5454–5476. https://arxiv.org/pdf/2005.14050
Breazu, P. y Katson, N. (2024). ChatGPT-4 as a journalist: Whose perspectives is it reproducing?. Discourse & Soc. https://doi.org/10.1177/09579265241251479
Bender, E.M., Gebru, T., McMillan-Major, A., y Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big?. ACM confer. on fairness, accountab., and transp. 610-623. https://doi.org/10.1145/3442188.344592
Borji, A. (2023). A categorical archive of chatgpt failures. https://doi.org/10.48550/arXiv.2302.03494
Brenna (2023, 16 de febrero). Losing the Plot: From the Dream of ai to Performative Equity. Tru Digital Detox. https://acortar.link/yuHibH
Cao, H. y Liu, S (2024). The Effectiveness of ChatGPT in Translating Chunky Construction Texts in Chinese Political Discourse. Journ. of Electrics Systems, 20(2). 1684-1698. https://doi.org/10.52783/jes.1616
Chalkidis, I. y Brandl, S. (2024). Llama meets EU: Investigating the European Political Spectrum through the Lens of LLMs. https://aclanthology.org/2024.naacl-short.40
Chowdhury, H. (2023). Sam Altman has one big problem to solve before ChatGPT can generate big cash—making it ‘woke’. Business Insider. ChatGPT will always have bias, says OpenAI boss (thetimes.com)
Dixon, L., Li, J., Sorensen, J., Thain, N. y Vasserman, L. (2018). Measuring and mitigating unintended bias in text classification. Proceedings of the 2018 AAAI/ACM Confer. on AI, Ethics, and Society, 67-73. https://doi.org/10.1145/3278721.3278729
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. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., Carter , L. y Wright, R. (2023).: “So what if ChatGPT wrote it?”. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642
DW. (2023). Resuelven en Colombia el primer caso jurídico con la ayuda de robot ChatGPT. bit.ly/4f2xAA1
Europa Press Internacional (2023). La primera ministra danesa usa ChatGPT para redactar parte de un discurso y alerta de sus posibles riesgos. 31/05/2023. bit.ly/3Wjfq5V
Farhat, F., Sohail, S. S. y Madsen, D. Ø. (2023). How trustworthy is ChatGPT? The case of bibliometric analyses. Cogent Engineering, 10(1), 2222988. https://doi.org/10.1080/23311916.2023.2222988
Feldstein, S. (2023). The consequences of generative AI for democracy, governance and war. In Survival: October–November 2023 (pp. 117-142). Routledge.
Feng, S., Park, C. Y., Liu, Y. y Tsvetkov, Y. (2023). From pretraining data to language models to downstream tasks: Tracking the trails of political biases leading to unfair NLP models. https://doi.org/10.48550/arXiv.2305.08283
Fujimoto, S. y Takemoto, K. (2023). Revisiting the political biases of ChatGPT. Frontiers in Artificial Intelligence, 6, 1232003. https://doi.org/10.3389/frai.2023.1232003
Gemenis, K. (2024). Artificial intelligence and voting advice applications. Frontiers in Political Science, 6, 1286893. https://doi.org/10.3389/fpos.2024.1286893
Ghafouri, V., Agarwal, V., Zhang, Y., Sastry, N., Such, J. y Suarez-Tangil, G. (2023, October). AI in the Gray: Exploring Moderation Policies in Dialogic Large Language Models vs. Human Answers in Controversial Topics. ACM. 556-565. https://doi.org/10.1145/3583780.3614777
Ghosh, S., Baker, D., Jurgens, D. y Prabhakaran, V. (2021). Detecting cross-geographic biases in toxicity modeling on social media. https://arxiv.org/pdf/2104.06999
Gibney, E. (2024). What the EU's tough AI law means for research and ChatGPT. Nature. https://doi.org/10.1038/d41586-024-00497-8
Gregorcic, B. y Pendrill, A. M. (2023). ChatGPT and the frustrated Socrates. Physics Education, 58(3), 035021. 10.1088/1361-6552/acc299
Guo, B., Zhang, X., Wang, Z., Jiang, M., Nie, J., Ding, Y., Yue, J. y Wu, Y. (2023). How close is chatgpt to human experts? comparison corpus, evaluation, and detection. https://doi.org/10.48550/arXiv.2301.07597
Guo, D., Chen, H., Wu, R. y Wang, Y. (2023). AIGC challenges and opportunities related to public safety: a case study of ChatGPT. Journal of Safety Science and Resilience, 4(4), 329-339. https://doi.org/10.1016/j.jnlssr.2023.08.001
Halpern, D. (2015). Inside the nudge unit: How small changes can make a big difference. Random House.
Hartmann, J., Schwenzow, J. y Witte, M. (2023). "The political ideology of conversational AI: Converging evidence on ChatGPT's pro-environmental, left-libertarian orientation". https://doi.org/10.48550/arXiv.2301.01768
Heimans, S., Biesta, G., Takayama, K., y Kettle, M. (2023). ChatGPT, subjectification, and the purposes and politics of teacher education and its scholarship. Asia-Pacific Journal of Teacher Education, 51(2), 105-112. https://doi.org/10.1080/1359866X.2023.2189368
Hutchinson, B., Prabhakaran, V., Denton, E., Webster, K., Zhong, Y. y Denuyl, S. (2020). Social biases in NLP models as barriers for persons with disabilities. https://arxiv.org/pdf/2005.00813
Hutson, M. (2022). Could AI help you to write your next paper?. Nature, 611, 192-193. https://doi.org/10.1038/d41586-022-03479-w
Jarquín-Ramírez, M. R., Alonso-Martínez, H. y Díez-Gutiérrez, E. (2024). Alcances y límites educativos de la IA: control e ideología en el uso de ChatGPT. DIDAC, 84, 84-102. DOI:10.48102/didac.2024.84_JUL-DIC.217
Jenks, C. J. (2024). Communicating the cultural Other: Trust and bias in generative AI and large language models. Applied Ling. Review, 0. https://acortar.link/zNGinC
Jiang, H., Beeferman, D., Roy, B. y Roy, D. (2022). CommunityLM: Probing partisan worldviews from language models. https://arxiv.org/pdf/2209.07065
Johnson, A. (2023). “Is ChatGPT Partisan? Poems About Trump And Biden Raise Questions About The AI Bot’s Bias—Here’s What Experts Think”, Forbes, (03/02/2023). bit.ly/4cWYho7
Jungherr, A. (2023). Artificial intelligence and democracy: A conceptual framework. Social media+ society, 9(3), 20563051231186353. https://doi.org/10.1177/20563051231186353
Kallury, P. (2020, julio 7). Don’t ask if artificial intelligence is good or fair, ask how it shifts power. Nature. https://doi.org/10.1038/d41586-020-02003-2
Khanal, S., Zhang, H. y Taeihagh, A. (2024). Why and how is the power of Big Tech increasing in the policy process? Policy and Society, puae012. https://doi.org/10.1093/polsoc/puae012
Kim, J., Lee, J., Jang, K. M. y Lourentzou, I. (2024). Exploring the limitations in how ChatGPT introduces environmental justice issues in the United States. Telematics and Informatics, 86, 102085. https://doi.org/10.1016/j.tele.2023.102085
Kocoń, J., Cichecki, I., Kaszyca, O., Kochanek, M., Szydło, D., Baran, J. Bielaniewicz, J., Gruza, M., Janz, A., Kanclerz, K., Kocón, A., Koptyra, B., Mielesczenko-Kowszewicz, W., Milkowski, P., Oleksy, M., Piasecki, M. Radlinski, L., Wojtasik, K. y Kazienko, P. (2023). ChatGPT: Jack of all trades, master of none. Information Fusion, 99, 101861. https://doi.org/10.1016/j.inffus.2023.101861
Li, Y., Zhang, G., Yang, B., Lin, C., Wang, S., Ragni, A. y Fu, J. (2022). Herb: Measuring hierarchical regional bias in pre-trained language models. https://arxiv.org/pdf/2211.02882
Li, P., Yang, J., Islam, M. A. y Ren, S. (2023). Making ai less" thirsty": Uncovering and addressing the secret water footprint of ai models. https://arxiv.org/pdf/2304.03271
Liu, R., Jia, C., Wei, J., Xu, G., Wang, L. y Vosoughi, S. (2021, May). Mitigating political bias in language models through reinforced calibration. AAAI Conference on Artificial Intelligence, 35(17), 14857-14866. https://doi.org/10.1609/aaai.v35i17.17744
Maltby, J., Rayes, T., Nage, A., Sharif, S., Omar, M. y Nichani, S. (2024). Synthesizing perspectives: Crafting an Interdisciplinary view of social media’s impact on young people’s mental health. Plos one, 19(7), e0307164. https://doi.org/10.1371/journal.pone.0307164
Martin, J. L. (2023). The Ethico-Political Universe of ChatGPT. Journal of Social Computing, 4(1), 1-11. https://doi.org/ 10.23919/JSC.2023.0003
McGee, R. W. (2023). Is chat gpt biased against conservatives? an empirical study. An Empirical Study. https://doi.org/10.2139/ssrn.4359405
McGee, R. W. (2024). What Were the Causes of the American Civil War? A Study in Artificial Intelligence. A Study in Artificial Intelligence http://dx.doi.org/10.2139/ssrn.4737710
Messner, W., Greene, T. y Matalone, J. (2023). From Bytes to Biases: Investigating the Cultural Self-Perception of Large Language Models. https://doi.org/10.48550/arXiv.2312.17256
Monrad, M. (2024). Feeling rules in artificial intelligence: norms for anger management. Emotions and Society, 1(aop), 1-19. https://doi.org/10.1332/26316897Y2024D000000016
Motoki, F., Pinho Neto, V. y Rodrigues, V. (2024). More human than human: measuring ChatGPT political bias. Public Choice, 198(1), 3-23. https://acortar.link/r7zBcb
Muzanenhamo, P. y Power, S. B. (2024). ChatGPT and accounting in African contexts: Amplifying epistemic injustice. Critical Perspectives on Accounting, 99, 102735. https://doi.org/10.1016/j.cpa.2024.102735
Naing, S. Z. S. y Udomwong, P. (2024). Public Opinions on ChatGPT: An Analysis of Reddit Discussions by Using Sentiment Analysis, Topic Modeling, and SWOT Analysis. Data Intelligence, 1-50. https://doi.org/10.1162/dint_a_00250
Okolo, C. T. (2023, November). The Promise and Perils of Generative AI: Case Studies in an African Context. 4th African Human Comp. Interaction Conf. 266-270. https://doi.org/10.1145/3628096.3629066
OpenAI, Achiam, J., Adler, S., Agarwal, S., Ahmad, L., Akkaya, I., Aleman, F. L., ... y McGrew, B. (2023). Gpt-4 technical report. https://doi.org/10.48550/arXiv.2303.08774
Page, J. M., McKenzie, J. E., Bossuyt, P. M., Boutron,I., Hoffmann, T. C.,Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville,J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., McGuinness, L. A., Stewart, L. A., Thomas, J., Tricco, A. C., Welch, V. A., Whiting,P. y Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 71, 1-9. https://doi.org/10.1136/bmj.n71
Pariser, E. (2011). Cuidado con las burbujas de filtro. TED. bit.ly/4f1YVST
Pariser, E. (2017). El filtro burbuja. Taurus.
Patel, S. B., Lam, K. y Liebrenz, M. (2023). ChatGPT: friend or foe. Lancet Digit Health, 5(3). https://doi.org/10.1016/S2589-7500(23)00023-7
Pagnarasmey, P., Xingjun, M., Conway, M., Quingyu, C., Bailey, J., Henry, P., Putrasmey, K., Watey, D. y Yu-Gang, J. (2024). Whose Side Are You On? Investig. Pol. Stance of Large Lang. Models. Arxiv. https://doi.org/10.48550/arXiv.2403.13840
Pollard, E. (2024). Back to the future: everything you wish you’d asked Derrida about ChatGPT when you had the chance!. Cultural Studies Critical Methodologies. https://doi.org/10.1177/15327086241232722
Preedipadma, N. (2020, 13 de febrero). New MIT neural network architecture may reduce carbon footprint by AI. Analytics Insight. https://tinyurl.com/5n8463cw
PRISMA. (s. f.). PRISMA 2020 Checklist. https://prisma.shinyapps.io/checklist/
Punset, E. (2008). Por qué somos como somos. Aguilar.
Retzlaff, N. (2024). Political Biases of ChatGPT in Different Languages. Preprints.org. https://doi.org/10.20944/preprints202406.1224.v1
Ricoy-Casas, R.M. (2021). "Sesgos y algoritmos: inteligencia de género” and "Algunos dilemas éticos en la utilización de la inteligencia artificial y los algoritmos". En P. R. Bonorino-Ramírez, R. Fernández y P. Valcárcel, P. (Dirs.). Nuevas normatividades. Th. Reuters Aranzadi.
Ricoy-Casas, R. M. (2021b). "Inteligencia artificial y administración de justicia: una política pública sub iudice". En P. R. Bonorino-Ramírez, R. Fernández, P. Valcárcel e I. S. García (Dirs.). Justicia, administración y derecho. Thomson Reuters Aranzadi.
Ricoy-Casas R. M. (2022a). Use of Technological Means and Personal Data in Electoral Activities: Persuasive Voters. En Á. Rocha, D. Barredo, P. C. López-López e I. Puentes-Rivera (Eds) Comm. and Smart Techn, (pp. 227-237). Springer. https://doi.org/10.1007/978-981-16-5792-4_23
Ricoy Casas, R. M. (2022b). Hologramas y Avatares para la persuasión política. International Visual Culture Review. https://doi.org/10.37467/revvisual.v9.3547
Roe, J. y Perkins, M. (2023). Lo que no te están contando sobre ChatGPT. Humanities and soc. sciences comm., 10(1), 1-9. https://doi.org/10.1057/s41599-023-02282-w
Roy, N. y Maity, M. (2023). An Infinite Deal of Nothing: critical ruminations on ChatGPT and the politics of language. Decision, 50(1), 11-17. https://acortar.link/YHBlqa
Rozado, D. (2023a). “The Political Biases of ChatGP”, Social Sciences, 12(3) 148. https://doi.org/10.3390/socsci12030148;
Rozado, D. (2023b). "Danger in the Machine: The Perils of Political and Demographic Biases Embedded in AI Systems", Manhattan Institute. bit.ly/3Wj2w82
Rutinowski, J., Franke, S., Endendyk, J., Dormuth, I., Roidl, M. y Pauly, M. (2024). The Self‐Perception and Political Biases of ChatGPT. Human Behavior and Emerging Technologies, 1, 7115633. https://doi.org/10.1155/2024/7115633
Salminen, J., Veronesi, F., Almerekhi, H., Jung, S. G. y Jansen, B.J. (2018). Online hate interpretation varies by country, but more by individual. Fifth intern. Conf. on social networks analysis, manag. and security (SNAMS), 88-94. 10.1109/SNAMS.2018.8554954
Salminen, J., Almerekhi, H., Kamel, A. M., Jung, S. G. y Jansen, B. J. (2019). Online hate ratings vary by extremes: A statistical analysis. Proceedings of the 2019 confer. on human information interaction and retrieval, 213-217. https://doi.org/10.1145/3295750.3298954
Sallam, M., Salim, N. A., Ala’a, B., Barakat, M., Fayyad, D., Hallit, S., Harapan, H., Hallit, R. y Mahafzah, A. (2023). ChatGPT output regarding compulsory vaccination and COVID-19 vaccine conspiracy: A Descriptive Study at the Outset of a Paradigm Shift in Online Search for Information Cureus, 15(2). https://doi.org/10.7759/cureus.35029
Sambasivan, N., Arnesen, E., Hutchinson, B., Doshi, T. y Prabhakaran, V. (2021). Re-imagining algorithmic fairness in india and beyond. Proceed. of the 2021 ACM confer. on fairness, accountab., and transp., 315-328. https://doi.org/10.1145/3442188.3445896
Sanchis, A. (2024). Cada vez más curas españoles utilizan ChatGPT para sus misas: “Lo usé hasta para un funeral”. El Confidencial. bit.ly/46aN1SY
Sellman, M. (2023). ChatGPT will always have bias, says OpenAI boss. The Times. https://acortar.link/EBqJfR
Seyyed-Kalantari, L., Zhang, H., McDermott, M. B., Chen, I. Y. y Ghassemi, M. (2021). Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations. Nature medicine, 27(12), 2176-2182. https://doi.org/10.1038/s41591-021-01595-0
Slater, G. B. (2024). Dread and the automation of education: From algorithmic anxiety to a new sensibility. Review of Education, Pedagogy, and Cultural Studies, 46(1), 170-182. https://doi.org/10.1080/10714413.2023.2299521
Špecián, P. (2024). Machine Advisors: Integrating Large Language Models into Democratic Assemblies. SSRN. http://dx.doi.org/10.2139/ssrn.4682958
Stahl, B. C. y Eke, D. (2024). The ethics of ChatGPT–Exploring the ethical issues of an emerging technology. International Journal of Information Management, 74, 102700. https://doi.org/10.1016/j.ijinfomgt.2023.102700
Stokel-Walker, C. (2022). AI bot ChatGPT writes smart essays-should academics worry?. Nature. https://doi.org/10.1038/d41586-022-04397-7
Stokel-Walher C. (2023). ChatGPT listed as author on research papers: many scientists disapprove. Nature, Jan 18. https://www.nature.com/articles/d41586-023-00107-z
Strubell, E., Ganesh, A. y McCallum, A. (2019). Energy and policy considerations for deep learning. NLP. 57th Ann. Meeting (ACL). https://doi.org/10.48550/arXiv.1906.02243
Suguri-Motoki, F. Y., Pinho Neto, V. y Rodrigues, V. 2023. More human than human: measuring ChatGPT political bias. Public Choice, 198(1), 3-23. https://doi.org/10.2139/ssrn.4372349
Sullivan-Paul, M. (2023). How would ChatGPT vote in a federal election? A study exploring algorithmic political bias in artificial intelligence. University of Tokyo.
Sunstein, C. (2003). República.com: Internet, democracia y libertad (Estado y Sociedad). Paidós.
Tepper, J. (2020). El mito del capitalismo. Los monopolios y la muerte de la competencia. Roca Ed.
Thaler, R. H. y Sunstein, C. R. (2009). Nudge: Improving decisions about health, wealth, and happiness. Penguin.
Theconversation (2023). ChatGPT could be a game-changer for marketers, but it won’t replace humans any time soon. bit.ly/4cY2at0
Thorp, H.H. (2023). ChatGPT is fun, but not an author. Science, 379(6630), 313-313. https://www.science.org/doi/10.1126/science.adg7879
Trapero, L. (2019). Los trabajadores de las tecnológicas, en huelga por el clima. Euronews. https://tinyurl.com/5fb5pbc7
Ulnicane, I. (2024). Governance fix? Power and politics in controversies about governing generative AI. Policy and Society. https://doi.org/10.1093/polsoc/puae022
UNESCO (2019). I'd blush if I could: closing gender divides in digital skills through education. https://doi.org/10.54675/RAPC9356
Urman, A. y Makhortykh, M. (2023). The Silence of the LLMs: Cross-Lingual Analysis of Political Bias and False Information Prevalence in ChatGPT, Google Bard, and Bing Chat. OSFPrepints. https://doi.org/10.31219/osf.io/q9v8f
Van-Dis, E.A., Bollen, J., Zuidema, W., Van-Rooij, R. y Bockting, C. L. (2023). ChatGPT: five priorities for research. Nature, 614(7947), 224-226. https://acortar.link/U3oqLL
Van-Wynsberghe, A. (2021). Sustainable AI: AI for sustainability and the sustainability of AI. AI and Ethics, 1(3), 213-218. https://doi.org/10.1007/s43681-021-00043-6
Vincent, J. (2023). AI art tools Stable Diffusion and Midjourney targeted with copyright lawsuit. The Verge. bit.ly/3NVbaG1
Vogels, E. A. (2023). A majority of Americans have heard of ChatGPT, but few have tried it themselves. Pew Research Center. bit.ly/3zGwN7S
Wang, S. H. (2023). OpenAI—explain why some countries are excluded from ChatGPT. Nature, 615(7950), 34-34. https://doi.org/10.1038/d41586-023-00553-9
Winkel, M. (2024). Controlling the uncontrollable: the public discourse on artificial intelligence between the positions of social and technological determinism. AI & SOCIETY, 1-13.https://doi.org/10.1007/s00146-024-01979-z
Wolf, Z. B. (2023). AI can be racist, sexist and creepy. What should we do about it. AI can be racist, sexist and creepy. What should we do about it? | CNN Politics
Zack, T., Lehman, E., Suzgun, M., Rodriguez, J. A., Celi, L. A., Gichoya, J., Jurafsky, D., Szolovits, P., Bates, D. W., E. Abdulnour, R. E., Butte, A. J. y Alsentzer, E. (2023). Coding Inequity: Assessing GPT-4's Potential for Perpetuating Racial and Gender Biases in Healthcare. medRxiv, 2023-07. https://doi.org/10.1101/2023.07.13.23292577
Zhao, J., Wang, T., Yatskar, M., Ordonez, V. y Chang, K. W. (2018). Gender bias in coreference resolution: Evaluation and debiasing methods. Human Language Technologies, 2, 15-20. https://arxiv.org/pdf/1804.06876
Zhou, D. y Zhang, Y. (2023). Red AI? Inconsistent Responses from GPT3. 5 Models on Political Issues in the US and China. https://doi.org/10.48550/arXiv.2312.09917
Zou, W. y Liu, Z. (2024). Unraveling Public Conspiracy Theories Toward ChatGPT in China: A Critical Discourse Analysis of Weibo Posts. Journal of Broadcasting & Electronic Media, 68(1), 1-20. https://doi.org/10.1080/08838151.2023.2275603
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Rosa María Ricoy Casas, Raquel Fernández González
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Non Commercial, No Derivatives Attribution 4.0. International (CC BY-NC-ND 4.0.), that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).