IDEAS home Printed from https://ideas.repec.org/p/zbw/itse23/277971.html
   My bibliography  Save this paper

AI-generated lemons: a sour outlook for content producers?

Author

Listed:
  • Howell, Bronwyn E.
  • Potgieter, Petrus H.

Abstract

Artificial intelligence (AI) techniques for natural language processing have made dramatic advances in the past few years (Lin 2023). Thunström & Steingrimsson (2022) demonstrated that the present generation of AI text engines are even able to write low-level scientific pieces about themselves, with relatively minimal prompting, whereas Goyal et al. (2022) show how good general-purpose AI language engines are at summarizing news articles. There is however a downside to all of this progress. Bontridder & Poullet (2021) point out how inexpensive it has become to generate deepfake videos and synthetic voice recordings. Kreps et al. (2022) look at AI generated text and find that "individuals are largely incapable of distinguishing between AI- and human-generated text". Illia et al. (2023) point to three ethical challenges raised by automated text generation that is difficult to distinguish from human writing: 1. facilitation of mass manipulation and disinformation; 2. a lowest denominator problem where a mass of low-quality but incredibly cheap text, crowds out higher-quality discourse; and 3. the suppression of direct communication between stakeholders and an attendant drop in the levels of trust. Our focus is mainly on (2) and we examine the institutional consequences that may arise in two specific sectors currently already facing challenges from AI-generated text: scientific journals and social media platforms. Drawing on the body of learning from institutional economics regarding responses to uncertainties in the veracity of information, it also proposes some elementary remedies that may prove helpful in navigating through the anticipated challenges. Distinguishing genuinely human-authored content from machine-generated text will likely be more easily done using a credible signal of the authenticity of the content creator. This is a variation of Akerlof's (1970) famous "market for lemons" problem. This paper uses an inductive approach to examine sections of the content industry that are likely to be particularly relevant to "market for lemons" substitution, referring to the framework of Giannakas & Fulton (2020).

Suggested Citation

  • Howell, Bronwyn E. & Potgieter, Petrus H., 2023. "AI-generated lemons: a sour outlook for content producers?," 32nd European Regional ITS Conference, Madrid 2023: Realising the digital decade in the European Union – Easier said than done? 277971, International Telecommunications Society (ITS).
    • Handle: RePEc:zbw:itse23:277971
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/277971/1/Howell-Potgieter.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Michael Park & Erin Leahey & Russell J. Funk, 2023. "Papers and patents are becoming less disruptive over time," Nature, Nature, vol. 613(7942), pages 138-144, January.
    2. Benoît Dupont & Anne-Marie Côté & Claire Savine & David Décary-Hétu, 2016. "The ecology of trust among hackers," Global Crime, Taylor & Francis Journals, vol. 17(2), pages 129-151, April.
    3. Adam Day, 2022. "Exploratory analysis of text duplication in peer-review reveals peer-review fraud and paper mills," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 5965-5987, October.
    4. Alessandro Checco & Lorenzo Bracciale & Pierpaolo Loreti & Stephen Pinfield & Giuseppe Bianchi, 2021. "AI-assisted peer review," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-11, December.
    5. Engers, Maxim & Gans, Joshua S, 1998. "Why Referees Are Not Paid (Enough)," American Economic Review, American Economic Association, vol. 88(5), pages 1341-1349, December.
    6. Jennifer Byrne, 2019. "We need to talk about systematic fraud," Nature, Nature, vol. 566(7742), pages 9-9, February.
    7. Holly Else, 2023. "Abstracts written by ChatGPT fool scientists," Nature, Nature, vol. 613(7944), pages 423-423, January.
    8. Guillaume Cabanac & Cyril Labbé, 2021. "Prevalence of nonsensical algorithmically generated papers in the scientific literature," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(12), pages 1461-1476, December.
    9. Chengcheng Shao & Giovanni Luca Ciampaglia & Onur Varol & Kai-Cheng Yang & Alessandro Flammini & Filippo Menczer, 2018. "The spread of low-credibility content by social bots," Nature Communications, Nature, vol. 9(1), pages 1-9, December.
    10. Vanja Pupovac, 2021. "The frequency of plagiarism identified by text-matching software in scientific articles: a systematic review and meta-analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(11), pages 8981-9003, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Justus Haucap & Johannes Muck, 2015. "What drives the relevance and reputation of economics journals? An update from a survey among economists," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(3), pages 849-877, June.
    2. Bruno Frey, 2005. "Problems with Publishing: Existing State and Solutions," European Journal of Law and Economics, Springer, vol. 19(2), pages 173-190, April.
    3. Francois, Patrick, 2000. "'Public service motivation' as an argument for government provision," Journal of Public Economics, Elsevier, vol. 78(3), pages 275-299, November.
    4. Ofer H. Azar, 2006. "The Academic Review Process: How Can We Make it More Efficient?," The American Economist, Sage Publications, vol. 50(1), pages 37-50, March.
    5. Besancenot, Damien & Vranceanu, Radu, 2008. "Can incentives for research harm research? A business schools' tale," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 37(3), pages 1248-1265, June.
    6. Xia, Huosong & Wang, Yuan & Zhang, Justin Zuopeng & Zheng, Leven J. & Kamal, Muhammad Mustafa & Arya, Varsha, 2023. "COVID-19 fake news detection: A hybrid CNN-BiLSTM-AM model," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    7. André Luis Araujo da Fonseca & Paula Castro Pires de Souza Chimenti & Maribel Carvalho Suarez, 2023. "Using deep learning language models as scaffolding tools in interpretive research," RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration), ANPAD - Associação Nacional de Pós-Graduação e Pesquisa em Administração, vol. 27(Vol. 27 N), pages 230021-2300.
    8. Azar, Ofer H., 2008. "Evolution of social norms with heterogeneous preferences: A general model and an application to the academic review process," Journal of Economic Behavior & Organization, Elsevier, vol. 65(3-4), pages 420-435, March.
    9. Thompson, Gary D. & Aradhyula, Satheesh V. & Frisvold, George B. & Tronstad, Russell, 2004. "Does Paying Referees Expedite Reviews?," 2004 Annual meeting, August 1-4, Denver, CO 19988, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    10. Kiri, Bralind & Lacetera, Nicola & Zirulia, Lorenzo, 2018. "Above a swamp: A theory of high-quality scientific production," Research Policy, Elsevier, vol. 47(5), pages 827-839.
    11. Wentao Xu & Kazutoshi Sasahara, 2022. "Characterizing the roles of bots on Twitter during the COVID-19 infodemic," Journal of Computational Social Science, Springer, vol. 5(1), pages 591-609, May.
    12. Popov, Sergey V, 2022. "Tactical Refereeing and Signaling by Publishing," Cardiff Economics Working Papers E2022/14, Cardiff University, Cardiff Business School, Economics Section.
    13. Bruno S. Frey, "undated". "Publishing as Prostitution? Choosing Between One�s Own Ideas and Academic Failure," IEW - Working Papers 117, Institute for Empirical Research in Economics - University of Zurich.
    14. Eric W. K. Tsang & Bruno S. Frey, 2006. "The as-is journal review process: Let authors own their ideas," CREMA Working Paper Series 2006-09, Center for Research in Economics, Management and the Arts (CREMA).
    15. Hajkowicz, Stefan & Naughtin, Claire & Sanderson, Conrad & Schleiger, Emma & Karimi, Sarvnaz & Bratanova, Alexandra & Bednarz, Tomasz, 2022. "Artificial intelligence for science – adoption trends and future development pathways," MPRA Paper 115464, University Library of Munich, Germany.
    16. Robert A. Margo, 2011. "The Economic History of the American Economic Review : A Century's Explosion of Economics Research," American Economic Review, American Economic Association, vol. 101(1), pages 9-35, February.
    17. Patrick Francois, 2004. "'Making a Difference': Labor Donations in the Production of Public Goods," The Centre for Market and Public Organisation 04/093, The Centre for Market and Public Organisation, University of Bristol, UK.
    18. Marta Pacheco & Patrícia Moura & Carla Silva, 2023. "A Systematic Review of Syngas Bioconversion to Value-Added Products from 2012 to 2022," Energies, MDPI, vol. 16(7), pages 1-24, April.
    19. Juin‐jen Chang & Ching‐chong Lai, 2001. "Is It Worthwhile to Pay Referees?," Southern Economic Journal, John Wiley & Sons, vol. 68(2), pages 457-463, October.
    20. Wenkai Zhou & Chi Zhang & Linwan Wu & Meghana Shashidhar, 2023. "ChatGPT and marketing: Analyzing public discourse in early Twitter posts," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(4), pages 693-706, December.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:itse23:277971. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: http://www.itseurope.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.