A Commentary on Kiazad et al. (2025): Generative AI as a Tool to Generate Bullshit at Work

Abstract

The use of generative AI tools in the workplace implies that previously studied human phenomena, such as workplace bullshit, may take on different forms. In this comment to Kiazad et al. (2025), we first discuss how the functional properties of generative AI tools guarantees that such tools will generate workplace bullshit, and then, we discuss the consequences of using generative AI's bullshit at work with respect to the development and connection workers might otherwise foster in the workplace. Our comment offers two propositions to summarize our discussions.

Keywords

artificial intelligence bullshit organizational effectiveness

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References

Aggarwal

Murahari

Rajpurohit

Kalyan

Narasimhan

Deshpande

(2024). GEO: Generative engine optimization. In: Proceedings of the 30th ACM SIGKDD conference on knowledge discovery and data mining (pp. 5–16). https://doi.org/10.1145/3637528.3671900

Andiappan

Dufour

(2020). Jealousy at work: A tripartite model. Academy of Management Review, 45(1), 205–229. https://doi.org/10.5465/amr.2016.0299

Babushkina

De Boer

(2024). Disrupted self, therapy, and the limits of conversational AI. Philosophical Psychology, 55(3), 1–27. https://doi.org/10.1080/09515089.2024.2397004

Bai

Liu

(2023). ChatGPT: The cognitive effects on learning and memory. Brain‐X, 1(3), Article e30. https://doi.org/10.1002/brx2.30

Baranetsky

D. V.

(2025). How data secrecy and privatization are gutting American democracy. https://casi.stanford.edu/news/how-data-secrecy-and-privatization-are-gutting-american-democracy

Bender

E. M.

Gebru

McMillan-Major

Shmitchell

(2021). On the dangers of stochastic parrots: Can language models be too big? In: Proceedings of the 2021 ACM conference on fairness, accountability, and transparency (pp. 610–623). Association for Computing Machinery. https://doi.org/10.1145/3442188.3445922

Carro

M. V.

(2024). Flattering to deceive: The impact of sycophantic behavior on user trust in large language model (no. arXiv:2412.02802). arXiv. https://doi.org/10.48550/arXiv.2412.02802

Chen

Arditi

Sleight

Evans

Lindsey

(2025). Persona vectors: Monitoring and controlling character traits in language models (no. arXiv:2507.21509). arXiv. https://doi.org/10.48550/arXiv.2507.21509

Dunning

Heath

Suls

J. M.

(2004). Flawed self-assessment: Implications for health, education, and the workplace. Psychological Science in the Public Interest: A Journal of the American Psychological Society, 5(3), 69–106. https://doi.org/10.1111/j.1529-1006.2004.00018.x

10.

Garousi

(2025). Why you shouldn’t fully trust ChatGPT: A synthesis of this AI tool’s error rates across disciplines and the software engineering lifecycle. No. (arXiv:2504.18858) arXiv. https://doi.org/10.48550/arXiv.2504.18858

11.

Grodniewicz

J. P.

Hohol

(2023). Waiting for a digital therapist: Three challenges on the path to psychotherapy delivered by artificial intelligence. Frontiers in Psychiatry, 14(3), Article 1190084. https://doi.org/10.3389/fpsyt.2023.1190084

12.

Hai

Long

Honora

Japutra

Guo

(2025). The dark side of employee-generative AI collaboration in the workplace: An investigation on work alienation and employee expediency. International Journal of Information Management, 83(25), Article 102905. https://doi.org/10.1016/j.ijinfomgt.2025.102905

13.

Hannigan

T. R.

McCarthy

I. P.

Spicer

(2024). Beware of botshit: How to manage the epistemic risks of generative chatbots. Business Horizons, 67(5), 471–486. https://doi.org/10.1016/j.bushor.2024.03.001

14.

Hao

(2025). Empire of AI: Dreams and nightmares in sam Altman’s OpenAI: Penguin Press.

15.

Harari

Y. N.

(2024). Nexus: A brief history of information networks from the stone age to AI: Penguin Press.

16.

Hicks

M. T.

Humphries

Slater

(2024). ChatGPT is bullshit. Ethics and Information Technology, 26(2), 38. https://doi.org/10.1007/s10676-024-09775-5

17.

Kiazad

Chen

F. X.

Restubog

S. L. D.

(2025). Workplace bullshitting: A multidimensional analysis of motives. Group & Organization Management. https://doi.org/10.1177/10596011251348757

18.

Kumaran

Fleming

S. M.

Markeeva

Heyward

Banino

Mathur

Pascanu

Osindero

Martino

B. DE

Velickovic

Patraucean

(2025). How overconfidence in initial choices and underconfidence under criticism modulate change of mind in large language models (no. arXiv:2507.03120). arXiv. https://doi.org/10.48550/arXiv.2507.03120

19.

Larson

B. Z.

Moser

Caza

Muehlfeld

Colombo

L. A.

(2024). Critical thinking in the age of generative AI. The Academy of Management Learning and Education, 23(3), 373–378. https://doi.org/10.5465/amle.2024.0338

20.

Licon

J. A.

(2025). ChatGPT is bullshit (partly) because people are bullshitters. Philosophy & Technology, 38(2), 75. https://doi.org/10.1007/s13347-025-00907-3

21.

Lindebaum

Fleming

(2024). ChatGPT undermines human reflexivity, scientific responsibility and responsible management research. British Journal of Management, 35(2), 566–575. https://doi.org/10.1111/1467-8551.12781

22.

Mazzola

J. J.

Disselhorst

(2019). Should we be “challenging” employees?: A critical review and meta-analysis of the challenge-hindrance model of stress. Journal of Organizational Behavior, 40(8), 949–961. https://doi.org/10.1002/job.2412

23.

Melisa

Ashadi

Triastuti

Hidayati

Salido

Ero

P. E. L.

Marlini

Zefrin

Al Fuad

(2025). Critical thinking in the age of AI: A systematic review of aI’s effects on higher education. Educational Process International Journal, 14(1), Article e2025031. https://doi.org/10.22521/edupij.2025.14.31

24.

OpenAI (2025). ChatGPT (Sep. 6 version) [Large Language Model]. https://chatgpt.com

25.

Sharma

Tong

Korbak

Duvenaud

Askell

Bowman

S. R.

Cheng

Durmus

Hatfield-Dodds

Johnston

S. R.

Kravec

Maxwell

McCandlish

Ndousse

Rausch

Schiefer

Yan

Zhang

Perez

(2025). Towards understanding sycophancy in language models (no. arXiv:2310.13548). arXiv. https://doi.org/10.48550/arXiv.2310.13548