The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index.
ChatGPT: More Than a “Weapon of Mass Deception” Ethical Challenges and Responses from the Human-Centered Artificial Intelligence (HCAI) Perspective
Open accessPublished version of a preprint
Abstract
This article explores the ethical problems arising from the use of ChatGPT as a kind of generative AI and suggests responses based on the Human-Centered Artificial Intelligence (HCAI) framework. The HCAI framework is appropriate because it understands technology above all as a tool to empower, augment, and enhance human agency while referring to human wellbeing as a “grand challenge”, thus perfectly aligning itself with ethics, the science of human flourishing. Further, HCAI provides objectives, principles, procedures, and structures for reliable, safe, and trustworthy AI which we apply to our ChatGPT assessments. The main danger ChatGPT presents is the propensity to be used as a “weapon of mass deception” (WMD) and an enabler of criminal activities involving deceit. We review technical specifications to better comprehend its potentials and limitations. We then suggest both technical (watermarking, styleme, detectors, and fact-checkers) and non-technical measures (terms of use, transparency, educator considerations, HITL) to mitigate ChatGPT misuse or abuse and recommend best uses (creative writing, non-creative writing, teaching and learning). We conclude with considerations regarding the role of humans in ensuring the proper use of ChatGPT for individual and social wellbeing. This is an original manuscript of an article published by Taylor & Francis in the International Journal of Human-Computer Interaction on June 27th, 2023, available online: https://doi.org/10.1080/10447318.2023.2225931
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Likewise, the perceived risk of encountering hallucinated outputs can lead users to fact-check content or rely on AI detection tools (Sison et al. 2024).”
From Bridging risk and retention: risk coping with privacy and hallucination in AI (2026) · cites this paper as Sison et al. 2024
In the citing paper
“This pattern is consistent with Sison et al. (2024), who argue that awareness of AI limitations can motivate users to adopt verification practices as a way of managing uncertainty, rather than disengaging from AI systems altogether.”
From Bridging risk and retention: risk coping with privacy and hallucination in AI (2026) · cites this paper as Sison et al. (2024)
Citations
Cites
LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2018) · arXiv · doi:10.48550/arxiv.1810.04805 · Cited by 73,173
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., & Liu, P. J. (2019) · arXiv · doi:10.48550/arxiv.1910.10683 · Cited by 10,929
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021) · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3442188.3445922 · Cited by 6,988 · cited 1×
“It has also been called a “ stochastic parrot, ” randomly stitching words together without reference or meaning (Bender et al., 2021).”
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., et al. (2023) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2023.102642 · Cited by 4,584
ELIZA—a computer program for the study of natural language communication between man and machine
Weizenbaum, J. (1966) · Communications of the ACM · doi:10.1145/365153.365168 · Cited by 4,452
Kung, T. H., Cheatham, M., Medenilla, A., Sillos, C., De Leon, L., Elepaño, C., Madriaga, M., Aggabao, R., Diaz-Candido, G., Maningo, J., et al. (2023) · PLOS Digital Health · doi:10.1371/journal.pdig.0000198 · Cited by 4,115
Experimental evidence of massive-scale emotional contagion through social networks
Kramer, A. D. I., Guillory, J. E., & Hancock, J. T. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1320040111 · Cited by 3,687
ELIZA — a computer program for the study of natural language communication between man and machine
Weizenbaum, J. (1983) · Communications of the ACM · doi:10.1145/357980.357991 · Cited by 2,807
What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023) · Smart Learning Environments · doi:10.1186/s40561-023-00237-x · Cited by 2,003 · cited 3×
“Generally, it ’ s better to be adaptive, focusing on the benefits technological innovation brings to education rather than resisting change, embracing AI instead of proscribing it (Mucharraz y Cano et al., 2023; Tlili et al., 2023).”
Research works printed but not linked: 11
- Cavoukian, A. (2009). Privacy by design, take the challenge. Information and Privacy Commissioner of Ontario, Canadian Electronic Library. ASIN: B007Z8DS6S.
- Friedland, A. (2023). Meta’s powerful language models leak online, the U.S. Commerce Department opens up applications for CHIPS funds, and a PRC reorganization will impact R&D and data. Center for Security and Emerging Technology.
- Garrido-Merchán, E. C., Arroyo-Barrigüete, J. L., & Gozalo-Brihuela, R. (2023). Simulating HP lovecraft horror literature with the ChatGPT large language model. arXiv Preprint, arXiv:2305.03429. · arXiv
- Hinton G. (2022). The forward-forward algorithm: Some preliminary investigations. arXiv preprint arXiv:2212.13345. · arXiv
- Liu Y. Ott M. Goyal N. Du J. Joshi M. Chen D. Levy O. Lewis M. Zettlemoyer L. & Stoyanov V. (2019). Roberta: A robustly optimized Bert pretraining approach. arXiv Preprint arXiv:1907.11692. · arXiv
- Martín L. A. & Garrido-Merchán E. C. (2021). Many objective Bayesian optimization. arXiv preprint arXiv:2107.04126. · arXiv
- Merchán E. C. G. & Lumbreras S. (2022). On the independence between phenomenal consciousness and computational intelligence. arXiv preprint arXiv:2208.02187. · arXiv
- Mollick, E., & Mollick, L. (2023). Why all our classes suddenly became AI classes. Harvard Business Publishing Education.
- 10.1093/os/9780192845290.001.0001 · DOI
- Van Der Linden, S. (2023). Foolproof: A psychological vaccine against fake news. University of Cambridge. ISBN 9780008466718.
- Zhong Q. Ding L. Liu J. Du B. & Tao D. (2023). Can ChatGPT understand too? A comparative study on ChatGPT and fine-tuned Bert. arXiv preprint arXiv:2302.10198. · arXiv
Cited by
Sorted by citations
Ferrara, E. (2024) · Journal of Computational Social Science · doi:10.1007/s42001-024-00250-1 · Cited by 296
Yu, H. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e24289 · Cited by 225
RetractedFactuality challenges in the era of large language models and opportunities for fact-checking
Augenstein, I., Baldwin, T., Cha, M., Chakraborty, T., Ciampaglia, G. L., Corney, D., DiResta, R., Ferrara, E., Hale, S., Halevy, A., et al. (2024) · Nature Machine Intelligence · doi:10.1038/s42256-024-00881-z · Cited by 187
Janson, A. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.107954 · Cited by 187
Choudhury, A., & Chaudhry, Z. (2024) · Journal of Medical Internet Research · doi:10.2196/56764 · Cited by 159
Metadata
- Authors
- Sison, A. J. G., Daza, M. T., Gozalo-Brizuela, R., & Garrido-Merchán, E. C.
- Affiliations
- School of Economics and Business Administration, Institute of Data Science and Artificial Intelligence (DATAI), Universidad de Navarra
- Universidad de Guadalajara (MX)
- Universidad Pontificia Comillas (ES)
- Quantitative Methods Department, Universidad Pontificia Comillas
- Corresponding author
- Daza, Marco Tulio
- Venue
- International Journal of Human–Computer Interaction
- Publisher
- Informa UK Limited
- Published
- 2023-06-27
- Volume
- 40
- Issue
- 17
- Pages
- 4853-4872
- ISSN
- 1044-7318 (ISSN-L)
- 1532-7590
- OpenAlex
- W4382249028
- Cited by
- 169
- References
- 56
- Citations by year
- 2026: 41 · 2025: 60 · 2024: 53 · 2023: 15
- FWCI
- 42.32
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- International Journal of Human-Computer Interaction (publishedVersion)
- SSRN Electronic Journal (acceptedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- ChatGPT, generative AI ethics, human-centered AI, AI deception, watermarking, AI detection, fact-checking, trustworthy AI, human agency, human well-being, human-in-the-loop, artificial intelligence in education, transparency, terms of use
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
