mlsanityData to 14 Oct 2026

Deceptive AI Ecosystems: The Case of ChatGPT

arXiv 2306.13671 ↗First posted 18 Jun 2023cs.CY cs.AI cs.HCcited by 7

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Abstract (arXiv)

ChatGPT, an AI chatbot, has gained popularity for its capability in generating human-like responses. However, this feature carries several risks, most notably due to its deceptive behaviour such as offering users misleading or fabricated information that could further cause ethical issues. To better understand the impact of ChatGPT on our social, cultural, economic, and political interactions, it is crucial to investigate how ChatGPT operates in the real world where various societal pressures influence its development and deployment. This paper emphasizes the need to study ChatGPT "in the wild", as part of the ecosystem it is embedded in, with a strong focus on user involvement. We examine the ethical challenges stemming from ChatGPT's deceptive human-like interactions and propose a roadmap for developing more transparent and trustworthy chatbots. Central to our approach is the importance of proactive risk assessment and user participation in shaping the future of chatbot technology.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 20 of its 81 references that are in the map. First posted on arXiv 18 Jun 2023.

Builds on

20 of 81 references.

References · 20

  1. 2022Training language models to follow instructions with human feedbackcited by 15,971
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  4. 2021What Makes Good In-Context Examples for GPT-3?cited by 1,195
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8 more
  1. 2018From Eliza to XiaoIce: Challenges and Opportunities with Social Chatbotscited by 85
  2. 2020The Radicalization Risks of GPT-3 and Advanced Neural Language Modelscited by 76
  3. 2022A Literature Survey of Recent Advances in Chatbotscited by 26
  4. 2021Exploring Interactions Between Trust, Anthropomorphism, and Relationship Development in Voice Assistantscited by 10
  5. 2019What's in an accent? The impact of accented synthetic speech on lexical choice in human-machine dialoguecited by 4
  6. 2021When is it permissible for artificial intelligence to lie? A trust-based approachcited by 2
  7. 2022When It's Not Worth the Paper It's Written On: A Provocation on the Certification of Skills in the Alexa and Google Assistant Ecosystemscited by 2
  8. 2022Can you meaningfully consent in eight seconds? Identifying Ethical Issues with Verbal Consent for Voice Assistantscited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 4; 2025: 1; 2026: 1.

7 papers.

  1. 2024AI Hallucinations: A Misnomer Worth Clarifyingcited by 34
  2. 2024Mapping the Ethics of Generative AI: A Comprehensive Scoping Reviewcited by 19
  3. 2023User Experience Design Professionals' Perceptions of Generative Artificial Intelligencecited by 16
  4. 2025SusBench: An Online Benchmark for Evaluating Dark Pattern Susceptibility of Computer-Use Agentscited by 8
  5. 2026Social physics in the age of artificial intelligencecited by 5
  6. 2024On the Ethical Considerations of Generative Agentscited by 4
  7. 2024Unmasking the Shadows of AI: Investigating Deceptive Capabilities in Large Language Modelscited by 2