# ChatGPT: More than a Weapon of Mass Deception, Ethical challenges and responses from the Human-Centered Artificial Intelligence (HCAI) perspective arXiv: https://arxiv.org/abs/2304.11215 ยท HTML: https://mlsanity.com/paper/2304.11215/ ## Key facts - Cited by 22 papers in the map (data through 14 Oct 2026). - Builds on 18 of its 182 references that are in the map. - First posted on arXiv 6 Apr 2023. ## Builds on (most cited first, 18 of 18) - [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018) - [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019) - [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019) - [Deep reinforcement learning from human preferences](https://mlsanity.com/paper/1706.03741/) (2017) - [DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature](https://mlsanity.com/paper/2301.11305/) (2023) - [The Forward-Forward Algorithm: Some Preliminary Investigations](https://mlsanity.com/paper/2212.13345/) (2022) - [Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy](https://mlsanity.com/paper/2002.04087/) (2020) - [Towards Making the Most of ChatGPT for Machine Translation](https://mlsanity.com/paper/2303.13780/) (2023) - [Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language Models](https://mlsanity.com/paper/2303.13809/) (2023) - [ChatGPT is not all you need. A State of the Art Review of large Generative AI models](https://mlsanity.com/paper/2301.04655/) (2023) - [GPT Takes the Bar Exam](https://mlsanity.com/paper/2212.14402/) (2022) - [ChatGPT and a New Academic Reality: Artificial Intelligence-Written Research Papers and the Ethics of the Large Language Models in Scholarly Publishing](https://mlsanity.com/paper/2303.13367/) (2023) - [Predictive Entropy Search for Multi-objective Bayesian Optimization with Constraints](https://mlsanity.com/paper/1609.01051/) (2016) - [ThoughtSource: A central hub for large language model reasoning data](https://mlsanity.com/paper/2301.11596/) (2023) - [E2S2: Encoding-Enhanced Sequence-to-Sequence Pretraining for Language Understanding and Generation](https://mlsanity.com/paper/2205.14912/) (2022) - [Parallel Predictive Entropy Search for Multi-objective Bayesian Optimization with Constraints](https://mlsanity.com/paper/2004.00601/) (2020) - [Many Objective Bayesian Optimization](https://mlsanity.com/paper/2107.04126/) (2021) - [On the independence between phenomenal consciousness and computational intelligence](https://mlsanity.com/paper/2208.02187/) (2022) ## Built on by (most cited first, 22 of 22) - [Factuality Challenges in the Era of Large Language Models](https://mlsanity.com/paper/2310.05189/) (2023) - [A Confederacy of Models: a Comprehensive Evaluation of LLMs on Creative Writing](https://mlsanity.com/paper/2310.08433/) (2023) - [Identifying and Mitigating the Security Risks of Generative AI](https://mlsanity.com/paper/2308.14840/) (2023) - [A Survey on Detection of LLMs-Generated Content](https://mlsanity.com/paper/2310.15654/) (2023) - [GenAI Against Humanity: Nefarious Applications of Generative Artificial Intelligence and Large Language Models](https://mlsanity.com/paper/2310.00737/) (2023) - [DPIC: Decoupling Prompt and Intrinsic Characteristics for LLM Generated Text Detection](https://mlsanity.com/paper/2305.12519/) (2023) - [Challenges and Remedies to Privacy and Security in AIGC: Exploring the Potential of Privacy Computing, Blockchain, and Beyond](https://mlsanity.com/paper/2306.00419/) (2023) - [Large Language Models and User Trust: Consequence of Self-Referential Learning Loop and the Deskilling of Healthcare Professionals](https://mlsanity.com/paper/2403.14691/) (2024) - [The Pursuit of Fairness in Artificial Intelligence Models: A Survey](https://mlsanity.com/paper/2403.17333/) (2024) - [Simulating H.P. Lovecraft horror literature with the ChatGPT large language model](https://mlsanity.com/paper/2305.03429/) (2023) - [Large-Language-Model-Powered Agent-Based Framework for Misinformation and Disinformation Research: Opportunities and Open Challenges](https://mlsanity.com/paper/2310.07545/) (2023) - [HULLMI: Human vs LLM identification with explainability](https://mlsanity.com/paper/2409.04808/) (2024) - [Mapping the Challenges of HCI: An Application and Evaluation of ChatGPT for Mining Insights at Scale](https://mlsanity.com/paper/2306.05036/) (2023) - [A Crowdsourced Study of ChatBot Influence in Value-Driven Decision Making Scenarios](https://mlsanity.com/paper/2511.15857/) (2025) - [Best uses of ChatGPT and Generative AI for computer science research](https://mlsanity.com/paper/2311.11175/) (2023) - [GPT, Ontology, and CAABAC: A Tripartite Personalized Access Control Model Anchored by Compliance, Context and Attribute](https://mlsanity.com/paper/2403.08264/) (2024) - [How to build trust in answers given by Generative AI for specific, and vague, financial questions](https://mlsanity.com/paper/2408.14593/) (2024) - [KERAIA: An Adaptive and Explainable Framework for Dynamic Knowledge Representation and Reasoning](https://mlsanity.com/paper/2505.04313/) (2025) - [Advances in Large Language Models for Medicine](https://mlsanity.com/paper/2509.18690/) (2025) - [Trustworthy AI Posture (TAIP): A Framework for Continuous AI Assurance of Agentic Systems at Horizontal and Vertical scale](https://mlsanity.com/paper/2603.03340/) (2026) - [The End of Trust: How Agentic AI Breaks Security Assumptions](https://mlsanity.com/paper/2605.16436/) (2026) - [The Vibe Shift in Software Engineering: Evaluating AI-Led Conversational Programming for Performance, Cognition, and Responsible Adoption](https://mlsanity.com/paper/2609.09560/) (2026) ## Abstract (arXiv) 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.