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Pitfalls (and advantages) of sophisticated large language models
7 references·1 citing·28 second hop
Pitfalls (and advantages) of sophisticated large language models (2024)Pitfalls (and advantages) of sophisticate…Comparing scientific abstracts generated by ChatGPT to real abstracts with detectors and blinded human reviewers (2023)Comparing scientific abstract…ChatGPT is fun, but not an author (2023)ChatGPT is fun, but not an au…Using deceased people’s personal data (2022)Using deceased people’s perso…Talking About Large Language Models (2022)Talking About Large Language …Could AI help you to write your next paper? (2022)Could AI help you to write yo…Ethical and social risks of harm from Language Models (2021)Ethical and social risks of h…Embodied artificial agents for understanding human social cognition (2016)Embodied artificial agents fo…Imitation and Large Language Models (2024)Imitation and Large Language …The Intentional Stance (1987)Action recognition in the premotor cortex (1996)THE MIRROR-NEURON SYSTEM (2004)From social brains to social robots: applying neurocognitive insights to human–robot interaction (2019)Social Cognition in the Age of Human–Robot Interaction (2020)Perception and Evaluation in Human–Robot Interaction: The Human–Robot Interaction Evaluation Scale (HRIES)—A Multicomponent Approach of Anthropomorphism (2021)On Human Dignity as a Foundation for the Right to Privacy (2016)The Political Economy of Death in the Age of Information: A Critical Approach to the Digital Afterlife Industry (2017)The Oxford Handbook of Cyberpsychology (2018)Digital remains and post-mortem privacy in the UK: what do users want? (2025)Abstracts written by ChatGPT fool scientists (2023)Evaluating the efficacy of AI content detection tools in differentiating between human and AI-generated text (2023)Testing of detection tools for AI-generated text (2023)Tools such as ChatGPT threaten transparent science; here are our ground rules for their use (2023)I.—COMPUTING MACHINERY AND INTELLIGENCE (1950)Minds, brains, and programs (1980)Metaphors We Live By (2003)The Fallacy of AI Functionality (2022)Co-Writing with Opinionated Language Models Affects Users’ Views (2023)The Opportunities and Risks of Large Language Models in Mental Health (2024)Academic Integrity considerations of AI Large Language Models in the post-pandemic era: ChatGPT and beyond (2023)Artificial intelligence in scientific writing: a friend or a foe? (2023)The false positives and false negatives of generative AI detection tools in education and academic research: The case of ChatGPT (2023)Current cases of AI misalignment and their implications for future risks (2023)The Emerging Social Status of Generative AI: Vocabularies of AI Competence in Public Discourse (2023)Large models of what? Mistaking engineering achievements for human linguistic agency (2024)ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope (2023)Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy (2023)
this work references cited by second hop

References

  • 2023ChatGPT is fun, but not an author1,433 cited
  • 2023Comparing scientific abstracts generated by ChatGPT to real abstracts with detectors and blinded human reviewers1,097 cited
  • 2021Ethical and social risks of harm from Language Models477 cited
  • 2022Could AI help you to write your next paper?226 cited
  • 2016Embodied artificial agents for understanding human social cognition176 cited
  • 2022Talking About Large Language Models68 cited
  • 2022Using deceased people’s personal data19 cited

Cited by

  • 2024Imitation and Large Language Models6 cited

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