AI for Research

References

References from every section of this guide in one place.

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• Artificial Intelligence: A Reading List. (2024) House of Commons Library.
• Australian National University. (2023). Chat GPT and other generative AI tools: What ANU academics need to know.
• Aylsworth, T., Castro, C. (2024). Should I Use ChatGPT to Write My Papers? Philosophy & Technology, vol. 37, article 117
• Bailey, J. (2023). One Way AI Has Changed Plagiarism. Plagiarism Today.
• Balloccu, S., Schmidtová, P., Lango, M., Dusek, O. (2024). Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMs. In Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers), pages 67–93, St. Julian’s, Malta. Association for Computational Linguistics
• Bender, E.M, Gebru, T., McMillan-Major, A., Shmitchell, Sh. (2021). On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?  In: Conference on Fairness, Accountability, and Transparency (FAccT ’21), March 3–10, 2021, Virtual Event, Canada. ACM, New York, NY, USA.
• Bergstrom, C. T., West, J. D. (2025). Modern-Day Oracles or Bullshit Machines? How to thrive is a ChatGPT world. Online course.
• Birhane, A., Han, S., Boddeti, V., & Luccioni, S. (2024). Into the LAIONs Den: Investigating Hate in Multimodal Datasets. Advances in Neural Information Processing Systems, 36.
• Braun, M., Vallery, A., Benizri, I. (2024). Obligations for Deployers, Providers, Importers and Distributors of High-Risk AI Systems in the European Union’s Artificial Intelligence Act. Wilmerhale Blog.
• Bsharat, S. M., Myrzakhan, A., Shen, Z. (2023). Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4.  arXiv:2312.16171.
• Bullwinkel, B., Minnich, A., Chawla, S., Lopez, G., Pouliot, M., Maxwell, W., … Russinovich, M. (2025). Lessons from red teaming 100 generative AI products. arXiv:2501.07238
• Capasso, M., Arora, P., Sharma, D., & Tacconi, C. (2025). On the Right to Work in the Age of Artificial Intelligence: Ethical Safeguards in Algorithmic Human Resource Management. Business and Human Rights Journal, 1–15.
• Cardon, P., Fleischmann, C., Aritz, J., Logemann, M., & Heidewald, J. (2023). The Challenges and Opportunities of AI-Assisted Writing: Developing AI Literacy for the AI Age. Business and Professional Communication Quarterly, 86(3), 257-295.
• Caulfield., J. (2023). ChatGPT Citations | Formats & Examples. Scribbr.
• Chang, K., Cramer, M., Soni, S., Bamman, D. (2023). Speak, Memory: An Archaeology of Books Known to ChatGPT/GPT-4. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 7312–7327, Singapore. Association for Computational Linguistics.
• Chesterman, S. 2024. Good Models Borrow, Great Models Steal: Intellectual Property Rights and Generative AI. Policy and Society.
• Dereza, O. (2024). AI and Libraries 4: Demystifying AI for Researchers. The HardiBlog.
• Digital Promise (2024). AI literacy: a framework to understand, evaluate, and use emerging technology [Executive Summary], Washington, D.C.
• Dodge, J., Prewitt, T., Tachet des Combes, R., Odmark, E., Schwartz, R., Strubell, E., ... & Buchanan, W. (2022). Measuring the carbon intensity of AI in cloud instances. In Proceedings of the 2022 ACM conference on fairness, accountability, and transparency (pp. 1877-1894).
• Dornis, T. W., Stober, S. (2024). Copyright and training of generative AI models — technological and legal foundations. SSRN.
• Edwards, B. (2023). Why ChatGPT and Bing Chat are so good at making things up. Ars Technica.
• Estes, A. C. (2024). What, if anything, is AI search good for? Vox.
• European Innovation Council and SMEs Executive Agency. (2024). Artificial intelligence and copyright: use of generative AI tools to develop new content. European Commission News Blog.
• Falconer, S. (2023). Privacy in the age of generative AI. StackOverflow Blog.
• Falk, S., Ekchajzer, D., Pirson, T., Lees-Perasso, E., Wattiez, A., Biber-Freudenberger, L., ... & van Wynsberghe, A. (2025). More than Carbon: Cradle-to-Grave environmental impacts of GenAI training on the Nvidia A100 GPU. arXiv:2509.00093.
• Goff, L., Dennehy, T. (2025). Toolkit for the Ethical Use of GenAI in Learning and Teaching. University College Cork.
• Gumaan, E. A. (2024). Transformers (Community Article). HuggingFace. 
• Hacker, P. (2024). The real existential threat of AI. OUPblog. Oxford University Press.
• Hao, K. (2024). Microsoft’s Hypocrisy on AI. The Atlantic.
• Harding, X. (2023). The Internet’s Invisible Carbon Footprint. Mozilla Blog.
• Hatakeyama-Sato, K., Yamane, N., Igarashi, Y., Nabae, Y., & Hayakawa, T. (2023). Prompt engineering of GPT-4 for chemical research: what can/cannot be done? Science and Technology of Advanced Materials: Methods, 3(1).
• Heikkilä, M. (2023). Three ways AI chatbots are a security disaster. MIT Technology Review.
• Henrickson, L., & Meroño-Peñuela, A. (2023). Prompting meaning: a hermeneutic approach to optimising prompt engineering with ChatGPT. AI & Society.
• Hicks, M. T., Humphries, J., Slater, J. (2024). ChatGPT is bullshit. Ethics and Information Technology, Volume 26.
• How do I cite generative AI in MLA style? (2023). MLA Style Centre.
• Jernite, Y., Nguyen, H., Biderman, S., Rogers, A., Masoud, M., Danchev, V., ... & Mitchell, M. (2022, June). Data governance in the age of large-scale data-driven language technology. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (pp. 2206-2222).
• Ji, J., Jun, J., Wu, M., Gelles, R. (2024). Cybersecurity Risks of AI-Generated Code. [Report]. Center for Security and Emerging Technology.
• Kalai, A. T., Nachum, O., Vempala, S. S., & Zhang, E. (2025). Why language models hallucinate. arXiv:2509.04664
• Kardys, D. (2024). Demystifying AI: Going Beyond the Hype. Diagram Views.
• Klosek, K. & Blumenthal, M. (2024). Training Generative AI Models on Copyrighted Works Is Fair Use. Association of Research Libraries Blog.
• Koerner, K. (2023). Generative AI: Privacy and tech perspectives. International Association of Privacy Professionals.
• Kreuz, R. J. (2024). Plagiarism is not always easy to define or detect. The Conversation.
• Lee, H., Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R., Wilson, N. (2025). The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers. Proceedings of the ACM CHI Conference on Human Factors in Computing Systems.
• Leo S. Lo. (2023). The CLEAR path: A framework for enhancing information literacy through prompt engineering. The Journal of Academic Librarianship, Volume 49 (4).
• Lin, Z., Tao, J., Yuan, Y., & Yao, A. C. C. (2025). Existing LLMs Are Not Self-Consistent For Simple Tasks. arXiv:2506.18781
• Liu, J. Z., Li, X. (2024). How do judges use large language models? Evidence from Shenzhen, Journal of Legal Analysis, Volume 16, Issue 1, Pages 235–262
• Lo, L. S. (2023). The Art and Science of Prompt Engineering: A New Literacy in the Information Age. Internet Reference Services Quarterly, 27(4), 203–210.  
• Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1–16).
• Luccioni, S., Akiki, C., Mitchell, M., & Jernite, Y. (2024). Stable bias: Evaluating societal representations in diffusion models. Advances in Neural Information Processing Systems, 36.
• Luccioni, A. S., Hernandez-Garcia, A. (2023). Counting carbon: A survey of factors influencing the emissions of machine learning. arXiv:2302.08476.
• Luccioni, S., Jernite, Y., & Strubell, E. (2024). Power hungry processing: Watts driving the cost of AI deployment? In The 2024 ACM Conference on Fairness, Accountability, and Transparency (pp. 85-99)
• Maleki, N., Padmanabhan, B., & Dutta, K. (2024). AI Hallucination: A Misnomer worth clarifying. arXiv:2401.06796.
• Man, S. (2025). How AI-Generated Code Is Unleashing A Tsunami Of Security Risks. Forbes.
• Marcus, G., Southen, R. (2024). Generative AI Has a Visual Plagiarism Problem. IEEE Spectrum.
• Marsh, O. (2024).  Chatbots are still spreading falsehoods. Algorithm Watch.
• McAdoo, T. (2023). How to cite ChatGPT. APA Style.
• Meehan, S. R. (2023). When AI Is Writing, Who Is the Author? Inside Higher Ed.
• Messeri, L., Crockett, M.J. (2024). Artificial intelligence and illusions of understanding in scientific research. Nature 627, pp. 49–58.
• Milmo, D., Hern, A. (2024). What will the EU’s proposed act to regulate AI mean for consumers? The Guardian.
• Nehring, J., Gabryszak, A., Jürgens, P., Burchardt, A., Schaffer, S., Spielkamp, M., Stark, B. (2024). Large Language Models Are Echo Chambers. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pp. 10117–10123, Torino, Italia. ELRA and ICCL.
• O'Brien, I. (2024). Data center emissions probably 662% higher than big tech claims. Can it keep up the ruse? The Guardian.
• Perry, N., Srivastava, M., Kumar, D., Boneh, D. (2023). Do Users Write More Insecure Code with AI Assistants? arXiv:2211.03622
• Rahman-Jones, I. (2024). AI drives 48% increase in Google emissions. BBC.
• Rebelo, M. (2023). How to write effective AI art prompts. Zapier.com
• Recommended citation method for ChatGPT. Q&A: Citation. Documentation of Sources. The Chicago Manual of Style.
• Recommended citation method for DALL-E. Q&A: Citation. Documentation of Sources. The Chicago Manual of Style.
• Riedl, M. (2023). A Very Gentle Introduction to Large Language Models without the Hype. Medium.
• Rogers, A., Luccioni, A. S. (2024). Position: Key Claims in LLM Research Have a Long Tail of Footnotes. In Forty-first International Conference on Machine Learning.
• Rose, D. (2023). Generative AI vs.Traditional AI. [Video] LinkedIn Learning.
• Ruschemeier, H. (2025). Generative AI and data protection. Cambridge Forum on AI: Law and Governance, 1, e6.
• Saenko, K. (2023). Is generative AI bad for the environment? A computer scientist explains the carbon footprint of ChatGPT and its cousins. The Conversation.
• Salvaggio, E. (2024). Challenging The Myths of Generative AI. Tech Policy Press.
• Schwamm, H. (2023). Navigating the AI Landscape in Research. Blog for the University of Galway Library.
• Shaw, D. (2025). The digital erosion of intellectual integrity: why misuse of generative AI is worse than plagiarism. AI & Society. Springer Nature Link.
• Silveira, L. (2024). The Fall of Z-Library: The “Burning of the Library of Alexandria” or Protection for Authors Against AI Companies, 27 SMU Sci. & Tech. L. Rev. 119
• Singh, M. (2023). As the AI industry booms, what toll will it take on the environment? The Guardian.
• Slattery, P., Saeri, A. K., Grundy, E. A., Graham, J., Noetel, M., Uuk, R., ... & Thompson, N. (2024). The AI Risk Repository: A Comprehensive Meta-Review, Database, and Taxonomy of Risks From Artificial Intelligence. arXiv:2408.12622.
• Thais, S. (2024). Misrepresented Technological Solutions in Imagined Futures: The Origins and Dangers of AI Hype in the Research Community. arXiv:2408.15244.
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• Varoquaux, G., Luccioni, A. S., Whittaker, M. (2024). Hype, Sustainability, and the Price of the Bigger-is-Better Paradigm in AI. arXiv:2409.14160
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• When AI Gets It Wrong: Addressing AI Hallucinations and Bias. MIT Sloan Teaching & Learning Technologies.
• Wierda, G. (2024). When ChatGPT summarises, it actually does nothing of the kind. R&A IT Strategy & Architecture.
• Yin, Z., Sun, Q., Guo, Q., Wu, J., Qiu, X., Huang, X. (2023). Do Large Language Models Know What They Don’t Know? In Findings of the Association for Computational Linguistics: ACL 2023, pages 8653–8665, Toronto, Canada. Association for Computational Linguistics.
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