# Scientists' Perspectives on the Potential for Generative AI in their Fields

arXiv: https://arxiv.org/abs/2304.01420 · HTML: https://mlsanity.com/paper/2304.01420/

## Key facts

- Cited by 22 papers in the map (data through 14 Oct 2026).
- Builds on 29 of its 58 references that are in the map.
- First posted on arXiv 4 Apr 2023.

## Builds on (most cited first, 29 of 29)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Evaluating Large Language Models Trained on Code](https://mlsanity.com/paper/2107.03374/) (2021)
- [Hierarchical Text-Conditional Image Generation with CLIP Latents](https://mlsanity.com/paper/2204.06125/) (2022)
- [Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding](https://mlsanity.com/paper/2205.11487/) (2022)
- [PaLM: Scaling Language Modeling with Pathways](https://mlsanity.com/paper/2204.02311/) (2022)
- [On the Opportunities and Risks of Foundation Models](https://mlsanity.com/paper/2108.07258/) (2021)
- [Sparks of Artificial General Intelligence: Early experiments with GPT-4](https://mlsanity.com/paper/2303.12712/) (2023)
- [Imagen Video: High Definition Video Generation with Diffusion Models](https://mlsanity.com/paper/2210.02303/) (2022)
- [Solving Quantitative Reasoning Problems with Language Models](https://mlsanity.com/paper/2206.14858/) (2022)
- [Scaling Autoregressive Models for Content-Rich Text-to-Image Generation](https://mlsanity.com/paper/2206.10789/) (2022)
- [LaMDA: Language Models for Dialog Applications](https://mlsanity.com/paper/2201.08239/) (2022)
- [Ethical and social risks of harm from Language Models](https://mlsanity.com/paper/2112.04359/) (2021)
- [Galactica: A Large Language Model for Science](https://mlsanity.com/paper/2211.09085/) (2022)
- [AudioLM: a Language Modeling Approach to Audio Generation](https://mlsanity.com/paper/2209.03143/) (2022)
- [Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studies](https://mlsanity.com/paper/2208.10264/) (2022)
- [Phenaki: Variable Length Video Generation From Open Domain Textual Description](https://mlsanity.com/paper/2210.02399/) (2022)
- [CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning](https://mlsanity.com/paper/1711.05225/) (2017)
- [MusicLM: Generating Music From Text](https://mlsanity.com/paper/2301.11325/) (2023)
- [ClimaX: A foundation model for weather and climate](https://mlsanity.com/paper/2301.10343/) (2023)
- [On the Origin of Hallucinations in Conversational Models: Is it the Datasets or the Models?](https://mlsanity.com/paper/2204.07931/) (2022)
- [Hierarchical Generative Modeling for Controllable Speech Synthesis](https://mlsanity.com/paper/1810.07217/) (2018)
- [Reading Between the Lines: Modeling User Behavior and Costs in AI-Assisted Programming](https://mlsanity.com/paper/2210.14306/) (2022)
- [A deep active learning system for species identification and counting in camera trap images](https://mlsanity.com/paper/1910.09716/) (2019)
- [The Prompt Artists](https://mlsanity.com/paper/2303.12253/) (2023)
- [PrefixRL: Optimization of Parallel Prefix Circuits using Deep Reinforcement Learning](https://mlsanity.com/paper/2205.07000/) (2022)
- [A Word is Worth a Thousand Pictures: Prompts as AI Design Material](https://mlsanity.com/paper/2303.12647/) (2023)
- [A Deep Learning Approach for Characterizing Major Galaxy Mergers](https://mlsanity.com/paper/2102.05182/) (2021)
- [Identifying Exoplanets with Machine Learning Methods: A Preliminary Study](https://mlsanity.com/paper/2204.00721/) (2022)

## Built on by (most cited first, 22 of 22)

- [Levels of AGI for Operationalizing Progress on the Path to AGI](https://mlsanity.com/paper/2311.02462/) (2023)
- [LLMs as Research Tools: A Large Scale Survey of Researchers' Usage and Perceptions](https://mlsanity.com/paper/2411.05025/) (2024)
- [Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning](https://mlsanity.com/paper/2502.02871/) (2025)
- [Interactive AI Alignment: Specification, Process, and Evaluation Alignment](https://mlsanity.com/paper/2311.00710/) (2023)
- [Generative Ghosts: Anticipating Benefits and Risks of AI Afterlives](https://mlsanity.com/paper/2402.01662/) (2024)
- [The Impact and Opportunities of Generative AI in Fact-Checking](https://mlsanity.com/paper/2405.15985/) (2024)
- [From Hypothesis to Publication: A Comprehensive Survey of AI-Driven Research Support Systems](https://mlsanity.com/paper/2503.01424/) (2025)
- [Language Models as Critical Thinking Tools: A Case Study of Philosophers](https://mlsanity.com/paper/2404.04516/) (2024)
- [Toward Reliable Ad-hoc Scientific Information Extraction: A Case Study on Two Materials Datasets](https://mlsanity.com/paper/2406.05348/) (2024)
- [Generative AI Uses and Risks for Knowledge Workers in a Science Organization](https://mlsanity.com/paper/2501.16577/) (2025)
- [AI and Generative AI for Research Discovery and Summarization](https://mlsanity.com/paper/2401.06795/) (2024)
- [Towards AI-assisted Academic Writing](https://mlsanity.com/paper/2503.13771/) (2025)
- [Synthetic Heuristic Evaluation: A Comparison between AI- and Human-Powered Usability Evaluation](https://mlsanity.com/paper/2507.02306/) (2025)
- [The whack-a-mole governance challenge for AI-enabled synthetic biology: literature review and emerging frameworks](https://mlsanity.com/paper/2402.00312/) (2024)
- [New contexts, old heuristics: How young people in India and the US trust online content in the age of generative AI](https://mlsanity.com/paper/2405.02522/) (2024)
- [Beyond the Desk: Barriers and Future Opportunities for AI to Assist Scientists in Embodied Physical Tasks](https://mlsanity.com/paper/2603.19504/) (2026)
- [AI empowering research: 10 ways how science can benefit from AI](https://mlsanity.com/paper/2307.10265/) (2023)
- [Deconstructing Jazz Piano Style Using Machine Learning](https://mlsanity.com/paper/2504.05009/) (2025)
- [PaperTok: Exploring the Use of Generative AI for Creating Short-form Videos for Research Communication](https://mlsanity.com/paper/2601.18218/) (2026)
- [How Researchers Navigate Accountability, Transparency, and Trust When Using AI Tools in Early-Stage Research: A Think-Aloud Study](https://mlsanity.com/paper/2604.23136/) (2026)
- [Will Scaling Improve Social Simulation with LLMs?](https://mlsanity.com/paper/2607.02464/) (2026)
- [Advances in Machine Learning for Directed Evolution: A Five-Year Retrospective](https://mlsanity.com/paper/2609.03046/) (2026)

## Abstract (arXiv)

Generative AI models, including large language models and multimodal models that include text and other media, are on the cusp of transforming many aspects of modern life, including entertainment, education, civic life, the arts, and a range of professions. There is potential for Generative AI to have a substantive impact on the methods and pace of discovery for a range of scientific disciplines. We interviewed twenty scientists from a range of fields (including the physical, life, and social sciences) to gain insight into whether or how Generative AI technologies might add value to the practice of their respective disciplines, including not only ways in which AI might accelerate scientific discovery (i.e., research), but also other aspects of their profession, including the education of future scholars and the communication of scientific findings. In addition to identifying opportunities for Generative AI to augment scientists' current practices, we also asked participants to reflect on concerns about AI. These findings can help guide the responsible development of models and interfaces for scientific education, inquiry, and communication.