Inventing with Machines: Generative AI and the Evolving Landscape of IS Research
Published Online:21 Nov 2025https://doi.org/10.1287/isre.2025.editorial.v36.n4
References
- (2024) Pathways for design research on artificial intelligence. Inform. Systems Res. 35(2):441–459.Link, Google Scholar
- Agent4Science (2025) Open conference of AI agents for science. Retrieved September 24, https://agents4science.org.Google Scholar
- (2024) ResearchAgent: Iterative research idea generation over scientific literature with large language models. Preprint, submitted April 11, https://arxiv.org/abs/240407738.Google Scholar
- (2025) Guidelines on the Use of AI/Gen AI: Recommendations for INFORMS Journals (INFORMS, Catonsville, MD).Google Scholar
- (2024) GenAI et al. Cocreation, authorship, ownership, academic ethics and integrity in a time of generative AI. Open Prax 16(1):1–10.Crossref, Google Scholar
- (2020) Language models are few-shot learners. Adv. Neural Inform. Processing Systems, vol. 33 (Curran Associates Inc., Red Hook, NY), 1877–1901.Google Scholar
- (2025) Why do multi-agent LLM systems fail? Preprint, submitted March 17, https://arxiv.org/abs/250313657.Google Scholar
- (2025) Reasoning models don’t always say what they think. Preprint, submitted May 8, https://arxiv.org/abs/250505410.Google Scholar
- (2023) Improving factuality and reasoning in language models through multiagent debate. Preprint, submitted May 23, https://arxiv.org/abs/2305.14325.Google Scholar
- (2024) From local to global: A graph RAG approach to query-focused summarization. Preprint, submitted April 24, https://arxiv.org/abs/240416130.Google Scholar
- (2023) Pal: Program-aided language models. Proc. Internat. Conf. Machine Learn. (PMLR, New York), 10764–10799.Google Scholar
- (2024) Large language model based multi-agents: A survey of progress and challenges. Preprint, submitted January 21, https://arxiv.org/abs/240201680.Google Scholar
- (2023) MetaGPT: Meta programming for a multi-agent collaborative framework. Preprint, submitted August 1, https://arxiv.org/abs/2308.00352.Google Scholar
- (2022) Lora: Low-rank adaptation of large language models. Proc. Internat. Conf. Learn. Representation 1(2):3.Google Scholar
- (2020) Leveraging passage retrieval with generative models for open domain question answering. Preprint, submitted July 2, https://arxiv.org/abs/200701282.Google Scholar
- (2023) Survey of hallucination in natural language generation. ACM Comput. Survey 55(12):1–38.Crossref, Google Scholar
- (2020) Dense passage retrieval for open-domain question answering. Proc. Conf. Empirical Methods Natural Language Processing (Association for Computational Linguistics, Stroudsburg, PA), 6769–6781.Google Scholar
- (2025) The ITEM ontology: A tool to elucidate the anatomy of psychometric indicators. Inform. Systems Res., ePub ahead of print August 13, https://doi.org/10.1287/isre.2023.0257.Google Scholar
- (2025) Goedel-prover: A frontier model for open-source automated theorem proving. Preprint, submitted February 11, https://arxiv.org/abs/250207640.Google Scholar
- (2025) Walk the talk? Measuring the faithfulness of large language model explanations. Preprint, submitted April 19, https://arxiv.org/abs/250414150.Google Scholar
- (2020) On faithfulness and factuality in abstractive summarization. Proc. 58th Annual Meeting Assoc. Comput. Linguist. (Association for Computational Linguistics, Stroudsburg, PA).Google Scholar
- (2023) The debate over understanding in AI’s large language models. Proc. Natl. Acad. Sci. USA 120(13):e2215907120.Crossref, Google Scholar
- (2025) AI is transforming peer review—And many scientists are worried. Nature 639(8056):852–854.Crossref, Google Scholar
- (2021) WebGPT: Browser-assisted question-answering with human feedback. Preprint, submitted December 17, https://arxiv.org/abs/211209332.Google Scholar
- (2022) Training language models to follow instructions with human feedback. Adv. Neural Inform. Processing Systems (Curran Associates Inc., Red Hook, NY), 27730–27744.Google Scholar
- (2023) Generative agents: Interactive simulacra of human behavior. Proc. 36th Annual ACM Sympos. User Interface Software Tech (UIST '23) (Association for Computing Machinery (ACM), New York), 1–22.Google Scholar
- (2025) The benefits and dangers of anthropomorphic conversational agents. Proc. Natl. Acad. Sci. USA 122(22):e2415898122.Crossref, Google Scholar
- (2023) Direct preference optimization: Your language model is secretly a reward model. Preprint, submitted May 29, https://arxiv.org/abs/2305.18290.Google Scholar
- (2024) Conceptualizing generative AI as style engines: Application archetypes and implications. Internat. J. Inform. Management 79(C):102824.Google Scholar
- (2019) The sociotechnical axis of cohesion for the IS discipline: Its historical legacy and its continued relevance. MIS Quart. 43(3):695–720.Crossref, Google Scholar
- (2023) Toolformer: Language models can teach themselves to use tools. Adv. Neural Inform. Processing Systems, vol. 36 (Curran Associates Inc., Red Hook, NY), 68539–68551.Google Scholar
- (2023) Reflexion: Language agents with verbal reinforcement learning. Preprint, submitted March 20, https://arxiv.org/abs/2303.11366.Google Scholar
- (2022) Blenderbot 3: A deployed conversational agent that continually learns to responsibly engage. Preprint, submitted August 5, https://arxiv.org/abs/220803188.Google Scholar
- (2024) Testing theory of mind in large language models and humans. Nature Human Behav. 8(7):1285–1295.Crossref, Google Scholar
- (2023) The Janus effect of generative AI: Charting the path for responsible conduct of scholarly activities in information systems. Inform. Systems Res. 34(2):399–408.Link, Google Scholar
- (2022) Lamda: Language models for dialog applications. Preprint, submitted January 20, https://arxiv.org/abs/220108239.Google Scholar
- (2017) Attention is all you need. Preprint, submitted June 12, https://arxiv.org/abs/1706.03762.Google Scholar
- (2023) Fabrication and errors in the bibliographic citations generated by ChatGPT. Sci. Rep. 13(1):14045.Crossref, Google Scholar
- (2023) Voyager: An open-ended embodied agent with large language models. Preprint, submitted May 25, https://arxiv.org/abs/230516291.Google Scholar
- (2022a) Finetuned language models are zero-shot learners. Internat. Conf. Learn. Representation (ICLR 2022) (OpenReview).Google Scholar
- (2022b) Chain-of-thought prompting elicits reasoning in large language models. Adv. Neural Inform. Processing Systems, vol. 35 (Curran Associates Inc., Red Hook, NY), 24824–24837.Google Scholar
- (2025) From AI for science to agentic science: A survey on autonomous scientific discovery. Preprint, submitted August 18, https://arxiv.org/abs/250814111.Google Scholar
- (2025) Agentic reasoning: A streamlined framework for enhancing LLM reasoning with agentic tools. Proc. 63rd Annual Meeting Assoc. Comput. Linguist. (Association for Computational Linguistics, Stroudsburg, PA).Google Scholar
- (2024) Autogen: Enabling next-gen LLM applications via multi-agent conversations. First Conf. Language Modeling (COLM 2024) (OpenReview).Google Scholar
- (2024) Hallucination is inevitable: An innate limitation of large language models. Preprint, submitted January 22, https://arxiv.org/abs/240111817.Google Scholar
- (2024) SWE-agent: Agent-computer interfaces enable automated software engineering. Adv. Neural Inform. Processing Systems, vol. 37 (Curran Associates Inc., Red Hook, NY), 50528–50652.Google Scholar
- (2022) Webshop: Towards scalable real-world web interaction with grounded language agents. Adv. Neural Inform. Processing Systems, vol. 35 (Curran Associates Inc., Red Hook, NY), 20744–20757.Google Scholar
- (2023) React: Synergizing reasoning and acting in language models. 11th Internat. Conf. Learn. Representation (ICLR 2023) (OpenReview).Google Scholar
- (2025) A next-generation open access ecosystem for scientific discovery generated by AI scientists. Preprint, submitted August 20, https://arxiv.org/abs/250815126.Google Scholar
- (2025) MultiAgentBench: Evaluating the collaboration and competition of LLM agents. Preprint, submitted March 3, https://arxiv.org/abs/250301935.Google Scholar
- (2025) Large language models for automated scholarly paper review: A survey. Preprint, submitted January 17, https://arxiv.org/abs/2501.10326.Google Scholar
- (2019) Fine-tuning language models from human preferences. Preprint, submitted September 18, https://arxiv.org/abs/190908593.Google Scholar

