Content revision ea31a3343577b30cee4337cf2fef2b0864a5741341f27598e9108766c486fb2d 15 matching sources. Offset 0. Limit 20. ## How AI changes the course of writing How AI changes the course of writing Source ID research-ai-writing-interview:overview Section research Original https://www.henryw.me/#/research/ai-writing-interview Read https://ask-henry.whenry6688.workers.dev/agent/sources/research-ai-writing-interview%3Aoverview?format=text Journalist and editor Tequia Burt interviewed me for a book she is reporting on what writers bring to their work when AI can produce fluent prose. She had read my paper, Early Epistemic Settlement in AI-Assisted Writing , and was interested in how a useful answer might change the inquiry through which a writer develops an argument. ## How did you arrive at the concept of early epistemic settlement? Was there a particular writing experience or limitation in the existing research that led you to it? How AI changes the course of writing Source ID research-ai-writing-interview:origins Section research Original https://www.henryw.me/#/research/ai-writing-interview#origins Read https://ask-henry.whenry6688.workers.dev/agent/sources/research-ai-writing-interview%3Aorigins?format=text Henry Wang I started from a fairly simple observation about what AI changes in writing. Writing has often been treated as part of thinking, not just a way of recording thought after the thinking is finished. Menary's Writing as Thinking captures this well (Menary, 2007). ## In professional writing, how might an AI response shape the direction of an inquiry even when the writer understands the response and continues thinking productively? Could you walk me through an example of the questions, connections, or alternative frames that might become less likely to emerge? How AI changes the course of writing Source ID research-ai-writing-interview:professional-writing Section research Original https://www.henryw.me/#/research/ai-writing-interview#professional-writing Read https://ask-henry.whenry6688.workers.dev/agent/sources/research-ai-writing-interview%3Aprofessional-writing?format=text Henry Wang Imagine a journalist has two interviews about hybrid work. One person says they are more productive at home because they can concentrate. Another says their team became less productive because coordination became harder. The journalist has not yet worked out what to do with those two observations. AI gives her a clean frame: hybrid work involves a trade-off between individual focus and team collaboration. ## What determines whether an AI suggestion settles an inquiry too early or becomes useful material the writer actively works through? How much depends on timing, the writer’s expertise, or the nature of the task? How AI changes the course of writing Source ID research-ai-writing-interview:timing-and-expertise Section research Original https://www.henryw.me/#/research/ai-writing-interview#timing-and-expertise Read https://ask-henry.whenry6688.workers.dev/agent/sources/research-ai-writing-interview%3Atiming-and-expertise?format=text Henry Wang I think this depends on what the writer is doing at the moment the suggestion arrives. Timing matters. If I already understand a relation and just cannot phrase it well, AI may be helping me say something I already know. If trying to write the sentence is how I am still figuring out the relation, the same answer can do something quite different. Expertise probably matters too. ## Editors and other collaborators can also provide a solution before a writer has completed the underlying thinking. What makes language models different, beyond the speed and frequency with which they can intervene? How AI changes the course of writing Source ID research-ai-writing-interview:models-and-collaborators Section research Original https://www.henryw.me/#/research/ai-writing-interview#models-and-collaborators Read https://ask-henry.whenry6688.workers.dev/agent/sources/research-ai-writing-interview%3Amodels-and-collaborators?format=text Henry Wang What seems different to me is how much independent structure tends to enter the exchange. When another person works with my material, they are processing it through their own understanding. In the hybrid-work example, an editor might notice that one interviewee's work depends much more heavily on coordination than the other's. ## What would an empirical study need to observe or capture to test this framework? How might researchers distinguish an avenue of inquiry that was foreclosed from one the writer simply considered and rejected? How AI changes the course of writing Source ID research-ai-writing-interview:studying-inquiry Section research Original https://www.henryw.me/#/research/ai-writing-interview#studying-inquiry Read https://ask-henry.whenry6688.workers.dev/agent/sources/research-ai-writing-interview%3Astudying-inquiry?format=text Henry Wang I'm still working this one out. I think there are two different questions hiding inside it. One is whether early settlement happened. The other is whether it was a bad trade. The first seems more straightforward to study. You could follow what a writer was doing immediately before and after assistance arrived. What were they trying to work out? Which notes or sources were they using? ## Are there practices that could help writers use AI without bypassing the work that expands what they are able to question, defend, or develop? How AI changes the course of writing Source ID research-ai-writing-interview:designing-assistance Section research Original https://www.henryw.me/#/research/ai-writing-interview#designing-assistance Read https://ask-henry.whenry6688.workers.dev/agent/sources/research-ai-writing-interview%3Adesigning-assistance?format=text Henry Wang I think there are two separate parts of the interaction that matter here. One is what the AI contributes. If I am stuck between two ideas, it can give me the connection needed to move forward. But it could also surface other relations around the problem that are not necessary for solving the immediate difficulty and might open up other directions. The other is how that contribution is presented. ## References How AI changes the course of writing Source ID research-ai-writing-interview:references Section research Original https://www.henryw.me/#/research/ai-writing-interview#references Read https://ask-henry.whenry6688.workers.dev/agent/sources/research-ai-writing-interview%3Areferences?format=text Danry, V., Pataranutaporn, P., Mao, Y., & Maes, P. (2023). Don’t just tell me, ask me: AI systems that intelligently frame explanations as questions improve human logical discernment accuracy over causal AI explanations. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 1–13. Read paper Doshi, A. R., & Hauser, O. P. (2024). ## Research I've Been Part Of Research Source ID research:overview Section research Original https://www.henryw.me/#/research Read https://ask-henry.whenry6688.workers.dev/agent/sources/research%3Aoverview?format=text I study how people and AI systems learn from experience, represent knowledge and use it to think and act. As AI becomes part of everyday thinking, I investigate how it shapes the understanding, judgement and abilities people develop. I study how people learn from experience and use what they know. ## The Resolving Power of Transfer Experiments: When Can Designs Distinguish Accounts of Generalization? Research Source ID research:transfer Section research Original https://www.henryw.me/#/research#transfer Read https://ask-henry.whenry6688.workers.dev/agent/sources/research%3Atransfer?format=text We developed a framework that links models of human generalisation to the design of experiments. I construct models by varying both how a learner represents information and how the learner uses it to respond. The same representation can support rule application, comparison with a category prototype or retrieval of remembered examples. ## BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval Research Source ID research:bright Section research Original https://www.henryw.me/#/research#bright Read https://ask-henry.whenry6688.workers.dev/agent/sources/research%3Abright?format=text Finding a useful document can depend on first understanding what a problem requires. We developed BRIGHT to evaluate this reasoning-intensive retrieval, using 1,384 real queries across domains including economics, psychology, mathematics and coding. I contributed biology and psychology data and reproduced programming examples to work through the questions and the material needed to answer them. ## Early Epistemic Settlement in AI-Assisted Writing Research Source ID research:fittedAssistance Section research Original https://www.henryw.me/#/research#structure-settles-thought Read https://ask-henry.whenry6688.workers.dev/agent/sources/research%3AfittedAssistance?format=text In trying to finish a passage, a writer may connect her material in ways that change both the argument she can make and the demands it needs to meet. I examined what happens when AI supplies a passage that resolves the immediate difficulty while this work is still unfolding. The writer can understand the answer, judge it adequate, and move on before discovering what her own attempt could have made possible. ## Function-Vector Heads Are Two Populations: Writers and Cancellers in In-Context Learning Research Source ID research:functionVector Section research Original https://www.henryw.me/#/research#functionVector Read https://ask-henry.whenry6688.workers.dev/agent/sources/research%3AfunctionVector?format=text I studied how a language model carries out a task inferred from examples in its prompt. Function vectors capture this task information through the combined outputs of attention heads. Among candidate function-vector heads, I identified writers that support the answer specified by the demonstrated rule and cancellers that systematically suppress it. ## Humans Disengage, Reasoning Models Persist: Separating Difficulty Registration from Deliberation Allocation Research Source ID research:humansDisengage Section research Original https://www.henryw.me/#/research#humansDisengage Read https://ask-henry.whenry6688.workers.dev/agent/sources/research%3AhumansDisengage?format=text I studied how people and large reasoning models allocate effort once a problem becomes difficult. Across visual abstraction, intuitive physics and relational reasoning, I analysed human response times alongside the length and content of reasoning traces, the text models generate before answering. Comparing attempts on the same problems let me separate sensitivity to difficulty from the allocation of further effort. ## Functional Encoding and Representational Binding in Componential Transfer Research Source ID research:encoding Section research Original https://www.henryw.me/#/research#encoding Read https://ask-henry.whenry6688.workers.dev/agent/sources/research%3Aencoding?format=text Why can a learner demonstrate a rule during training yet fail to use it on a new item? We built a computational account in which transfer depends on how useful components are encoded and bound together. Functional encoding determines which components enter the representation used to generate a response.