Artificial Intelligence Use
I believe in being transparent and explicit about the use of Generative Artificial Intelligence (AI) tools, like Large Language Models (LLMs), in my intellectual work. On this page, you’ll find a collection of statements about if and how I use AI for specific tasks.
Everything in my research and on this website was written by me.
AI tools are becoming ubiquitous in the daily workflow of many knowledge workers. These text-generation models are showing up in email applications, coding environments, job application portals, internet search engines, and just about anywhere else they can be embedded. The implicit promise of these tools is that they save time and money by reducing the amount of human effort required in tasks ranging from mundane to mission-critical. Here’s how I am using (or not using) these tools:
I was inspired to write this page by Andrew Heiss’ own version of this sort of statement, as well as the references he linked: “The ‘/ai’ manifesto”. See the /ai public database for more.
Writing
I am strongly opposed to the use of AI for writing anything. I have been particularly persuaded by arguments in this area that, because LLMs are statistical prediction machines, the model is completely and utterly incapable of regard for the moral or ethical content of the text that it generates. It is also almost impossible to verify the intellectual provenance of any text generated. In short, there is not a human behind the writing, so how could it possibly be worth reading? For this reason, I do not use LLMs to generate any portion of a research paper, cover letter, grant, email, blog post, course assignment, or similar text. While this website was built with extensive (and agentic) help from Gen. A.I., all of the text on this website is my own writing.
Coding
Generative A.I. tools are amazingly good at coding. Transformers and embeddings are really amazing technologies and the rigid syntactical structure of programming is a match made in heaven for them. I use Gen. AI to help me write code. Specifically, I use them to:
- Document or comment on long scripts or functions.
- Turn a chunk of code I’ve written into a more general function with type checks and tests.
- Translate from one language to another.
- Explain complex code chunks.
- Review code for logical errors or potential problems.
- Plotting data
Some important nuance is worth discussing here. As a scientist, it is extremely important to me that I have complete ownership over the most critical software and ideas upon which my scientific inference depends. That is: theory, simulations, statistical models, etc. The central code is and always will be code and logic that I wrote. Having said that, in addition to the uses above, I also use AI to help me write this critical code. However, I think adding friction to my workflow when developing the most important code is a good thing (i.e. Using the web-based chat interface to frontier intelligence models rather than agentic harnesses). This ensures I stay on top of what the code and math I am writing is actually doing. IF I do leverage agentic (Claude Code, OpenCode, etc.) tools to build models, I use seperate working directories and only simulated data. I sometimes use this more automated modality to prototype ideas. When I do, I like to use Agents that I built myself so that the output is very similar to how I write code and in this way is much easier to audit and review en masse.
Learning
I think this might be one of the worst use cases for LLMs, depending on what exactly is being “learned.” I value the struggle in learning something new. I think that is what actually develops problem-solving and critical thinking. Nonetheless, I do find Gen A.I. to be occassionally very helpful in learning a new concept in math or programming. It isn’t where I turn to first though. I am a huge fan of hardcopy textbooks, visualize demonstrations, lecture videos, and doing exercises to learn material.
Images and Video
I have less sophisticated thoughts here currently. I have used Generative AI to create images before. In fact, the little favicon for this website was generated using an LLM! When I see AI generated figures in presentations though, something about it irritates me a bit. Maybe I shouldn’t be so grumpy about it though… if the graphic communicates information effectively I guess it is fine. Don’t get me started on A.I. video though…