Others have suggested and made “/ai manifesto” pages on their websites, so this is mine. It reflects my current thoughts and perspective.

First, I think it is worthwhile to delineate what is meant by ‘AI’, since this is an ‘AI manifesto’. I find it to be an overused and unhelpful term. ‘AI’ and ‘LLM’ are conflated to an extent that makes AI meaningless. If by ‘AI’, one means machine learning (beyond LLMs), then I would generally say that ‘AI’ has some utility. I think various applications (chemical structures, protein structures, etc.) show some promise for exploratory purposes, but I think there are large gaps. Pursuing those avenues of research is worthwhile. In my own work, use of machine learning appears to have some utility for nuisance function estimation, but I am a bit more skeptical of how useful it will prove to be than many of my peers. The remainder of this page focuses on LLMs.

Large Language Models

My view is that LLMs have some uses, but these are far narrower than what is advertised by businesses financially invested in their widespread integration. I have a general interest in how statistical model operate in different tasks (unsurprisingly I hope). I have previous made simple character-based text generators, with code publicly available here. When building your own text generator, their fragility becomes quite apparent (when messing with the training set of the model I built, it sometimes would just repeat a single sentence due to where the optimizer landed). Ultimately, these are probabilistic models giving a highly likely word following a sequence of prior words (which I think is differently from how thinking works). The ability of current LLMs to recreate text are impressive, but I think it speaks more to the regularity in language (which would seem to be necessary feature to enable complex communication) than any particular ‘ghost’ inside the statistical machine. If anything, I think the propensity for people to interact with them as if they are cognizing beings reveals a special place language holds in the human mind.

The areas where I have used LLMs:

• Rephrasing sentences I have written (I often hate the phrasing provided, but it can lead me to something I like).
• Rubber ducking code (again the solution is often not directly provided, but the back-and-forth is helpful. The “conversing” aspect helps speed this up for me)
• Synonyms for fields of study (think thesaurus but for concepts instead of words)
• Language translation (this is not active on my part, but it underlies some online text translation services)

What I do not use LLMs for:

• Writing scientific papers (this is like a third of my job, so if I hated it that much I would find a different occupation)
• Summarizing research papers
• Teaching or creation of teaching materials
• Any image/audio/video generation
• Writing software documentation or examples (it is not good for the areas I work in, where text online is sparse)
• Generating social media posts or text on this website

I also think use of LLMs is ethically fraught, including issues related to lack of attribution, environmental damage, misuse by various actors (propaganda, scams, etc.), workers’ rights, and others. I minimize my own uses (where I think LLMs can be a useful tool) for these reasons.