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::Interpretability and explainability are related concepts, but they are not necessarily subsets of one another. [[User:Geysirhead|Geysirhead]] ([[User talk:Geysirhead|talk]]) 20:09, 12 June 2023 (UTC)
:I agree with Geysirhead. I've been writing articles about AI, and I've been continuously frustrated by the fact that I can't provide a link to help people understand what interpretability means in ML because this page is all that exists, and it doesn't explain what the field of interpretability is about at all. As I understand it, XAI refers to AIs that were built to be interpretable while interpretability refers to the field. It seems nonsensical to me that XAI, one possible result of the field of interpretability, would have a page while the field itself isn't allowed to have one. If "interpretable AI" is considered too similar for some people, perhaps "interpretability (machine learning)" would be acceptable? [[User:Penrose Delta|Penrose Delta]] ([[User talk:Penrose Delta|talk]]) 16:11, 10 July 2023 (UTC)
::There is indeed a distinction. If the article is to be split, what about the title "AI interpretability" (https://effectivethesis.org/thesis-topics/human-aligned-ai/mechanistic-interpretability/) ? It would reuse the same pattern as some other article titles (such as AI safety or AI alignment). The title "Mechanistic interpretability" should also be considered, it is more likely to be searched as-is and is more clearly defined, although this term seems mostly used in research (primary sources). By the way, I agree that "interpretability (machine learning)" is probably also a better title than "interpretable AI". [[User:Alenoach|Alenoach]] ([[User talk:Alenoach|talk]]) 05:15, 21 August 2023 (UTC)
:I am not sure that interpretability is consistently used to ''only'' refer to understanding the inner workings of a machine learning model. [https://docs.aws.amazon.com/whitepapers/latest/model-explainability-aws-ai-ml/interpretability-versus-explainability.html AWS Docs] comments that "the terms interpretability and explainability are commonly interchangeable"; indeed, LIME is variously referred to as an interpretability or explainability technique. I think it's easiest to explain the nuances on a single page about both interpretable and explainable AI rather than having separate pages. Otherwise, I'm concerned that there will be considerable duplicated content across both pages. For example, is the paper [https://openai.com/research/language-models-can-explain-neurons-in-language-models "Language models can explain neurons in language models"] an interpretability or an explainability paper? I believe it could be considered both. [[User:Enervation|Enervation]] ([[User talk:Enervation|talk]]) 05:35, 24 July 2023 (UTC)
: Would I be wrong in guessing that explanation leans heavily on social psychology (what is an explanation, anyway?) while interpretability is highly mathematical in nature? My fear is that "explanation" will turn into a sop. What might happen is that we build a large model of what people will accept as an explanation, and then we map the AI model to some convenient point in the space of acceptable explanation. Obviously, this can be done badly or it can be done well. But even when done well, is it useful other than for sop value? But then people go "it's not a sop, as you can see from this hardcore dive into interpretability". And then I go, "so far as anyone could tell, it ''was'' a sop until you laid out the interpretable equivalence, and so far as I'm concerned, the interpretable equivalence is wearing the pants here". Maybe it's just me, but I suspect that "explanation" is never going to float my own boat. I might be more convinced by ''accountable'' AI, though that also has a problematic social backdrop. — [[user:MaxEnt|MaxEnt]] 02:41, 5 August 2023 (UTC)
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