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Judgments are not generally impossible to automate -- judgements are typically binary or quantifiable interpretations, so in some sense are perfect targets for
by vector_spaces 17d ago
Judgments are not generally impossible to automate -- judgements are typically binary or quantifiable interpretations, so in some sense are perfect targets for automation, but the sheer volume of judgements needed to build something coherent is overly cumbersome to specify to the point of being intractable. There are also many hidden judgements, ones where the thresholds may not be well understood, and interactions between them.
But humans still manage to wrangle these, sometimes seemingly effortlessly, through a process which we call by shorthand "taste". This is a largely vibes-based heuristic that combines expertise with life experience and cultural training -- intuition, more or less.
This is likely not possible to automate either -- aspects of it may be automatable for a given expert, in small pieces in narrow subsets of their particular domains of interest, but even those likely will require some manual intervention.
This is in part because it is, to a large degree, a black box, even to the expert deploying it. With some self-awareness and strong language skills we can articulate approximations of the judgements that go into taste. But even those will fall short, as even the most self-aware individual will fail to notice certain judgements and dependencies.
In practice many of these are not even explicitly articulable. Humans are idiosyncratic and messy and dynamic, and the suggestion that we can build a machine that approximates this in a way that pleases our sensibilities and doesn't require supervision is kind of ludicrous, even in light of recent developments.
- 0c3ca83 17d agoTaste is just a set of statistically expressible heuristics for what other people will think is good. I don't undestand why you think this is impossible for AI to do. It feels like today, taste in design is similar to where software engineering was about a year ago.
- visarga 17d agoYou don't need to describe it; just show samples of the style you want to achieve. Of course it's not perfect, but it's easier than describing it. I have my own theory about why it's impossible to remove the human from the loop: 1. Any task emerges from a need, from a human context. We need the human to pay and assume the risks and costs of using the model. So intent emerges from context. 2. While the task is being worked on, constant interaction with the context is needed, for action, for feedback, and for steering. 3. At the end of a task, consequences accumulate in the context, they don't fly to the model provider. The cost, risk, liability, gains and losses remain there. So the LLM is great except for the start, middle and end of a task. Contexts are humans, teams, projects, and they are maximally distributed, you can't copy a context, it is indexical and relational, just as you can't copy my phone number or eat for me.