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kaseda t1_j1vvbna wrote

Although we've used the term AI, we are specifically talking about machine learning models. You cannot program an ML model, you can only teach it. A very reasonably programmed model with all else correct can fail if you train it on a dataset with mostly 1s.

You assume a few things that are incorrect - firstly, you cannot just "program" a model to take certain actions under certain conditions. That may be the case in some AI, but not machine learning. In ML, you must teach the model, which is more difficult and not always precise. Secondly - you assume the model cares about anything besides the data they are trained on. If it sees mostly 1s in the training set, it will never adjust to the fact that this isn't the case in it's actual application. You would have to retrain it on a different dataset to get it to act accordingly. Third, you assume the AI somehow has a conscious decision to just choose to not be offensive.

How would an AI determine that they don't want to represent racism? The only way this can be is if the data set is curated to exclude it, or even more accurately, trained to explicitly reject it. Pollute the dataset and it will act differently.

And, strictly speaking, AI is stupid. They have no clue what they are doing, they are just doing it. All AI gives is a semblence of intelligence.

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joyloveroot OP t1_j1zlrvt wrote

If what you say about ML is true, then ML is a dead end, technologically speaking. If an ML-trained bot can’t differentiate between the hand-written digit contexts I laid out above, then it is basically useless.

This is why I would like to get a job in this field because when you say things are not possible, I don’t believe it. I believe I could make it possible. I believe sitting down with programmers for 6 months where I could transfer my philosophical knowledge and they could transfer their coding knowledge.. we could together create an ML-bot that could do all the things you question above.

About the “conscious decision” thing. I’m not going to get into definitions of consciousness and all that. But what I’m saying is that two ML/AI’s could be presented the same exact data set, but the context will always be even just slightly different. Perhaps one ML/AI is presented the data set in a slightly different sequence, etc.

These slight variations will lead to slightly or majorly different outcomes. One AI could adopt a racist nazi persona and another could adopt a 50’s housewife persona as their main personas (metaphorically speaking).

In other words, from how you are presenting it above that an AI given the whole internet data set becomes Nazi racist, etc… I’m actually agreeing with you here that such a thing is absurd. As you say, the AI is not sentient and conscious in any meaningful sense and so it should not take on any persona, let alone a very specific evil/ignorant persona. In other words, there should be no discernible pattern about what persons it adopts, other than pure probability based on what percentage of data is out there.

Like I alluded to above, if 1% of the data out there is that which would train a human to be Nazi racist, then we should expect 1% or AI’s to become Nazi racist. We should expect more or less a similar proportion of humans and AI’s to adopt certain personas because we are using data sets which represent collective humanity…

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kaseda t1_j1zp7x5 wrote

In case you're curious, I have a degree in computer science with a concentration in AI and ML. I'm not saying ML is a "dead end" but there are limited things it can do if humans cannot already do them because ML models need training data to work and that data must be produced by a human. This is all in it's current state - it would take a revolutionary change in ML to break free of the need for training data, particularly for generative models like chat bots or image generators.

2nd, ML has basically nothing to do with philosophy - at least, not in a way that philosophy could help develop it. Had you said psychology? That's a much more related field, and the entire concept of a neutral network is modelled after the human brain.

>Like I alluded to above, if 1% of the data out there is that which would train a human to be Nazi racist, then we should expect 1% or AI’s to become Nazi racist.

It may be true for 1% of the dataset to not influence the model much, but ML models are very hard to predict or analyze. As that percentage increases, the model will non-linearly learn that data more and more strongly. In the case of the digits, if 85% of the dataset is 1s, not only is it being presented 1s more frequently to learn on, but when it gets better at recognizing a 1, it isn't just getting better at recognizing that 1, it gets better at recognizing all 1s. Better recognition of 1s is better recognition of 85% of the dataset, while other digits is only a measly 2 or 3.

There are methods to prevent this issue - for example, you could sample your digits from the internet, and then only take a certain number of each digit from your sample, so all are equal.

This is much harder with training data for a chat bot. How do you know if something expresses a racist sentiment? How do you know if something is inaccurate? The only two options are to train an AI to do it for you, or produce a curated dataset. And to train the AI to do it for you? You would have to feed it a curated data set as well.

I'm not saying that using training data straight from the internet and getting a feasible AI is impossible - but with ChatGPT, and pretty much every language model that does or has ever existed, it is foolish and can be manipulated. People will find a way. The only solution is curation until we have an AI good enough to curate for us.

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joyloveroot OP t1_j24ce9g wrote

Philosophy is a term that has a wide range of meanings amongst the general public so I can understand how you don’t see the connection. Perhaps ironically, I majored in maths and psych in uni and minored in philosophy. I see the connection between all 3.

In any case, probably good to leave the discussion here as there is a limit to the nuance we can further explore in a Reddit thread :)

Curious, since you work in the field. If you know, what kinds of positions are available to non-coders in this field? I would love to contribute more in some way or at least see if my contributions can be valuable. What would you recommend?

I can provide further context if necessary…

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kaseda t1_j24p5bz wrote

Most jobs in AI and ML require master's degrees specialized in the topic. The teams that work on these things tend to be small so it's harder to justify training someone who might not know what they're doing. Granted, I've never seen listings for places like OpenAI, where the structure might be different.

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joyloveroot OP t1_j27t951 wrote

If that’s true, then clearly some amount of hubris is holding the field back 😂

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kaseda t1_j280cu1 wrote

AI and ML are not trivial things to just get into. A master's is roughly appropriate, not just for the education but also for the pay.

More so than hubris, is capitalism. It's hard to come across money for research's sake. Most companies don't care to invest in AI or ML if they can't see a ROI in it. That's the other reason the jobs are hard to come by.

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joyloveroot OP t1_j295lcl wrote

Yeah also ridiculous that we don’t dedicate resources based on some more rational criteria than the random movement of the capitalist market…

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