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We're All Wrong About AI
Remember when we thought personal computers were for tracking recipes?
Looking back at the Apple II, in 2018 Michael Halvorson recalled marketing blurbs
stating that you can use the device to teach your kids arithmetic and make learning fun, manage household finances, chart the stock market, track your recipes and record collection, and control your home.
I don’t have to spell out the applications for personal computers that have emerged since then.
I think that with the latest developments in AI, we are at the “track your recipes” stage of imagination. What people think that AI will do is probably poorly correlated with how AI’s actually will be used. Meanwhile, I have a few pet peeves about claims people are making concerning what AI’s will and won’t do.
AI’s Can be Creative
Anyone who makes the argument that AI’s can never be creative, and that you need humans for that, probably understands neither human creativity nor the working of the current generation of AI.
Human creativity does not mean coming up with ideas full-blown out of nowhere. Creativity is recombinant. A creative idea takes two or more previous ideas and combines them in a way that they have never been combined before.
Current versions of AI represent words or other concepts (such as musical sounds) as multidimensional vectors. All it takes for an AI to be creative is for it to try to add vectors that have never been added before.
Adding two arbitrary vectors is very unlikely to result in a new concept that is at all useful. For an AI to be creative, it will have to be able to extract from many possible vector combinations those rare syntheses that are worth retaining.
Human creativity is no different. Pop songwriters have no problem coming up with different possible chord progressions. The challenge is to choose the ones that are both novel and pleasing.
A schizophrenic and I can both come up with novel word sequences. The schizophrenic is better at generating them. I am better at filtering out the ones that don’t provide meaning.
If you wanted it to, a large language model could beat the most prolific schizophrenic at generating novel content. But in order to be appreciated as creative, AI’s will have to become excellent at filtering out the novel content that doesn’t work. Once they learn to do that, AI’s will reach human or super-human levels of creativity. If there is some barrier to AI’s becoming excellent at such filtering, I do not see it.
AI is not Google on steroids
When I was searching for a reference to the early days when Apple was touting home computers as devices to help track recipes, I tried several different large language models. None of them helped me. I found the quote that I used for this essay using plain old Google.
Large language models are trained using data on the Internet. But unlike Google, they are not trying to analyze the data on the Internet. Google is restructuring and modeling data on the Internet in order to feed an algorithm for search. Large language models are using the data in order to learn how to write (or draw, or make sounds).
AI can understand you as an individual
Many people are focused on generic AI skills. They see it drafting news articles. They see it doing preliminary data analysis. They see it writing software. It could do all of these things without knowing anything about the person it is doing it for.
But another possibility captivates many of us. That is, an AI will learn about you as an individual, becoming your companion. For a child, it becomes a tutor. For an adult, it becomes a personal assistant. For anyone, it becomes a friend.
The potential use of an AI as a friend immediately calls to mind the “AI girlfriend” or romantic partner. I am dubious about this, but entrepreneurs and some consumers are trying it.
An AI relationship does not have to involve romance in order for it to be personal. An AI just has to remember past interactions with you and use that memory to better interact with you and align itself to your preferences.
Returning to where this essay began, I do not believe that we know enough to predict with any accuracy which uses of AI will take off and which will prove to be either too trivial (recipe tracking) or too elusive (maybe it’s too much to hope that AI will allow children to escape from school-prison). The best way to find out is to work with it, not to dismiss it.