#ChatGPT Archives – THE PAGE TURNS

Image created by the AI Art Generator. See explanation below.

Rampant fear or unquestioning enthusiasm. These seem to be the two fundamental attitudes people have about Generative AI models. Programs like Chat GPT, Bloom, and Replika are demonstrating the power, potential, and problems associated with having technology that seems to talk. Aside from getting some definitional clarity around what Chat/AI is and is not, I present here a couple of Use Cases. They may inspire in you, as they have in me, both fear and enthusiasm.

Let’s Call It What It Is: Simulated Talking

A few definitions might be in order. First of all, Artificial Intelligence (AI) is a large field, so let’s be clear that AI and Generative AI are different things. AI models are ones where you feed in data to get recommendations and predictions. We use simple models and algorithms ourselves, for instance, checking the weather by looking outside; that’s an unsophisticated algorithm that isn’t terribly predictive. In the past, computer models were similarly limited. They broke down fairly quickly if the variables got complicated or the model tried to look too far in the future. I can guess the weather in an hour, but what about next Sunday at 11 am, when I want to play pickleball? AI means that the models are big enough and full of enough data that the predictive accuracy is far beyond what computers “used” to predict. A self-driving car might be an example of AI. It’s not creating text or art, but it needs a huge influx of data and sophisticated decision-making capabilities in order to navigate a very complex environment.

Generative AI, which I’ll also call Chat/AI here, is a model that can create “new” content as part of its predictive output. You feed it tons of examples, and it creates something “new” or seems new, based on previous human-created patterns that made sense. The following example came from Prof. Louis Hyman, who will be discussed below. Suppose you asked Chat/AI to fill in the cat sat on the ____. The model might suggest floor, chair, lap, or mat. But mat might be the highest likelihood, perhaps 50%, so the generative AI picks that word.

I’ve been futzing about for a few days, trying to decide whether to write a post that centers on Aristotle, “Barbie” and “Oppenheimer.” My big hang-up is frankly … audience. How much are y’all going to balk if you read the word Aristotle in the first sentence? And yet I can’t write my film review without mentioning him. So I’ve been stuck between the urge to get these ideas out and the knowledge that we’re living in a time of anti-intellectualism.

It’s like a seesaw effect. We don’t even know what we think about smarts. There are constant little tests nestled in among Corgi pictures on the interwebs that tell you to “solve this puzzle and your IQ is 180.” Which anybody with some kind of education knows is patently false because that’s not how IQ works and nobody has IQs over 170 except that little kid they found in Nepal once. (OK, I checked the Internet; there are a few people now with IQs over 170. But not because they can do some little puzzle.)

Meanwhile, we don’t even care if people learn how to write anymore because we have ChatGPT and other tools coming that will just write stuff for us. As if Chat knows. I think of ChatGPT as like a rather stupid, random World Book Encyclopedia. If you happen to go to the right page and copy the right bits word for word (or verbatim–we used to use that word in a business context until we were told people didn’t know what it meant, so we had to replace it with “word for word” because people can’t learn what words mean anymore)… If you go to the right page and plagiarize it, you might just get away with it. But what if you have to combine things? And if you’re not learning because all you ever do is copy things other people wrote, then you just wander through school and come out as dumb as you started.