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ChatGPT proves that AI is finally mainstream – and things are only going to get weirder




A friend of mine texted me earlier this week to ask what I thought of ChatGPT. I wasn’t surprised that he was curious. He knows that I write about AI and is the type who keeps up with what is trending online. We chatted a bit, and I asked him: “and what do you do?”[ads1]; you think about ChatGPT?” To which he replied, “Well, I wrote a half-decent Excel macro with it this morning that saved me a few hours at work” – and my jaw dropped.

For context: this is someone whose job involves a fair amount of messing around with databases, but who I wouldn’t describe as particularly tech-minded. He works in higher education, studied English at university, and never formally learned to code. But here he was, not only playing with an experimental AI chatbot, but use it to do their job faster after only a few days of access.

“I asked it a few questions, asked it some more, put it into Excel, and then did some debugging,” is how he described the process. “It wasn’t perfect, but it was easier than Googling.”

Tools like ChatGPT have made AI publicly available like never before

Stories like this have been piling up this week like the first patches of rain that gather before a downpour. Across social media, people have shared stories of using ChatGPT to write code, draft blog posts, write college essays, compile work reports, and even up their chat-up game (okay, that last one was definitely done as a joke, but the prospect of AI-augmented rizz is still tempting). As a reporter covering this area, it’s initially been impossible to keep up with everything that’s happening, but there’s one overarching trend that has stood out: AI is going mainstreamand we are only just beginning to see the effect this will have on the world.

There’s a concept in AI that I’m particularly fond of that I think helps explain what’s going on. It’s called “capability overhang” and refers to the hidden characteristics of AI: skills and abilities that lie latent in systems that researchers haven’t even begun to investigate yet. You may have heard before that AI models are “black boxes” – that they are so huge and complex that we don’t fully understand how they work or come to specific conclusions. This is largely true and is what creates this overhang.

“Today’s models are far more capable than we think, and our techniques available to explore [them] are very young,” is how AI policy expert Jack Clark described the concept in a recent issue of his newsletter. “What about all the traits we don’t know about because we’re not going to test for them?”

Capability overhang is a technical term, but it also perfectly describes what is happening right now as AI enters the public domain. For years, researchers have been on a tear, pumping out new models faster than they can be commercialized. But in 2022, a flurry of new apps and programs have suddenly made these skills available to a general audience, and in 2023, as we continue to scale this new territory, things will start to change – fast.

The bottleneck has always been availability, as ChatGPT demonstrates. The bones of this program aren’t entirely new (it’s based on GPT-3.5, a major language model released by OpenAI this year, but itself an upgrade to GPT-3, as of 2020). OpenAI previously sold access to GPT-3 as an API, but the company’s ability to improve the model’s ability to speak in natural dialogue and then publish it online for anyone to play with brought it to a much larger audience. And no matter how imaginative AI researchers are in examining a model’s skills and weaknesses, they will never be able to match the mass and chaotic intelligence of the internet at large. Suddenly the overhang is available.

The same dynamic can also be seen in the rise of AI image generators. Again, these systems have been in development for years, but access was limited in various ways. This year, however, systems like Midjourney and Stable Diffusion allowed anyone to use the technology for free, and suddenly AI art is everywhere. Much of this is due to Stable Diffusion, which offers an open source license for companies to build upon. In fact, it’s an open secret in the AI ​​world that whenever a company releases a new AI imaging feature, there’s a decent chance it’s just a repackaged version of Stable Diffusion. This includes everything from viral “magic avatar” app Lensa to Canvas AI text-to-image tool to MyHeritage’s “AI Time Machine.” It’s the same technology underneath.

As the metaphor suggests, however, the prospect of an ability overhang is not necessarily good news. In addition to hidden and new abilities, there are hidden and new threats. And these dangers, like our new skills, are almost too numerous to mention. For example, how will colleges adapt to the proliferation of AI-written essays? Will the creative industries be decimated by the spread of generative AI? Will machine learning create a tsunami of spam that will destroy the web forever? And what about the inability of AI language models to distinguish fact from fiction or the proven biases of AI image generators that sexualize women and people of color? Some of these problems are known; others are ignored, and still more are just beginning to be noticed. As the excitement of 2022 winds down, it’s certain that 2023 will feature some rude awakenings.

Welcome to the AI ​​overhang. Hold on tight.



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