Although I don’t subscribe to the idea that history or technology moves in jerky one-year increments, it’s still valuable to take stock at the start of a new year, look at what happened last year, and decide what was important and what wasn’t.
We started the year with many people talking about an “AI winter.” A quick Google search shows that anxiety about an end to AI funding has continued through the year. Funding comes and goes, of course, and with the possibility of a media-driven recession, there’s always the possibility of a funding collapse. Funding aside, 2022 has been a fantastic year for AI. GPT-3 wasn’t new, of course, but ChatGPT made GPT-3 usable in ways people hadn’t imagined. How will we use ChatGPT and its descendants? I don’t believe they put an end to search. When I search, I’m (usually) more interested in the source than I am in an “answer.” But I have a question. Much has been made about ChatGPT’s ability to “hallucinate” facts. I wonder whether that kind of hallucination could be a prelude to “artificial creativity”? I’ll try to have something more to say about that in the coming year.
GitHub CoPilot also wasn’t new in 2022, but in the last year we’ve heard of more and more programmers who are using ChatGPT to write production code. It isn’t just people “kicking the tires”; AI-generated code will inevitably be part of the future. The important questions are: who will it help, and how? Right now, it seems like CoPilot will be less likely to help beginners, and more likely to be a force-multiplier for experienced programmers, allowing them to focus more on what they are trying to do than on remembering details about syntax and libraries. In the longer term, it might bring about a complete change in what “computer programming” means.
DALL-E 2, Stable Diffusion, and Midjourney made it possible for people without artistic skills to generate pictures based on verbal descriptions, with results that are often fantastic. Google and Facebook haven’t released anything to the public, but they have demoed similar applications. All of these tools are raising important questions about intellectual property and copyright. They are already inspiring new startups with new applications, and those companies will inevitably attract investment.
Those tools aren’t without their problems, and if we really want to avoid another AI Winter, we’d do well to think about what those problems are. Intellectual property is one issue: GitHub is already being sued because CoPilot’s output can reproduce code that it was trained on, without regard for the code’s initial license. The art generation programs will inevitably face similar challenges: what happens when you tell an AI system to produce a drawing “in the style of” some artist? What happens when you ask the AI to create an avatar for a woman, and it creates something that’s highly sexualized? ChatGPT’s ability to produce plausible text output is spectacular, but its ability to discriminate fact from non-fact is limited. Will we see a Web that’s flooded with “fake news” and spam? We arguably have that already, but tools like ChatGPT can generate content at a scale that we can’t yet imagine.
At its heart, ChatGPT is really a user interface hack: a chat front end bolted onto an updated version of the GPT-3 language model. “User interface hack” sounds pejorative, but I don’t mean it that way. We now need to start building new applications around these models. UI design is important–and UI design for AI applications is a topic that hasn’t been adequately explored. What can we build with large language and generative art models? How will these models interact with their human users? Exploring those questions will drive a lot of creativity.
After ChatGPT, perhaps the biggest surprise of 2022 was the rise of Mastodon. Mastodon isn’t new, of course; I’ve been looking in from the outside for some time. I’ve never thought it had achieved critical mass, or that it was capable of achieving critical mass. I was proven wrong when Elon Musk’s antics drove thousands of Twitter users to Mastodon (including me). Mastodon is a federated network of communities that are (mostly) pleasant, friendly, and populated by smart people. The sudden influx of Twitter users proved that Mastodon could scale. There were some growing pains, but not as much as I would have expected. I haven’t seen a single “fail whale.”
The growth of Mastodon proved that the federated model worked. It’s important to think about this. Mastodon is a decentralized service based on the ActivityPub protocol. Nobody owns it; nobody controls it, though individuals control specific servers. And there isn’t a blockchain or a token in sight. In the past year, we’ve been treated to a steady diet of noise about Web3, most of which insists that the next step in online interaction must be built on a blockchain, that everything must be owned, everything must be paid for, and that rent collectors (aka “miners”) will have their hands out taking their cut on each transaction. I won’t go so far as to claim that Mastodon is Web3; but I do think that the next generation of the Web, however it evolves, will look much more like Mastodon than like OpenSea, and that it will be based on protocols like ActivityPub.
Which leads us to blockchains and crypto. I’m not going to engage in Schadenfreude here, but I’ve long wondered what can be built with blockchains. At one time, I thought that supply chain management would be the poster child for the Enterprise Blockchain. Unfortunately, IBM and Maersk have abandoned their TradeLens project. NFTs? I have always been skeptical of the connection between NFTs and the art world. NFTs seemed an awful lot like buying a painting and framing the receipt. They existed purely to show that you could spend cryptocurrency at scale, and the people who spent their coins that way have gotten what they deserved. But I’m not willing to say that there’s no value here. NFTs may help us to solve the problem of online identity, a problem that we haven’t yet solved on the Web (though I’m not convinced that NFT advocates have really understood how complex identity is). Are there other applications? A number of companies, including Starbucks and Universal Studios, are using NFTs to build customer loyalty programs and theme park experiences. At this point, NFTs still look like a technology in search of a problem to solve, but I suspect that the appropriate problem isn’t out there.
There was more in 2022, of course. Will we see a Metaverse, or was that just Facebook’s attempt to change the narrative about its actions? Will Europe continue to take the lead in regulating the tech sector, and will other nations follow? Will our daily lives be improved by a flood of interoperable smart devices? In 2023, we shall see.