Bel pezzo, da leggere e divulgare.
Questa la parte finale
Source: New Yorker
Combined, these observations provide good news for those who fear that ChatGPT is just a small number of technological improvements away from becoming HAL, from “2001: A Space Odyssey.” It’s possible that super-intelligent A.I. is a looming threat, or that we might one day soon accidentally trap a self-aware entity inside a computer—but if such a system does emerge, it won’t be in the form of a large language model.
Even if ChatGPT isn’t intelligent, couldn’t it still take our jobs? Our new understanding of how these programs work can also help us tackle this more pragmatic fear. Based on what we’ve learned so far, ChatGPT’s functionality seems limited to, more or less, writing about combinations of known topics using a combination of known styles, where “known” means that the program encountered a given topic or style enough times during its training. Although this ability can generate attention-catching examples, the technology is unlikely in its current form to significantly disrupt the job market. Much of what occurs in offices, for example, doesn’t involve the production of text, and even when knowledge workers do write, what they write often depends on industry expertise and an understanding of the personalities and processes that are specific to their workplace. Recently, I collaborated with some colleagues at my university on a carefully worded e-mail, clarifying a confusing point about our school’s faculty-hiring process, that had to be sent to exactly the right person in the dean’s office. There’s nothing in ChatGPT’s broad training that could have helped us accomplish this narrow task. Furthermore, these programs suffer from a trustworthiness crisis: they’re designed to produce text that sounds right, but they have limited ability to determine if what they’re saying is true. The popular developer message board Stack Overflow has had to ban answers generated by ChatGPT because, although they looked convincing, they had “a high rate of being incorrect.” Presumably, most employers will hesitate to outsource jobs to an unrepentant fabulist.
This isn’t to say that large language models won’t have any useful professional applications. They almost certainly will. But, given the constraints of these technologies, the applications will likely be more focussed and bespoke than many suspect. ChatGPT won’t replace doctors, but it might make their jobs easier by automatically generating patient notes from electronic medical-record entries. ChatGPT cannot write publishable articles from scratch, but it might provide journalists with summaries of relevant information, collected into a useful format.
Imitating existing human writing using arbitrary combinations of topics and styles is an impressive accomplishment. It has required cutting-edge technologies to be pushed to new extremes, and it has redefined what researchers imagined was possible with generative text models. With the introduction of GPT-3, which paved the way for the next-generation chatbots that have impressed us in recent months, OpenAI created, seemingly all at once, a significant leap forward in the study of artificial intelligence. But, once we’ve taken the time to open up the black box and poke around the springs and gears found inside, we discover that programs like ChatGPT don’t represent an alien intelligence with which we must now learn to coexist; instead, they turn out to run on the well-worn digital logic of pattern-matching, pushed to a radically larger scale. It’s hard to predict exactly how these large language models will end up integrated into our lives going forward, but we can be assured that they’re incapable of hatching diabolical plans, and are unlikely to undermine our economy. ChatGPT is amazing, but in the final accounting it’s clear that what’s been unleashed is more automaton than golem.
L’articolo completo è qui: What Kind of Mind Does ChatGPT Have? | The New Yorker
