These are some highlights from several sources focused on large language models (LLM) and generative pre-trained transformers (GPT) — all published in 2023. It might be useful to first read — Nobody knows how many jobs will “be automated” Whatever that even means.
But “AI will increase labor productivity while forcing a small number of people to find new jobs” is not the kind of story that goes viral on social media, while “300 million jobs will be lost” definitely is that kind of story. People love to read about the impending apocalypse, and it’s the media’s responsibility not to indulge that desire … Instead of telling us who will be “automated”, they [A Method to Link Advances in Artificial Intelligence to Occupational Abilities – 2018] tell us who’s more likely to be affected by automation in some way. Obviously we’d like to know whether it’ll be a good way or a bad way. But the truth is that no one knows that yet, and economists do the world a service by refusing to pretend that they do know.
ChatGPT is about to revolutionize the economy
The optimistic view: it [GPT] will prove to be a powerful tool for many workers, improving their capabilities and expertise, while providing a boost to the overall economy. The pessimistic one: companies will simply use it to destroy what once looked like automation-proof jobs, well-paying ones that require creative skills and logical reasoning; a few high-tech companies and tech elites will get even richer, but it will do little for overall economic growth.
GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models
Our findings reveal that around 80% of the U.S. workforce could have at least 10% of their work tasks affected by the introduction of LLMs, while approximately 19% of workers may see at least 50% of their tasks impacted … Our findings indicate that the importance of science and critical thinking skills are strongly negatively associated with exposure, suggesting that occupations requiring these skills are less likely to be impacted by current LLMs. Conversely, programming and writing skills show a strong positive association with exposure, implying that occupations involving these skills are more susceptible to being influenced by LLMs.
Secret Cyborgs: The Present Disruption in Three Papers
AI can increase productivity for workers in fields where automation and economies of scale were previously very rare. These jobs often require more autonomy and encompass multiple types of tasks (teachers need to prep lessons, grade, write letters of recommendation, run classes, respond to parents, run after school programs, do administrative work, etc.). With the power to outsource the most annoying and time consuming parts of their jobs, workers in these industries are highly incentivized to adopt AI quickly, either to do less work or to be able to bill out more work themselves. It is a recipe for rapid adoption at the individual level.
Interestingly, these same incentives suggest that many workers may be hesitant to reveal the extent to which they use AI tools. The advantage of producing AI-written letters and reports that seem like they were made by humans diminishes quickly if people know they are generated by AI. I conducted a bit of an unscientific Twitter poll, and over half of generative AI users reported using the technology without telling anyone, at least some of the time. Their are secret cyborgs among us.
CURATED READS FOR GEN Z—AND THEIR Z-CURIOUS COLLEAGUES
Whether you’re a new grad or have a few after-college years under your belt, you might be worried that generative AI is going to disrupt the job market and throw a huge wrench in your career plans, particularly at the entry level. It’s true that generative AI is going to change the way plenty of us work, but there’s no sense in fighting against it. Embracing generative AI and learning the technical skills required to work with it, no matter what industry you’re going into, is probably a good idea.
But there are also “soft skills”—qualities that make you a valuable teammate and leader—that, no matter how the job market changes, will keep you employable: critical thinking, intellectual curiosity, and flexibility.
The Potentially Large Effects of Artificial Intelligence on Economic Growth
Our baseline analysis incorporates our key findings from above, including that about 7% of workers are fully displaced but that most are able to find new employment in only slightly less productive positions, that partially exposed workers experience a boost in productivity consistent with existing estimates (Exhibit 9), and that effects are realized over a 10-year period that starts around the time when roughly half of businesses have adopted generative AI. Under these assumptions we estimate that widespread adoption of generative AI could raise overall labor productivity growth by around 1.5pp/year (vs. a recent 1.5% average growth pace), roughly the same-sized boost that followed the emergence of prior transformative technologies like the electric motor and personal computer.
