GPT and other AI generative tools and the (future of) the world of work.
Dr Alex Sims speaks about how the proliferation of AI will affect our world of work.
Late 2022 was an inflexion point as ChatGPT-3 (or, more accurately, ChatGPT-3.5) was launched.
The results ChatGPT-3 generates can be stunningly good, or they can range across the spectrum to terrible and are often laughed at. Some effects contain invented sources/citations, dismissively called “AI Hallucinations”.
People’s reaction to laughing at the often-basic errors and new technology is expected. New technologies are rarely as good as existing technology. Yet, as history has shown, the latest technologies often surpass the previous ones.
Digital cameras are an excellent example of the adoption of new technology. The early mass-produced digital cameras, starting from the early 1990s, produced photos that were far from as good as traditional photographs. But as the quality of digital images improved and the cost of digital cameras fell, digital cameras slowly replaced traditional SLR cameras. Now SLR cameras are rarely used.
However, there are two points of difference between GPT and other AI generative tools and the general trend of new technologies replacing old. First, as the digital camera example shows, the replacement of technologies has traditionally been slow. In contrast, the speed of change in technology with GPT and other AI generative tools is exponential. It took just five days for ChatGPT to hit 1 million downloads, and the release of GPT-4 in March 2023 has made ChatGPT-3 effectively obsolete.
While much of the focus has been on ChatGPT and text generation, the past few months have seen the release of a swath of AI generative tools covering art, design, video, voice, music and computer code.
Second, it usually is the case of new technology replacing an existing one, e.g. digital cameras replacing SLR cameras, cars and trucks replacing horses and carts and so on. However, with GPT and other AI generative tools, humans’ knowledge and skill are being replaced. Indeed, at the time of writing, tech industry leaders are calling for a pause on the continued development of AI beyond GPT-4 due to AI’s societal and other impacts.
Dr Alex Sims
To be sure, some new technologies have replaced human labour. For example, bulldozers and other machines replaced some men’s physical labour. However, those were isolated examples, and new jobs were created to drive and operate those machines.
So what do the AI generative tools mean for the future of the world of work? First, we are talking about something other than the future of work. The future is here. These technologies are already in use. For example, for some advertising agencies, what previously had taken three days and required a range of people, can now be done by one person in less than three hours. There is little need for copy editors and graphic artists in that advertising agency. It is easy to understand the predictions that in the US and Europe, up to one-fourth of human work will be replaced by AI tools and automation.
The advertising agency example does not mean that “one person” can be anyone. For a person to achieve high-quality content for the advertising agency, they must be highly skilled in marketing/advertising and using a broad array of AI generative tools.
As with all the use of all new technologies, there will be winners and losers. The winners are those people and organisations who can learn new skills and strategies and harness AI generative tools. The losers will be the ones who need help to use the latest technology effectively. History is littered with examples of skilled people rendered jobless who could not adapt to the new technology.
Granted, it will be painful for those who cannot change. But no one should be surprised at this turn of events. Over 50 years ago, the futurist Alvin Toffler, in the book, Future Shock, said, “The illiterate of the twenty-first century will not be those who cannot read and write, but those who cannot learn, unlearn, and relearn.”
Dr Alex Sims is an associate professor in the Department of Commercial Law at the University of Auckland Business School. As well as her research in AI, her other research areas include blockchain and decentralised autonomous organisations (DAOs). Her legacy research and publication include copyright law and consumer law. Alex has taught in the Department of Commercial Law since 2000.
31 March 2023
