The impacts of generative AI, large language models (LLMs), and ChatGPT on the automation of work, making parallels with the waves of automation observed over the last 200 years. The adoption of these AI technologies, such as ChatGPT, is rapid, but their effects on employment, disruption, and broader socioeconomic structures are still a topic of ongoing discussion. The historical pattern of automation has often led to the creation of new jobs, counterbalancing those lost, however, this dynamic is uncertain with AI, as it’s advancing quickly and its impact on job displacement and creation is unpredictable.
- Generative AI and LLMs, such as ChatGPT, represent a significant shift in software automation capabilities. However, the pace at which these technologies will impact job displacement and creation is uncertain.
- Historically, automation has led to both job loss and creation, resulting in a net gain over time. However, the introduction of AI into the workforce could potentially disrupt this trend, due to its capability to automate cognitive tasks.
- The ‘Lump of Labour’ fallacy argues against the idea of a fixed amount of work in society, suggesting that while automation might make some jobs redundant, it also creates new industries and employment opportunities.
- The Jevons Paradox suggests that as technology makes tasks cheaper and more efficient, we end up using more of it and expanding its application to new areas, thus leading to more jobs.
- The pace at which AI is being adopted, particularly in the workplace, is faster than previous technology waves, such as PCs or the internet, raising concerns about the potential for heightened disruption and friction in employment transitions.