Goldman Sachs has published a research note titled “The Potentially Large Effect of Artificial Intelligence on Economic Growth,” in which the authors suggest that AI could boost global productivity and GDP by 7%, and that the US economy could achieve a growth rate of 2.5% to 3%.
The report highlights that while there is significant uncertainty around the potential of generative AI, its ability to generate content that is indistinguishable from human-created output and to break down communication barriers between humans and machines reflects a major advancement with potentially large macroeconomic effects.
However, the report also acknowledges potential downsides to the widespread adoption of generative AI technology. For example, if generative AI delivers on its promised capabilities, the labour market could face significant disruption.
Using data on occupational tasks in both the US and Europe, the report finds that roughly two-thirds of current jobs are exposed to some degree of AI automation, and that generative AI could substitute up to one-fourth of current work. Extrapolating these estimates globally suggests that generative AI could expose the equivalent of 300 million full-time jobs to automation globally.
However, it is important to note that these estimates are based on extrapolations from data on occupational tasks in the US and Europe, and may not be applicable in all regions or industries.
Which jobs are most at risk?
The report provides a framework for assessing the impact of AI on different jobs based on the exposure of importance- and complexity-weighted tasks to automation.
According to Exhibit 8 from the report, jobs for which at least 50% of importance- and complexity-weighted tasks are exposed to automation are likely to be substituted by AI, while jobs with an exposure of 10-49% are more likely to be complemented, and jobs with a 0-9% exposure are unlikely to be impacted.
Emerging work types
According to a recent study by economist David Autor and co-authors using Census data, 60% of workers today are employed in occupations that did not exist in 1940. This implies that over 85% of employment growth over the last 80 years is explained by the technology-driven creation of new positions.
The report also notes that generative AI has the potential to create new work types that do not currently exist, such as jobs related to developing and maintaining AI systems, as well as jobs in industries that may be transformed by AI technology. However, it is important to note that the specific nature and number of emerging work types will depend on a variety of factors, including the capabilities and adoption timeline of generative AI technology.
How can organisations prepare for disruption?
The report provides some suggestions for how businesses can prepare for potential disruption caused by generative AI automation. These include:
- Investing in training programs: Businesses can invest in training programs for employees whose jobs are at risk of automation. This can help employees develop new skills that are in demand and enable them to transition to new roles within the company.
- Exploring new business models: Businesses can explore new business models that leverage generative AI technology to create new products and services. For example, they could use generative AI to develop personalized content or to automate customer service interactions.
- Collaborating with policymakers: Businesses can collaborate with policymakers to develop policies that support workers who are impacted by automation. This could include policies such as retraining programs, unemployment benefits, or wage subsidies.
- Fostering a culture of innovation: Businesses can foster a culture of innovation that encourages employees to experiment with new technologies and ideas. This can help them stay ahead of the curve and adapt more quickly to changes in the labour market.
Potential downsides to the widespread adoption of generative AI technology
- Disruption in the labour market: As mentioned earlier, generative AI has the potential to automate various tasks that were previously done by humans. This could lead to significant disruption in the labour market, with many workers losing their jobs or having to transition to new roles.
- Bias and discrimination: Generative AI algorithms are only as unbiased as the data they are trained on. If the training data is biased or discriminatory, then the resulting output will also be biased or discriminatory.
- Privacy concerns: Generative AI algorithms can generate highly realistic content that can be difficult to distinguish from human-created content. This raises concerns about privacy and security, as it could be used to create fake news or impersonate individuals online.
- Ethical considerations: The use of generative AI technology raises ethical considerations around issues such as ownership of generated content, accountability for errors or mistakes made
The potential economic benefits of generative AI are significant. However, as highlighted in the Goldman Sachs research note, the widespread adoption of generative AI technology also poses potential downsides, including disruption in the labour market, bias and discrimination, privacy concerns, and ethical considerations. To mitigate these risks, businesses can prepare for potential disruption caused by automation through investing in training programs, exploring new business models, collaborating with policymakers, and fostering a culture of innovation.
Policymakers, businesses, and society as a whole will need to work together to ensure that the benefits of this technology maximised while addressing potential risks and challenges. Brave New World is more appealing than 1984.