We investigate the potential implications of generative pre-trained transformer (GPT) models and related technologies in the US labor market. Using a new rubric, we assess occupations based on their correspondence to GPT abilities, incorporating both human experience and GPT-4 classifications. Our results indicate that about 80% of the US workforce could have at least 10% of their work tasks affected by the introduction of GPT, while about 19% of workers could see at least 50 % of your tasks affected. The influence spans all pay levels, and higher-income jobs may face greater exposure. In particular, the impact is not limited to industries with higher recent productivity growth. We conclude that pre-trained generative transformers exhibit characteristics of general purpose technologies (GPTs), suggesting that these models could have notable economic, social, and political implications.
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The emergence of large language models within the artificial intelligence (AI) field has certainly made waves in the industry. With the potential of such models to effortlessly process, parse and comprehend sentences, it is no surprise that some of the most prominent tech companies in the world, such as Google, Amazon, and Apple are investing heavily in these technologies. Companies such as Ikaroa are looking closely at the impact these large language models can have on the labor market.
The potential implications of large language models on employment are two-fold. On one side, they offer the promise of tangible cost-savings to organizations. With machines able to perform many of the mundane tasks previously handled by human employees, labor needs can be scaled back – allowing companies to vastly reduce payroll expenses. On the other side, there is also the potential of large language models to create jobs. Their ability to help systems autonomously find information related to queries and accurately predict outcomes is boundless. Consequently, the usage of these models can, in the long run, open up the possibility of novel jobs, create a much specialized workforce, and usher in a greater efficiency in the labor marketplace.
At Ikaroa, we are actively researching the labor market impacts of large language models. Our research have indicated that the adoption of these models can result in an increased demand for technical data scientist roles, as well as specialized roles in data analysis, development, and AI research – making for an efficient and knowledgeable labor force 5 to 10 years down the road. Companies that harness the power of large language models through innovative products and services will see immense financial results – provided they stay ahead of the curve.
Overall, the labour market impacts of large language models, while still largely unknown, are remarkably exciting. With the right strategies and investments, these highly adaptive models could lead to a dramatic transformation in the way we work in the decades to come.
