The rise of generative AI and possible effects on the economy

Authors

DOI:

https://doi.org/10.18559/ebr.2023.2.732

Keywords:

Artificial Intelligence, AI, Large Language Models (LLM), Generative AI, business models, disruptive technology

Abstract

The aim of the paper is to analyse the likely implications of Generative AI (GAI) on various aspects of business and the economy. Amid the rapid growth and maturing of Generative AI technologies such as Large Language Models (like ChatGPT by OpenAI) a rapid growth of both immediate and potential applications can be seen. The implications for the economy and industries of this technological shift will be discussed. The foreseeable scenarios for the level and types of adoption that GAI might achieve - from useful analytical tool, invaluable assistant to the white-collar workers of the world to being trusted with a wide array of business and life-critical decision making. Both disruptive and premium service opportunities are foreseen. For instance general purpose models may provide quality service – such as copywriting – to overserved customers leaving human writers as the premium option. In this context, overserved customers would be those who would be satisfied with a non-human, potentially less creative content. On the other hand highly specialized models – specifically trained in a given domain and with access to proprietary knowledge can possibly provide a premium service over that provided by human experts. It is expected that some jobs will be replaced by new AI applications. However new workplaces will emerge. Not only the obvious expert-level data scientist roles but also low grade, “model supervisors” – people training the models, assessing the quality of responses given and handling escalations. Lastly new cybercrime risks emerging from the rise of GAI are discussed.

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Published

2023-07-20

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Section

Research article- regular issue

How to Cite

Orchard, T., & Tasiemski, L. (2023). The rise of generative AI and possible effects on the economy. Economics and Business Review, 9(2). https://doi.org/10.18559/ebr.2023.2.732

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