Artificial Intelligence and Ten Societal Megatrends: An Exploratory Study Using GPT-3
This paper examines the potential of artificial intelligence (AI) to address societal megatrends, with a specific focus on OpenAI’s Generative Pre-Trained Transformer 3 (GPT-3). To do this, we conducted an analysis using GPT-3 in order to explore the benefits of AI for digitalization, urbanization,...
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Published in | Systems (Basel) Vol. 11; no. 3; p. 120 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Basel
MDPI AG
01.03.2023
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Subjects | |
Online Access | Get full text |
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Summary: | This paper examines the potential of artificial intelligence (AI) to address societal megatrends, with a specific focus on OpenAI’s Generative Pre-Trained Transformer 3 (GPT-3). To do this, we conducted an analysis using GPT-3 in order to explore the benefits of AI for digitalization, urbanization, globalization, climate change, automation and mobility, global health issues, and the aging population. We also looked at emerging markets as well as sustainability in this study. Interaction with GPT-3 was conducted solely through prompt questions, and generated responses were analyzed. Our results indicate that AI can significantly improve our understanding of these megatrends by providing insights into how they develop over time and which solutions could be implemented. Further research is needed to determine how effective AI will be in addressing them successfully, but initial findings are encouraging. Our discussion focuses on the implications of our findings for society going forward and suggests that further investigation should be conducted into how best to utilize new technologies such as GPT-3 when tackling these challenges. Lastly, we conclude that, while there is still much work left to do before any tangible effects can be seen from utilizing AI tools such as GPT-3 on societal megatrends, early indications suggest it may have a positive impact if used correctly. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ISSN: | 2079-8954 2079-8954 |
DOI: | 10.3390/systems11030120 |