A Review of the Knowledge Worker as Prompt Engineer: How Good is AI at Societal Analysis and Future Predictions?

Klaus Solberg ()
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Klaus Solberg: Halmstad University

Foresight and STI Governance (Foresight-Russia till No. 3/2015), 2024, vol. 18, issue 2, 6-20

Abstract: What is the literature on AI missing for prompting engineering so far, and how good are these services at Societal Analysis and Future Predictions? A literature review and laboratory tests were conducted using different AI services. This study provides an extensive list of research gaps based on an analysis of existing literature. Furthermore, it demonstrates that AI with well-crafted prompts performs as well as or better than senior intelligence analysts in Societal Analysis and Future Predictions. The literature and analysis make it clear that the role of the prompter, to ensure reliability, must be divided into two parts: Prompt Engineering and Information Quality Control (IQC), which in this context is distinct from Prompt Answer Engineering. This study also proposes a working process in the form of a model for using AI in information or intelligence gathering. Additionally, it outlines the rationale for why top managers’ salaries are likely to decrease as a result of these developments.

Keywords: prompt engineering; AI; ChatGPT; Crystal Bowl Conundrum; total intelligence society; knowledge worker; information worker; intelligence analyst; competitive intelligence; business intelligence; market intelligenceJournal: Foresight and STI Governance (search for similar items in EconPapers)
JEL-codes: O33 (search for similar items in EconPapers)
Date: 2024
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