The Coevolution of Artificial Intelligence and the Future: A Systematic Analysis of the Theoretical Literature

Document Type : Review Paper

Authors

1 Assistant Professor of Technology Management, Department of Technology Management, CT.C. Islamic Azad University, Tehran, Iran

2 Assistant Professor of Technology Management, ,Department of Technology Management, ST.C., Islamic Azad University, Tehran, Iran

3 PhD student in Technology Management, Tehran Science and Research Branch, Islamic Azad University, Tehran, Iran

Abstract

Over the past decade, AI has evolved from a largely technical technology to a key driver of socio-economic transformation and the redefinition of decision-making and governance. At the same time, futures studies have moved beyond the level of “forecasting” to an approach to understanding technological consequences and responsibly guiding technological development paths. Despite the rapid growth of research, the literature on the intersection of “AI” and “the future” is fragmented and interdisciplinary, often highlighting one of the two orientations of “the future of AI” or “future-making AI” (as a tool for shaping the future and decision-making); therefore, a unified picture of the two-way and co-evolutionary relationship between these two streams and their conceptual evolution is less well presented. The present study uses a mixed (quantitative-qualitative) approach with the aim of mapping the knowledge structure and explaining the theoretical framework of this co-evolution. In the quantitative part, bibliometric data were extracted from the Web of Science and analyzed using the bibliometrics package in the R environment and CiteSpace software to draw the structure of science production, conceptual and citation networks, thematic map and thematic evolution. Then, in the qualitative part, selected articles were analyzed and theoretical concepts and themes were integrated using Sandelowski and Barroso meta-synthesis and coding. The findings of the study include mapping the dominant streams and clusters of literature, formulating a conceptual framework to explain the two-way relationship between “the future of artificial intelligence” and “future-making artificial intelligence,” and extracting policy and governance implications for the responsible use of artificial intelligence in shaping the future. This study also contributes to bridging fragmented debates by offering an integrative, future-oriented perspective for interdisciplinary AI research.

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References

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