The Potential Impact of Disruptive AI Innovations on U.S. Occupations

• URL: http://arxiv.org/abs/2507.11403v1
• Date: Tue, 15 Jul 2025 15:20:09 GMT
• Title: The Potential Impact of Disruptive AI Innovations on U.S. Occupations
• Authors: Munjung Kim, Marios Constantinides, Sanja Šćepanović, Yong-Yeol Ahn, Daniele Quercia,
• Abstract summary: We calculate the disruption index of 3,237 U.S. AI patents (2015-2022)<n>Our analysis reveals that consolidating AI primarily targets physical, routine, and solo tasks.<n>By contrast, disruptive AI affects unpredictable and mental tasks, particularly in coastal science and technology sectors.
• Score: 4.616985737735413
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The rapid rise of AI is poised to disrupt the labor market. However, AI is not a monolith; its impact depends on both the nature of the innovation and the jobs it affects. While computational approaches are emerging, there is no consensus on how to systematically measure an innovation's disruptive potential. Here, we calculate the disruption index of 3,237 U.S. AI patents (2015-2022) and link them to job tasks to distinguish between "consolidating" AI innovations that reinforce existing structures and "disruptive" AI innovations that alter them. Our analysis reveals that consolidating AI primarily targets physical, routine, and solo tasks, common in manufacturing and construction in the Midwest and central states. By contrast, disruptive AI affects unpredictable and mental tasks, particularly in coastal science and technology sectors. Surprisingly, we also find that disruptive AI disproportionately affects areas already facing skilled labor shortages, suggesting disruptive AI technologies may accelerate change where workers are scarce rather than replacing a surplus. Ultimately, consolidating AI appears to extend current automation trends, while disruptive AI is set to transform complex mental work, with a notable exception for collaborative tasks.

Related papers

• A roadmap for AI in robotics [55.87087746398059]
  We are witnessing growing excitement in robotics at the prospect of leveraging the potential of AI to tackle some of the outstanding barriers to the full deployment of robots in our daily lives.<n>This article offers an assessment of what AI for robotics has achieved since the 1990s and proposes a short- and medium-term research roadmap listing challenges and promises.
  arXiv  Detail & Related papers  (2025-07-26T15:18:28Z)
• Superintelligence Strategy: Expert Version [64.7113737051525]
  Destabilizing AI developments could raise the odds of great-power conflict.<n>Superintelligence -- AI vastly better than humans at nearly all cognitive tasks -- is now anticipated by AI researchers.<n>We introduce the concept of Mutual Assured AI Malfunction.
  arXiv  Detail & Related papers  (2025-03-07T17:53:24Z)
• Adapting to the AI Disruption: Reshaping the IT Landscape and Educational Paradigms [0.0]
  Artificial intelligence (AI) signals the beginning of a revolutionary period where technological advancement and social change interact. This essay addresses the opportunities and problems brought about by the AI-driven economy as it examines the effects of AI disruption on the IT sector and information technology education.
  arXiv  Detail & Related papers  (2024-09-01T09:39:25Z)
• Towards the Terminator Economy: Assessing Job Exposure to AI through LLMs [10.844598404826355]
  One-third of U.S. employment is highly exposed to AI, primarily in high-skill jobs requiring a graduate or postgraduate level of education.<n>Even in high-skill occupations, AI exhibits high variability in task substitution, suggesting that AI and humans complement each other within the same occupation.<n>All results, models, and code are freely available online to allow the community to reproduce our results, compare outcomes, and use our work as a benchmark to monitor AI's progress over time.
  arXiv  Detail & Related papers  (2024-07-27T08:14:18Z)
• Artificial intelligence and the transformation of higher education institutions [0.0]
  This article develops a causal loop diagram (CLD) to map the causal feedback mechanisms of AI transformation in a typical HEI. Our model accounts for the forces that drive the AI transformation and the consequences of the AI transformation on value creation in a typical HEI. The article identifies and analyzes several reinforcing and balancing feedback loops, showing how the HEI invests in AI to improve student learning, research, and administration.
  arXiv  Detail & Related papers  (2024-02-13T00:36:10Z)
• Brief for the Canada House of Commons Study on the Implications of Artificial Intelligence Technologies for the Canadian Labor Force: Generative Artificial Intelligence Shatters Models of AI and Labor [1.0878040851638]
  As with past technologies, generative AI may not lead to mass unemployment. generative AI is creative, cognitive, and potentially ubiquitous. As AI's full set of capabilities and applications emerge, policy makers should promote workers' career adaptability.
  arXiv  Detail & Related papers  (2023-11-06T22:58:24Z)
• Managing extreme AI risks amid rapid progress [171.05448842016125]
  We describe risks that include large-scale social harms, malicious uses, and irreversible loss of human control over autonomous AI systems. There is a lack of consensus about how exactly such risks arise, and how to manage them. Present governance initiatives lack the mechanisms and institutions to prevent misuse and recklessness, and barely address autonomous systems.
  arXiv  Detail & Related papers  (2023-10-26T17:59:06Z)
• Fairness in AI and Its Long-Term Implications on Society [68.8204255655161]
  We take a closer look at AI fairness and analyze how lack of AI fairness can lead to deepening of biases over time. We discuss how biased models can lead to more negative real-world outcomes for certain groups. If the issues persist, they could be reinforced by interactions with other risks and have severe implications on society in the form of social unrest.
  arXiv  Detail & Related papers  (2023-04-16T11:22:59Z)
• Acceleration AI Ethics, the Debate between Innovation and Safety, and Stability AI's Diffusion versus OpenAI's Dall-E [0.0]
  This presentation responds by reconfiguring ethics as an innovation accelerator. The work of ethics is embedded in AI development and application, instead of functioning from outside.
  arXiv  Detail & Related papers  (2022-12-04T14:54:13Z)
• Examining the Differential Risk from High-level Artificial Intelligence and the Question of Control [0.0]
  The extent and scope of future AI capabilities remain a key uncertainty. There are concerns over the extent of integration and oversight of AI opaque decision processes. This study presents a hierarchical complex systems framework to model AI risk and provide a template for alternative futures analysis.
  arXiv  Detail & Related papers  (2022-11-06T15:46:02Z)
• Trustworthy AI: A Computational Perspective [54.80482955088197]
  We focus on six of the most crucial dimensions in achieving trustworthy AI: (i) Safety & Robustness, (ii) Non-discrimination & Fairness, (iii) Explainability, (iv) Privacy, (v) Accountability & Auditability, and (vi) Environmental Well-Being. For each dimension, we review the recent related technologies according to a taxonomy and summarize their applications in real-world systems.
  arXiv  Detail & Related papers  (2021-07-12T14:21:46Z)
• Building Bridges: Generative Artworks to Explore AI Ethics [56.058588908294446]
  In recent years, there has been an increased emphasis on understanding and mitigating adverse impacts of artificial intelligence (AI) technologies on society. A significant challenge in the design of ethical AI systems is that there are multiple stakeholders in the AI pipeline, each with their own set of constraints and interests. This position paper outlines some potential ways in which generative artworks can play this role by serving as accessible and powerful educational tools.
  arXiv  Detail & Related papers  (2021-06-25T22:31:55Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.