Techno-Managerial Twin Transition Challenges Confronting ESMA Strategy: Digitalization, Decarbonization, and Depoliticization

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🔬研究者:Offers a critical framework linking AI/ML, ESG ratings, and deglobalization, useful for STS and political economy scholars.

🏢実務担当者:Highlights risks of relying on AI-generated ESG scores; encourages due diligence and transparency.

🏛政策担当者:Cautions regulators about unintended consequences of AI adoption in financial oversight, especially regarding ESG ratings.

Increasingly, ultrafast (opaque) AI-digitalization intensifies the stress from the collision of (existential) climate crisis 'critical uncertainties' and 'geoeconomic fragmentation'. Their fragile intersectional sustainability focuses attention on how AI-machine learning (ML) algorithmic-based, techno-managerial capitalist dynamics and digital-driven finance aggravate 'deglobalization'. Straining the European Securities and Market Authority's (ESMA) capacity to execute its Strategy 2023-28, this paper contends, it jeopardizes Europe's green transition and UN SDGs/Agenda 2030. Specifically, I analyze how algorithmic/automated decision-making (ADM) conflicts plague ESMA Strategy's principal thematic drivers: a) enabling sustainable finance; b) facilitating technological innovation and effective data use. Assessing EU/ESMA's data science and techno-managerial modalities reveals the positive/negative externalities of sustainable finance AI-ML anticipatory technologies for European decarbonization and SDG success. First, ESMA's green transition facilitation and investment oversight entails ensuring ESG rating quality and integrity, especially curbing (AI) 'greenwashing'. Nonlinear climate catastrophes, societal inequalities/upheaval, or wars escape capture through market (ergodic) risk-dominant ESG rating econophysics, which ill-informs futurity financialization. ESG score-assimilated AI-ML, I argue, widely institutionalizes dubious technoscientific measures, AI 'hallucinations', plus systematic sustainability failures. ESG data scarcity increases its AI-ML synthetic modelling and (automatic) hyperparameter optimization. Moreover, EU's/ ESMA's green transition conundrums are exacerbated by Strategy facilitation of technological innovation and effective data usage. Rather than AI catalyst, frequently, regulation lags innovation. Europe's official response is the most comprehensive and ambitious to date. But failing to address serious AI/ADM distortions entangling sovereign/ESG ratings, ESMA may reinforce automated (neoliberal) quant dominance and sanction the predatory financial firepower against its democracies, and SDGs. Rather than exploit potential AI/ADM investment strategies for collective EU purposes, this paper explores how suspect ESMA techno-managerial modalities expose countries to critical imbalances. Bridging business management/OS, economic sociology/STS, and political economy, I problematize how controversial ESG ratings-integrated AI-ML threatens systemic failures fueling nationalist backlash and ecosystems collapse: deglobalization.

• openaire https://doi.org/10.2139/ssrn.6684618first seen 2026-07-09 04:37:14