Leonelli, Sabina (2025) Environmental Intelligence: Redefining the Philosophical Premises of AI. [Preprint]

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Abstract

As an alternative to the long history of interpreting Artificial Intelligence as the attempt to rationalize and mechanize human ingenuity, thereby transcending nature and its perceived limits, this article proposes an interpretation of the conceptual foundations of Environmental Intelligence as the effort to develop digital technology and data-intensive algorithmic systems to sustain and enhance life on this planet. Thus articulated, EI provides a framework to challenge and redefine the philosophical premises of AI in ways that can explicitly spur the responsible and sustainable development of computational technologies towards public interest goals.

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Item Type:	Preprint
Creators:	Creators Email ORCID Leonelli, Sabina s.leonelli@exeter.ac.uk 0000-0002-7815-6609
Keywords:	Artificial Intelligence; evidence; cognition; environment; planetary health; data science; transdisciplinary research.
Subjects:	General Issues > Data Specific Sciences > Artificial Intelligence > AI and Ethics Specific Sciences > Biology Specific Sciences > Cognitive Science Specific Sciences > Computation/Information Specific Sciences > Artificial Intelligence Specific Sciences > Environmental Science General Issues > Ethical Issues General Issues > Evidence General Issues > Science and Society General Issues > Science Education General Issues > Science and Policy General Issues > Technology General Issues > Values In Science
Depositing User:	Sabina Leonelli
Date Deposited:	06 Aug 2025 12:52
Last Modified:	06 Aug 2025 12:52
Item ID:	26135
Subjects:	General Issues > Data Specific Sciences > Artificial Intelligence > AI and Ethics Specific Sciences > Biology Specific Sciences > Cognitive Science Specific Sciences > Computation/Information Specific Sciences > Artificial Intelligence Specific Sciences > Environmental Science General Issues > Ethical Issues General Issues > Evidence General Issues > Science and Society General Issues > Science Education General Issues > Science and Policy General Issues > Technology General Issues > Values In Science
Date:	2025
URI:	https://philsci-archive.pitt.edu/id/eprint/26135

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