Uploaded April 2024 | Updated September 2026, 2 weeks ago
One of the central paradigms in the current AI field is that once intelligent systems become advanced enough, they will solve our problems and society will benefit from these intelligent technologies. However, many of the current problems we face, such as the acceleration of environmental breakdown, have been a result of the same Euro-Western system of scientific knowledge and neo-liberal ideals that have shaped the definition of what this intelligence entails.
Within AI systems, you might recognize these ideals in optimizing or solving problems related to immediate short-term economic benefit for a selected group, while often ignoring systemic or long-term effects for all. Even though ethical or human-centered AI research exists, it is often restricted to research on the bias of datasets or increasing the explainability of model outcomes, and ignores the more political and social aspects of AI technology. After an introduction to these perspectives on AI, we try to shift away from this neoliberal capitalist worldview and shift our focus to various other perspectives, such as degrowth, feminist, indigenous wisdom, and systems thinking.
As the layers of neo-liberal influence on AI become apparent, how would some fundamental aspect of AI change, both in its functioning, application, and theoretical framework? Would AI still be of use when we start from principles of these various other perspectives and do not see AI as a technical fix for systemic problems?
#systems #systemschange #ai #anthropology #history #economy
One of the central paradigms in the current AI field is that once intelligent systems become advanced enough, they will solve our problems and society will benefit from these intelligent technologies. However, many of the current problems we face, such as the acceleration of environmental breakdown, have been a result of the same Euro-Western system of scientific knowledge and neo-liberal ideals that have shaped the definition of what this intelligence entails.
Within AI systems, you might recognize these ideals in optimizing or solving problems related to immediate short-term economic benefit for a selected group, while often ignoring systemic or long-term effects for all. Even though ethical or human-centered AI research exists, it is often restricted to research on the bias of datasets or increasing the explainability of model outcomes, and ignores the more political and social aspects of AI technology. After an introduction to these perspectives on AI, we try to shift away from this neoliberal capitalist worldview and shift our focus to various other perspectives, such as degrowth, feminist, indigenous wisdom, and systems thinking.
As the layers of neo-liberal influence on AI become apparent, how would some fundamental aspect of AI change, both in its functioning, application, and theoretical framework? Would AI still be of use when we start from principles of these various other perspectives and do not see AI as a technical fix for systemic problems?
#systems #systemschange #ai #anthropology #history #economy
