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Indirect Material Harms

Harm to Nonhuman Animals from AI: a Systematic Account and Framework

Coghlan & Parker (2023)

Sub-category
Risk Domain

The development and operation of AI systems causing environmental harm, such as through energy consumption of data centers, or material and carbon footprints associated with AI hardware.

"AI proliferation causes harm to the environment through energy use and e-waste thereby destroying animal habitat"(p. 12)

Supporting Evidence (2)

1.
"Infrastructure supporting AI is materially impactful, and the effects of climate change may be the most significant. AI models are often computationally expensive and generate significant carbon emissions (Coeckelbergh, 2021; Schwartz et al., 2020), causing potentially massive effects on living things."(p. 19)
2.
"AI applications can also accelerate personalised advertising, fuelling further production and consumption of material goods. They can help locate the hardest to find fossil fuels, build better factories, and intensify existing impacts of indus- trial technology. Such outcomes heighten climate change and habitat loss (Clutton- Brock et al., 2021)."(p. 19)

Part of Unintentional: indirect

Other risks from Coghlan & Parker (2023) (11)