Skip to main content
MIT AI Risk Initiative
BackUnintentional: indirect
Home/Risks/Coghlan & Parker (2023)/Unintentional: indirect
AI harms animals due to mistake or misad…
Indirect Material Harms

Unintentional: indirect

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

Coghlan & Parker (2023)

SourceDOI
Category
Risk Domain
6Socioeconomic & Environmental
6.6Environmental harm

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 impacts human or ecological systems in ways that ultimately harm animals"(p. 12)

Entity— Who or what caused the harm

Human

Due to a decision or action made by humans

AI system

Due to a decision or action made by an AI system

Other

Due to some other reason or is ambiguous

Intent— Whether the harm was intentional or accidental

Intentional

Due to an expected outcome from pursuing a goal

Unintentional

Due to an unexpected outcome from pursuing a goal

Other

Without clearly specifying the intentionality

Timing— Whether the risk is pre- or post-deployment

Pre-deployment

Occurring before the AI is deployed

Post-deployment

Occurring after the AI model has been trained and deployed

Other

Without a clearly specified time of occurrence

Supporting Evidence (1)

1.
"The possible unintentional and indirect harms of AI are manifold. While digital technologies are often perceived primarily as immaterial, they do have real but indirect material impacts on ecological systems (Brevini, 2022; Crawford, 2021a; Taffel, 2022). And while there has been considerable attention to the unintentional indirect effects of AI by disrupting civility, democracy, and discourses that support human dignity, there has been little attention to the possibility that animals can be indirectly affected by civility, democratic gov- ernance, and ethical discourses. That is, AI-enabled system can cause epistemic and representational harms to animals as well as humans."(p. 13)

Sub-categories (3)

Indirect Material Harms

"AI proliferation causes harm to the environment through energy use and e-waste thereby destroying animal habitat"

6.6 Environmental harm
AI systemUnintentionalPost-deployment

Harms from Estrangement

"Replacement by AI of human observation and interaction leads to neglect of certain interests"

6.6 Environmental harm
AI systemUnintentionalPost-deployment

Epistemic Harms

"Algorithmic recommender systems reinforce and amplify anthropocentric bias or desire of some people for animal cruelty as entertainment — leading to greater harm to animals through reinforcement of meat eating from factory farms, cruel uses of animals for entertainment, etc"

6.6 Environmental harm
AI systemUnintentionalPost-deployment

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

Intentional: socially condemned/illegal

6.6 Environmental harm
HumanIntentionalPost-deployment

Intentional: socially condemned/illegal > AI intentionally designed and used to harm animals in ways that contradict social values or are illegal

6.6 Environmental harm
HumanIntentionalPost-deployment

Intentional: socially condemned/illegal > AI designed to benefit animals, humans, or ecosystems is intentionally abused to harm animals in ways that contradict social values or are illegal

6.6 Environmental harm
HumanIntentionalPost-deployment

Intentional: socially accepted/legal

6.6 Environmental harm
HumanIntentionalPost-deployment

Unintentional: direct

6.6 Environmental harm
OtherUnintentionalOther

Unintentional: direct > AI is designed in a way that shows ignorant, reckless, or prejudiced lack of consideration for its impact on animals

6.6 Environmental harm
HumanUnintentionalPre-deployment
View all 11 risks from this paper →