Table of Contents
- Introduction
- Why Investigate AI's Risks to Animals?
- The Harm Framework: 5 Types of AI Harm to Animals
- Intentional Illegal Harms
- Intentional Legal Harms
- Unintentional Direct Harms
- Unintentional Indirect Harms
- The Harm of Omission
- Who Has a Seat at the Table?
- Recommendations for AI Governance
- Final Thoughts
Introduction
As humans continue finding new ways of applying artificial intelligence to their lives, an important question is being raised: what about the impact on non-human animals?
A research paper by Coghlan and Parker (2023) considers both the intentional and unintentional ways that AI can harm animals. It develops a "harm framework" that outlines the intentional, unintentional, direct, and indirect ways that AI may negatively impact animals — providing a clear basis to design and regulate AI technologies while considering animal welfare.
This blog is based on a peer-reviewed study from Coghlan, S. & Parker, C. (2023), originally published December 11, 2023. While the research is a few years old, its framework is increasingly relevant as AI adoption accelerates.
Why Investigate AI's Risks to Animals?
Throughout history, human technologies have tended to both help and harm animals. For example, while advanced farming machinery eliminated the need for animals to pull heavy loads, the development of modern factory farms has led to the mass confinement, exploitation, and slaughter of billions of animals annually.
The researchers outline three main reasons to investigate the risks that AI technologies pose to animals:
- Ethically — Animals are sentient and possess moral value
- Interdependence — Humans and non-humans are interdependent, so AI technologies that harm non-humans may harm humans (and vice-versa)
- Overlooked — Thus far, AI ethics has largely overlooked animals or only considers their well-being as far as it's instrumental to humans' well-being
"Animals are sentient and possess moral value. Humans and non-humans are interdependent, so AI technologies that harm non-humans may harm humans (and vice-versa)."
— Coghlan & Parker (2023)The Harm Framework: 5 Types of AI Harm to Animals
The researchers' framework is based on the work of animal welfare scientist David Fraser and includes five types of possible harms that AI can inflict on animals:
1. Intentional Illegal Harms
Under this category, illegal AI technologies may be designed to harm animals, or legal AI technologies may be misused in an illegal or socially condemned way.
Examples:
- Drones may trace animals for the illegal wild animal trade
- Drones used to track animals for conservation purposes could be hacked by poachers
The same AI tools designed to protect animals can be turned against them when hacked or misused by bad actors.
2. Intentional Legal Harms
AI technologies may be designed to harm animals in a way that society generally accepts.
Examples:
- The agriculture industry might use AI that supports or reinforces factory farming methods
- Researchers may create technologies to enable animal testing
These harms are "intentional" because the technology is designed to achieve an outcome, and "legal" because society currently accepts the practice — but that doesn't make them ethically neutral.
3. Unintentional Direct Harms
AI technologies that are designed to benefit society may unintentionally harm animals because they disregard or overlook them.
Examples:
- AI devices that collect underwater garbage may accidentally harm certain aquatic species
- AI may make a mistake — an automated feeding device may fail to provide enough food for the animals who rely on it
Even AI systems built with good intentions can cause harm if animal welfare isn't part of the design process from the start.
4. Unintentional Indirect Harms
Generally beneficial AI can also indirectly harm animals. This can occur:
- Materially — AI may emit carbon and contribute to climate change
- Epistemically — Algorithmic systems may reinforce the anthropocentric bias of meat-eating or the use of animals for entertainment
- Through distancing — If AI technologies distance animals from their caretakers, humans may struggle to read and interpret the animals' needs
Indirect harms are often the hardest to see — and the hardest to regulate — because they emerge from the cumulative effects of many systems rather than a single decision.
5. The Harm of Omission
According to the authors, choosing not to invest in and develop AI to benefit animals results in another type of harm.
Examples:
- AI has the potential to eliminate the use of animals in research
- AI could help find suitable plant-based meat alternatives
But such technologies can only happen with investment and support. In other words, the absence of beneficial AI is itself a harm.
Who Has a Seat at the Table?
The authors argue that whether or not AI harms animals depends on who has a seat at the table as these technologies are being developed and regulated.
"Farming technologies created by big agriculture will likely have a much different purpose than technologies created by farmed animal advocates. As such, it's necessary for advocates to play an active role in the AI sector to speak on behalf of animals and their needs."
— Coghlan & Parker (2023)This is a critical insight for anyone working in AI development, policy, or ethics. The interests of animals won't be represented unless someone is explicitly advocating for them.
Recommendations for AI Governance
As we continue to make society aware of the full breadth of harms that AI can pose to humans and animals, the authors recommend:
- Design specific AI principles addressing animal welfare
- Include animals in AI guidelines — not just as an afterthought
- Address animal welfare in laws and regulations targeted at AI systems
- Ensure animal advocates have a seat at the table in AI development and policy discussions
- Invest in AI for animal benefit — not just AI that might harm them
The framework provides a practical tool for regulators, developers, and advocates to systematically evaluate how AI systems might affect animals — intentionally or not.
Final Thoughts
AI doesn't have to be a threat to animals — but without conscious effort, it easily could be. The Coghlan & Parker harm framework gives us a way to think about the risks more clearly and to build AI systems that consider animal welfare from the start.
Key takeaways:
- Ethical foundation — Animals are sentient and possess moral value
- Interdependence — Harm to animals often means harm to humans
- Five harm types — Intentional illegal, intentional legal, unintentional direct, unintentional indirect, and harm of omission
- Who's at the table matters — AI outcomes depend on who's shaping the technology
- Regulation needed — Specific AI principles and laws addressing animal welfare
- Investment matters — AI for animal benefit requires deliberate support
- Proactive approach — Design AI with animal welfare in mind from the beginning
If your organization is developing or deploying AI systems and wants to ensure responsible, ethical AI practices, contact SystemLogicIT for expert guidance across the United States and United Kingdom.