I’ve spent 15+ years working in animal advocacy (including 5 years as the Australia & New Zealand Outreach Manager for Vegan Outreach and 2 years running a vegan digital marketing agency) and am now working at the intersection of AI safety and animal advocacy, where I strive to address the urgent and under-addressed challenge of speciesism in AI.
By combining my expertise in animal advocacy and artificial intelligence, I developed VEG3, the world’s first AI assistant dedicated to helping both individuals and organisations be more effective in advocating for animals and navigating a vegan lifestyle.
I also run Open Paws, a nonprofit organisation dedicated to training and deploying animal-aligned AI systems, empowering animal-friendly organizations to integrate AI into their operations, and advocating for the widespread adoption of animal-alignment in all AI systems.
Through this work, we hope to create a future where artificial intelligence respects all sentient life, simultaneously protecting animals whilst reducing existential risks to humanity.
Sam Tucker
It’s important to emphasise how much our actions as a movement influence those odds. We’re not just bystanders, our strategies, dedication, and execution all play a role. That’s why I’ve given a range of probabilities based on the actions we take as a movement. Each individual member has the power to decide their level of contribution—0% or 100%—so that probability is something everyone can decide for themselves.
You’re right about the balance needed with optimism. Over-optimism about one solution, like cultivated meat, can hinder exploration of other options. But optimism about our overall goal is a different story. It leads to self-fulfilling prophecies: if we don’t believe ending factory farming is possible, we automatically decrease the probability. But if we believe it’s possible and that our actions determine the outcome, we massively increase our chances of success.
Yes, I use an LLM for almost everything I write. I usually draft my ideas and then refine them through a conversation with the LLM, making them clearer and easier to understand. This saves me time and improves the quality of my writing. I’m also autistic and sometimes find it challenging to get the right tone across in my writing, and LLMs helps me with that too.
By “ending factory farming,” I mean a 95% reduction in animals raised in intensive industrial farming operations globally by 2060. Predicting the likelihood of this is complex, but I’d estimate it as:
10-30% if we continue with current strategies and resource allocation.
Pros: Growing veganism, plant-based options, investment in alternatives, and public awareness are all positive signs.
Cons: Cultural habits around meat consumption, powerful industry lobbies, and potential increased meat consumption in developing countries pose serious challenges.
35-50% if we effectively leverage exponential technologies and focus on strategic leverage points.
Pros: AI-powered advocacy shows promise, and targeting key global hubs can create ripple effects. The movement itself appears to be entering a phase of rapid growth, and history suggests society tends to expand its moral circle over time.
Cons: AI advocacy may need a strong global movement to be effective across diverse cultural contexts. The identified leverage points may not be as influential as predicted, and preventing animal agriculture from leveraging those same technologies to compete is crucial.
55-70% if we achieve exceptional movement coordination and execute optimally on key interventions.
Pros: Combining exponential social movement growth with technological advancement creates immense potential for rapid change. AI advocacy is proving effective, and a systems-level approach generates powerful feedback loops.
Cons: Achieving and sustaining global coordination is incredibly difficult. Unforeseen consequences, potential loss of momentum, and adaptation by the industry are all risks.
These are rough estimates, and many unknowns could influence the outcome. It’s easy to get caught up in predictions, but the future of factory farming rests in our hands. Our strategies, dedication, and ability to overcome challenges will ultimately determine success or failure.
Instead of fixating on a fixed probability, we should adopt a mindset of radical responsibility.
Every animal advocate can shift the odds. Imagine two extremes:
Scenario 1: Complacency. We lose focus, funding dries up, infighting weakens the movement, and opportunities are squandered. The probability of ending factory farming plummets towards 0%.
Scenario 2: Optimal Execution. We embrace technology, forge alliances, and execute flawlessly. We inspire millions, drive innovation, and hold industry accountable. The probability of success skyrockets towards 100%.
The reality will fall somewhere in between. But the key takeaway is this: we are not passive observers, we are active participants in shaping the future for animals.
One major obstacle I see is the slow rate of adoption of AI by animal advocates. Currently, about 50% of animal advocates rarely or never use AI in their work: https://www.openpaws.ai/research-and-reports/report-on-the-use-of-ai-in-animal-advocacy
Funding is another major obstacle, we clearly don’t have the resources to compete with animal agriculture on computing power. That’s why I think our best bet is open sourcing models and data (which animal agriculture won’t do because they give them a competitive advantage) and leveraging the power of a passionate community to improve our models, rather than “throwing money at the problem”.
Whilst it’s not really an issue of exponential growth not applying to animal advocates, one other major concern is that exponential growth can also apply to the animal agriculture industry, as @GoodHorse413🔸 pointed out. I think that’s a threat we should take very seriously as a movement and something we should aim to disrupt through a combination of lobbying for legislative changes and engaging in corporate campaigns to restrict or ban various uses of AI in factory farms and slaughterhouses.
I agree that these technologies are also being used by the animal agriculture industry and that represents a very serious threat to the animal protection movement. A large part of my theory of change involves taking actions to slow the adoption of these technologies in animal agriculture whilst increasing them in animal protection, but I thought that was outside of the scope of this post given how long it already was.
I spoke about this fairly extensively at the International Animal Rights Conference though and if you’re interested in learning more about how we can address that threat, here is a link to the recording of the talk.
I understand the appeal of focusing on immediate, measurable reductions in animal suffering and the disillusionment many animal advocates feel regarding our ability to achieve our ultimate goal as a movement. But I believe that limiting our ambition to merely “reducing suffering” in the short term undersells the potential of this movement, risks complacency, and most importantly, fails to capitalize on the momentum we are currently experiencing.
To elaborate further on why maintaining the goal of ending factory farming is crucial, and how it is indeed an achievable goal, I’ve written a separate post outlining the key factors contributing to our potential success. These factors include:
The Achievability of Ending Factory Farming in Our Lifetime: This is possible due to the exponential growth of the animal advocacy movement, coupled with technological advancements (especially in AI), and the adoption of systems-level thinking.
Exponential Growth is Key: Social change often follows an S-curve, and the movement to end factory farming is entering a phase of rapid acceleration. We must harness this momentum.
AI Can Revolutionize Advocacy: AI has the potential to personalize messages, identify key influencers, accelerate research, and generate persuasive content, dramatically increasing our effectiveness.
Systems-Level Thinking Maximizes Impact: By focusing on influencing key institutions and decision-makers, we can create ripple effects throughout society, leading to widespread change.
Strategic Hubs Amplify Change: Concentrating our efforts on just 20 influential cities can transform global perceptions and practices related to factory farming.
While acknowledging the importance of immediate suffering reduction, we must not lose sight of our ultimate goal: ending factory farming. By embracing technological advancements, strategic thinking, and the power of exponential growth, we achieving this ambitious goal within our lifetime is entirely possible.
My point was that the 10-70% range reflects different outcomes depending on the actions we take, not just optimism as a feeling or a belief. Optimism can certainly motivate us to act, but without those actions, it has little to no impact on the actual probabilities.
It seems our main disagreement lies in how we view these probabilities. I see them as dynamic and heavily influenced by the actions we take as a movement, while you seem to view them as more static and inherent to the situation, essentially outside of our control.
I think that’s an extremely important distinction because it fundamentally shifts how we approach this challenge. If we believe the odds are fixed, we become passive observers, resigned to whatever fate has in store. But if we recognise our power to influence those odds through strategic action, technological innovation, and effective execution, we become active participants in creating the future we want. This empowers us to take responsibility, to strive for optimal solutions, and to push beyond the limitations of the status quo.
To better understand your perspective, could you provide your estimated probabilities for ending factory farming by 2060, considering these scenarios:
Scenario 1: Complacency. We maintain the status quo, with minimal changes to our current approach. We fail to identify and effectively target the key pressure points within the system, and we don’t create the necessary feedback loops to amplify our impact and hinder the growth of industrial animal agriculture.
Scenario 2: Moderate Improvement. We make incremental progress in our strategies and adoption of new technologies, but we don’t fully capitalize on opportunities for exponential growth. We achieve some success in identifying and influencing key pressure points, but our efforts are not comprehensive or optimally coordinated.
Scenario 3: Optimal Execution. We proactively identify and exploit every opportunity for exponential growth within the movement. Simultaneously, we precisely target the most influential pressure points within the system and create powerful feedback loops that accelerate our progress while hindering the expansion of industrial animal agriculture. We achieve maximum coordination and efficiency, fully leveraging every available resource and opportunity with optimal strategic foresight.
I’m really interested in seeing how your probabilities compare across these scenarios, especially for scenarios 2 and 3. While 1-5% might seem understandable (albeit quite pessimistic) for scenario 1, where we assume minimal change, it seems considerably less likely that those odds wouldn’t drastically increase with the improved strategy and execution described in scenarios 2 and 3.
To put it into perspective, imagine a basketball team with a 1-5% chance of winning a game. If they then acquire a star player, develop a brilliant new strategy, and execute it flawlessly, wouldn’t their chances of winning increase substantially? Similarly, in the fight against factory farming, if we effectively leverage exponential technologies, coordinate our efforts optimally, and execute our strategies with precision, it seems almost impossible that our probability of success wouldn’t see a major boost.