AI Veganism: The Rise of Ethical Minimalism in the Digital Age

The concept of veganism—abstaining from animal products for ethical, environmental, or health reasons—has found an unexpected parallel in the digital world. Enter AI veganism, an emerging movement where individuals deliberately avoid artificial intelligence tools and systems on similar principles of ethical consumption.

Just as traditional vegans scrutinise the origins and impact of their food choices, AI vegans are questioning the hidden costs of our increasingly AI-driven lives. This isn't about technological hesitation—it's a conscious consumer choice rooted in ethics, sustainability, and personal well-being.

The Philosophy Behind AI Veganism

Ethical Parallels to Traditional Veganism

Like food veganism, AI veganism is grounded in three big concerns:

Consent and Exploitation: Vegans reject using animals without consent; AI vegans reject training AI on creative work without permission or payment. The 2023 Writers Guild and SAG-AFTRA strikes made this issue headline news.
Environmental Impact: Where vegans highlight animal agriculture's carbon footprint, AI vegans point to the emissions, energy, and water demands of training large models. Training GPT-3, for example, consumed ~700,000 litres of freshwater.
Personal Autonomy: Both movements centre conscious choice. For AI vegans, it's about intentionality—deciding when and where to embrace or reject algorithmic tools.

The Four Pillars of AI Veganism

Emerging research points to four areas driving this philosophy:

Data Exploitation – Creators' works used without consent.
Environmental Impact – Massive carbon, energy, and water demands.
Cognitive Effects – Over-reliance on AI dulling critical thinking.
Social Justice – AI systems reinforcing bias and inequality.

Environmental Concerns: AI's Hidden Carbon Footprint

The numbers are stark:

Energy: Data centres already consume 2–3% of global electricity, projected to rise further as AI adoption accelerates.
Water: Cooling data centres for training large models can require millions of litres.
E-waste: With rapid hardware turnover, AI contributes to a global e-waste crisis projected to hit 120 million tonnes by 2050.

Even efficiency gains may backfire—the rebound effect means more efficient systems often just increase overall use, raising total emissions.

Cognitive Concerns: The Mental Health Dimension

Over-reliance on generative AI may undermine critical thinking.

Reduced analysis: Microsoft Research found users more confident in AI answers showed weaker critical reasoning.
Attention & memory: Constant digital reliance correlates with shorter attention spans and impaired recall.
Neurological changes: Brain imaging shows heavy tech use can reduce grey matter in areas linked to decision-making.

For AI vegans, abstaining becomes a way of preserving cognitive autonomy.

The Speciesism Debate

Philosophically, AI veganism also raises questions about speciesism bias embedded in algorithms.

Studies show language models often rate harm to farmed animals as more acceptable than harm to pets—reflecting human biases. Some ethicists warn that, if AI internalises such hierarchies, it could one day replicate them in how it treats humans.

How AI Veganism is Practised

Much like food veganism, it exists on a spectrum:

Strict AI vegans – avoid AI entirely.
Selective vegans – use only "ethical AI" (transparent, consent-based, environmentally responsible).
Reducetarians – consciously cut down use, like a "flexitarian" approach.

Challenges remain: AI is ubiquitous, often invisible, and difficult to avoid completely. Yet, as with plant-based diets, even partial abstinence can create cultural and market pressure.

The Business & Policy Response

Market Trends: AI-conscious consumers are driving demand for privacy-focused tools (e.g. DuckDuckGo), open-source transparency (e.g. Hugging Face), and greener AI models.

Regulation: The EU AI Act is embedding transparency and environmental standards that align with AI vegan concerns.

Corporate Strategy: Companies are already exploring "ethical AI" as a competitive differentiator—through carbon-neutral operations, transparent training data, and user-centric consent.

Looking Forward

Like veganism itself, AI veganism may remain niche—but its influence could reshape industries far beyond its numbers.

Niche markets: Services branded "AI-free" may emerge.
Mainstream pressure: Tech giants will face increasing calls for transparency and sustainability.
Regulatory support: Ethical abstinence movements often find traction once regulators step in.

The parallel is clear: a once-fringe philosophy can redefine mainstream practices.

Conclusion: A Conscious Choice

AI veganism isn't simply rejection—it's reflection. It forces us to ask:

What are the unseen costs of AI adoption?
How do we weigh convenience against conscience?
What kind of digital society do we want to build?

In the same way food veganism reshaped global markets, AI veganism could reshape the ethics of technology. The ultimate question it poses is simple but profound:

In a world mediated by artificial intelligence, what are we willing to sacrifice for ethical consistency?