Does ‘Woke’ AI Actually Exist?

President Donald Trump’s recent ban on ‘woke AI’ in White House operations has sparked debate and raised questions about the nature of artificial intelligence. This article will delve into what ‘woke AI’ purports to mean, examine whether major AI models truly exhibit such biases, and explore the far-reaching implications of this executive order for AI development and deployment within government and industry.

The White House Executive Order and the Concept of ‘Woke AI’

On July 23, 2025, President Trump signed an executive order titled ‘Preventing Woke AI in the Federal Government‘ as part of a broader AI action plan. The White House fact sheet states that President Trump is ‘protecting’ Americans from ‘biased’ AI systems that sacrifice accuracy for ideological purposes.

The order bans federal agencies from contracting with tech companies that operate AI chatbots displaying partisan bias, which the action defines as diversity, equity, and inclusion, critical race theory, and ‘transgenderism’, forces that the order says pose ‘an existential threat to reliable AI’. This marks the first time the U.S. government has explicitly attempted to shape the ideological behavior of AI systems through federal procurement policies.

The focus seems to be entirely on chatbots and generative AI. It’s hard to say how an AI that monitors an organization’s cloud or extracts data from PDFs could be considered ‘woke’.

Defining ‘Woke AI’ from the Administration’s Perspective

While the term ‘woke AI’ itself is not explicitly defined within the executive order’s legal text, the White House has equated it with AI outputs that support concepts like diversity, equity, and inclusion (DEI) at the cost of accuracy. The order established that any AI company doing business with the federal government must be free of ‘ideological dogmas such as DEI‘.

The new executive order cites an incident where ‘one major AI model changed the race or sex of historical figures,’ when Google’s AI image generator last year produced pictures that showed the founding fathers of the U.S. and Nazi soldiers as Black. Such examples have been cited by Trump allies as evidence of intentional bias programmed into AI systems.

The administration’s definition of prohibited content includes the suppression or distortion of factual information about race or sex, manipulation of racial or sexual representation in model outputs, and the incorporation of concepts such as critical race theory, transgenderism, unconscious bias, intersectionality, and systemic racism.

AI Bias and ‘Wokeness’

Experts generally agree that AI models do not possess beliefs or biases in the human sense, but they can exhibit systematic leanings influenced by their training data, feedback, and instructions. Some argue there’s ‘no such thing as woke AI’, only AI that may discriminate or that works for all people. AI models are trained on vast datasets scraped from the internet, which inherently contain the biases and contradictions present in human language and online content.

The very concept of ‘woke’ is subjective and contentious, having originated in the Black community to signify awareness of racial injustice but subsequently co-opted by conservatives as a pejorative term for progressive ideals.

Achieving absolute objectivity in AI could be considered a ‘fantasy’, as language itself is never neutral. The challenge lies in distinguishing between legitimate bias mitigation efforts and what the administration characterizes as ideological manipulation.

Tech Companies, Political Alignment, and Environmental Concerns

The Shifting Stance of Big Tech

Once seen as embracing Diversity, Equity, and Inclusion (DEI) and ‘woke capitalism’, many mega-corporations in the U.S. tech sector are now turning away from this language, particularly with Trump’s return to the White House. Meta and Amazon are re-evaluating diversity initiatives in response to shifting political and legal landscapes in the U.S.

Major technology companies have made significant financial commitments to Trump’s administration. Google and Microsoft each contributed $1 million to Donald Trump’s inauguration fund, joining the ranks of other prominent tech companies. The CEOs of several of the world’s biggest technology companies attended President Trump’s inauguration, including the leaders of Amazon, Google, Meta, Tesla, TikTok, and OpenAI.

The shift in corporate positioning is evident in policy changes. Google, which has cloud-computing contracts with federal agencies, announced in February that it would retire its aspirational hiring targets following Trump’s executive orders. However, some companies are maintaining their commitments, while Apple and Microsoft have reaffirmed their commitment to DEI.

The Environmental Cost of AI and ‘Greenwashing’

The demand for AI is creating significant environmental challenges for tech companies. The computational power required to train generative AI models that often have billions of parameters can demand a staggering amount of electricity, which leads to increased carbon dioxide emissions and pressures on the electric grid. Data centres and data transmission networks are already responsible for 1% of energy-related greenhouse gas emissions, with data centre electricity usage expected to double by 2026, and AI set to generate a 160% increase in demand for data centre power.

Perhaps most damaging to any claims of being “woke” or environmentally conscious, major AI companies engage in systematic greenwashing that undermines their social responsibility credentials. Companies including Meta, Google, Microsoft and Apple could be emitting 7.623 times more greenhouse gases than they admit to. Amazon, Microsoft and Meta are concealing their actual carbon footprints, buying credits tied to electricity use that inaccurately erase millions of tons of planet-warming emissions from their carbon accounts.

This environmental deception directly contradicts the principles of social awareness and responsibility that ‘woke’ ideology supposedly represents. Microsoft recently secured 3.5 million carbon credits in a deal with Re.green, aiming to offset its rising AI-driven carbon emissions rather than reducing actual emissions. Such practices reveal how AI companies prioritize profit and growth over genuine environmental stewardship, making claims of progressive values ring hollow.

Future Implications for AI Development and Deployment

Shifts in Federal Procurement and Vendor Relationships

The executive order mandates that large language models (LLMs) procured by federal agencies must adhere to “truth-seeking” and “ideological neutrality” principles. Vendors will be required to disclose their LLM’s system prompts, specifications, and evaluations to demonstrate compliance, though not necessarily sensitive technical data.

Non-compliance could result in contract termination, with decommissioning costs charged to the vendor. This introduces a significant new regulatory hurdle for tech companies seeking government contracts. As noted by Brookings researchers, this directive puts strong pressure for companies to self-censor in order to stay in the government’s good graces and keep the money flowing, effectively coercing the industry into a culture war battle.

The financial stakes are substantial. The AI industry is projected to be worth $2 trillion by 2030, and federal AI contracts represent billions in potential revenue for tech companies. This creates powerful incentives for compliance, regardless of companies’ internal views on diversity and inclusion principles.

Impact on AI Innovation and Bias Mitigation

Civil rights advocates express concern that this order will compel the tech industry to abandon years of effort dedicated to combating racial and gender biases embedded within AI systems.

Experts warn of a potential ‘chilling effect’ on developers, who may feel pressured to align model outputs and datasets with White House rhetoric to secure federal funding, potentially slowing innovation. The challenge extends beyond technical implementation to fundamental questions about AI development priorities.

The notion of achieving complete ‘ideological neutrality’ in AI is seen as unworkable by some experts, as political and factual objectivity can be highly subjective. The broader concern is that government intervention in AI development could stifle the kind of diverse perspectives and approaches that have historically driven technological innovation.

Setting a Precedent for Algorithmic Ideology Policing

This executive order sets a precedent for direct U.S. government intervention in shaping AI’s ideological outputs, drawing comparisons to China’s efforts to ensure AI tools reflect the ruling Communist Party’s values. Critics argue that by defining liberal political beliefs and even certain groups of people as “inherently biased,” the order threatens free speech and could violate the First Amendment.

Concerns exist that AI companies might proactively rework their training data to align with the directive.

The Trump administration’s broader ‘AI Action Plan’ signals a national priority shift towards building AI infrastructure, cutting ‘red tape’, and enhancing national security, potentially at the expense of addressing societal risks. The long-term effectiveness of this order in achieving its stated goals and the implications for future administrations attempting to control AI’s ‘ideology’ remain a key area of observation.

Conclusion

The concept of ‘woke AI,’ as defined by the White House, highlights deep-seated tensions between technological advancement, political ideology, and societal values. While AI models reflect the biases of their human creators and training data, the push for ‘ideological neutrality’ through executive action raises complex questions about free speech, innovation, and governmental influence. The future of AI development will undoubtedly be shaped by how industry and policy navigate these contentious and evolving definitions.