For Donald Trump’s “AI tsar”, America risks “losing the race to artificial intelligence” because of “excess pessimism” and a framework considered too restrictive. David Sacks, White House special advisor on AI and cryptocurrencies, calls for massive deregulation in order to preserve American competitiveness, even if it means brushing aside the social, environmental and ethical issues raised by the accelerated development of these technologies.
Is the “AI Tsar” afraid of failing… his revolution? A novice in the world of Washington politics, entrepreneur David Sacks quickly exceeded expectations to become a member of the Trump administration the most influential. Officially chairman of the council responsible for guiding the president on science and technology, he is in fact considered Donald Trump’s Mr. AI and cryptocurrencies, navigating between political role and experience as a technological investor.
Sacks returned to the subject, on the sidelines of the Davos forumto denounce “the pessimistic vision of AI”, which imagines that artificial intelligence without limits could have a negative impact on humanity and even cause a collapse of society. According to him, this pessimism constitutes a “self-inflicted wound” on the part of the United States. “We generally see that in Western countries there is much less optimism about AI,” David Sacks said Wednesday in a conversation with Marc Benioff, CEO of Salesforce.
The Edelman Trust Barometer confirmed this observation in 2025, revealing that Americans were more pessimistic than most other world populations in the face of AI. The tech investor expressed fear of a “wave of pessimism” fueled by excessive regulation. He was referring in particular to Senator Bernie Sanders’ call for a moratorium on the construction of data centers.
“If we have 1,200 different AI laws in different states that are holding back innovation, I fear we will lose the AI race,” David Sacks commented to Marc Benioff, highlighting the risk that regulatory rigidity could cause the United States to fall behind in the field of artificial intelligence.
In the United States, however, AI raises several major risks. On a social level, it threatens employment in many sectors, accentuates inequalities and can reinforce bias or facilitate the dissemination of disinformation. Also ecologically, AI models and data centers consume enormous amounts of energy, increasing the carbon footprint and pressure on resources.
On the economic level, moreover, it concentrates wealth and power between a few tech giants, weakens small businesses and destabilizes certain traditional markets, while exposing the economy to cyberattacks and automated manipulation.
A liberal line on AI
Table of Contents
- 1. A liberal line on AI
- 2. Economy and geopolitics
- 3. What are the environmental and ethical implications of Trump’s proposal too appoint an ‘AI czar’?
- 4. Trump’s “AI Czar” and the Perilous Path of Unchecked Optimism
- 5. The “AI Race” Narrative: A Dangerous Simplification
- 6. The Illusion of Pure Optimism
- 7. The Ecological Footprint of AI
- 8. The Need for a Holistic Approach
Not enough to change David Sacks’ guideline. Since taking office a year ago, Donald Trump has adopted a decidedly liberal approach to the development of AI. In his action plan published last summer, his administration dismantled many regulations governing artificial intelligence research, breaking with the government approach of the Biden era, which involved stricter federal control.
In December, a presidential decree went even further, weakening safeguards at the state level and asserting that AI’s global dominance depended on the freedom of American companies to “innovate without excessive regulation.”
During the Davos Forum, David Sacks reaffirmed this line, criticizing any state intervention deemed excessive. In a interview granted at CNBC, he notably denounced the Californian project of billionaire wealth tax (a single tax of 5% on total assets residents with more than a billion dollars, which will be put to a vote in November) as an example of a counterproductive measure in the face of innovation and the competitiveness of American companies.
Economy and geopolitics
“If they get away with this, there will be a second and third time, and it will mark the start of something new in the country,” he said. Critical of the Californian project, he joins other rich expatriates like Larry Page and Sergey Brin, denouncing a potential abuse of power by the state in question.
In the United States, the debate on AI goes well beyond partisan divisions. If Donald Trump and his advisor, David Sacks, plead for a deregulated approach in order to stimulate innovation and maintain American competitiveness, other voices call for stricter supervision. In December, Florida Governor Ron DeSantisfor example, called for greater oversight over the construction of data centers, while a bipartisan House of Representatives committee studied the impact of AI in primary and secondary education.
Although some Republicans have warned of the risk of hampering innovation with overly restrictive regulations, there is consensus on the dangers of exposing children to AI. This debate more broadly reflects the race for supremacy in artificial intelligence, pitting Silicon Valley giants, Washington policymakers and Chinese competition against each other, and highlights the tensions between rapid innovation and national security.
What are the environmental and ethical implications of Trump’s proposal too appoint an ‘AI czar’?
Trump’s “AI Czar” and the Perilous Path of Unchecked Optimism
Donald Trump’s recent pronouncements regarding artificial intelligence – specifically, his insistence on appointing an “AI czar” and warnings that America risks “losing the AI race” due to “excess pessimism” – are sparking debate. While a degree of competitive drive is understandable, the framing of AI development as solely a race, coupled with a dismissal of legitimate concerns, is deeply problematic. This isn’t simply about technological advancement; it’s about navigating a revolution with profound social and ecological consequences.
The “AI Race” Narrative: A Dangerous Simplification
The rhetoric of an “AI race,” ofen pitting the US against China, fuels a relentless push for innovation at any cost.This overlooks crucial considerations:
* Ethical Development: Prioritizing speed over ethical guidelines risks embedding bias into AI systems, perpetuating and amplifying existing societal inequalities.Algorithmic bias in areas like loan applications, criminal justice, and healthcare is already a documented issue.
* Job Displacement: The rapid automation driven by AI is projected to displace millions of workers across various sectors. Ignoring this reality and focusing solely on economic gains is a recipe for social unrest. The manufacturing sector, already impacted by automation, faces further disruption.
* National Security Concerns: While Trump frames AI dominance as a national security imperative, the unchecked development of autonomous weapons systems (AWS) presents a meaningful threat to global stability. The debate surrounding “killer robots” highlights the urgency of international regulations.
The Illusion of Pure Optimism
Trump’s dismissal of “pessimism” isn’t a call for balanced assessment; it’s a silencing of critical voices. Genuine concerns about AI’s potential downsides aren’t negativity, they’re responsible foresight.
Consider these points:
- Data Privacy: AI systems rely on vast amounts of data, raising serious privacy concerns. The Cambridge Analytica scandal serves as a stark reminder of how personal data can be exploited.
- Misinformation & Manipulation: AI-powered deepfakes and refined disinformation campaigns pose a threat to democratic processes. The 2024 US Presidential election saw increased instances of AI-generated propaganda.
- Concentration of Power: The development and control of AI are currently concentrated in the hands of a few powerful tech companies. This creates a potential for monopolies and undue influence.
The Ecological Footprint of AI
Often overlooked in the “AI race” is the considerable environmental cost. training large language models (LLMs) like GPT-4 requires immense computational power, translating to significant energy consumption and carbon emissions.
* Energy demand: A single training run of a large AI model can consume as much energy as several households over a year.
* Water Usage: Data centers, essential for AI operations, require vast amounts of water for cooling. This poses a strain on water resources, particularly in arid regions.
* E-Waste: The rapid obsolescence of hardware used for AI development contributes to the growing problem of electronic waste.
The Need for a Holistic Approach
A truly successful AI strategy isn’t about winning a race; it’s about responsible innovation. This requires:
* Robust Regulation: Governments need to establish clear ethical guidelines and regulations for AI development and deployment. The EU AI Act is a pioneering example,though its effectiveness remains to be seen.
* Investment in Reskilling: Preparing the workforce for the changing job market requires significant investment in education and reskilling programs. Focus should be on skills that complement AI, such as critical thinking, creativity, and emotional intelligence.
* Lasting AI Practices: Prioritizing energy efficiency, reducing water usage, and promoting responsible e-waste management are crucial for mitigating the environmental impact of AI.
* Public Dialog: Fostering open and informed public discussions about the societal implications of AI is essential for building trust and ensuring that AI benefits everyone.
The appointment of an “AI czar” isn’t inherently problematic, but thier mandate must extend beyond simply accelerating innovation. They must prioritize ethical considerations, social obligation, and environmental sustainability. Blind optimism, as championed by Trump, risks steering us towards a future where the benefits of AI are overshadowed by its unintended consequences. The future of AI isn’t about if we win the race, but how we run it.
