Taxing a specific industry like AI is problematic as it invites lobbying and creates definitional ambiguity. A more effective and equitable approach is broad tax reform, such as eliminating the capital gains deduction, to create a fairer system for all income types, regardless of the source industry.
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The AI industry and the US government both require trillions in funding. This creates a paradox: the more successful AI becomes, the more it erodes the white-collar tax base by automating jobs, forcing the Treasury to borrow even more and intensifying the competition for scarce capital.
Congressman Ro Khanna proposes a tax on the total net worth of individuals with over $100 million. Unlike an income or capital gains tax, this targets unrealized wealth, forcing the liquidation of assets like stocks to generate the cash needed to pay the tax.
Emad Mostaque argues that the math for a tax-funded Universal Basic Income (UBI) doesn't work. Providing even a poverty-level UBI in the U.S. would cost $5 trillion, the entire federal tax base. Corporate taxes from AI giants wouldn't come close, necessitating a fundamental rethinking of how money is created and distributed.
Following Amazon's model, AI-native companies will reinvest all available cash into acquiring more compute power for a competitive edge. They will operate in a perpetual land-grab mode and never need to show a profit, making them impossible to tax effectively and rendering corporate taxation an obsolete funding mechanism for the state.
Tax policy is a reflection of societal values. By taxing capital gains at a lower rate than ordinary income, the U.S. tax code inherently suggests that wealth generated from existing money (assets, stocks) is more valuable or 'noble' than wealth generated from work and labor.
The US tax system disproportionately penalizes high-income 'workhorses' (e.g., doctors, lawyers) who earn from labor. In contrast, the super-rich, who derive wealth from capital gains and have mobility, benefit from loopholes that result in dramatically lower effective tax rates.
Even if AI drives productivity, it may not fuel broad economic growth. The benefits are expected to be narrowly distributed, boosting stock values for the wealthy rather than wages for the average worker. This wealth effect has diminishing returns and won't offset weaker spending from the middle class.
Advocating for a single national AI policy is often a strategic move by tech lobbyists and friendly politicians to preempt and invalidate stricter regulations emerging at the state level. Under the guise of creating a unified standard, this approach effectively ensures the actual policy is weak or non-existent, allowing the industry to operate with minimal oversight.
Instead of attacking wealth, a more effective progressive strategy is to champion aggressive, 'hardcore' capitalism while implementing high, Reagan-era tax rates on the resulting gains. This framework uses the engine of capitalism to generate wealth, which is then taxed heavily to fund public investments in infrastructure and education, creating a virtuous cycle.
Since taxing profitless AI companies is impossible, a new system is needed. Instead of redistribution, money creation itself must be re-engineered. Capital could be generated and injected directly to individuals for simply existing and participating in the economy, fundamentally changing how money enters circulation.