Tag: AI Policy

  • The Data Center Casino: Why America Needs Elected Technology Leaders Now

    By the Founders, Department of Technology | San Diego, California | November 13, 2026

    America needs more data centers. That part is not in dispute. What is in dispute is who decides where they go, who pays for them, and whether anyone is looking at the whole board.

    If the United States wants to remain the world leader in artificial intelligence, it has to build the computing capacity, and the power to run it. We start from that premise. But for several years, officials in both major parties, in red states and blue, have treated new data centers less like public infrastructure and more like a slot machine: pull the lever, hope for a jackpot of investment, tax revenue and ribbon-cuttings, and worry later about who covers the losses.

    The question that has been asked is “how much money can be made?” The question that should be asked is “what is the best outcome for the community that has to live next to this?”

    Three risks pull in three different directions. Build too fast, and we strain an aging grid and inflate a financial bubble. Build too slow, and other countries may make our lead obsolete. Ignore what AI could do to employment, and we erode the tax base a modern society runs on. No one in government is currently accountable for all three at once.

    The casino logic

    Thirty-eight states offer tax incentives to data centers, and at least 28 of them considered scaling those incentives back this year, according to the National Conference of State Legislatures. At least ten states forgo more than $100 million a year in these breaks, with Texas and Virginia each losing as much as $1 billion annually, according to Good Jobs First, as reported by Broadband Breakfast.

    In Ohio, Policy Matters Ohio reports the break cost state and local governments about $2 billion last year, far more than the state had forecast, which led Republican Governor Mike DeWine, who had previously vetoed a repeal, to order a temporary pause.

    The backpedaling is bipartisan, which is exactly the point. In Virginia, 21 Democrats and seven Republicans in the state Senate voted to curtail a 5.3% tax break. Kentucky’s Democratic governor, Andy Beshear, has called for ending his state’s incentives, and Ohio, Arizona, Nebraska and Illinois have paused theirs.

    When lawmakers of both parties are reversing course, the original approach was not a partisan mistake. It was a structural one: the deals were made one project at a time, often in secret (as we noted in our open letter, 25 of 31 Virginia local governments involved in data center development had signed NDAs), and no one owned the cumulative consequences.

    Build too fast: the grid and the bubble

    Our electrical grid is where the cost of speed shows up first. In PJM, the nation’s largest grid market, wholesale power prices jumped almost 76% in the first quarter of 2026 compared with a year earlier, and the market monitor said the price effects on customers were very large and not reversible, according to E&E News.

    Capacity auction prices rose roughly tenfold in two years, from about $29 to $329 per megawatt-day, and the December 2025 auction fell short of its reliability target for the first time, per one analysis of PJM’s results. Ordinary ratepayers are paying for capacity built to serve some of the wealthiest companies in the world.

    Then there is the money behind the buildout. Hyperscalers will spend about $750 billion this year, and they are borrowing heavily to do it, while economy-wide statistics still show little or no productivity growth from AI. Jefferies warns that AI investment was the main driver of U.S. economic growth last year after consumer spending, so a sudden collapse would leave the economy exposed. And The Economist notes that more than half the spending has gone to servers and specialized chips that become obsolete within a few years. A technology can be transformative and still be overbuilt. If that happens, the stranded assets and the unpaid debts will not stay on Wall Street.

    Build too slow: the electron gap

    The opposite risk is just as real. The United States leads in advanced chips but is short on power, while China has the power and is short on chips. BloombergNEF estimates China will add more than six times as much generating capacity as the U.S. over the next five years. Morgan Stanley has forecast a 44-gigawatt shortfall for U.S. data centers within three years, roughly the summertime capacity of New York State. According to calculations reported by The Washington Post, Chinese data centers pay about a third of what American ones do for electricity.

    We cannot answer that gap with moratoriums and lawsuits alone, and we cannot answer it with secrecy and subsidies either. Speed that costs public trust is not speed. As voters showed on November 3, when they favored limits in 40 of 41 local data center measures, communities will stop projects they feel were done to them rather than with them.

    Ignore the jobs: the tax base

    The third risk is the quietest. A RAND analysis found that 84 percent of federal revenue in 2024 came from individual and payroll taxes, both collected from labor income. Because income is concentrated in high-paid white-collar jobs, replacing those roles with AI would hit revenue harder than the headcount suggests, and higher corporate profits would not make up the difference unless corporate tax rates roughly doubled.

    The same logic applies closer to home. New York City’s Comptroller built five AI scenarios for the city’s finances, put a combined 50 percent probability on the three with worse outcomes for jobs, growth or tax revenue, and recommended building a reserve fund to 16 percent of annual tax revenue. Every county and state should be asking the same question before the layoffs arrive, not after.

    Why we need elected technology leaders

    Look at who currently holds a piece of this problem. Utility commissions watch rates. Economic development offices watch ribbon-cuttings. Treasurers watch revenue. Each sees one slice, and none is answerable to voters for the combination. That is how a state can win a data center, lose a billion dollars a year, raise its residents’ power bills and weaken its future tax base, all through decisions that each looked reasonable on its own.

    We are calling for elected technology leaders at the local, county, state and federal levels, with one job: to weigh speed, grid capacity, public cost and long-term fiscal health together, in public. In practice that means:

    • Public plans before approvals. Grid, water and fiscal impact published before a project is approved, not after.
    • No secret deals. Public bodies should not sign NDAs that keep residents from learning what their own governments agreed to.
    • Large users pay for what they trigger. Grid upgrades and capacity costs assigned to the facilities that cause them, not spread across households.
    • Incentives with accountability. Tax breaks tied to measurable jobs and revenue, with clawbacks if the promises are not met.
    • Fiscal readiness for AI displacement. Scenario planning and reserves at every level of government.

    They should be elected, not appointed, because the tradeoffs here are value judgments about whose power bills, whose land and whose jobs, and those belong to voters. And they are needed now because the contracts are being signed now.

    The case against our case

    A fair reading includes the strongest objections.

    • Incentives may be what brings projects at all. The Data Center Coalition’s Dan Diorio argues that revenue estimates overlook the chance a project would never have been built without exemptions, and notes that states with the most growth, including Virginia, Texas and Pennsylvania, offer them, while Colorado, which does not, has less (S&P Global).
    • The electron gap may be overstated. The Brookings Institution cautions that no one knows how many data centers will be needed or how fast chips will become more efficient, and that worries from builders are not the same as geopolitical shocks (Brookings).
    • Job forecasts are uncertain. One UK think tank’s scenarios range from eight million jobs lost to none at all (IPPR), and New York’s Comptroller itself says it is hard to tie current trends to AI with certainty.
    • Another elected office is another layer. Critics may reasonably prefer strengthening utility regulators and legislatures over creating new positions. Our answer is that each existing body owns only a slice, but that is a debate worth having in public.

    Start the conversation

    Neither the casino nor the moratorium is a plan. The country needs people whose job it is to build enough, build in the right places, make the builders pay their share, and prepare for what comes after. That job does not exist yet. We are asking every candidate and every sitting official, of every party, to start the discussion about creating it, at department.technology/.

  • Preemption Without an Owner: Why the Federal-State AI Fight Needs Someone Accountable

    By the Founders, Department of Technology | San Diego, California | November 13, 2026

    Washington is arguing over whether federal law should override state AI rules. Both sides have real arguments. But whoever wins, someone has to enforce the result and answer to voters for it, and right now no one does.

    Few questions in technology policy have produced more heat than federal preemption: whether Congress should replace the growing body of state AI laws with a single national standard. This piece does not argue that preemption is right or wrong. We lay out the strongest case on each side, review what the record shows, and make one claim that holds under either outcome: a national standard, or a patchwork, without a named, accountable owner is not a policy. It is a vacuum.

    The case for a national standard

    Supporters of preemption make an argument that deserves a fair hearing. AI development does not stop at state borders, they say, and companies facing dozens of different rules face rising compliance costs that favor the largest firms. In December 2025, a presidential executive order called for a uniform national framework, directed the Justice Department to challenge state laws it deemed onerous, and tied some federal broadband funding to state policy. Industry groups and senators including Ted Cruz have argued for explicit federal preemption of conflicting state laws, and some supporters now say the longer Congress waits, the harder preemption becomes as more state laws pile up.

    In March 2026, the White House sent Congress a national framework that called for preempting burdensome state AI laws, with exceptions for child safety, general consumer-protection and fraud laws, state procurement and state zoning for AI infrastructure.

    The case against

    Opponents make an equally serious argument. States, they say, are closer to the people affected and can respond faster than Congress, and preemption without enforceable federal protections would leave residents with fewer remedies than they have today. The opposition has been broad. In July 2025, the Senate voted 99 to 1 against a proposed state AI moratorium. When it returned in the defense bill, more than 300 state lawmakers from across the political spectrum urged Congress to reject it, and prominent Republicans including Senator Josh Hawley, Representative Marjorie Taylor Greene and Arkansas Governor Sarah Huckabee Sanders spoke against it. The defense bill text did not include the moratorium, and House Republican leaders were left searching for another vehicle.

    What the record shows

    Whatever one thinks of preemption, the practical result so far is a stalemate. Two attempts to attach it to must-pass bills failed. The White House framework has not become law. By one account, Congress left for its August recess without moving a federal AI framework out of committee. Meanwhile, 29 states enacted AI legislation in 2026, and for the first time both Republican- and Democratic-led states passed laws adding requirements or oversight for data centers.

    The states did not wait for permission, and no one in Washington was positioned to tell them to stop or to give them something better to follow.

    The part both sides already agree on

    Here is the detail that gets lost in the argument. Even the strongest preemption proposals carve out data center infrastructure. The December executive order said legislation should not preempt state laws on data center infrastructure, and the March framework would leave state zoning for AI infrastructure in place. In other words, the people who favor the broadest national standard agree that decisions about where data centers go, how they are powered and who pays remain local and state decisions.

    That has a consequence. Whatever Congress decides about model rules, child safety or algorithmic discrimination, the data center decisions that voters care about most, and that voted on November 3, will be made by city councils, county boards, state utility commissions and legislatures. Those officials are making multibillion-dollar decisions with no technology counterpart whose job it is to see the whole picture.

    Where the owner is missing under each outcome

    • If broad preemption passes, a federal standard replaces state rules. Who enforces it, who updates it as the technology changes, and who do residents call when it fails? Without an accountable federal office, critics of preemption are right that residents lose remedies.
    • If preemption fails, the patchwork grows. Companies face rules that differ by state, and states and counties negotiate against the same few buyers with little shared information. Without a coordinating office, supporters of a national standard are right that the burden falls hardest on smaller firms and communities.
    • If a narrow hybrid passes, federal and state authority meet at a boundary that will be contested. Someone has to be accountable for where that boundary sits and for what falls through it.

    In every case, the missing piece is the same: an office that answers to voters for how the system works as a whole.

    Three tests for any national AI standard

    We take no position on how broad preemption should be. We do suggest three tests for any proposal, from any party:

    1. Is the federal protection enforceable? If a national standard replaces state rules, it should carry real enforcement and clear remedies, not just guidance.
    2. Is there a named, accountable official? Someone should be answerable to voters, and to Congress, for how the standard is administered and updated.
    3. Does it keep data center decisions local and public? Siting, rates and disclosure of public deals should stay with local and state governments, with transparency rules attached.

    And a procedural test: was it debated on its own, with hearings and a public text, instead of inside a must-pass bill?

    The case against our case

    • Accountability can be built into existing agencies. Some will say a regulator or a White House coordinator could play this role without a new elected office. That is a reasonable design, though we think voters should be able to hold someone to account directly.
    • Local decisions are the problem. Some supporters of preemption believe local control over data centers is what slows the buildout, and would prefer more federal permitting authority. The administration has proposed streamlining federal permitting for AI data centers, and reasonable people can weigh that against local consent.
    • It adds a layer. Another layer of officials could slow decisions. We would answer that the status quo already has many layers and no owner, but we welcome the debate.

    The question underneath

    The preemption fight will continue, and we hope it is resolved by open debate and not by rider. But the question underneath it will not go away: when the technology goes wrong, or when it goes right and the gains are not shared, who is responsible? We think the answer should be someone voters can elect, at every level of government. Find our proposal at department.technology/.

  • A Briefing for the New Congress: What the Last Two Years Got Wrong, and What to Do Differently

    By the Founders, Department of Technology | San Diego, California | November 13, 2026

    To the newly elected: you are about to inherit the most consequential technology decisions in a generation, and the last Congress left you a map of what not to do.

    This is not a partisan scorecard. The record we describe below includes members of both parties acting in good faith and members of both parties falling short. Newly elected members of Congress are sworn in this January, and we think you are better served by an honest account of what happened than by a flattering one. We start with what worked.

    What the last Congress got right

    It is easy to say Congress did nothing on data centers. That is not quite true. In July, the House Energy and Commerce Committee passed the Ratepayer Protection Act 52 to 0, a bill from Republican Gabe Evans and Democrat Kathy Castor. In September, the full House passed it 417 to 3 under a procedure that required a two-thirds majority. The bill would require state utility regulators to consider standards that make large data center customers pay the full cost of the grid upgrades built to serve them. In a polarized era, that is a real accomplishment, and it shows what is possible when members start from a problem their constituents can feel: the electric bill.

    Then came the mistakes.

    Mistake 1: Trying to pass the big thing through the back door

    For two years, advocates of a national AI framework tried to move federal preemption of state AI laws by attaching it to must-pass bills. Those efforts, including the defense authorization bill and the 2025 budget reconciliation law, were unsuccessful. Senators rejected a broad preemption proposal 99 to 1. In March 2026, the White House sent Congress a national policy framework that again called for preempting burdensome state laws while carving out areas such as child safety and state zoning for AI infrastructure. By one account, Congress left for its August recess without moving a federal AI framework out of committee.

    The lesson is not that preemption is right or wrong. Reasonable people disagree, and we lay out both sides below. The lesson is that a question this large cannot be settled by rider. It needs its own hearings, its own text and its own public debate.

    Mistake 2: Letting the one agreement become a campaign prop

    The Ratepayer Protection Act did not stall because no one wanted it. It stalled because of how it arrived. On September 30, five weeks before Election Day, the Senate voted 57 to 43 on a procedural motion that needed 60 votes. Only four Democrats voted yes.

    The two sides told different stories, and each has a serious argument:

    • Republican supporters said the bill had passed the House almost unanimously, with Democratic votes and Democratic cosponsors, and accused Senate Democrats of refusing to take yes for an answer for political reasons.
    • Senate Democrats said the bill’s core protection is optional, since states need only consider standards, and offered their own GRID Savings Act to make large customers actually pay for grid upgrades. Senator Schumer called the Republican bill “optional” and toothless.

    We take no side on optional versus mandatory. We do note that Reuters reported Senate Republicans aimed to improve their midterm prospects with the vote, and that the bill arrived at the end of the session, after the Senate had not moved on data centers for months. A measure introduced in July and brought to a test vote in the last weeks before an election will be judged as a campaign move whatever its merits. The practical lesson for new members: if you want a data center bill to become law, negotiate the mandatory-versus-optional question in the spring, not the fall.

    Mistake 3: Solving one slice of a three-part problem

    Even if the Ratepayer Protection Act had passed, it would have addressed one of three risks we described in our earlier piece, “The Data Center Casino.” It deals with who pays for grid upgrades. It does not address how fast we can build power to compete with China, the financial exposure if the AI investment boom turns, or what happens to federal and state revenue if AI displaces high-paid white-collar work. Congress legislated the slice that polls well. No committee is responsible for the whole.

    Mistake 4: Leaving a vacuum for states and for secret local deals

    When Congress does not act, others do. In 2026, 29 states enacted AI legislation, and for the first time both Republican- and Democratic-led states passed laws adding requirements or oversight for data centers. That is encouraging, and it is also a patchwork. Meanwhile, at the local level, many deals are still negotiated under non-disclosure agreements. As we noted in our open letter, 25 of 31 Virginia local governments involved in data center development had signed NDAs. Residents learn about the largest infrastructure project in their county after the decision is made.

    Mistake 5: Nobody owns it

    This is the mistake underneath the others. AI, data centers, the power grid, student data, surveillance and the workforce are governed by a patchwork of committees and agencies. Each handles a slice, and no one is accountable to voters for how the slices fit together. We raised this directly. In February 2025 we submitted a proposal to the White House Office of Science and Technology Policy for a national AI action plan, and in July 2025 we published a response to the plan that followed. We have not had a substantive engagement with either. We mention it not as a complaint, since a good idea should not depend on one administration, but because it illustrates the structural problem: there was no office whose job it was to say yes or no.

    What new members can do in the first 100 days

    1. Hold hearings on the whole picture. Grid capacity, public cost, competitiveness and fiscal impact together, with the same witnesses in the same room.
    2. Settle optional versus mandatory early. Bring Republicans and Democrats who both voted for ratepayer protection into one room and write the version that can reach 60 votes.
    3. Keep big structural questions out of must-pass bills. Preemption, if it happens, should be debated on its own.
    4. Open the deals. Require public disclosure of data center agreements that involve public land, public utilities or public incentives.
    5. Create a single point of accountability. At minimum, a standing joint committee with jurisdiction over the whole question. Ideally, an elected technology leader at every level of government, including a Secretary of Technology at the federal level, whose job is to answer to voters for the combination.

    The case against our case

    A fair briefing includes the strongest objections.

    • Preemption advocates argue a patchwork of state laws slows innovation and that national competitiveness requires one national standard, and they note that the longer Congress waits, the harder preemption becomes as states pass more laws (Broadband Breakfast). Opponents respond that preemption without enforceable federal protections would leave residents with fewer remedies.
    • Optional standards may be the right design. Supporters of the Ratepayer Protection Act argue that utility regulation has long been a state responsibility and that a federal mandate would overreach. Critics respond that voluntary pledges have not been enough.
    • Congress already has committees for this. Some will say the problem is political will, not structure, and that a new office adds a layer. Our view is that structure shapes will: when every committee owns a slice, no one is blamed for the whole. But we welcome the argument.

    The first step

    The new Congress does not need to solve everything in January. It needs to stop treating the central question, who is accountable for the technology buildout, as someone else’s job. Start the conversation about a Department of Technology and elected technology leaders at every level. We will help, and we will be honest with you when we think you are wrong. Find our proposal at department.technology/.

  • Voters Didn’t Reject AI. They Rejected Building It Backward


    By the Founders, Department of Technology | San Diego, California | November 9, 2026


    Voters Didn’t Reject AI in 2026. The ever-increasing number of paid memberships for OpenAI, Anthropic (Claude AI), Google Gemini, and others has proved this to be the case.

    They Rejected Building It Backward.

    On November 3rd, voters across ten states said no to data centers almost every time they were asked. The reason is not that they oppose AI. It is that they have watched the buildout run ahead of the power grid, and they suspect the people steering it are not putting the public first.

    In Ashville, Ohio, the village council had already approved an agreement with a data center developer. Residents petitioned to put it on the ballot anyway. On Election Day, 82% of voters rejected the deal, according to Northeast Ohio reporting by Fox 8.
    Ashville was not an outlier. Ballotpedia counted 41 local data center measures on the November 3rd ballot across 10 states, with Ohio accounting for 21. Voters favored limiting data center development in 40 of the 41. The one exception was Harwood, North Dakota, where voters defeated a proposed review requirement. Voters in Granville, Ohio, approved a ban by 84%. In Urbana, 77% backed one.

    This was not a one-day mood. A Heatmap poll reported by Forbes found more than 70% of Americans would oppose a data center planned for their area, with rising electricity prices the top reason.
    Many voters may not weigh how much national AI leadership depends on new computing capacity. That is a fair criticism, and we take it seriously below. But the voters who showed up made a different judgment, and it deserves a hearing: they believe this buildout is being driven first by profit, with national strategy a distant second, and that their concerns about power bills and the environment were treated as obstacles rather than inputs.
    The comparison with China shows why that suspicion is not irrational.

    What China Did First
    China and the United States are in a race for AI leadership, but they are not running it from the same starting line.
    According to Inside Climate News, China added an estimated 540 gigawatts of generating capacity in 2025, more than 80% of it renewable. The United States added about 54 gigawatts, roughly 60% renewable. Al Jazeera reports that China already generates more than twice as much electricity as the US, and that BloombergNEF expects China to add more than six times as much generating capacity over the next five years.

    Transmission, the high-voltage lines that carry power from where it is made to where it is used, tells the same story. Grid Strategies estimates the US needs roughly 5,000 new miles of high-capacity transmission per year but has averaged only about 600 since 2017, according to Yale Climate Connections. China, by the same report, has been building over 1,000 miles of ultra-high-voltage lines per year. In January, China’s State Grid announced a CNY 4 trillion (about $580 billion) investment plan for 2026 to 2030, up 40% from the prior plan, including 15 new ultra-high-voltage lines, according to Enerdata.

    Getting connected is the other bottleneck. A ChinaTalk analysis finds that the time for a US generation project to connect has grown from under two years in the early 2000s to over four years for projects built from 2018 to 2024. Because China plans generation, transmission, and demand together under state direction, the American concept of a years-long interconnection queue for large loads barely exists there.

    The US leads on the other side of the equation. Stanford’s AI Index counts an estimated 5,427 US data centers in 2025 versus 449 in China. As one analyst quoted by Al Jazeera framed it, the US has the chips and is short on power, while China has the power and is short on chips.

    Cost is where the picture gets less lopsided. Reporting from bne IntelliNews puts Chinese industrial electricity rates roughly in line with the US, at about $0.08 to $0.11 per kilowatt-hour, while Chinese households pay about $0.08 versus $0.15 to $0.17 for American households. The Financial Times reported that Beijing is subsidizing power for data centers using domestic chips down to about 5.6 cents per kilowatt-hour, against a US industrial average of 9.1 cents.

    The Warnings Were Public
    Here is the part voters understand best. The power shortfall was not a secret.

    In its Long-Term Reliability Assessment, the North American Electric Reliability Corporation (NERC) raised its ten-year summer peak demand forecast sharply and said new data centers account for most of the projected growth, with several regions at high risk of supply shortfalls by the end of the decade. This spring, NERC issued a Level 3 alert, its highest tier, over large computational loads like data centers, and found that grid operators cannot reliably model how 77% of operating data center load behaves during grid disturbances, according to reporting by SAN and Utility Dive.

    Grid operators are also being overwhelmed at the front door. Texas’s ERCOT built its process for a large-load queue of 40 to 50 projects, then received 225 new interconnection requests in 2025 alone, about 70% of them data centers, according to the Texas Tribune. ERCOT itself cautions that many requests are speculative and its demand forecast is probably inflated. That caution cuts both ways: it means some projects may never be built, and it also means officials are approving and planning against numbers nobody can fully trust.
    We want to be precise. We are not claiming that officials privately concealed a known shortfall. What the public record shows is that independent grid reliability authorities published escalating warnings, and in many places projects advanced anyway, sometimes under nondisclosure agreements and sometimes over local objections. When voters see that sequence, and then see their bills, they draw a conclusion.

    Why the Bill Concern Is Real, and Why It Is Contested
    The electricity price argument is the most contested part of this debate, so it deserves care.

    In PJM, the grid operator serving 13 states and Washington, DC, capacity auction prices rose from $28.92 per megawatt-day for 2024/25 to $329.17 for 2026/27, roughly tenfold. PJM’s independent market monitor attributed 63% of the increase in the 2025/26 auction to data center demand, about $9.3 billion in added costs recovered from ratepayers, according to analysis by the Institute for Energy Economics and Financial Analysis.
    But capacity charges are only about 10% to 20% of a typical bill, as FactCheck.org notes, and several studies find no clear nationwide link between data centers and household rate increases. A Rutgers policy lab analysis found no statistically significant local bill effect yet, while warning that “not yet” is not the same as “nothing to worry about.” FactCheck.org also cites an estimate that capacity increases added about $18 per month to the average home bill in western Maryland and $16 in Ohio between mid-2025 and mid-2026, with 63% of that tied to data centers.

    The honest summary: the bill effect is real and documented in some regions, overstated in others, and likely to grow if the cost-allocation rules do not change. Voters are reacting to the direction of travel, and the direction is up.

    “Doesn’t Slowing Down Hand China the Win?”
    This is the strongest objection, and it is not frivolous. If China is building power at this scale and pricing it for AI, then any delay in the US could cost real strategic ground.

    But the China comparison cuts against the current approach, not for it. The binding constraint on American AI is no longer chips alone. It is power, transmission, and public consent, and the backlash of November 3rd shows what happens when a project skips the last of those. Projects imposed on unwilling towns get voted down, and every vote down is a delay no strategist planned for.

    We also want to avoid the lazy conclusion that the US should copy Beijing. China’s model rests on centralized, state-directed planning that the US system, with its many jurisdictions and its commitment to local consent, cannot and should not replicate. China’s buildout has its own costs: Oxford Institute for Energy Studies notes it added as much as 80 gigawatts of new coal-fired power in 2025, and Al Jazeera reports a gap between China’s data center capacity and how much of it is actually used. The lesson is narrower and more useful: China treats the grid as infrastructure to be built before the load arrives. We have been building the load and hoping the grid catches up.

    The Fix: Grid First, Public Accountability Always
    The way out is not a moratorium on AI infrastructure and not a free pass for developers. It is a different order of operations. The framework at Department of Technology proposes layered accountability: a confirmed federal Secretary of Technology, and elected technology leaders at the state, county, and local level who answer to the voters whose bills and water supply are on the line. Concretely:
    Grid first. No major data center approval without a utility- or grid-operator-certified plan covering power supply, transmission, and interconnection timing.

    Make the large loads pay. Require large-load tariffs so the full cost of new generation and grid upgrades lands on the facilities that cause it, not on residential ratepayers. Pennsylvania’s governor has moved this direction with an executive order requiring developers to build, bring, or buy their own capacity, and a Republican challenger has pressed for a ratepayer-protection moratorium. This is not a one-party issue.

    Publish the grid impact. Before any rezoning or tax abatement, publish projected power demand, water use, and cost allocation in plain language, and limit NDAs on projects that use public land, money, or incentives.

    Fund the wires. Treat transmission and interconnection reform as national AI infrastructure, because it is. If the United States wants to out-build China on compute, it has to stop being out-built on the grid.

    What Each of Us Can Do
    Congress: Prioritize transmission permitting and interconnection reform, and pass transparency rules for large-load projects.
    Statehouses and utility commissions: Adopt large-load tariffs and grid-readiness tests before approvals, and require public notice before rezoning or tax breaks.
    Candidates and local officials: Answer two questions in public. Who pays for the power this project needs? Where is the grid study that says it can be delivered?

    Voters: Ask every candidate those same two questions, at every level, before the next ballot.

    The Choice
    The United States can win the AI race, but not by asking communities to host the buildout on faith. China’s advantage is not that it has better engineers. It is that it built the power first. If we want national AI leadership, we have to earn it the way voters just demanded: build the grid, make the costs transparent, and put people accountable to the public in charge of the decisions.

    Summary
    Voters in 40 of 41 local data center ballot measures on November 3rd chose limits, and polls show most Americans oppose a data center near them. The backlash is not a rejection of AI. It reflects a buildout that outran the grid, a shortfall that grid reliability authorities publicly warned about, and a bill impact that is real in some regions and contested in others. China built power and transmission first, at a scale and speed the US has not matched, though its model is not one we should copy. The answer is to put the grid first, make the large loads pay, and make the decisions accountable to the people who live with them.
    Sources

  • America Won’t Lose the AI Race to China’s Chips. It Will Lose It to Distrust.

    Voters have already rejected data centers at the ballot box in 2026. The officials building this infrastructure are still hiding deals and holding stakes in the companies they oversee.

    Last week, on November 3rd, 2026, voters delivered a verdict on the AI buildout. They weighed nearly 40 data center-related ballot measures across 10 states, and in Edgewater, Florida, over three-quarters of voters approved a ban on new data centers. This week, ProPublica reported that our United States Secretary of the Interior, Doug Burgum is leading the push to put data centers on public lands while holding between $18.1 million and $64.4 million in AI-company investments, according to an analysis by the advocacy group Save Our Parks.

    Our United States Secretary of the Interior, Doug Burgum says any suggestion that his decisions are driven by personal investments is false. But lawyers told ProPublica his holdings appear to be acceptable under current law. That is the real scandal. If an official can steer national AI policy while holding a stake in the industry he is steering, the problem is the law, not just the official.

    The argument of this piece is simple: America will not lose the AI race to foreign chips. America will lose it to its own distrust, unless the people building our AI infrastructure are accountable to the people who live next to it.

    A Lead That Depends on Power and Public Trust

    The United States still dominates the hardware and capital side of AI. Global data center capacity is projected to grow by 97 GW between 2026 and 2030, effectively doubling, and that buildout could require $3 trillion in investment. China, meanwhile, is closing the capabilities gap and training a large share of the world’s AI researchers.

    Chips are no longer the binding constraint. Energy and public consent are. BloombergNEF estimates a 63 GW gap between what AI chip shipments imply the U.S. should build by 2033 and what energy constraints will allow. A country that cannot power its data centers, or persuade its citizens to host them, will not win this race.

    Washington DC Has Not Built the Grid

    AI is, at bottom, a question of electricity. A serious national defense strategy would fast-track nuclear baseload, advanced renewables, and modernized transmission lines. Instead, Congress has taken only minimal steps to regulate these facilities, and the cost is landing on aging local utility systems and the people who pay for them.

    The Backlash Is Rational

    Gallup found that 71% of Americans oppose an AI data center in their local area, including 48% who are strongly opposed. A later Heatmap Pro poll put strong support at just 4%, down from 13% a year earlier. This is not simple NIMBYism. A majority of Americans, 59%, expect their electricity bills to rise if a data center opens nearby, and these facilities also draw heavily on local water and grid capacity.

    When officials answer this with dismissal, they deepen the problem. Burgum has blamed the mass rejection of data centers on a foreign psyop. Calling public worry about bills and water a foreign plot cannot win the cooperation of the communities that must host the infrastructure of national power.

    Secrecy and Self-Dealing

    Consider Tucson, a drought-stricken city. Amazon Web Services and a developer spent nearly two years negotiating a $3.6 billion, 290-acre data center campus behind NDAs, keeping the public in the dark about projected water usage. Residents learned the details only after the deal was largely set.

    Tucson is not unusual. In Virginia, 25 of 31 local governments involved in data center development had signed NDAs. In Louisiana, records requests found at least 54 NDAs signed by elected officials. This is the pattern we warned about in our analysis of America’s AI Action Plan: data centers sited without local democratic input.

    The conflicts reach the top, too. ProPublica’s database shows more than 320 members of our Trump administration have ties to Alphabet, with large numbers also tied to Nvidia and Meta. Our Secretary of the Interior, Doug Burgum pledged to divest many of his AI investments, but not his stake in Titan Development, a real estate firm that has handled land acquisitions for data centers in the Southwest. And the administration has not completed any environmental reviews for data centers on public lands.

    This is not a one-party problem, and the rules must not be one-party rules. The standards proposed here should apply to every official in every administration, including all members of Congress, the White House and others.

    Reform is starting. Lawmakers in at least ten states have introduced bills to restrict or ban these NDAs, Pennsylvania’s governor has barred them for agencies under his control, and a bipartisan federal bill, the No Secrets for Data Centers Act, would void NDAs signed by officials acting in their official capacity. Industry has a defense: one developer says NDAs protect officials from insider-trading exposure, since a planned campus can count as material non-public information. That argues for narrow disclosure rules and a limited carve-out for genuine trade secrets. It does not justify blanket secrecy over water, power, and tax breaks.

    “Won’t Rules Slow Us Down?”

    The strongest objection is that accountability will slow the buildout and hand China an advantage. The opposite is closer to the truth. Projects imposed on unwilling communities are the ones being voted down, and secrecy is what turns a zoning question into a ballot-box revolt. Transparency is how projects survive.

    The Fix: Accountability at Every Level

    Our AI strategy is currently shaped by appointed officials, zoning boards, and “AI czars” who answer to executives rather than voters. The framework at Department of Technology proposes a permanent Department of Technology with layered accountability:

    • Federal: a cabinet-level Secretary of Technology, nominated by the President and confirmed by the Senate. That gives one accountable official real authority over national AI policy, cybersecurity, and digital infrastructure, with a public confirmation process where conflicts must be disclosed and divestment pledges can be tested.
    • State, county, and local: elected technology leaders. They face voters, and they would decide questions like whether a data center goes up beside a reservoir.

    An elected state secretary of technology or county technology commissioner cannot easily hide behind a corporate NDA when residents are looking at their utility bills and voting on the next term. A federal Secretary who is vetted, confirmed, and held to strict divestment rules would have far less room to wave away grid concerns.

    As we argued in Stop the Litigation Loop, a national AI strategy works best when elected state and local partners help carry it out. Elected officials can be conflicted too, so the office needs disclosure and divestment rules from day one.

    Four Legal Changes, Now

    1. Treat AI infrastructure as defense infrastructure. Foundational models, sovereign compute clusters, and their dedicated power supply should be formally classified as critical to national defense.
    2. Create an AI conflict-of-interest offense, modeled on war profiteering law. Criminalize officials trading stock, holding options, or receiving deferred compensation from AI companies bidding on or serving federal defense and intelligence contracts, including public land leases, where the official has authority over those decisions. Provide a safe harbor for diversified index funds and qualified blind trusts, so the rule targets real conflicts rather than ordinary retirement savings.
    3. Ban NDAs on public-interest infrastructure. Void any NDA that binds public officials or covers projects using public funds, land, or incentives, with a narrow carve-out for real trade secrets.
    4. Require divestment as a condition of office. Anyone overseeing technology, public lands, or energy policy, including the proposed Secretary of Technology, should divest direct holdings in AI and tech companies before taking office. Violations should be prosecuted as threats to national defense, not settled with ethics fines.

    What Each of Us Can Do

    • Congress: pass the No Secrets for Data Centers Act and adopt divestment rules that cover both parties.
    • Statehouses: enact NDA bans like those introduced in at least ten states, and require public notice before any rezoning or tax abatement for a data center.
    • Voters: ask every candidate, at every level, two questions. Will you divest from AI and tech holdings while in office? Will you refuse NDAs on projects that use public land, money, or water?

    The Choice

    Our adversaries will not be stopped by a nation whose officials hold stock in the contractors they oversee, hide deals from the towns that host them, and brush off voters’ concerns about their own bills. To win the algorithmic cold war, we have to build the grid and earn public trust. We also have to make sure those who write AI policy have no stake in the outcome. The voters have already spoken. Now the law has to catch up.

    Summary

    Seven in ten Americans oppose a data center in their community, and the officials deciding where they go may own a piece of the companies building them.

    Gallup found that 71% of Americans oppose an AI data center in their local area, and last week voters made that opposition official, weighing nearly 40 data center-related ballot measures across 10 states. This week, ProPublica reported that the Interior Secretary, who is pushing to build data centers on public lands, holds between $18.1 million and $64.4 million in AI-company investments, according to an analysis by the advocacy group Save Our Parks.

    Interior disputes the characterization, and lawyers told ProPublica the holdings appear to be acceptable under current law. That last part is the heart of our new article; America Won’t Lose the AI Race to China’s Chips. It Will Lose It to Distrust, which argues that our race will be decided by the power grid and public trust as much as by chips, and that trust collapses when local officials sign NDAs that hide water and power costs from their own residents and when officials hold stakes in the industries they oversee.

    This is not a Republican or Democratic problem, and the rules we propose would cover every official in every administration. Imagine being able to see what your town agreed to before the contract is signed, knowing the people overseeing AI and energy policy have no financial stake in the outcome, and having a vote over whether a data center goes up beside your reservoir.

    That future is within reach: lawmakers in at least ten states have introduced bills to restrict or ban these NDAs, and a bipartisan federal bill, the No Secrets for Data Centers Act, would void NDAs signed by officials acting in their official capacity. What the momentum needs is public pressure, and public pressure starts with people knowing what is happening.

    So please share this article today: post it with one sentence on why it matters to your town, send it to your city council member or state legislator, forward it to a neighbor who pays an electric bill, and ask every candidate whether they will divest from AI and tech holdings while in office and refuse NDAs on projects that use public land, money, or water. The voters have already spoken, so help make sure the law catches up at department.technology/.

  • An Open Letter to Every Elected Official in America: Put the Country First

    To the Members of Congress, Governors, State Legislators, County Supervisors, Mayors, and City and Town Council Members of both parties:

    We write as an independent, nonpartisan policy project based in San Diego, California. We belong to no party and take no money from advertisers, PACs, or lobbyists. We are asking for one thing: start the public discussion on establishing a Department of Technology at the local, county, state, and federal levels, as proposed at department.technology/.

    What we did first, and what happened

    We did not begin with an open letter. We began by going directly to the executive branch. In February 2025, the Office of Science and Technology Policy asked the public for input on a national AI Action Plan, and we submitted our proposal by email. When the White House released America’s AI Action Plan in July 2025, we published a response. We welcomed its focus on innovation, infrastructure, and diplomacy, and pointed out the gap in it: no one in the plan is directly accountable to the American people for how it gets carried out.

    Those efforts have not led to any engagement with our proposal. We hold no grudge about that. A good idea should not depend on one administration. It has to be able to survive from one administration to the next, which is why we are now writing to all of you.

    Why this can’t wait

    Technology is no longer a niche subject. It is a daily political reality in your districts.

    We are not raising these points to attack any person or party. The pattern would be a problem under any administration, and the rules we propose cover every official, including every member of Congress.

    AI, data centers, surveillance, student data, autonomous systems, and the power grid are being governed by a patchwork of agencies and appointed officials, with no one in charge and often no one voters can hold accountable.

    What we propose

    A Department of Technology with layered accountability:

    • Federal: a cabinet-level Secretary of Technology, nominated by the President and confirmed by the Senate. That gives the country one accountable official for national AI policy, cybersecurity, and digital infrastructure.
    • State, county, and local: elected technology leaders, so the people deciding how technology is used in your community answer directly to the people who live there, much as an attorney general or district attorney does.

    The full proposals are public and free to use: Legal Guidelines for a Federal Department of Technology, Legal Framework for State, County, and Local Departments, a draft California ballot initiative, and our argument for why this is essential to American AI leadership. They are drafts, offered for debate, and we welcome amendments.

    What we are asking you to do

    You don’t have to agree with every detail. We are asking you to begin the conversation:

    1. Hold a public hearing or town hall on how technology is governed in your jurisdiction and who is accountable for it.
    2. Introduce a resolution calling for study of a Department of Technology, as proposed by us at www.department.technology, at your level of government.
    3. Adopt two interim safeguards now, whichever way the larger debate goes: a ban on NDAs for projects using public funds, land, or incentives, and disclosure and divestment rules for officials who oversee technology, energy, and public lands. A bipartisan federal bill, the No Secrets for Data Centers Act, would void NDAs signed by officials acting in their official capacity, and lawmakers in at least ten states have introduced bills to restrict or ban these NDAs.
    4. Tell us where you stand. If you will support the discussion, or if you have objections, to a Department of Technology, as proposed by us at www.department.technology, we want to hear them and will publish your response with your permission.

    A request across party lines

    This is not a Republican idea or a Democratic idea. Voters in both parties oppose secrecy around local projects, want their utility bills protected, and want to know that the people steering technology policy answer to them. Whoever holds power next year or in ten years will inherit the same questions.

    We are asking you to put the country’s interests ahead of party interests and start this discussion in the open, where voters can take part.

    Respectfully,

    The Founders, Department of Technology
    San Diego, California
    department.technology/

  • Navigating Robotics Regulation: How Departments of Technology Will Lead the Way

    As robotics technology continues to evolve, ensuring its safe and beneficial integration into the hands of consumers, homes, businesses, schools, government, and society in general, will become increasingly important. Departments of Technology (DoTs) at municipal, county, state, and federal levels will play a crucial role in this endeavor. By leveraging frameworks like the AI Legislation Framework, these departments will effectively navigate the complexities of robotics regulation. Here’s a comprehensive look at how a DoT will accomplish this task, addressing the who, what, when, where, why, and how of robotics regulation.

    Who: Key Players in Robotics Regulation

    Municipal, County, State, and Federal Authorities

    The regulation of robotics will involve various levels of government, each with distinct but complementary roles. At the municipal level, local governments will oversee day-to-day interactions between robotics and residents. County governments will coordinate regional efforts, while state governments will establish and enforce broader regulations. The federal government will provide national standards and policy frameworks. Each of these entities will contribute to a cohesive regulatory environment by collaborating and aligning their efforts.

    What: The Focus of Robotics Regulation

    Safety, Innovation, and Ethical Standards

    The primary focus of robotics regulation will be to ensure safety, promote innovation, and address ethical concerns. This will include:

    • Safety Standards: Implementing regulations to ensure robotics operate safely in public and private spaces.
    • Innovation Support: Encouraging technological advancement while balancing regulation to foster growth.
    • Ethical Guidelines: Addressing issues such as privacy, data security, and the impact on employment and society.

    When: Timely Implementation and Updates

    Ongoing Adaptation and Evolution

    Robotics technology and its applications will continually evolve. Therefore, regulation will need to be dynamic and adaptable. According to the AI Legislation Framework, the implementation of regulations will occur in phases:

    • Initial Development: Establish foundational regulations and standards.
    • Ongoing Updates: Regularly review and update regulations to keep pace with technological advancements and emerging issues.
    • Responsive Adjustments: Quickly adapt to unforeseen challenges or opportunities as technology evolves.

    Where: Implementation Across Different Levels

    Local, Regional, State, and National Jurisdictions

    The implementation of robotics regulations will occur at various levels:

    • Municipal Level: Will focus on local ordinances and public safety, ensuring that robotics technologies are integrated smoothly into community life.
    • County Level: Will coordinate regional policies and infrastructure to support robotics deployment and innovation.
    • State Level: Will develop comprehensive regulations and support innovation through funding and research initiatives.
    • Federal Level: Will establish national standards and policies, ensuring consistency across the country and facilitating international collaboration.

    Why: The Importance of Effective Regulation

    Maximizing Benefits While Minimizing Risks

    Effective regulation of robotics will be essential for several reasons:

    • Public Safety: Will ensure that robotics systems are safe for use and do not pose risks to people or property.
    • Economic Growth: Will support innovation and economic development by providing clear guidelines and reducing uncertainty for businesses and investors.
    • Ethical Considerations: Will address ethical concerns related to privacy, data security, and the impact on employment.

    How: Implementing the Framework

    Using the AI Legislation Framework

    The AI Legislation Framework will provide a structured approach for regulating robotics. Here’s how a DoT will utilize this framework:

    Establishing Standards:

      • Municipal Level: Will implement local safety standards and compliance requirements tailored to community needs.
      • County Level: Will develop regional policies and coordinate with municipalities to ensure consistent application of state regulations.
      • State Level: Will create comprehensive state-wide regulations, provide certification processes, and support innovation through grants and research funding.
      • Federal Level: Will develop and enforce national standards, support cross-border collaboration, and address global regulatory challenges.

      Supporting Innovation:

        • Municipal and County Levels: Will facilitate pilot programs and provide local incentives for robotics projects.
        • State Level: Will offer funding and research support to advance robotics technology.
        • Federal Level: Will lead national research initiatives and collaborate on global standards.

        Ensuring Compliance and Adaptability:

          • Regular Reviews: Will continuously review and update regulations based on technological advancements and emerging issues.
          • Feedback Mechanisms: Will establish channels for public and industry feedback to address concerns and improve regulatory processes.

          The Department of Technology, guided by frameworks like the AI Legislation Framework, will play a pivotal role in the regulation of robotics. By coordinating efforts across municipal, county, state, and federal levels, the DoT will ensure that robotics technology is safely and effectively integrated into society. Through careful planning, ongoing adaptation, and collaborative efforts, we will harness the benefits of robotics while addressing its challenges and risks.

          Scenarios

          Discover how our Dot will apply the AI Legislation Framework to ensure safety, drive innovation, and address ethical concerns with our hypothetical scenarios. From local integration to national standards, learn how these strategies will shape the future of robotics. Dive into practical scenarios and see the impact firsthand!

          Scenario 1: Local Robotics Integration

          Situation:
          A city council in a major metropolitan area is preparing to implement a new robotics delivery service. The robots will navigate public sidewalks to deliver packages within the city.

          Implementation:

          • Developing Local Standards: The DoT will work with the city council to establish specific safety and operational standards for the robots. These standards will align with broader state regulations but will address local issues such as pedestrian traffic and urban infrastructure.
          • Compliance and Certification: The robots will undergo a certification process to ensure they meet safety protocols, including obstacle detection and emergency stop functions.
          • Public Engagement: The city will host community workshops to inform residents about the new service, address concerns, and gather feedback on the robots’ integration into public spaces.

          Outcome:
          The robots are successfully integrated into the city, improving delivery efficiency while maintaining public safety. Residents feel informed and engaged, and the technology operates within the established safety standards.

          Scenario 2: Regional Robotics Innovation Hub

          Situation:
          A county is looking to become a leading center for robotics innovation by supporting local tech startups and research institutions.

          Implementation:

          • Research Grants: The DoT will provide grants to local startups and research institutions focusing on robotics advancements that align with the AI Legislation Framework.
          • Pilot Programs: The county will launch pilot programs to test new robotics technologies, such as autonomous farming equipment or robotic assistants for elderly care.
          • Regional Coordination: The DoT will facilitate coordination between neighboring municipalities to ensure that regional policies support innovation while adhering to safety and ethical standards.

          Outcome:
          The county establishes itself as a hub for robotics innovation, attracting investment and talent. The pilot programs help refine new technologies and demonstrate their benefits, fostering a supportive environment for technological advancement.

          Scenario 3: Statewide Robotics Regulation

          Situation:
          A state is developing a comprehensive regulatory framework for robotics that aligns with national standards but addresses state-specific needs.

          Implementation:

          • Creating Statewide Regulations: The DoT will draft and implement regulations covering all aspects of robotics, including safety, operational guidelines, and ethical considerations.
          • Certification and Compliance: The state will establish a certification process for robotics technologies, ensuring that all systems meet the required safety and ethical standards.
          • Support for Innovation: The state will offer funding and resources for robotics research and development, promoting innovation while maintaining rigorous regulatory oversight.

          Outcome:
          The state successfully implements a unified regulatory framework that provides clear guidelines for robotics deployment. Innovation is encouraged through state-sponsored initiatives, while compliance ensures safety and ethical use of technology.

          Scenario 4: National Robotics Standards and Global Collaboration

          Situation:
          The federal government is working on establishing national standards for robotics and collaborating with international bodies to harmonize regulations.

          Implementation:

          • Developing National Standards: The DoT will create and enforce national standards for robotics, addressing safety, ethical guidelines, and operational protocols.
          • International Collaboration: The federal government will engage with international organizations to align U.S. standards with global practices and facilitate cross-border robotics operations.
          • Public Awareness: The DoT will launch national campaigns to educate the public about new regulations and their implications for robotics technology.

          Outcome:
          The national standards provide a consistent regulatory environment across the U.S., and international collaboration helps facilitate global trade and cooperation. Public awareness initiatives ensure that citizens understand and support the new regulations.

          Scenario 5: Public-Private Partnership for Robotics Research

          Situation:
          A private robotics company is developing a new autonomous vehicle technology and seeks to collaborate with government agencies for testing and regulatory approval.

          Implementation:

          • Partnership Agreements: The DoT will establish partnership agreements with the company to facilitate testing under controlled conditions, ensuring compliance with safety and ethical standards.
          • Pilot Testing: The autonomous vehicles will undergo rigorous testing in designated areas to assess their performance and safety in real-world scenarios.
          • Feedback and Adjustment: Based on testing results and public feedback, the DoT will work with the company to refine the technology and adjust regulations as needed.

          Outcome:
          The collaboration results in successful testing and refinement of the autonomous vehicle technology. The technology is introduced to the market with a proven track record of safety and compliance, benefiting both the company and the public.

          Scenario 6: Ethics and Data Security in Robotics

          Situation:
          A robotics company develops a new system that collects and analyzes data on user behavior. Concerns arise about data privacy and security.

          Implementation:

          • Ethical Guidelines: The DoT will establish clear ethical guidelines for data collection and usage, ensuring that privacy concerns are addressed and data security is maintained.
          • Compliance Checks: The company will undergo regular audits to ensure adherence to data protection regulations and ethical standards.
          • Public Transparency: The DoT will require the company to provide transparency reports detailing how data is collected, used, and protected.

          Outcome:
          The company operates in compliance with ethical guidelines, and public concerns about data privacy are addressed through transparency and rigorous data protection measures. This fosters trust and ensures that the technology is used responsibly.

        1. The Politicization of AI.gov: A Missed Opportunity for Genuine Bipartisanship

          Artificial intelligence (AI) is often hailed as the next frontier in technology, with the potential to revolutionize industries, economies, and our daily lives. As such, it demands careful, thoughtful governance—one that transcends party lines and fosters innovation while safeguarding public interests. Unfortunately, the federal government’s AI.gov website, intended to serve as the central hub for AI initiatives in the United States, has become emblematic of a missed opportunity for true bipartisanship.

          The Promise of AI.gov

          When AI.gov was launched in 2018, located online at https://ai.gov/, it held the promise of being a platform that could unite policymakers, technologists, and citizens in a common goal: to ensure that the U.S. remains at the forefront of AI while addressing the ethical, social, and economic challenges that come with it. The site was supposed to be a beacon of transparency, providing unbiased information and fostering an environment where diverse viewpoints could converge to shape the future of AI.

          AI, by its very nature, is a non-partisan issue. It’s a tool—a powerful one—that can be harnessed for the betterment of society or, if misused, can lead to unintended consequences. Given its impact on national security, economic competitiveness, and civil liberties, AI governance should be a collaborative effort across the political spectrum. The potential benefits of AI—such as improving healthcare, enhancing education, and boosting economic productivity—are goals that should resonate with both sides of the aisle.

          The Reality: A Politicized Platform

          However, a closer look at AI.gov reveals that it has strayed from its original mission. Rather than being a neutral platform that welcomes diverse perspectives, the site has increasingly reflected the priorities of whichever administration is in power. This politicization has alienated stakeholders who seek balanced, data-driven insights into AI policy.

          For instance, the site often emphasizes AI initiatives and accomplishments that align with the current administration’s agenda while downplaying or omitting contributions from previous administrations or from experts whose views may not align with the prevailing political narrative. This selective presentation of information not only skews public perception but also undermines the collaborative spirit that is essential for effective AI governance.

          The politicization of AI.gov is evident in the way it frames issues such as AI ethics, data privacy, and national security. Rather than fostering an open dialogue on these complex topics, the site often presents them through a partisan lens, leaving little room for meaningful debate. This approach not only stifles innovation but also erodes public trust in the government’s ability to manage AI in a way that benefits all Americans, regardless of their political affiliations.

          A Missed Opportunity for Bipartisanship

          The politicization of AI.gov is a missed opportunity for genuine bipartisanship. At a time when the U.S. faces stiff competition from other nations in AI development, a divided approach only weakens our position on the global stage. AI is too important to be reduced to a partisan issue; it requires a unified strategy that draws on the best ideas from across the political spectrum.

          Imagine a version of AI.gov that truly embodies bipartisanship. Such a platform would present a balanced view of AI’s potential and its challenges, incorporating insights from a wide range of experts, policymakers, and citizens. It would prioritize transparency, providing clear and accessible information about AI initiatives, funding opportunities, and ethical guidelines. Most importantly, it would foster a collaborative environment where differing viewpoints are not just tolerated but encouraged, leading to more robust and innovative solutions.

          The Path Forward

          To reclaim AI.gov as a platform for genuine bipartisanship, several steps must be taken. First, the site should be depoliticized by ensuring that its content is reviewed and curated by a diverse panel of experts, representing a range of political and ideological perspectives. This would help restore trust in the site’s objectivity and make it a go-to resource for anyone interested in AI, regardless of their political leanings.

          Second, AI.gov should actively seek to engage with stakeholders from across the political spectrum, including those who may have differing views on AI policy. This could be achieved through regular public forums, town hall meetings, and collaborative workshops that bring together policymakers, technologists, and the public to discuss the future of AI in a constructive, non-partisan manner.

          Finally, the site should prioritize transparency by providing clear, accessible information about how AI policies are developed, funded, and implemented. This includes making public all relevant data, reports, and decision-making processes, so that citizens can hold their government accountable and actively participate in shaping AI policy.

          Summary

          AI has the potential to transform our world in profound ways, but only if it is governed wisely. AI.gov was created to be the cornerstone of this effort, but it has fallen short by becoming a politicized platform that reflects the priorities of the administration in power rather than serving as a neutral, bipartisan resource. By depoliticizing AI.gov and fostering a more inclusive, transparent approach to AI governance, we can ensure that the U.S. remains a leader in AI while protecting the interests of all Americans. It’s time to seize the opportunity for genuine bipartisanship and make AI.gov a platform that truly serves the common good.

          Did you know?

          The AI.gov website, serving as the central platform for U.S. federal AI initiatives, must adhere to the highest standards of security, credibility, and neutrality. Hosting this critical government resource on Automattic.com raises significant concerns. Unlike routine commercial or personal websites, which may rely on third-party hosting services like Automattic, a federal website dedicated to AI should be directly managed by federal agencies. This direct oversight is essential to ensure that all content is thoroughly vetted, secure, and authoritative, thereby maintaining public trust.

          Moreover, the importance of cybersecurity in AI cannot be overstated. Given the strategic significance of AI to national security and economic competitiveness, any potential vulnerabilities in hosting could have far-reaching consequences.

          Automattic.com, while a reputable and popular WordPress hosting service based in San Francisco, California, is not designed to meet the stringent security requirements necessary for safeguarding sensitive government information. Relying on such a platform could undermine the integrity and independence of AI.gov, leading to a loss of public confidence and potentially compromising the security of critical data.

          Currently, as of August 2024, the Internet address www.ai.gov is managed by Cybersecurity and Infrastructure Security Agency. Most recent 2024 budget reports state that CISA or Cybersecurity and Infrastructure Security Agency will exceed $3 billion. The hosting company Automattic.com is also known as department.technology/ and has hosting plans starting at $4 a month.

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        2. Biden-Harris Administration’s AI Strategy: Just Another Chapter in a Long History of Inadequate Oversight?

          The Biden-Harris Administration last Spring, announced its latest actions on artificial intelligence (AI), touting voluntary commitments from major tech companies. While this move is framed as progress, a closer look reveals that it’s a continuation of a pattern seen in previous Democratic and Republican administrations—a pattern marked by inadequate oversight and over-reliance on corporate promises.

          Our Concern:

          1. Continued Reliance on Voluntary Commitments: The Biden-Harris Administration, like its predecessors, places heavy reliance on voluntary commitments from tech giants. This approach has been favored by past administrations, including the Obama administration’s focus on self-regulation in the tech industry and the Trump administration’s emphasis on industry-led AI initiatives . These voluntary commitments are non-binding and lack robust enforcement mechanisms, raising serious concerns about accountability. By sticking to this approach, the current administration risks repeating the same mistakes that led to insufficient oversight in the past.
          2. A Bipartisan Failure to Enforce Concrete Regulations: The difficulty in implementing strong AI regulations is not unique to the Biden-Harris Administration. Previous administrations, both Democratic and Republican, have similarly struggled to put in place effective and enforceable standards. For instance, the Obama administration faced criticism for its light-touch approach to regulating big tech , and the Trump administration was similarly criticized for prioritizing innovation over regulation in AI policy . The current administration’s strategy follows this same pattern, prioritizing corporate cooperation over the creation of binding regulations that could provide real oversight.
          3. Vague Promises, Unclear Outcomes—A Familiar Story: The Biden-Harris Administration’s fact sheet is filled with vague promises, much like those seen in previous administrations. While the fact sheet mentions initiatives such as AI safety research and the development of ethical guidelines, it lacks detailed plans on how these initiatives will be implemented, monitored, or enforced. This mirrors the shortcomings of previous administrations, which made similar promises that ultimately failed to materialize into meaningful action.
          4. Ignoring Broader Implications—A Repeated Oversight: The Biden-Harris Administration’s focus on AI’s potential for economic growth is not new. Previous administrations also tended to emphasize the economic benefits of AI while downplaying the broader societal implications, such as job displacement, privacy concerns, and the exacerbation of existing inequalities. The failure to address these issues comprehensively has been a bipartisan oversight, with both the Obama and Trump administrations criticized for their narrow focus on innovation at the expense of broader societal impacts.

          The Bottom Line:

          The Biden-Harris Administration’s AI fact sheet may be presented as a step forward, but it follows a familiar pattern of missed opportunities and insufficient oversight seen in previous administrations. The reliance on voluntary commitments and vague promises reflects the continuation of a bipartisan failure to provide the necessary regulatory framework to guide AI development responsibly.

          Summary

          As AI continues to advance, the need for comprehensive, enforceable regulations becomes ever more urgent. Yet, the Biden-Harris Administration appears content to follow in the footsteps of previous administrations, placing corporate cooperation above government accountability. If this administration truly wants to lead on AI, it must break from the ineffective strategies of the past and deliver a regulatory framework that safeguards public interests, promotes transparency, and addresses the broader societal impacts of AI. Without this, the promises of progress will remain just that—promises, as history repeats itself once again.

          References:

          1. “Obama’s Approach to Tech Regulation: Self-Regulation and Industry-Led Initiatives,” Tech Policy Review.
          2. “Trump Administration’s AI Policy: Innovation Over Regulation,” AI Governance Repor.
          3. “The Obama Administration’s Struggle with Tech Regulation,” Policy Analysis Quarterly.
          4. “Trump’s AI Executive Order: A Focus on Innovation, Not Regulation,” Tech and Society Journal.
          5. “Promises Unkept: The Obama Administration’s Tech Regulation Shortcomings,” Regulatory Insights.
          6. “Vague AI Promises: How Previous Administrations Failed to Deliver,” Government Technology Review.
          7. “AI and Society: The Oversights of the Obama Administration,” Tech Impact Journal.
          8. “The Trump Administration’s Narrow AI Focus: Innovation at What Cost?” Society and Technology Analysis.

        3. Elected Technology Leaders: Balancing AI Innovation and Regulation for America’s Future

          Amid growing concerns about artificial intelligence (AI), the United States faces a critical challenge: balancing innovation with public safety and privacy rights. While AI legislation is essential for maintaining America’s leadership in this field, there is a real danger that excessive regulation could hinder innovation, stifle job growth, and impede enforcement—issues that have already begun to surface within the European Union.

          In our article, “EU’s 2024 AI Regulation: A Critical Analysis of Its Potential Pitfalls and Missed Opportunities”, we explore how the EU’s approach could serve as a cautionary tale for the U.S. Conversely, insufficient regulation poses significant risks, as we detail in “How a Future Secretary of Technology Could Lead an International Treaty to Prohibit AI in NBC Warfare”.

          To address these challenges effectively, the U.S. needs elected technology leaders who are accountable to voters and taxpayers. These leaders could enact sensible, practical, and necessary legislation, striking the right balance between innovation and regulation. Our article, “Guide to Technology Governance: From Federal to Municipal Levels”, outlines how elected technology officials at every level of government could drive this effort.

          The importance of elected technology leaders becomes even more evident when considering the shortcomings of current AI initiatives. As discussed in “FACT SHEET: Biden-Harris Administration Announces New AI Actions and Receives Additional Major Voluntary Commitment on AI”, without direct accountability to the public, such initiatives risk falling short of their potential.

          By electing technology leaders rather than politicians lacking in technology expertise, we can ensure that AI legislation both safeguards public interests and fosters an environment where innovation thrives, helping to maintain the U.S.’s competitive edge in this crucial sector.