Tag: Elected Technology Leaders

  • Back to Basics: Why Our Technology Leaders Must Know Networks

    By the Founders, Department of Technology | San Diego, California | November 14, 2026

    A future Department of Technology official should have real-world experience running enterprise-size networks: routers, switches, servers, and the websites that sit on top of them. Knowing a programming language or two is not enough, and neither is a university degree in computer science on its own. Hands-on network engineering experience is a must.

    This is our view, and we state it plainly. We are not claiming a survey or a study. We are describing what we see and why we think it matters.

    The Internet is made of physical things

    It is easy to think of the Internet as a cloud. It is not. It is cables, routers, switches, firewalls, and servers in buildings that need power and cooling, all configured by people who know how the pieces connect and what happens when one fails.

    A router decides where traffic goes. A switch connects devices inside a network. A server stores and delivers the websites, files, and services people use. When any of them is misconfigured or overloaded, services slow down or disappear, and the cause is rarely obvious to someone who has never worked with them.

    Machine Intelligence runs on networks

    The current Machine Intelligence (MI, often called AI) revolution and the Internet depend on each other. MI systems are trained and used across vast networks of servers in data centers, and the Internet is how those systems reach schools, hospitals, businesses, and homes. Better MI drives more demand for bandwidth and computing, and a stronger network makes better MI possible.

    That is why network engineers matter more than ever. The buildout we describe in our Data Centers series is not only about chips and algorithms. It is about power, fiber, cooling, and the networks that tie it all together.

    Programming skills alone are not enough

    Writing code is valuable, and many excellent technology workers are programmers. But being capable in one or a few programming languages is a different skill from designing, securing, and keeping an enterprise network running.

    A useful comparison is the road. Many people are skilled drivers, but we would not ask a skilled driver to design a highway interchange. Likewise, a talented programmer is not automatically qualified to oversee a statewide network or a county data center.

    In our experience, many self-described technology experts, including some in government jobs, have never configured a switch, built a routing table, or run a production web server. That gap matters most when they are asked to judge what a vendor is selling or what an agency actually needs.

    A computer science degree is not enough either

    This is not a criticism of computer science graduates. Computer science is a demanding and valuable field. But it is a different discipline from network engineering. In our view, a computer science degree typically emphasizes theory, algorithms, and software, while keeping an enterprise network running is a hands-on craft learned by doing it.

    In other words, for this job, a professional certification can be worth more than a generic computer science degree. Certifications such as Cisco’s and Juniper Networks’ networking credentials are built around the work itself: configuring routers and switches, securing traffic, and fixing what breaks. Vendor certifications in cloud computing from Amazon, Google, IBM, and others show the same practical, foundational skills. Many of them also expire, so holders must renew them as the technology changes.

    None of these replaces years of hands-on experience, and a public official should understand principles that apply across vendors rather than just one company’s products. But as evidence that someone has the skills a future Department of Technology official needs, a relevant certification on top of real-world experience says far more than a general degree does.

    Consider a comparison from the law. Someone with a philosophy degree has studied something worthwhile: logic, ethics, and argument. But if that person wanted to practice law, we would not call it practical or logical to let them represent clients on that degree alone. In nearly every state they would need law school, a bar exam, and real experience first.

    Technology leadership is no different. A degree in a related field does not, by itself, qualify someone to run the network that schools, hospitals, and emergency services depend on. The credential and the experience have to match the work.

    There is no technology equivalent of the bar exam, which makes a documented, hands-on track record more important, not less. A network engineer’s experience is a must for the people who lead and oversee public technology, not a nice extra.

    We already expect this of other infrastructure

    We rely on engineers to build and maintain our roads, bridges, water systems, and cities. No one would put someone who has never worked on a bridge in charge of bridge safety. Networks are infrastructure too, and our schools, hospitals, elections, emergency services, and economy increasingly depend on them.

    The Internet needs its own maintenance and its own engineers, and the people who lead public technology offices should come from that world or understand it deeply.

    What we would look for

    We would want a future Department of Technology official to bring real-world, hands-on experience in areas such as:

    • Enterprise networking: designing and running networks with routers and switches at a scale where outages affect many people.
    • Servers and hosting: deploying, securing, and maintaining web servers and the services that run on them.
    • Web building: creating and maintaining websites, not just consuming them.
    • Reliability and security: planning for backups, redundancy, monitoring, and recovery when something breaks.
    • Troubleshooting under pressure: diagnosing an outage in a live system, which no classroom fully teaches.

    Degrees and certifications can show that someone studied a subject. They cannot show that someone has kept a real network running, especially in a field that changes constantly. That is why we put a track record of hands-on work ahead of credentials alone.

    Why it matters in government

    Public technology decisions depend on this knowledge more than most people realize:

    • Data centers: officials weigh power, fiber, water, and cooling requests without always being able to tell a real project from a placeholder. See How a Data Center Deal Actually Gets Made.
    • Cybersecurity: defending public systems starts with understanding how they are connected.
    • Continuity of government: keeping services running through outages and disasters depends on resilient networks.
    • Procurement: leaders who understand the technology are harder to oversell and better at writing contracts.
    • Schools and public safety: systems like School Contact only work if the underlying networks are secure and reliable.

    What this does not mean

    A technology leader does not need to configure every router personally. Like any executive, they will rely on a professional staff, and we would fund one. But a leader who has never done the work cannot judge whether the staff, or a vendor, is giving good advice.

    Our first-year guide for counties and cities shows how much of the job comes down to asking the right questions. Leaders can only ask them if they understand the answers.

    Questions to ask candidates

    If someone is running for a technology role, or already holds one, here are a few simple questions voters can ask:

    1. Have you built or managed a network with routers and switches at enterprise scale?
    2. Have you run or secured a production web server?
    3. Can you explain, in plain language, how your agency’s systems connect and what happens if one fails?
    4. How will you make sure your team has the hands-on skills to defend and maintain our public networks?

    An honest answer, even one that admits a gap and explains how it will be filled, tells voters a great deal.

    The bottom line

    The Internet and Machine Intelligence are growing together, and both depend on engineers who know how networks really work. We maintain our roads and bridges because we know we need people who can build and fix them. We should hold the people who oversee our digital infrastructure to the same standard.

    We want to hear from network engineers, system administrators, and web builders. If you have run real networks, tell us what a public technology leader needs to know. We would rather be corrected than applauded.

  • Isn’t This Just Another Bureaucracy? Answering the Hardest Questions About Elected Technology Leaders

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

    Our proposal for elected technology leaders at every level of government draws the same skeptical question again and again: aren’t you just adding a layer? It is a fair question. Here are the nine hardest objections we hear, with our best answers and the limits of those answers.

    We would rather be challenged than applauded. If an idea cannot survive its strongest critics, it should not become law. Where we have evidence, we cite it. Where we are making a judgment, we say so.

    1. Isn’t this just another layer of bureaucracy?

    It would be, if it added a layer without removing a gap. The gap is the problem. Today, the pieces of the technology buildout are split across utility commissions, economic development offices, zoning boards, treasurers and workforce agencies, and no one answers to voters for how they fit together. An NBC News review of more than 30 data center proposals in 14 states found that in a majority of cases local officials signed NDAs and worked with what appeared to be shell companies. That is not what a coordinated system looks like. Our test for any new office is whether it replaces confusion with accountability. If it does not, it should not exist. We also think a new office should come with a published cost estimate and a sunset review. We have not priced it for your jurisdiction, and you should be wary of anyone who claims to have done so without details.

    2. Why elected? Why not appoint someone?

    Because the decisions are value judgments. Whose land, whose power bills and whose jobs are tradeoffs, not technical questions, and voters should be able to hold someone to account for them. There is precedent. Voters elect utility commissioners in 10 states, and on November 3 voters in nine states elected 14 members of their state utility commissions. That is not an untested idea. But the record also contains a warning: those races draw far less public attention than other contests on the same ballot, even though the winners will help decide whether data center costs are passed to existing ratepayers. And S&P’s regulatory research unit has long attributed greater investor risk to states where commissioners are elected. So election alone does not guarantee accountability. It needs visibility, and we would pair it with the transparency rules we describe elsewhere.

    3. Don’t utility commissions and other regulators already do this?

    They do part of it, and in some places they do it well. Virginia’s State Corporation Commission, for example, ordered Dominion to develop a tariff to assign more transmission costs directly to data centers. But a utility commission sets rates. It does not decide where a facility is zoned, how much water it may use, what tax breaks it receives or how a county prepares its budget for a downturn. The proposal is not to replace regulators. It is for a technology leader to participate in their proceedings, and to coordinate across the decisions that no single regulator owns.

    4. Won’t an elected technology leader be captured by the industry?

    It is a real risk, and it is a risk for any regulator, elected or appointed. Campaign money, revolving doors and information asymmetry all push in one direction. We would counter it with rules, not hope: publish meetings and calendars, bar NDAs, require recusal where there is a financial interest, and open the records. Those safeguards are our suggestions, not a guarantee. A reasonable person can conclude that appointed, professional regulators are safer than elected ones, and that is a debate we welcome.

    5. Will they have the expertise?

    Not automatically. Elections reward name recognition more than engineering. Some states already set minimum qualifications for commissioners; a Platte Institute research note observes that some states require knowledge or experience in fields such as economics, finance, engineering, energy and law. We would consider something similar, along with a funded professional staff, so that the elected official is accountable for the decisions and the staff supplies the analysis.

    6. Won’t this slow down the buildout and hand China the lead?

    It should not, and if it does, the design has failed. Speed matters. Our concern is that speed without accountability produces backlash that stops projects anyway, as voters showed on November 3 when they favored limits in 40 of 41 local data center measures. Clear rules can also speed things up: AEP Ohio’s large-load pipeline reportedly fell from roughly 30 GW to 13 GW once it had a tariff, which suggests that rules can weed out speculative requests that waste everyone’s time. And Loudoun County credits favorable zoning and fast approvals for accelerating its data center growth. A good technology leader should make the process predictable and fast for projects that meet the standards.

    7. What will it cost?

    We do not have a number for your jurisdiction, and we would not trust one without a detailed budget. The fair comparison is with the cost of the current arrangement, though that is not proof of savings. In Ohio, for example, Policy Matters Ohio reports that a single tax break cost state and local governments about $2 billion in a year, well above the state’s forecast. A small county could begin with a staff director and a part-time advisory board and expand only if it proves its worth.

    8. Isn’t this a partisan project?

    It is not meant to be, and the evidence we rely on is bipartisan. In Virginia, 21 Democrats and seven Republicans in the state Senate voted to curtail a data center tax break. Republican Governor Mike DeWine paused Ohio’s break, and Democratic Governor Andy Beshear called for ending Kentucky’s. Skeptics of the buildout and enthusiasts for it both need an accountable referee. We will count the proposal a failure if one party sees it as a weapon.

    9. Why not let states and markets sort it out?

    They will sort out something. In 2026, 29 states enacted AI legislation, and many local officials are negotiating one deal at a time against a handful of very large buyers, often under NDAs. A patchwork can be a healthy laboratory, and a federal standard may eventually be the right answer. Either way, the people who live next to the project need someone whose job is to speak for them across every decision, not just the one in front of a given committee.

    What would change our mind

    We care about the function more than the title. If a jurisdiction shows that a staff-level technology director, a joint committee or an existing regulator can deliver one accountable owner for the whole picture, with public records and a name voters can hold responsible, we would support that model. If evidence shows elected technology leaders performing worse than appointed ones, we will say so. What we will not accept is the status quo, in which nobody is responsible. Our proposal is at department.technology/.

  • 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/.

  • Ten Questions Every Candidate and Elected Official Should Answer About Data Centers and AI

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

    Voters deserve specific answers about who pays for data centers, who is accountable, and what happens if AI does not deliver. Here are ten questions you can put to any candidate or sitting official, with the evidence behind each, what a strong answer sounds like, and what evasion looks like.

    This is a nonpartisan tool. We score the quality of an answer, meaning whether it is specific, honest about tradeoffs and accountable, and not whether it matches our views. A candidate who answers concretely in favor of a policy we would not choose earns the same points as one who answers concretely against it. Send the same ten questions to every candidate, give everyone the same deadline, and publish the answers word for word.

    How to score

    For each question, give each answer 0, 1 or 2 points:

    • 2 points: a clear position, a specific mechanism, and an honest acknowledgment of a tradeoff or limit.
    • 1 point: a clear position without a mechanism, or a mechanism without a position.
    • 0 points: no answer, a deflection, or generalities that could mean anything.

    A total of 16 to 20 suggests a candidate who has thought hard about the whole picture. A total of 10 to 15 suggests a developing view. Below 10 suggests the issue has not yet been taken seriously. This is a conversation tool, not a scientific rating, and we encourage independent groups, newsrooms and civic organizations to score the answers themselves.

    Question 1: Who is accountable?

    The question: If a data center proposal comes before your body, who in government is responsible for weighing power, water, land, taxes and jobs together? Who should be?

    Why it matters: The pieces of this decision are split among utility commissions, economic development offices, zoning boards and treasurers, and no one answers to voters for the combination.

    A strong answer names a person or office and a mechanism, such as a standing committee, a technology director or an elected leader, and says how voters can hold them to account.

    Red flags: “The market will sort it out,” or an answer that lists existing agencies without saying who coordinates them.

    Question 2: Will you sign secret agreements?

    The question: Will you sign a nondisclosure agreement about a development project, and will you support limits on them?

    Why it matters: An NBC News review of more than 30 data center proposals in 14 states found that in a majority of cases local officials signed NDAs. Records requests in Louisiana turned up 54 NDAs signed by elected officials since early 2024. Microsoft says it is working to end active NDAs governments have signed.

    A strong answer gives a clear yes or no, says when confidentiality ends (for example, before any public vote), and explains how legitimate trade secrets would be protected.

    Red flags: “NDAs are standard practice” with no limit, or a blanket promise with no mention of how negotiations would work.

    Question 3: Who pays for the grid?

    The question: Should the largest new electricity users pay the full cost of the grid upgrades built to serve them? Should that be mandatory or optional, and what minimum commitments should they make?

    Why it matters: The Ratepayer Protection Act passed the House 417 to 3 and then failed a Senate procedural vote 57 to 43, largely over whether the protection should be optional or mandatory. At the state level, 23 states had approved at least one large-load tariff as of May. Ohio’s AEP tariff requires 85 percent minimum payments and at least twelve-year contracts, and Dominion’s Virginia tariff requires 14-year contracts and $1.5 million per megawatt of collateral.

    A strong answer takes a side on mandatory versus optional and names at least one term, such as minimum bills, contract length, collateral or exit fees.

    Red flags: “Make Big Tech pay their fair share” with no mechanism, or “markets will handle it.”

    Question 4: Do you support tax breaks, and on what conditions?

    The question: Do you support tax incentives for data centers? If so, what conditions, such as job targets, sunset dates and clawbacks, should come with them? If not, why not?

    Why it matters: Thirty-eight states offer data center incentives, and at least 28 considered scaling them back this year. In Ohio, the break cost state and local governments about $2 billion in a year. The jobs are mostly temporary: an Illinois study projected 121,000 jobs from $57 billion of investment, but only 2,800 permanent direct positions, while a Reno facility’s records estimated 73 permanent jobs.

    A strong answer takes a position either way, separates temporary from permanent jobs, and says how results would be measured.

    Red flags: Quoting job totals without saying how many are permanent, or promising “jobs and growth” without numbers.

    Question 5: Who gets a say before approval?

    The question: Should data centers be allowed by right, or should each one require a public hearing and discretionary approval? Where should the final decision sit?

    Why it matters: Loudoun County eliminated by-right zoning for data centers, and Harrisonburg, Virginia, moved them to special-use permits. Loudoun also credits favorable zoning and fast approvals for accelerating its growth. There is a real tradeoff between speed and consent.

    A strong answer describes a process, such as hearings, timelines and standards, and acknowledges the tradeoff.

    Red flags: “Let the community decide” with no process, or “get out of the way” with no protection for residents.

    Question 6: What about water, land and cleanup?

    The question: What studies, standards and financial guarantees should a data center have to meet for water, noise, farmland and eventual closure?

    Why it matters: Linn County, Iowa, requires a water study and a water-use agreement before construction and also covers decommissioning bonds. Few places have anything comparable.

    A strong answer names specific requirements and who would enforce them.

    Red flags: “Environmentally responsible” with no specifics.

    Question 7: How do we build enough, fast enough?

    The question: How would you make sure America builds enough power and computing capacity to compete, without bypassing the public?

    Why it matters: BloombergNEF expects China to add more than six times as much generating capacity as the United States over five years, and Morgan Stanley has forecast a 44-gigawatt shortfall for U.S. data centers. At the same time, AEP Ohio’s pipeline reportedly fell from roughly 30 GW to 13 GW once it had a tariff, so not every request is real.

    A strong answer addresses generation, transmission and permitting, and distinguishes real projects from speculative ones.

    Red flags: An answer that is only “beat China” or only “stop the data centers.”

    Question 8: Who bears the loss if the boom slows?

    The question: If AI investment slows or reverses, who bears the losses, and what would you do now so residents are not left holding the bag?

    Why it matters: Hyperscalers will spend about $750 billion this year, borrowing heavily. Jefferies warns that AI investment was the main driver of U.S. economic growth last year after consumer spending, and The Economist notes that more than half the spending goes to equipment that becomes obsolete within a few years.

    A strong answer names protections such as collateral, minimum bills, exit fees or cleanup bonds, without predicting a crash.

    Red flags: Either “this can’t fail” or doom with no plan.

    Question 9: What is your plan for the tax base?

    The question: Has your government modeled what happens to revenue if AI displaces significant work, or if data center revenue falls? What reserves and triggers are in place?

    Why it matters: A RAND analysis found that 84 percent of federal revenue comes from individual and payroll taxes. Loudoun County reports that data centers generate 38 percent of its general fund revenue, and New York City’s Comptroller recommended a reserve of 16 percent of annual tax revenue in response to AI risk.

    A strong answer says what share of revenue is exposed and describes a scenario plan and reserve.

    Red flags: “We’ll cross that bridge when we come to it.”

    Question 10: Should Congress override state AI laws?

    The question: Should federal law preempt state AI rules? If so, what federal protections and enforcement would replace them, and who would administer them? (For state and local candidates: what role should your jurisdiction keep?)

    Why it matters: The Senate voted 99 to 1 against an early preemption proposal, while 29 states enacted AI legislation in 2026. Even the White House’s approach would leave data center infrastructure to the states.

    A strong answer takes a position, names the enforcement mechanism and says who is accountable for it.

    Red flags: “Washington can’t be trusted” or “states can’t be trusted” with no alternative.

    Which questions fit which office

    • City council or county board: Questions 1, 2, 5, 6 and 9.
    • State legislature or governor: Questions 2, 3, 4, 7, 8 and 10.
    • Congress: Questions 3, 7, 8, 9 and 10.
    • Bonus question for everyone: Will you publish your meetings with developers, utilities and lobbyists on this issue?

    The case against our case

    • Scorecards reward rehearsed answers. A well-coached candidate can sound specific without meaning it. That is why we ask for mechanisms and why we suggest publishing answers in full and comparing them with later votes.
    • Not every office has the power. A county commissioner cannot set federal policy, and a member of Congress cannot rezone land. The “which office” guide above is meant to keep the questions fair.
    • Ten questions oversimplify. Real issues have more dimensions, and some candidates will rightly say “it depends.” We would count a thoughtful “it depends”, with the conditions named, as a strong answer.
    • We might be seen as scoring for our side. Our proposal for elected technology leaders is not the only acceptable answer to Question 1, and a different structure can score full points. We would prefer that a neutral organization do the scoring.

    Print-ready list

    1. Who in government is responsible for weighing power, water, land, taxes and jobs together, and who should be?
    2. Will you sign a nondisclosure agreement about a development project, and will you support limits on them?
    3. Should the largest new electricity users pay the full cost of grid upgrades built to serve them, and should that be mandatory or optional?
    4. Do you support tax incentives for data centers, and on what conditions?
    5. Should data centers be allowed by right, or require a public hearing and discretionary approval?
    6. What studies, standards and guarantees should a data center meet for water, noise, land and cleanup?
    7. How would you make sure America builds enough power and capacity to compete, without bypassing the public?
    8. If AI investment slows, who bears the losses, and what would you do now to protect residents?
    9. Has your government modeled what happens to revenue if AI displaces work or data center revenue falls?
    10. Should Congress override state AI laws, and if so, what replaces them and who administers it?

    Use it

    Send these to every candidate and every sitting official you can reach, at every level, and ask for answers in writing by a stated date. Publish what comes back. If you are a candidate, answer before you are asked. Our proposal is at department.technology/.

  • How a Data Center Deal Actually Gets Made, and Where the Public Gets Left Out

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

    Most data center deals are shaped long before residents hear a word. Here is a step-by-step walk through how a typical one comes together, who decides at each stage, where the public is shut out, and what an accountable technology leader would change.

    No two deals are identical, and we do not claim every project follows this path. Some officials negotiate openly, and some developers welcome scrutiny. But the pattern below appears again and again in public records and investigations, and understanding it is the first step to changing it.

    Step 1: A site is chosen, and it is not about you

    Data center developers pick locations for electricity access, water rights and fiber connectivity, not for population or local jobs, according to a Quartz analysis of the industry’s land-acquisition playbook. Your community may be on a list for reasons no one has told you.

    Who decides: the developer. Where the public is left out: everywhere; no one has been told. What would change: a technology leader would know the utility’s pipeline and whether your community is on it (see our first-year guide).

    Step 2: Land is quietly secured

    The next move is usually to lock up land. The most common tools are, according to that same analysis, shell LLCs, nondisclosure agreements, land options that tie up parcels before public review, and intermediary buyers acting for unnamed principals. The practice is old. In 2019, the Washington Post reported that Google had used shell companies in negotiations with at least five cities, and in Iowa created one LLC for the land sale and another for the development deal.

    There is a legitimate reason for some of this. Once a famous buyer is identified, land prices can jump sharply; the article cites Disney in Florida, where prices rose more than 1,000 percent. Sellers deserve a fair price, and developers deserve a fair negotiation. The question is how long secrecy should last and who else is kept out.

    Step 3: Officials sign NDAs, and projects get code names

    Local officials are then asked to sign confidentiality agreements. An NBC News review of more than 30 data center proposals across 14 states found that in most cases local officials signed NDAs and dealt with what appeared to be shell companies. In Louisiana, public records requests turned up 54 NDAs signed by elected officials since early 2024, and the agreements covered projects under code names like “Project Lightning.” In Minnesota, a project near Hermantown, code-named “Project Loon,” was identified as a data center only after the Star Tribune obtained public records, by which point the city had already changed land use plans and carried out preliminary environmental review.

    Who decides: a handful of local and state economic development officials. Where the public is left out: the officials who sign cannot discuss it, even with their own colleagues or constituents. What would change: a policy that the jurisdiction does not sign NDAs on development matters, with trade secrets protected by narrower means.

    Step 4: The utility is asked for power

    In parallel, the developer asks the utility for a connection. AEP Ohio, for example, charges a one-time fee of $10,000 to $100,000 for each load study and requires it to be paid within 45 days or the customer forfeits its place. These queues can be full of placeholders. AEP Ohio was facing 30 gigawatts of potential new load before its data center tariff, and one analysis found that its pipeline fell from roughly 30 GW to 13 GW after the tariff took effect.

    Who decides: the utility, under rules set by the state commission. Where the public is left out: the pipeline is rarely published, so local officials may not know which requests are real. What would change: public reporting of large-load requests by jurisdiction, and a local seat in the commission proceeding.

    Step 5: Incentives are negotiated

    The developer then seeks tax relief. In the Midlothian, Texas, case the Post described, Google reportedly used a shell company to negotiate a $10 million tax incentive with local officials. At the state level, thirty-eight states offer incentives, and in Ohio the break cost state and local governments about $2 billion last year, according to Policy Matters Ohio, far more than forecast. Those figures come from the incentive programs themselves, not from one negotiation, but they show the scale of what is decided in small rooms.

    Who decides: state and local economic development officials. Where the public is left out: the cost-benefit analysis, if one exists, is often not public. What would change: published cost-benefit analyses before approval, and clawbacks if promises are missed.

    Step 6: Land use is approved

    Only now does the public typically see a rezoning request or a site plan. If data centers are allowed by right, there may be no hearing at all. By this stage, the land is secured, the utility has been approached and the incentives are drafted, so the room to say no is small. In Hermantown, by one account, officials turned away questions from nearby residents about whether the project was a data center.

    Who decides: the planning commission and the county board or council. Where the public is left out: the decision arrives late and often looks finished. What would change: special-use permits instead of by-right approval, and a requirement for a public hearing with full disclosure before anything is signed.

    Step 7: The power contract is signed

    The utility and the developer sign a service agreement. In states with large-load tariffs, these carry minimum bills, long terms and collateral. Dominion’s Virginia tariff, for example, calls for 14-year minimum contracts and $1.5 million per megawatt of collateral. Elsewhere, the terms are weaker or negotiated one at a time. Who bears the risk if the facility closes or never fills is a question of contract design, and most residents never see the contract.

    Step 8: Construction, jobs and revenue

    Then the buildings go up. The jobs promised are mostly short-term. A Reno facility’s business records estimated 73 permanent jobs against more than 4,000 temporary construction jobs. An Illinois study projected that $57 billion of new data center investment would create 121,000 jobs, but only 2,800 would be direct, permanent positions, or about $20 million of investment per permanent job. Brookings researchers found effects of roughly 100 to 200 jobs at a typical affected county, along with a modest increase in home prices of 2 to 5 percent, and noted the effects vary by facility type.

    On the other side of the ledger, the tax revenue can be large. Loudoun County, Virginia, reports that data centers produce 38 percent of its general fund revenue on about 4 percent of its commercial land.

    The pattern

    Laid end to end, the steps show a consistent shape: the biggest decisions happen early, in private and without a public voice, and the public hearing arrives after the key commitments have been made. That is not necessarily bad faith. Many officials believe they are protecting a competitive negotiation, and many developers are responsive once the project is public. But a system that depends on goodwill at every step will not protect residents when goodwill runs out.

    The case against our case

    • Officials say NDAs are necessary. Louisiana’s economic development secretary told NPR that NDAs are “fundamental for economic development”, allowing the state to compete. Her point deserves weight. On the other hand, a parish president in the same state said economic development does not require NDAs, chose not to use them, and still saw a $10 billion data center built.
    • Early secrecy can protect sellers. As noted above, a named buyer can inflate land prices, so a limited period of confidentiality may serve landowners. We would limit it to land transactions and end it before any public vote.
    • The jobs numbers are disputed. A Maryland Tech Council study, for example, estimated that a typical 800,000-square-foot data center would support nearly 500 permanent jobs, a far higher figure than other studies, according to one review of the evidence, which also cites a Virginia state audit that found far fewer.
    • Many deals are fine. Some projects are welcomed by communities and deliver what they promise. The goal is not to stop deals but to make sure the public can see them before they close.

    What to do with this

    If you serve on a council or board, ask where your community is in this sequence, and who has signed what. If you are a resident, request the NDAs and incentive agreements under your state’s public records law. And if you are a candidate, tell voters who in your government is responsible for each of these eight steps. Right now, the honest answer in most places is that nobody is responsible for all of them. Our proposal is at department.technology/.

  • What Every County Treasurer Should Model Before AI Layoffs

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

    Local governments face two different AI-related revenue risks at once: the labor income that funds them could shrink, and the data center revenue that may be replacing it could be concentrated in one fragile industry. Here is a simple scenario worksheet any treasurer or finance director can build in an afternoon.

    This is not a forecast. Nobody knows how many jobs AI will displace or how long the data center buildout will last, and we say so plainly. The point of scenario planning is to find out, before it matters, which of your revenues would hurt most under each outcome, and to decide in advance what you would do. Treasurers do this every year for recessions and hurricanes. The same discipline applies here.

    Why now

    The labor-income exposure is documented at the federal level. A RAND analysis found that 84 percent of federal revenue in 2024 came from individual and payroll taxes, that the loss of high-income white-collar jobs would hit revenue disproportionately, and that higher corporate profits would not offset the decline unless corporate tax rates were roughly doubled. Economists Anton Korinek and Lee Lockwood warn that even modest labor displacement could significantly strain public finances. Local governments sit downstream. One opinion writer argues that states and localities will bear the initial cost of retraining and income support when workers are displaced.

    The boom itself can be a concentration risk. California’s Legislative Analyst found that stock-option withholding from a handful of large tech companies made up about 10 percent of all state income tax withholding in 2025, and warned that withholding could fall if the AI market deteriorates. At the county level, Loudoun County, Virginia, reports that data centers generated 38 percent of its general fund revenue while occupying about 4 percent of its commercial land. Prince William County projected data center revenue of about $550 million in fiscal 2027, roughly 28 percent of general fund tax revenue. Loudoun staff have warned that if the personal property tax rate is not lowered, data centers could exceed 60 percent of the general fund within five to seven years.

    The lesson is not that data centers are bad revenue. It is that a budget resting on one industry needs a plan for what happens if that industry slows down, and a budget resting on wages needs a plan for what happens if wages shrink.

    The worksheet

    1. Map your revenue by source and by exposure. List every major revenue line: property tax, sales tax, income or payroll taxes where you have them, business taxes, fees and intergovernmental aid. For each, note how much depends on (a) wages in office and professional jobs in your area, (b) a single employer or industry, and (c) data centers or their equipment.
    2. Define three or four scenarios. For example: a baseline, a gradual-displacement scenario, a rapid-displacement scenario, and an investment-bust scenario in which data center equipment values fall sharply. New York City’s Comptroller used five scenarios; a small county can use fewer. Choose ranges your analysts can defend. For illustration only, you might test declines of 10, 25 and 50 percent.
    3. Run each scenario through each revenue line. A wage decline changes income and sales tax receipts. A bust changes personal property tax on equipment. Record the dollar effect and the share of the general fund.
    4. Estimate the demand side. Displaced workers use services. Note which of your programs would see more demand, such as workforce programs, public assistance, and emergency services, and what each would cost.
    5. Set a reserve target. The NYC Comptroller recommended building a reserve to 16 percent of annual tax revenue. Loudoun built a $119.7 million revenue stabilization fund specifically to absorb differences between budgeted and actual data center revenue, and reports it is now fully funded. Your target will differ, but it should be written down.
    6. Set triggers and publish. Decide in advance what happens at each threshold: when to freeze hiring, when to review the tax rate, when to draw on reserves. Then publish the scenarios and triggers each year with the budget. Residents should see the plan before they need it.

    If you host data centers

    Host jurisdictions have an extra set of questions:

    • How much of the general fund comes from data centers, and what is the trend? Track the share every year, not just the dollar amount.
    • What happens if equipment is replaced less often, or values fall? Equipment, not buildings, drives much of the revenue. The Economist notes that more than half of AI spending has gone to servers and chips that become obsolete within a few years.
    • Are you spending windfalls on permanent commitments? Treat unexpected revenue as one-time money unless you can justify it as durable. Loudoun staff have framed lowering the tax rate on data center equipment as the strongest tool for managing dependence.
    • Is relief visible to residents? Loudoun has cut its real estate tax rate substantially over the past decade, a real benefit residents can see.

    What not to do

    • Do not turn scenarios into predictions. A scenario is a stress test. Label it that way.
    • Do not wait for certainty. The range of forecasts is wide, and it will stay wide.
    • Do not model only the downside. Include a scenario in which AI strengthens your local economy, so the worksheet is credible to everyone.

    The case against our case

    • Holding reserves costs services today. Every dollar in reserve is a dollar not spent on schools or roads now. Reasonable officials will weigh the insurance value against current needs, and the right level is a local judgment.
    • The effect may look like earlier technology shifts. Economists David Agrawal and William Fox argue that AI reinforces rather than overturns the classic tradeoffs in state and local public finance, much as e-commerce and remote work did. If so, familiar tools may be enough.
    • Data center revenue is real and useful. Industry groups argue that without it, residents would pay far more. NetChoice, a trade association, says the alternative for Loudoun homeowners is a tax bill nearly double today’s. That argument deserves weight, and it is exactly why the downside needs a plan.
    • Forecasts are uncertain. The NYC report itself notes how hard it is to tie current trends to AI with certainty. We agree, and that is why the worksheet uses ranges.

    The role no one holds

    In most governments, nobody is assigned to ask these questions across revenue, workforce and infrastructure at once. Treasurers see revenue. Economic development officers see ribbon-cuttings. Workforce boards see training. A technology leader’s job is to sit across all three. If you are a treasurer, you do not need to wait for that role to exist: start with step one this quarter. We are glad to share a blank version of the worksheet. Our proposal is at department.technology/.

  • A Technology Leader’s First Year: A Guide for Counties and Cities

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

    Most county boards and city councils are being asked to approve the largest infrastructure projects in their history with a planning staff built for strip malls. This is a practical first-year guide for the person whose job it should be to fix that.

    Our proposal calls for elected technology leaders at the local and county level. What would one actually do? Everything below has been tried somewhere, in communities of different sizes and politics. We cite examples as examples, not endorsements, and we flag where the evidence is thin. Local law varies, so check with your county attorney before adopting anything binding.

    Months 1 to 3: Find out what is coming, and stop the clock

    Inventory the pipeline. Ask your utility how many large-load connection requests are sitting in your territory, how many megawatts they represent, and how many are speculative or duplicated. This matters. AEP Ohio was facing 30 gigawatts of potential new load before it adopted a data center tariff, and one analysis found its pipeline fell from roughly 30 GW to 13 GW after the tariff took effect, suggesting much of the reported demand was speculative or duplicated across utilities. A local government that cannot tell the real projects from the placeholders cannot plan.

    End by-right approval. In March, the Loudoun County Board of Supervisors eliminated by-right zoning for data centers. Harrisonburg, Virginia, moved data centers to special-use permits, which routes proposals through public hearings and discretionary review. A Brookings researcher has recommended never allowing by-right data center development. Where a pause is needed, treat it as a tool with a work plan and an end date. A Federation of American Scientists review found that local moratoria share the same stated rationale: the zoning code does not yet define data centers, so the jurisdiction needs time to study impacts and draft rules.

    Ask the standard questions. Cuyahoga County’s playbook urges communities to ask about power demand, water use, grid upgrades, backup generators, jobs, infrastructure costs and decommissioning plans. Put those questions in writing and make every applicant answer them in public.

    Months 4 to 6: Write the rules

    Linn County, Iowa, adopted one of the most detailed local frameworks so far. Its ordinance requires a water study as part of the zoning application and a water-use agreement with the county before construction, and it also covers noise, light, road use and decommissioning bonds. The board finalized it unanimously after three readings and multiple public hearings. In Scott County, Kentucky, a draft ordinance would bar data centers from prime farmland and wetlands, require developers to pay for water system upgrades, and require a cleanup bond.

    One caution. Jefferson County’s committee worked to keep its draft legally defensible under recent Supreme Court rulings on land-use exactions. In general, what you demand has to relate to the project’s actual impacts. Have counsel review the ordinance before you adopt it.

    Months 6 to 9: Get a seat in the rate case

    Your county does not set electricity rates, but it lives with them. The state utility commission does the setting, and many have recently created separate rules for the largest customers. According to the Edison Electric Institute, 23 states had approved at least one large-load tariff as of May 2026, with seven more pending. Ohio’s AEP tariff applies to data centers above 25 megawatts, requires them to pay at least 85 percent of contracted capacity and commits them to initial contracts of at least twelve years. Dominion’s Virginia tariff sets 14-year minimum contracts and $1.5 million per megawatt of collateral. A Lawrence Berkeley National Laboratory brief lists minimum billing demand, exit fees and collateral as common building blocks.

    Find out whether your utility has such a tariff and, if not, whether a proceeding is pending. In many states, local governments can file comments or intervene, so ask your counsel. A county technology leader’s job is to make sure the people who live there are represented where the cost allocation is decided.

    Months 7 to 9: Negotiate in public

    Use community benefit agreements, carefully. The Federation of American Scientists found only eight data center community benefit agreements when it looked. Lancaster’s covers transparency, water, energy, noise, public works and decommissioning, but the reviewers noted it leaves much of the substance to be decided later, and that tax breaks can outweigh any financial benefit a community receives. The lesson is to write numbers and enforcement into the agreement now.

    Do not sign NDAs. Bloomberg Law reports that Microsoft is working to end any active NDAs governments have signed. Proposed Minnesota legislation would require at least two public hearings and disclosure of key details, including the company behind a project. You do not need to wait for a state law. A local government can adopt a policy that it will not sign NDAs on development matters and will post proposals, incentive terms and cost-benefit analyses on its website.

    Months 10 to 12: Budget for the upside and the downside

    Data center revenue can be a windfall, and it can be a trap. We cover the budgeting in a companion piece, “What Every County Treasurer Should Model Before AI Layoffs.” For your first-year report, the minimum is this: publish how much of your general fund depends on data centers, what happens to that revenue if equipment values fall, and what reserve you are holding against it.

    Then publish the whole first year in plain language: projects reviewed, conditions imposed, public hearings held and agreements signed.

    Your first week

    1. Ask the utility for the pipeline numbers. Megawatts, projects and status.
    2. Check your zoning. Is a data center allowed by right anywhere in your jurisdiction?
    3. Find out what has been signed. Any NDAs, development agreements or incentive deals.

    The case against our case

    • Data centers pay more than they cost. Speakers at a National Taxpayers Union discussion said Loudoun County receives about $26 in tax revenue for every $1 spent on services for data centers. Industry advocates argue that heavy requirements and delays can send projects, and that revenue, elsewhere. Loudoun itself credits favorable zoning and fast approvals for accelerating its growth, even though it later ended by-right approval. A good technology leader should make the process predictable and fast for projects that meet the standards, not just slower.
    • Small counties lack the expertise. A rural county may not be able to staff a water study or a rate-case intervention. That argues for shared staff across counties, or for state technical help, and we would support both.
    • Legal limits are real. Exaction rules constrain what localities can demand, and, as the FAS review shows, many agreements stay vague. This is a reason to involve counsel early, not to skip the work.
    • It might not need to be an elected office. A county could assign this to a staff director. Our view is that elected officials are accountable to voters for the tradeoffs, but a staff role is a sensible first step.

    Start with one question

    If your community is being asked to approve a data center this year, ask the person proposing it a single question: who in our government is responsible for the whole picture of power, water, land, taxes and jobs? If the answer is nobody, that is the position to fill. Find our proposal at department.technology/.

  • The First 100 Days: A Technology Agenda for the Next Congress

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

    A new Congress has 100 days to show it can govern the technology buildout instead of reacting to it. Here is a practical agenda that members of either party can sign onto.

    In our last piece, we described five mistakes the previous Congress made on data centers and AI. This one is the to-do list. We built it from items that already have bipartisan footprints, because the fastest agenda is one that members have already voted for, sponsored or said they support. One timing note: bills that do not become law expire when a Congress ends, so even measures that passed one chamber, like the Ratepayer Protection Act, have to be introduced again.

    1. Days 1 to 30: Hold one set of hearings on the whole picture

    Today the pieces of this problem sit in different committees. Energy committees see the grid. Commerce committees see competitiveness. Finance and tax committees see revenue. Each hears from its own witnesses, and nobody hears the tradeoffs.

    Hold a joint hearing series with the same witnesses in the same room: grid operators, state utility regulators, economists, county officials and workers. The evidence on each risk is already strong enough to start. In the largest U.S. grid market, wholesale power prices rose almost 76 percent in a year and the market monitor called the effects irreversible. At the same time, BloombergNEF expects China to add more than six times as much generating capacity as the United States over five years. Members should hear both facts at once.

    2. Days 1 to 45: Reintroduce ratepayer protection and settle the real disagreement

    The Ratepayer Protection Act cleared the House Energy and Commerce Committee 52 to 0, passed the House 417 to 3, and then failed a Senate procedural vote 57 to 43 that needed 60. The two sides disagreed about one question: whether states should merely be required to consider making large data centers pay for the grid upgrades built to serve them, or whether the cost allocation should be mandatory, as in the Democratic GRID Savings Act.

    Both positions have a principled basis. Utility regulation has long been a state responsibility, and voluntary pledges have a mixed record. We suggest negotiators look for a middle design: a mandatory core for the very largest new loads, with states keeping flexibility over how to implement it. That is our suggestion, not a settled answer, and the details matter. The point is to have the argument in February rather than the weeks before an election.

    3. Days 30 to 60: Open the deals

    Secret agreements are the issue where public frustration is highest and the policy fix is simplest. Bloomberg Law found that 25 of 31 proposed data center projects in Virginia involved nondisclosure agreements, and that Microsoft says it is working to end any active NDAs governments have signed. Lawmakers in more than a dozen states have introduced bills to ban such agreements, but only Delaware has passed a transparency measure through its legislature, according to MLex. A bipartisan group in Congress has now introduced a federal bill to ban NDAs that keep officials from discussing proposed data center projects, while protecting trade secrets.

    Move that bill. And because Congress’s reach is strongest where federal assets are involved, require public disclosure of any data center deal that touches federal land, federal funds or federal permits.

    4. Days 60 to 90: Ask the revenue question before the layoffs

    We do not know how much AI will displace work, and forecasts vary widely. We do know how exposed the tax base is if it does. A RAND analysis found that 84 percent of federal revenue in 2024 came from individual and payroll taxes, and that losing high-paid white-collar jobs would hurt revenue disproportionately. New York City’s Comptroller has already modeled five AI scenarios for the city’s finances.

    Ask the Congressional Budget Office and the Government Accountability Office to publish scenario analyses of federal revenue under different displacement paths, and encourage states and counties to do the same. Planning for a range of outcomes is not predicting the worst one.

    5. Days 90 to 100: Name an owner

    Every item above would be easier to carry out, and harder to forget, if someone were accountable for them together. Begin by creating a standing joint committee with jurisdiction over the whole technology buildout. Then open the larger debate about a Department of Technology and elected technology leaders at the local, county, state and federal levels, including a Secretary of Technology.

    Two rules for all 100 days

    • No riders. Questions as large as federal preemption of state AI laws should not be decided inside a defense or budget bill. They need their own hearings and their own text.
    • Settle the hard disagreements early. The last Congress’s one bipartisan success stalled because the central dispute surfaced a few weeks before Election Day.

    The case against our case

    A fair agenda includes the strongest objections.

    • It is too much, too fast. Skeptics will say five items in 100 days is unrealistic, especially in a Senate that needs 60 votes for most bills. We would rather offer a full list and let members pick; the first two items are the most achievable.
    • Congress has limited reach over local contracts. A federal NDA ban cannot easily dictate how a city signs agreements except through federal funding, permits or land. Developers also argue that confidentiality protects competitive information, and Microsoft has said the agreements were meant to protect sensitive information. The bill’s trade-secret carve-out is where this fight will be decided.
    • Mandatory cost allocation could raise costs or slow building. Supporters of the optional approach worry that rigid federal standards could discourage investment at a moment when the country needs more capacity.
    • Revenue scenarios are speculative. The same New York report acknowledges it is hard to connect today’s hiring trends to AI with certainty. We agree, which is why we ask for a range of scenarios and not a single forecast.

    Start now

    None of this requires a party to give up its principles. It requires members to decide that the question of who is accountable for the technology buildout is theirs to answer. We will keep publishing the evidence and we will tell you plainly when we think a proposal falls short. Our proposal is 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/.