‘No Kings' Protests: Scenes From Across the Nation
Crowds of demonstrators gathered around the country on Saturday, protesting what they called President Trump's overreach. The rallies, many of which were organized as part of the 'No Kings Day' movement, took place in cities including New York, Atlanta, Philadelphia, San Diego and Miami.
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Fast Company
an hour ago
- Fast Company
Why government's AI dreams keep turning into digital nightmares—and how to fix that
Government leaders worldwide are talking big about AI transformation. In the U.S., Canada, and the U.K., officials are pushing for AI-first agencies that will revolutionize public services. The vision is compelling: streamlined operations, enhanced citizen services, and unprecedented efficiency gains. But here's the uncomfortable truth—most government AI projects are destined to fail spectacularly. The numbers tell a sobering story. A recent McKinsey analysis of nearly 3,000 public sector IT projects found that over 80% exceeded their timelines, with nearly half blowing past their budgets. The average cost overrun hit 108%, or three times worse than private sector projects. These aren't just spreadsheet problems; they're systemic failures that erode public trust and waste taxpayer dollars. When AI projects go wrong in government, the consequences extend far beyond budget overruns. Arkansas's Department of Human Services faced legal challenges when its automated disability care system caused 'irreparable harm' to vulnerable citizens. The Dutch government collapsed in 2021 after an AI system falsely accused thousands of families of welfare fraud. These aren't edge cases—they're warnings about what happens when complex AI systems meet unprepared institutions. The Maturity Trap The core problem isn't AI technology itself—it's the mismatch between ambitious goals and organizational readiness. Government agencies consistently attempt AI implementations that far exceed their technological maturity, like trying to run a marathon without first learning to walk. Our research across 500 publicly traded companies for a previous book revealed a clear pattern: organizations that implement technologies appropriate to their maturity level achieve significant efficiency gains, while those that overreach typically fail. Combining this insight with our practical work implementing digital solutions in the public sector led to the development of a five-stage AI maturity model specifically designed for government agencies. Stage 1: Initial/Ad Hoc. Organizations at this stage operate with isolated AI experiments and no systematic strategy. Stage 2: Developing/Reactive. Agencies begin showing basic capabilities, typically through simple chatbots or vendor-supplied solutions. Stage 3: Defined/Proactive. Organizations develop comprehensive AI strategies aligned with strategic goals. Stage 4: Managed/Integrated. Agencies achieve full operational integration of AI with quantitative performance measures. Stage 5: Optimized/Innovative. Organizations reach full agility and influence how others use AI. Most government agencies today operate at stages 1 or 2, but AI-first initiatives require stage 4 or 5 maturity. This fundamental mismatch explains why so many initiatives fail. Without the right cultural frameworks, technological expertise, and technical infrastructure, organization-wide transformation based around AI capabilities stand little chance of success. Start Where You Are, Not Where You Want to Be The path to AI success begins with brutal honesty about current capabilities. A national security agency we studied exemplifies this approach. Despite seeing enormous opportunities in large language models, they recognized serious risks around data drift, model drift, and information security. Rather than rushing into advanced implementations, they are pursuing incremental development grounded in institutional knowledge and cultural readiness. This measured approach doesn't mean abandoning ambitious goals—it means building toward them systematically. Organizations must select projects that are appropriate to their maturity level while ensuring each initiative serves dual purposes: delivering immediate value and advancing foundational capabilities for future growth. Three Immediate Opportunities For agencies at early maturity stages, three implementation areas offer immediate value creation opportunities while building toward transformation: 1. Information Technology Operations IT represents the most accessible entry point for government AI adoption. The private sector offers a road map — 88% of companies now leverage AI in IT service management, with 70% implementing structured automation operations by 2025, up from 20% in 2021. AI can transform government IT through chatbots handling common user issues, intelligent anomaly detection identifying network problems in real-time, and dynamic resource optimization automatically adjusting allocations during peak periods. These capabilities deliver immediate efficiency gains while building the technical expertise and collaborative patterns needed for higher maturity levels. The challenge lies in government's unique constraints. Stringent security requirements along with legacy systems at agencies like Social Security and NASA create implementation hurdles that private sector organizations rarely face. Success requires careful navigation of these constraints while building foundational capabilities. 2. Predictive Analytics Predictive analytics represents perhaps the highest-value opportunity for early-stage agencies. Government organizations possess vast data resources, complex operational environments, and urgent needs for better decision-making—perfect conditions for predictive AI success. The U.S. military is already demonstrating this potential, using predictive modeling for command and control simulators and live battlefield decision-making. The Department of Veterans Affairs has trialed suicide prevention programs using risk prediction algorithms to identify veterans needing intervention. Beyond specialized applications, predictive analytics can improve incident management, enable predictive maintenance, and forecast resource needs across virtually any government function. These implementations advance AI maturity by building essential data management practices and analytical capabilities while delivering immediate operational benefits. Unlike complex generative AI systems, predictive analytics can be implemented successfully at any maturity stage using well-established machine learning techniques. 3. Cybersecurity Enhancement Cybersecurity offers critical immediate value, with AI applications spanning digital and physical protection domains. Modern AI security platforms process vast amounts of data across networks, endpoints, and physical spaces to identify threats that traditional systems miss—a capability that is particularly valuable given increasing attack sophistication. Current implementations demonstrate proven value. The Cybersecurity and Infrastructure Security Agency's Automated Indicator Sharing program enables real-time threat intelligence exchange. U.S. Customs and Border Protection deploys AI-enabled autonomous surveillance towers for border situational awareness. The Transportation Security Administration uses AI-driven facial recognition for streamlined security screening. While national security agencies implement the most advanced applications, these capabilities offer immediate value for all government entities with security responsibilities, from facility protection to data privacy assurance. Building Systematic Success Creating sustainable AI capabilities requires following five key principles: Build on existing foundations. Leverage current processes and infrastructure while controlling implementation risks rather than starting from scratch. Develop mission-driven capabilities. Create implementation teams that mix technological and operational expertise to ensure AI solutions address real operational needs rather than pursuing technology for its own sake. Prioritize data quality and governance. AI systems only perform as well as their underlying data. Implementing robust data management practices, establishing clear ownership, and ensuring accuracy are essential prerequisites for success. Learn through limited trials. Choose use cases where failure won't disrupt critical operations, creating space for learning and adjustment without catastrophic consequences. Scale what works. Document implementation lessons and use early wins to build organizational support, creating momentum for broader transformation. The Path Forward Government agencies don't need to choose between ambitious AI goals and practical implementation. The key is recognizing that most transformation happens through systematic progression. While 'strategic leapfrogging' is possible in some situations, it is the exception rather than the norm. By starting with appropriate projects, building foundational capabilities, and scaling successes, agencies can begin realizing concrete AI benefits today while developing toward their longer-term transformation vision. The stakes are too high for continued failure. With 48% of Americans already distrusting AI development and 77% wanting regulation, government agencies must demonstrate that AI can deliver responsible, effective, and efficient outcomes. Success requires abandoning the fantasy of overnight transformation in favor of disciplined, systematic implementation that builds lasting capabilities. The future of government services may indeed be AI-first, but getting there requires being reality-first about where agencies stand today and what it takes to build toward tomorrow. (This article draws on the cross-disciplinary expertise and applied research of Faisal Hoque, Erik Nelson, Professor Thomas Davenport, Dr. Paul Scade, Albert Lulushi, and Dr. Pranay Sanklecha.)
Fox News
an hour ago
- Fox News
Trump endorses House freshman for reelection less than six months into the lawmaker's congressional tenure
President Donald Trump issued a full-throated endorsement of Rep. Abe Hamadeh, R-Ariz., backing the lawmaker for re-election less than half a year into the freshman House member's first term in office. "Abe Hamadeh has my Complete and Total Endorsement for Re-Election – HE WILL NEVER LET YOU DOWN!" the president declared in a Truth Social post in which he described the congressman as "an America First Patriot." Trump endorsed Hamadeh in December 2023, ahead of the 2024 GOP U.S. House primary in Arizona's 8th Congressional District. But then later he issued an unusual dual endorsement of both Hamadeh and another GOP primary candidate, Blake Masters, just ahead of the 2024 contest that Hamadeh ultimately won. Back in February Hamadeh introduced a resolution to limit the types of flags that may be displayed in House facilities, though the text of the proposal stipulates that it would not "apply to the individual personal office space of a Member of the House of Representatives." The resolution would allow for displaying the American flag and various other kinds of flags, some of which would include "The State flag of the represented district of a Member of the House of Representatives, displayed adjacent to the office of such Member" and "The flags of visiting foreign dignitaries during an official visit." "Congress is supposed to embody the AMERICAN people. That's why I've introduced a resolution to ban foreign and ideological flags in the Halls of Congress. It's pathetic that I even have to introduce this resolution," Hamadeh declared in a tweet this month. Six other House Republicans are listed as cosponsors on including three original cosponsors and three other lawmakers listed as backing the measure this month. "You have inspired me and so many other young men and women to fearlessly serve our country in our nation's Armed Services and the halls of Congress," Hamadeh wrote in a June 14 letter to Trump marking the president's 79th birthday and the Army's 250th.
CNN
an hour ago
- CNN
Here's how Trump's ‘big beautiful bill' would impact housing
Americans face a shortage of affordable homes, but the mega tax and spending bill championed by the Trump administration has the potential to shape housing affordability for years to come. The 'One Big Beautiful Bill' Act, a linchpin of President Donald Trump's economic agenda, is primarily a sweeping tax overhaul, intended to make the 2017 tax cuts passed during Trump's first administration permanent. The version passed by House Republicans last month, now being deliberated in the Senate, would also push more Americans off Medicaid and food assistance, according to multiple assessments. The bill is also estimated to add trillions of dollars to the national debt over the next decade. But tucked inside the bill's more than 1,000 pages are a set of housing-related tax changes that could expand affordable housing and deliver new tax breaks to homeowners in higher-cost states. Critics, however, warn the bill may also tilt the playing field in favor of wealthy buyers and powerful landlords, particularly through a provision that blocks local governments from regulating rent-setting algorithms for the next decade. 'Broadly speaking, this is not intended to be a housing bill,' said Andy Winkler, the director of the Bipartisan Policy Center's housing and infrastructure projects. 'But there are several provisions that, if they do get enacted, could affect housing supply, preservation and affordability.' Here's what you should know about how the bill may affect housing: America's home affordability woes are partially driven by a shortage of available homes for sale, which has driven up costs. A Zillow analysis estimated America was short 4.5 million homes in 2022. Trump's 'big beautiful bill' includes provisions designed to address the shortage of low-income and moderate-income housing at a time when nearly half of American households spend more than 30% of their income on rent or mortgage payments, falling under the US Department of Housing and Urban Development's definition of 'cost-burdened.' The House version of the bill extends and expands the Low-Income Housing Tax Credit (LIHTC), a federal program that incentivizes private investors to develop affordable rental housing for low-income tenants. The bill restores and extends a temporary 12.5% increase in LIHTC allocations through 2029 and lowers the amount of government-issued bonds that developers are required to use to qualify for federal tax credits to build affordable housing. Novogradac, an accounting firm that provides services for developers, estimates that 527,700 additional affordable rental homes could be financed between 2026 and 2035 if these provisions were to become law. 'The bill would have a decent impact on housing supply,' Winkler said. 'And there's a lot of interest in the Senate in doing more than what the House-passed version of the bill does for housing.' 'But they're already having to walk a pretty tight rope to balance the cost of these expiring tax credits, not impact deficits too much and keep costs down to be able to have the bill move forward,' Winkler added. The bill also raises the State and Local Tax (SALT) deduction, which allows taxpayers to deduct what they paid in state and local taxes — like income taxes and property taxes — from their federal tax bill. Under the 2017 Trump tax law, the deduction was capped at $10,000, no matter how much was paid. Under the House version of the new tax bill, that deduction would be raised to $40,000, allowing homeowners in high-tax states like New York and California to deduct more of their property taxes. Jim Tobin, the CEO of the National Association of Home Builders, said the LIHTC and SALT deduction expansions, along with increased tax benefits for small businesses, would be beneficial to homebuilders. 'We believe the bill will provide certainty in taxation for most individuals that are needed to usher in continued economic growth at a time when the housing industry desperately needs it,' Tobin told CNN. One provision buried in the House's version of the bill would block states from regulating artificial intelligence models or automated decision systems. If that provision were to remain in the final bill, it would be a victory for companies that provide rent-setting algorithms to landlords. One of the best-known of these companies, Texas-based RealPage, which uses non-public rent data from landlords to train its algorithms and create pricing recommendations, is facing legal challenges and potential regulation from at least eight states. The GOP tax bill would effectively put an end to the potential regulation. Last month, a group of 40 state attorneys general signed a letter asking Congress to reject the measure. 'The impact of such a broad moratorium would be sweeping and wholly destructive of reasonable state efforts to prevent known harms associated with AI,' the letter read, directly citing states' efforts to 'protect renters when algorithms are used to set rent.' The housing provisions are a small part of the overall bill, which, overall, would add $2.4 trillion to the debt over the next decade, according to the Congressional Budget Office's analysis. Americans will feel that growing mountain of debt in the form of higher interest rates, economists warn. When the government has a lot of debt, it needs to borrow money to keep paying the bills by selling Treasury bonds. If investors believe the government is more leveraged, they will demand higher interest rates to compensate for the risk of their investment. Though it may seem like an overly broad financial concept, those higher interest rates affect housing in the form of higher mortgage rates and higher borrowing rates for homebuilders, which can then translate to higher costs for new construction. At a time when average mortgage rates are hovering near 7%, a further rise in borrowing costs would make homeownership more difficult for some Americans. 'We care quite a lot about higher interest rates in the housing world,' Winkler said. 'It means people buying fewer homes and people being able to build fewer homes.' 'Some of these broader impacts are just as important, if not more important than some of the specific housing provisions,' he added. The White House's plan to curb government spending could do even more damage to housing affordability. Last month, the White House released its budget proposal for 2026. It included steep cuts to housing and community development programs. David Dworkin, the president of the National Housing Conference, a nonprofit that advocates for affordable housing solutions, told CNN that he is hopeful Congress will not agree to cut housing programs suggested by the White House. 'The president's budget is an opening proposal,' Dworkin said. Trump 'put out an executive order addressing the issue of housing affordability on Day 1 and we support that emphasis. We disagree with the budget proposals around housing, and we look forward to reconciling that with the administration.'
