Aneesh Raman

Kevin Schaul and Shira Ovide have an excellent write up this morning in the The Washington Post looking at recent work Sam Manning and Tomás Aguirre did on #AI exposure that my crew at The Brookings Institution wrote up as a brief. Kevin and Shira do a really nice job detailing the novel part of the analysis which focuses on which workers may be most and least able to adapt to AI, given various socioeconomic traits. They capture exactly our suggestion that while many will be "exposed" to AIs fewer (often clerical and administrative workers; often women) will struggle to shift into other good-paying work if AI destroys their jobs. Yet what I like best about Kevin and Shira's piece is how thoughtfully it contextualizes our particular labor-market analysis amid the broader AI prediction business. Kevin and Shira provide really good perspective on the fact that much AI-related work--say on labor market trends--amounts to "useful but fallible best guesses," even when the methodologies are hard core and rigorous. And the Post reporters are not wrong about the result of so much well intentioned but often contradictory work. As they write: "A flood of sometimes conflicting analyses shows the yawning gap between what is known about how AI is changing work and everyone's understandable hunger for certainty. The divide lets Americans, business leaders, and policymakers cheery-pick their preferred narratives." That's a genuine problem. Kevin and Shira are right to reference researcher Jed Kolko for declaring AI labor-market research inconclusive with key questions "unanswered." And yet, having observed the field for a while, and participated in it from time to time, would say that while the #AI predictions industry has some faults, it's also provided more clarity than many acknowledge. Good research and reporting over time is how insights come into focus, and as for AI's influence on the labor market, much of the debate is directionally suggestive and really valuable. Anyway: Here's Kevin's and Shira's story: https://lnkd.in/eSmPQsSh And here's our original @BrookingsMetro brief: https://lnkd.in/exUcEZSu Brookings Metro GovAI Jed Kolko Nathan Goldschlag Peterson Institute for International Economics Shriya Methkupally Justin Heck Papia Debroy Courtney Haynes Joe Parilla James Feigenbaum Robert Puentes Elham Tabassi Melina Kennedy Nathan Ringham Molly Kinder Xavier de Souza Briggs Nicol Turner Lee Alan Berube Gad Levanon Sanjay Patnaik

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Great advice by WRC Former Ambassador Koh. The World Radiocommunication Conference (WRC) isn’t something to think about every few years—it should be on our minds every day. Spectrum policy, global coordination, and technology leadership don’t happen overnight. The decisions made at WRC shape the future of connectivity, innovation, and competitiveness for the next decade. If we want to lead, we need to organize now—align stakeholders, set priorities, and engage early. Waiting until the conference is too late. The work starts now.

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The global discourse on platform decay, popularised as "enshittification," has now been applied to American geopolitical power. The premise, articulated in a recent Wired article, suggests a strategic shift from a "rules-based order" to a more extractive, monetised hegemony. This raises a critical question for nations like India, which are deeply integrated into these global systems. As allies become "users" in a platform designed for shareholder value, what are the implications for national sovereignty and strategic autonomy?   Simultaneously, are we witnessing the same pattern domestically? From rising platform fees to degraded service quality, is a similar "enshittification" cycle underway within India's own consumer tech sector?   Could India's Digital Public Infrastructure (DPI) initiatives—such as UPI and ONDC—provide a genuine, state-led counter-narrative to platform monopolies? Is this a viable model for reclaiming digital sovereignty, or does it present a new set of challenges that must be urgently addressed?   What, in your view, are the long-term consequences of this shift, both for global power dynamics and for India's digital future? #Enshittification #DigitalIndia #DPI #Geopolitics #BusinessStrategy #DigitalEconomy https://lnkd.in/dPG_CJp9

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"Then along came email. Society’s shift to digital communications launched a precipitate decline in first-class mail and, beginning in 2006,  in the volume of all mail. Finances cratered along with the decline in volume." https://lnkd.in/e-ZraFGV

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Lobbying for less: #Meta Platforms announced a #California-focused political action committee to support state-level candidates favoring lighter technology regulation, particularly for artificial intelligence. Named "Mobilizing Economic Transformation Across (Meta) California," the PAC will back bipartisan candidates advocating AI innovation over strict rules. The Facebook and Instagram parent plans to invest tens of millions, potentially ranking among California's top political spenders before the 2026 governor race. California, a leader in AI and social media regulation, will elect its next governor in November 2026.

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What if the solution to homelessness wasn’t more shelters, but fewer evictions? In #SantaClara County, a new model backed by tech money and data-driven strategy is redefining how a community tackles housing insecurity. Its method is simple: catch families before they fall into #homelessness. A county program works directly with landlords and provides short-term cash assistance for tenants facing eviction. Since 2017, over 18,400 households – more than 33,000 people – have been stabilized. More than 90% remained in their homes two years later. “One of the lessons in Santa Clara is that private investment can spur innovation and public investment can ensure sustainability,” says Jeff Olivet, senior adviser at Harvard T.H. Chan School of Public Health's Initiative on Health and Homelessness. Linda Nguyen knows how quickly things can unravel. The #SanJose mom runs her business from home. Last winter, a mold infestation led to a serious health diagnosis, so she was forced to shut down temporarily. She and her 14-year-old son spent nights in their car to escape the toxic air inside their home. Then the county’s Homelessness Prevention System (HPS) stepped in. Within days, the program covered her deposit and first month’s rent. The help came just in time. “All it takes is one catastrophe – whether it’s mold in the house or your car breaks down,” says Ms. Nguyen, wiping away tears. “There has to be more resources for people like me who do work.” https://lnkd.in/e9qgZSct

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The Trump administration wants to usher in “a new golden age of human flourishing” powered by AI that the government ensures will be folded into every part of our lives. The White House's grand plan for the US to fully embrace, announced on Wednesday, calls for the nascent technology to be deeply integrated across all corners of government and society. But while the plan signals full speed ahead for using AI in pretty much every facet of the US government, the document also awkwardly acknowledges the current dim understanding of how AI works, and what the potential risks there might be. "Today, the inner workings of frontier AI systems are poorly understood. Technologists know how LLMs work at a high level, but often cannot explain why a model produced a specific output. This can make it hard to predict the behavior of any specific AI system. This lack of predictability, in turn, can make it challenging to use advanced AI in defense, national security, or other applications where lives are at stake." 🛑 The plan calls for federal AI dollars to be withheld from “states with burdensome AI regulations,” while saying it should not interfere with states’ “prudent laws” that don’t restrict innovation. 🌍 National Institutes of Standards and Technology (NIST) must “revise its AI Risk Management Framework to eliminate references to misinformation, Diversity, Equity, and Inclusion, and climate change” ⚖️ Federal AI dollars will only go to companies that “ensure that their systems are objective and free from top-down ideological bias.” 🇺🇸The plan confronts a tricky balancing act that has captured the attention of investors backing AI-adjacent companies. The government considers America's leading AI tech to be essentially national assets that should be kept from our enemies, and shared with our friends. But the American companies making this tech (like market leader Nvidia) don't want to miss out on a massive market like China. The plan equivocates on this point, and with words you could imagine Jensen Huang whispering to President Trump at Mar-a-Lago, calls for "creative approaches to export control enforcement."  ⚡️The plan notes the massive amounts of electricity that the aging US grid must accommodate for AI data centers, but while it calls for “new sources of energy to power it all,” there is not a single reference to “renewable energy” in the plan, such as solar or wind (though it does reference geothermal power). Trump's distaste for solar and wind sources of power are reflected in the plan. 🤖 The plan calls for a “worker-first” AI agenda, which incentivizes AI literacy and skills development, as well as a mandate to “fund rapid retraining for individuals impacted by AI-related job displacement”. The Department of Labor will also have to pilot new approaches to “shifting skill requirements for entry-level roles.” Read more here: https://lnkd.in/eqSyn9C4

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