Aneesh Raman

Christy Romer: Lessons on fiscal & monetary policy coordination from American history/ When does rowing together work out well and when doesn't it. From her survey of the history, she draws four lessons: Lesson 1: Policy coordination is not sufficient to ensure good economic outcomes. Lesson 2: Economic ideas matter. Lesson 3: Because policy mistakes occur, the independence of central banks is vital. Lesson 4: Successful policy coordination demands accurate data and honest information on the federal budget.https://https://lnkd.in/epTiUntV. via The Brookings Institution

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Nonpartisan institutions that rely on facts and research to shape public understanding are being left behind — not because they lack insight, but because they lack presence where it matters most. Today’s media ecosystem rewards authenticity, resonance, and networked participation — not credentials, citations, or carefully crafted op-eds. Institutions can’t afford to treat audience engagement as an afterthought. Renee DiResta and I just published a new paper with the Carnegie Endowment: "For Expertise to Matter, Nonpartisan Institutions Need New Communications Strategies." We argue that the old top-down comms playbook — press releases, Sunday shows, reports behind paywalls — isn’t just outdated, it’s increasingly speaking only to a niche audience. So we offer alternatives strategies for building trust, networks, and long-term partnerships, in a call-to-action for funders, think tanks, and public interest institutions: Read the whitepaper here. And if you're experimenting with new ways of connecting with audiences, we'd love to hear about them: https://lnkd.in/eHvKNaBN

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Scott Wallsten's recent research on AI Intensity by Occupation reveals that AI adoption is 12x more intensive among writers than their workforce size suggests. At the same time, major employment sectors like healthcare (9.4% of workers) barely use AI at all—showing that AI's economic impact remains deep but narrow, concentrated in just 5-7% of the workforce rather than broadly transforming the labor market. • New Measurement Approach: Scott's study introduces an "AI Intensity" metric that divides each occupation's share of AI usage by its share of total employment. A score above 1.0 indicates disproportionately high AI adoption relative to workforce size, addressing the limitation that raw usage data can reflect large employment bases. • Writers and Researchers Lead Adoption: Writers and media professionals show the highest AI intensity at 12.3x their employment share, followed by life/social science technicians (11.0x) and social scientists (9.7x). This concentrated usage pattern reveals that AI adoption is "deep but narrow," with a heavy concentration in small occupational groups that represent only 5-7% of the workforce. • Major Employment Sectors Lag Significantly: Despite potential benefits, large employment sectors show minimal AI engagement: healthcare practitioners (9.4% of workforce) at only 0.2x intensity, business operations specialists (6.7% of workforce) at 0.2x, and K-12 teachers at 0.3x. Even within similar fields, adoption varies dramatically - postsecondary teachers show 18x higher intensity than K-12 teachers. • Data Limitations Reveal Usage Patterns: The analysis relies on Claude.ai data (1% market share vs ChatGPT's 80%), and notably, programmers show low chatbot AI intensity because they primarily use specialized tools like GitHub Copilot via APIs rather than conversational interfaces, highlighting that AI adoption patterns vary by tool type. • Economic Implications: Current AI usage patterns suggest productivity gains and disruptions will disproportionately affect high-wage knowledge workers rather than automating routine tasks. The "missing middle" of office workers shows unexpectedly low adoption despite apparent task compatibility. • Barriers Beyond Technology: Low adoption in healthcare, education, and business operations suggests sector-specific barriers, including regulatory constraints, workflow integration challenges, infrastructure gaps, and organizational change resistance that won't be solved by better AI models alone. • Future Research Priorities: Scott calls for longitudinal analysis tracking whether these concentrated patterns persist or broaden, research linking AI intensity to wage/employment outcomes, and comparative studies across different AI tools to provide a complete picture of AI's labor market impact. #AI #Workforce Here's the work ⬇️ https://lnkd.in/eUeTRGeG

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Want to know more about how the Bureau of Labor Statistics does its job? Curious why (and how) job numbers get revised every few months and year-over-year? Want to know what the BLS Commissioner actually does? Check out the latest episode of the PolicyViz Podcast with former BLS Commissioner Erica Groshen to learn more about how this important agency works and how to keep it healthy, objective, and independent. https://lnkd.in/egP_AZQS

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See what you think of some new work on an important #AI question from Sam Manning and Tomás Aguirre aided and abetted by Shriya Methkupally and myself. Here it goes: The important question: If AI leads to job displacement, who will adapt best and who will struggle most? The new work finds that for the most part AI exposure and adaptive capacity travel together. As Sam says, "Many occupations that are highly exposed to AI also contain workers with relatively strong means to manage a job transition if displacement occurs." Or as I'd put it: Many of the white-collar office workers who are most exposed to AI are also some of the best equipped workers in the economy to manage disruption and find a new job. Think here of their strong educations, useful skills, and savings. If anybody is going to do all right they will. At the same time, though, not everybody is so lucky. According to the new research, 6.1 million workers are in occupations that are both highly exposed to AI and have low expected adaptive capacity. These workers are disproportionately concentrated in clerical and administrative roles, where savings tend to be lower and required skillsets are more narrow and less transferable. >80% of workers in these occupations are female. Ultimately, the new work depicts a national economy characterized by wide swaths of likely resilience variegated by concerning pockets of precariousness job loss could be existential. Workforce officials and others need to take this on board. Policymakers need to recognize the special challenges of the vulnerable who could have trouble finding new work after dislocation. Thread here from Sam: https://lnkd.in/emgG43rc And here's our The Brookings Institution brief, a collaboration of Sam, Tomas, Shriya and myself: https://shorturl.at/CvvXH Brookings Metro Xavier de Souza Briggs Molly Kinder Alan Berube Anna Stansbury Andre M. Perry Erik Brynjolfsson Scott Andes Annelies Goger Nicol Turner Lee Elham Tabassi Alex Tamkin Kevin Roose Gopi Shah Goda Brent Orrell Michael Hicks

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Trust, and verification: Why do people seem better disposed to chatbots than to news organizations, despite well-documented hallucinations? It may be less to do with LLM's features and more with the way we interact with them. My latest post for the Tow-Knight Center for Journalism Futures at Craig Newmark Graduate School of Journalism at CUNY. https://lnkd.in/gWeMwyBE

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Anthropic’s weekslong battle with the Department of Defense has played out over social media posts, admonishing public statements, and direct quotes from unnamed Pentagon officials to the news media. But the future of the $380 billion AI startup comes down to just three words: “any lawful use.” The new terms, which other AI labs have reportedly already agreed to, would give the US military carte blanche to use services for mass surveillance and lethal autonomous weapons -- or AI that has full power to track and kill targets with no humans involved in the decision-making process. The negotiations have turned ugly, with Pentagon CTO Emil Michael, formerly a top executive at the ridehailing company Uber, driving the government’s threats to designate Anthropic as a “supply chain risk,” according to two people familiar with negotiations. This classification is usually reserved for threats to national security, including malicious foreign influence or cyber warfare. Anthropic CEO Dario Amodei will reportedly meet with Secretary Pete Hegseth today at the Pentagon, and an unnamed Defense official described it as a “shit-or-get-off-the-pot meeting.” (The Verge, with Tina Nguyen) Gift link here: https://lnkd.in/eVbGJfnp

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In my latest piece for Americans for Responsible Innovation, I explore: ✅ The AI Action Plan’s strengths—from interpretability investments and trustworthy evaluations to workforce training and secure infrastructure ✅ How it addresses national security risks and builds public-private readiness ⚠️ And why funding restrictions on states with “onerous” AI laws and procurement standards for “objective” LLMs could alienate both sides of the aisle When AI policies prioritize performance, transparency, and public trust, America leads. But when governance becomes politicized, we all lose. Read the full breakdown here 👉 https://lnkd.in/gDG3bZKP #AI #AIGovernance #TechPolicy #Innovation #ArtificialIntelligence #ResponsibleAI #AIActionPlan #PublicTrust #PolicyAnalysis #ARI #BipartisanTech

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🚨 New episode of The Coursera Podcast is live! This week, Anthony Salcito and I sat down with Danielle Haro, Director of Transition Programs at the USO, to discuss how service members and military spouses navigate one of the most important transitions of their lives. Leaving the military isn’t just a career move — it’s a major life shift. Danielle shared how the USO combines personalized support, strong community, and skills-based learning to help people move forward with confidence in a rapidly changing workforce. We covered: 🧭 What “career-readiness” really means today 💥 How individualized action plans guide learners to new job pathways 🚀 How learning on Coursera builds confidence and career momentum 🤖 Why AI literacy and human skills matter across every role 🎧 Tune in: https://lnkd.in/gbu_wVFE #TheCourseraPodcast #MilitaryTransition #SkillsFirst #WorkforceDevelopment #FutureOfWork #LifelongLearning

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