When CEOs say what they really think. The rise and fall of worker power and are you a "NPC"?
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James Cowie, The yellow glove 1928
Inside the Room Where CEOs Say What They Really Think of Trump’s Policies
Corporate leaders regularly praise the Trump administration and its policies in public. Behind closed doors, their mood is darker. At a meeting of CEOs and other executives on Wednesday convened by the Yale School of Management, dozens of America’s business leaders sounded off on their concerns about tariffs, immigration, foreign policy matters and what many described as an increasingly chaotic, hard-to-navigate business environment. “They’re being extorted and bullied individually, but in private discourse, they’re really upset,” said Jeffrey Sonnenfeld, a Yale management professor who organized the event, referring to recent deals that give the U.S. government a cut of certain Nvidia chip sales and a “golden share” in U.S. Steel.
In a series of poll questions, the executives in the room made their frustrations known. Asked if tariffs had been helpful or hurtful to their businesses, 71% of respondents described the levies as harmful. Another question centered on the legality of tariffs. About three quarters of respondents said courts were correct in saying the tariffs are illegal as executed. The Supreme Court will take up the matter this fall.
Source: WSJ
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Worker power measured by the link between wage growth and the output gap (stroke of genius by Dario Perkins)
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James Cowie, The Reader
Source: National Galleries
The AI gold rush has sparked a vibe shift in San Francisco.
The city is flush with money again after the post-ZIRP recession of 2022. Cracked 22-year-old coders are telling the world they’re going to “solve hurricanes” and the "national debt.” Lurie is mayor, nature is healing, the technology brothers are back with a vengeance. Take a look—$100 million salaries, glitzy hype videos for fundraises, lavish parties with dress codes—Silicon Valley is swelling with Trump-era opulence—blustery, spendy, and male. It is easy to think from the outside that San Francisco is the one place on earth insulated from crisis. Everyone else is living in fear of political upheaval and mass job loss, while the rich nerds discovered suit jackets and now they’re the ones on top. “My mutuals run the world,” goes one Twitter refrain. For the tech industry as a whole, this may be true. But for most individual participants, the swagger is a gilded surface, paper-thin. To make an analogy: while most English-language headlines about China emphasize its industrial might, some observers have turned to internet anthropology as a way to find cracks in the story. Social media slang like 996, tangping, laoshuren, and involution point to the slice of urban youth who feel they are getting crushed by the development machine. Humor is a release valve for what you can’t say. Likewise, read between the tweets, and you’ll find an uneasy blend of ironic zoomer nihilism and a triumphant tech bro resurgence, big-mouthed hustle-posting with an undercurrent of AI status anxiety:
Are you a live player or a dead one?
Are you high-agency or an NPC?
Do you think you’ll escape the permanent underclass?
This summer, my Twitter algorithm was dominated by talk of escaping the “permanent underclass” and the “great lock-in” of September to December 2025.
These are mostly jokes, of course. But they express young tech workers’ latent anxiety about who will win and lose in the age of AGI—or at least, the assumption that there will be winners and losers, rather than AGI bringing about widespread abundance in a massively positive-sum game. Even the people building AI don’t feel insulated from precarity. Nobody knows if they’ll end up above or below the API: whether you’ll be the automaters or the automated. And despite CEOs’ attempts at optimism, I hear the “gentle singularity” and “personal superintelligence” deployed more often as punchlines than earnest visions of utopia.
Taste
The current consensus is that Rick Rubin is the most human human to ever live. In a world where intelligence is too cheap to meter, what matters is not skill but knowing where to direct it.
“Research taste” is about naturally intuiting the most impactful problems to work on; “high-taste testers” are what OpenAI calls the power-users they ask to qualitatively assess model vibes (presumably, low-taste testers are the unwashed masses, relegated to mere thumbs up/down votes). Marc Andreessen proclaimed that the “taste element” means VC is the one job that can’t be automated: “It’s not a science—it’s an art.
Decel / doomer
I gotta hand it to the e/accs: “decel” is a beautiful turn of phrase. It effortlessly links “decelerationist” to the reviled “incel,” making it a perfect all-purpose slur for anyone advocating more than zero tech regulations or who’s unwilling to raze a neighborhood in service of a new chip factory.
Why is the US avian flu epidemic killing other mammals but not humans?
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When I asked ChatGPT where the idea of a “theory of change” came from it gave me this:
The phrase “Theory of Change” as a method or term in program design / evaluation / political/social strategy does not appear to have a single clear inventor who used it in full in exactly the form it’s used today; but it is strongly associated with Carol Weiss (and others) via her work (mid-1990s) and particularly through Aspen Institute’s Roundtable on Community Change. Below is a summary of what the available literature says, including who popularized it, what earlier precursor ideas there were, and what uncertainties remain.
Which pointed to a quasi official website!
Theory of Change (TOC) Origins
It is difficult to trace precisely when the term “theory of change” was first used, but a hint at its origins can be found in the considerable body of theoretical and applied development in the evaluation field, especially among the work of people such as Huey Chen, Peter Rossi, Michael Quinn Patton, and Carol Weiss. These evaluation theorists and practitioners, along with a host of others, have been focused on how to apply program theories to evaluation for many decades. The stream of work leading to the use of theories of change in evaluation can be traced back to the late 1950s with Kirkpatrick’s ‘Four Levels of Learning Evaluation Model’. Further progress and evolution has included Daniel Stufflebeam’s CIPP (context, input, processes and products) and the widely used logical frameworks (logframes) or logical models which set out causal chains usually consisting of inputs, activities, outputs and outcomes coupled to long-term goals. Methods such as logframes were a significant advance, providing a framework through which the relationships between a program’s components could be drawn out and articulated. However, US writers such as Weiss, Chen and Patton increasingly highlighted the challenges in evaluating complex social or community change programs when it was not clear precisely what the programs had set out to do or how and therefore difficult to evaluate whether or how they had achieved it (James, 2011). One organisation which began to focus on these issues was the US based Aspen Institute and its Roundtable on Community Change. The work of the Roundtable led to the publication in 1995 of New Approaches to Evaluating Comprehensive Community Initiatives. In that book, Carol Weiss, a member of the Roundtable’s Steering Committee on Evaluation, hypothesized that a key reason complex programs are so difficult to evaluate is that the assumptions that inspire them are poorly articulated. She argued that stakeholders of complex community initiatives typically are unclear about how the change process will unfold and therefore give little attention to the early and mid-term changes that need to happen in order for a longer term goal to be reached. The lack of clarity about the “mini-steps” that must be taken to reach a long term outcome not only makes the task of evaluating a complex initiative challenging, but reduces the likelihood that all of the important factors related to the long term goal will be addressed (Weiss, 1995). Weiss popularized the term “Theory of Change” as a way to describe the set of assumptions that explain both the mini-steps that lead to the long-term goal and the connections between program activities and outcomes that occur at each step of the way. She challenged designers of complex community-based initiatives to be specific about the theories of change guiding their work and suggested that doing so would improve their overall evaluation plans and would strengthen their ability to claim credit for outcomes that were predicted in their theory. She called for the use of an approach that at first blush seems like common sense: lay out the sequence of outcomes that are expected to occur as the result of an intervention, and plan an evaluation strategy around tracking whether these expected outcomes are actually produced.
Source: Theory of change
View from a Window, James Cowie R.S.A. (1886-1956)
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