Casey Newton

The television media architecture provides the public with two types of frames: episodic and thematic. The episodic news framing will treat political issues/events as specific, isolated and individual events. Iyengar argues that television news relies overwhelmingly on episodic framing, focusing on individual cases, individual victims and individuals responsible for it. Using such episodic framing, the television media leads the audience to blame individual choices or flaws rather than focus on systematic, governmental or structural failures.

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Sorry, you techies dreaming of a new career in park ranger-ing. Those jobs got DOGE'd. On this week's episode of Pacific Standard Time, we spoke with Rya Jetha about the doomsday dinner conversations workers in Silicon Valley are having as AI takes over their job responsibilities.

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For my last freelance story, I wrote about how software engineers are fighting AI code slop. Among other approaches, engineers are scrutinizing plans before AI begins coding, deploying specialized AI agents to catch routine flaws, sending risky changes to human reviewers, or requiring developers to defend the code their agents produce. The increased focus on code review has implications for early-career engineers -- and the profession as a whole. Read more in IEEE Spectrum: https://lnkd.in/gvVEnZDv

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As large language models begin to hallucinate less, we're starting to trust them more. That's a mistake. "When you hear that the iceberg is mostly under the water, you don't feel better," Dan Klein a University of California, Berkeley professor and co-founder and CTO of Scaled Cognition told me. Last June I also wrote about how chatbots were still making stuff up and since then we keep hearing about people believing, sharing and publishing chatbot hallucinations. Here's my annual reminder not to be lulled into believing everything your seemingly smart AI friend tells you. (Also, not your friend.) https://lnkd.in/g4sv9t3x

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Not enough marketing and communications pros are paying attention to what is already this generation's big platform shift of information: What is the source of all those AI results? This story (link in comment) from Pete Pachal sums it up nicely: "Comms teams now often put a number on which reporters shape what a chatbot says about their clients, and that has quietly made PR a more strategic job than it was two years ago. A pitch becomes an article, the article gets cited in an AI answer, and you have about as clean a line from cause to effect as the influence business ever produces. Courting influence is nothing new, of course, but there’s often a big difference in what AI counts as influential vs. the old ways, at least for particular brands. Muck Rack compared the journalists PR teams pitch most against the ones AI actually cites most, and the overlap was just 2%. That chasm is there because AI answers reward topical authority over general authority." This is rapidly becoming a primary strategy for Technical.ly, which maintains editorial independence exactly so we can disproportionately shape AI results for the ecosystems we report on. Place-based economic developers underwrite *where* we report, not *what*, which ensures there is consistent, high-quality coverage of their local economies. This is moving so fast, now is the time to set the narrative your organization, or community, is proudest of.

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