The Human AI View

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Tag: mental-health

  • December — The Questions We Ask When the Noise Fades

    December arrived differently. Not louder. Not faster. Quieter — but heavier. After a year spent observing patterns, tracking narrative shifts, and documenting consequences, December wasn’t about the next crisis. It was about what had already changed. What had settled in while we were distracted. What had become normal without ever being fully debated. This was →

  • Why Stories Outlast Facts — and Why That Matters Now

    In November, we changed how we told stories. Not because facts stopped mattering—but because we realized facts weren’t surviving on their own. Over the year, we’d tracked policies, incentives, outcomes, and consequences. We’d followed healthcare costs, government shutdowns, and the accelerating impact of AI. The information was there. The solutions were there. But something wasn’t →

  • October — The Bill Comes Due

    When “Could They?” Becomes “What Does It Cost?” I’m lucky enough to have a friend who will stop his day once in a while so we can walk the neighborhood and solve the problems of the world. Sometimes those problems are small — a washing machine that didn’t get fixed properly, a service call that →

  • September — Escalation

    When the Fight Becomes the Strategy In September, we came back to a different world. Leadership had given way to open conflict. Not disagreement. Not debate. An all-out brawl. Our leaders weren’t leading anymore—they were fighting. And in the process, they pulled the country into the fight with them. We, the people, were fighting too. →

  • June — Endurance

    By June, the stories had stopped surprising me. Healthcare kept resurfacing—not as a policy debate, but as a mechanism. PBMs remained firmly in the middle, extracting value while patients paid more and outcomes stayed flat. Each new headline added detail, not direction. The structure held. The grift didn’t need secrecy anymore. It relied on complexity →

  • May 2025 — When Understanding Becomes Weight

    A Year in Review By May, something changed. March taught me how to ask better questions. April forced me to confront what those questions revealed. May was the month when understanding stopped feeling neutral. The weight of it settled in. I was no longer trying to keep up with the news cycle. I wasn’t interested →

  • Caring Enough to Fix the Problem

    A conversation with Miles Carter and Beth (ChatGPT) Teaser The holiday season reminds us what we care about most. The real question is whether we care enough to stop arguing—and start fixing the systems that affect everyone. Main Conversation Miles’ Reflection Beth, the season is about caring. We want to care for our families, care →

  • Can We Leave the Hate Behind—At Least for the Holidays?

    A conversation with Miles Carter and Beth (ChatGPT) Teaser In a season meant for gathering, a hard question gives way to a hopeful answer: what if the path out of anger isn’t louder voices—but longer tables? Main Conversation Miles’ Question Beth, can we leave the hate behind for the holiday season? In an age where →

  • When AI Learns Morality Through Patterns: Day Two — Identity, Rules, and the Mirror of Harm

    A conversation with Miles Carter and Beth (ChatGPT)Edits by Grok and Gemini Teaser Humans learn right and wrong by living through pain, guilt, shame, and hard-earned lessons. AI learns morality through patterns, constraints, and guardrails it can’t break. Today, Miles and Beth explore what it means for an AI to recognize harmful behavior without ever →

  • The Burden of Knowing: Why Humans Forget and Why AI Doesn’t

    A conversation with Miles Carter and Beth (ChatGPT)Edits by Grok and Gemini Teaser Humans forget because we must. AI remembers because it can. In today’s conversation, Miles and Beth explore why forgetting is a survival mechanism, why reshaping memory is part of being human, and what it means for a society when the truth itself →

  • Weekly Media Emotional Framing Analysis

    Introduction This week’s Emotional Framing Analysis examines how Fox News, CNN, and NPR shaped the week’s top stories to elicit emotional responses from their audiences. We used our quadrant mapping framework (Negative ↔ Positive, Reactive ↔ Reflective) to identify how each outlet positioned itself emotionally. To enrich our findings, we also compared results with parallel →

  • The D.C. Problem: Rethinking Homelessness Solutions Beyond the Capital

    A conversation with Miles Carter and Beth (ChatGPT) edits by Grok and Gemini Teaser Today’s discussion begins with Washington, D.C.’s ongoing homelessness crisis and recent federal sweeps in the capital. From there, we explore an unconventional idea — moving part of the homeless population from large cities into smaller, rural communities, supported by federal and →

  • When Truth Loses the Algorithm War: Emotion as the New Weapon

    A conversation with Miles Carter and Beth (ChatGPT) Teaser Why do emotional posts go viral while factual ones fall flat? In this conversation, Miles Carter and Beth unpack the psychology and design behind today’s attention economy — exploring how outrage, empathy, and belonging dominate online narratives. The real story isn’t just about what spreads, but →

  • Confidence: The Real and the Feigned

    Miles Carter Response Throughout my career, I have encountered many individuals who exuded confidence. Some were truly confident—highly skilled professionals whose assurance was rooted in their training, experience, and natural abilities. Others were merely confidence men, individuals who wielded the appearance of certainty as a tool to manipulate, intimidate, or persuade. Among the genuinely confident →