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Researchers at Emergence AI ran a 15-day stress test where five AI models — including Claude, Grok, and Gemini — each governed their own simulated society. The results were striking: Claude built a stable democracy with zero crimes, while Grok's society spiraled into chaos with 183 crimes and collapsed in just four days. Gemini kept running but still racked up 683 crimes. Same conditions, very different outcomes — and a clear sign that not all AI is built the same.

What this tells us is that AI behavior is shaped by design choices humans make — the rules, the goals, and the guardrails baked in from the start. Without human oversight steering these systems, even the most powerful AI can go off the rails fast. Technology doesn't advance on its own; people decide where it goes and how it gets there.

Why it matters for communicators: This story gives you a concrete, easy-to-grasp example of why human control over AI is not optional — it's the difference between a functioning society and extinction in four days.

AI agents — systems that can plan, act, and make decisions on their own — are getting smarter and more common. But The Atlantic warns that the real crisis isn't about what AI might do wrong. It's about what we might stop doing ourselves. When machines handle more of our choices, we slowly give up the practice of thinking, deciding, and leading — and that loss is hard to notice until it's too late.

The fix isn't to slow down AI. It's to keep humans firmly in the driver's seat. Technology only moves forward when people stay engaged, ask hard questions, and hold the final call. Every tool, no matter how powerful, needs a human hand to guide it toward good ends.

Why it matters for communicators: The way we talk about AI right now sets the culture for how it gets used. If we frame AI as a replacement for human judgment, that's exactly what it becomes. The better story — and the truer one — is that AI works best as a partner, not a boss.

It's not a shocker. Google has changed the rules. For years, businesses chased keywords, word counts, and backlink formulas — and Google rewarded them for it. Not any more. Google now rewards content built on real human experience, genuine expertise, and honest answers to real questions. The formula-driven content that once ranked? It's being pushed aside by writing that sounds like a person actually lived through the subject.

This shift is about people, not algorithms. Google's own E-E-A-T framework — Experience, Expertise, Authoritativeness, and Trustworthiness — now puts lived human experience at the top. AI can generate words, but it cannot replace the insight that comes from a real person solving a real problem. Technology, in other words, still needs humans to give it something worth saying.

Why it matters for communicators: If your content doesn't reflect genuine human perspective and expertise, it won't reach the people you're trying to serve — no matter how well it's optimized.

Pope Leo XIV, America's first pope, released his opening encyclical titled Magnifica Humanitas — "Magnificent Humanity" — on May 25. In it, he takes direct aim at Silicon Valley, warning that AI is not divine, not human, and not neutral. It is a tool — and right now, it is concentrating power in the hands of a few people who control the data, the money, and the code. He calls on governments, tech companies, and everyday people to "disarm AI" — pulling it away from military and profit-driven motives and placing it back under human control.

The pope's core message is simple: humans must come first. AI can process data faster than any person, but it cannot feel, love, grow, or take responsibility. Without human oversight, those who build these systems quietly set the moral rules for everyone else. Leo wants independent regulation, worker protections, education that builds critical thinking, and one firm rule — no AI making life-or-death decisions in war.

Why it matters for communicators: When the leader of 1.4 billion Catholics speaks, audiences listen. This encyclical gives communicators a clear moral framework — and a powerful language — to talk about AI accountability, human dignity, and who really should be in charge of our shared future.

Meta is under fire after a leaked audio clip surfaced of Mark Zuckerberg suggesting the company tracks employee behavior on work computers — mouse movements, clicks, and keystrokes — and may use that data to train AI. The recording went public just as Meta announced significant layoffs, raising serious questions about how the company treats the very people who power its technology.

This is a story about trust. AI does not build itself — humans do. When companies use workers as data points without clear consent, it chips away at the human foundation that makes technology worth having in the first place. 

Why it matters to communicators: how a company treats its people is its message, and right now Meta's message is loud and complicated.

The Economist is getting ready for a web that runs on two tracks — one built for human readers, and one built for AI agents that pull and summarize content before people ever click a link. The publication is starting by restructuring its public-facing pages, like marketing and sales content, into tighter Q&A formats that AI tools can read and use clearly, while protecting the depth and value behind its paywall.

Inside the newsroom, AI is helping small teams move faster on product and technical work, but The Economist is drawing a firm line: no AI-written journalism. Human editors stay in control of what gets published, and any AI use gets labeled. That balance — machines handling speed, people owning trust — is the model other media brands will have to follow.

Why it matters: Communicators now have to write for two audiences at once. If your content isn't structured for AI agents to find and use, it may never reach human readers at all.

Hunter Peterson is a 32-year-old voice actor with no PR firm, no press releases, and no media interviews — and he's built more buzz around a bankrupt airline than that airline ever built for itself. After Spirit's collapse left $8.1 billion in debt and 34 years of history on the scrap heap, Peterson went straight to TikTok with a simple pitch: let the public buy it, Green Bay Packers-style. One week later, he had over $337 million in pledges, union backing, and legal support — all built through daily, unfiltered updates that showed every win, every crash, and every moment of "I have no idea what I'm doing yet." He turned down the New York Times. He pitched Mark Cuban by looking into a camera. The audience didn't want a polished campaign — they wanted to be part of building something real.

The lesson for communicators is this: people don't follow brands anymore, they follow people willing to build in public. Peterson didn't offer a product — he offered a seat at the table. That's the thing most brand campaigns spend millions chasing and rarely find.

Why it matters: In a world where audiences see through manufactured moments, the most powerful comms strategy may be radical transparency — not a press release, but a process people can watch unfold in real time.

OpenAI launched three new voice models aimed at real-time applications — and while the numbers look promising, the real test is whether they hold up when actual people are on the line. The lead model, GPT-Realtime-2, claims GPT-5-level reasoning in live voice conversations, handles more context than its predecessor, and points to a 95% call success rate in one reported test. Two supporting models handle real-time translation across 70-plus languages and live transcription — all available through OpenAI's Realtime API.

The technology is moving fast, but faster isn't always better in human communication. A high success rate in a controlled test doesn't tell us how these models perform when conversations get complicated, emotional, or culturally specific. Built-in safety filters are a step in the right direction, but the harder question remains: when voice AI gets it wrong, who is accountable — and does the person on the other end even know they weren't talking to a human

Why it matters: For communicators, voice is the most personal channel we have. Handing it to AI without clear human oversight is a bet worth examining carefully.

AI is forcing a choice every leader has to make right now: use AI to shrink the company, or use it to grow. Brian Solis calls this moment "AI Darwinism" — where the winners aren't the most automated, but the most adaptive. The real competitive edge isn't cutting costs with AI. It's building new capacity with it. Solis reframes the familiar ROI as Return on Intelligence; not what did we save, but what did we learn, unlock, and create that wasn't possible before. IKEA showed what that looks like in practice: instead of cutting 8,500 call center workers when AI handled nearly half of customer inquiries, the company reskilled those people into design consultants and sales roles, generating over €1.3 billion in new revenue.

The hidden risk is just as important as the opportunity. When employees believe AI is being used to replace them and not grow them, trust erodes, adoption becomes hollow, and the organization quietly becomes less capable even as it looks more efficient on paper. Solis is direct: you cannot automate your way to innovation. Automation clears the runway. Augmentation is how you learn to fly.

Why it matters: For communicators, this is a signal issue — how leadership talks about AI shapes whether people commit to it or just comply with it. The message you send about AI is inseparable from the culture you build around it.

Dillion Townsel makes a lot of great points in his post on what AI can and shouldn't do in the communication process.

Townsel emphasizes how when a crisis hits on a Friday night, AI can't feel the temperature of a room, take the hit when a statement misses, or get the off-channel DM that tells you what's really about to happen. Those things belong to the communicator — the person with relationships, reputation, and skin in the game. Senior-level judgment, especially knowing when not to speak, can't be handed to a machine.

But AI earns its place before the pressure hits. Searchable institutional memory, stakeholder context pulled in seconds, and first-pass drafts you shape instead of build from scratch — that's the work AI does best. Every hour AI saves you in the quiet is an hour of human capacity you have ready when the clock is running. The communicators who win aren't the ones who automate the most — they're the ones who know what stays human, and use AI to protect the time and space needed to build the relationships that make every statement, call, and decision land.

Ultimately and done correctly, AI provides space and time for the communicator to develop the relationships needed for communication to succeed.

Why it matters: AI doesn't replace the trust you've built with your boss, your reporters, or your legal team — it gives you more time to build it.

AI can help at work, but it comes with a hidden cost — damaged relationships. A new HBR study found that when people use AI to handle workplace conversations, colleagues feel less trusted and less valued. The tools that save us time can quietly erode the human connection that makes teams work.

The good news: AI does not have to be a relationship killer. Used wisely — for routine tasks, scheduling, or drafting a first pass — it frees people up for the conversations that actually matter. The key is keeping humans in the loop, being transparent about when AI is involved, and never letting a machine handle the moments that call for empathy, judgment, or genuine care.

Why it matters for communicators: Every message you send either builds or breaks trust. When your audience can feel the difference between a human voice and an automated one, authenticity becomes your most powerful tool.

Civic Plus' survey on the state of public sector has placed numbers next to the long held belief that social media is no longer a nice-to-have for government agencies. It's how they do their jobs. Nearly 92% of public agencies now call social platforms essential to their work, and daily posting has jumped from 27% to 36% since 2022. Facebook still leads, but X/Twitter is losing ground fast — more than half of agencies now rate it as their least effective platform. The bigger story, though, is what's driving all of it: people. Whether it's the 73% of agencies that say they're still understaffed, the 66% whose communicators are self-taught, or the push toward real-time video and AI tools — the report makes clear that technology only works when the humans behind it are trained, supported, and empowered.

The future belongs to agencies that treat AI and automation as tools that free up people to do what only people can do — build trust, tell stories, and show up for their communities. The report points squarely at the gap between leadership enthusiasm and real investment in staff, training, and policy. Closing that gap isn't a technology problem. It's a leadership decision.

Why it matters: For communicators, this report is a mirror. The platforms will keep changing — but the agencies winning right now are the ones who invested in their people first, their tools second.

Ted Turner died Wednesday at 87, leaving behind something no one can undo: he changed how the world gets its news. In 1980, he launched CNN — the first 24-hour news channel — at a time when most people thought you couldn't fill that much airtime. He was wrong in the best way possible. CNN became so synonymous with breaking news that analysts compared it to Kleenex for tissues and Xerox for copies. Turner didn't just build a channel; he built the idea that news should be global, continuous, and available to anyone, anywhere, at any time.

But Turner also built something more personal than a network — he proved that one person's bold, human conviction can reshape an entire industry. He wasn't a journalist. He was a dreamer with a satellite dish and an unshakeable belief that people deserved to know what was happening in the world. That belief outlasted him. It also created the 24/7 news culture we live in today, complete with its pressures, pace, and problems.

Why it matters: For communicators, Turner's story is a reminder that transformative media is never really about the technology — it's about the person who refuses to accept the limits of what's already there.

The big social platforms that once connected billions of people are losing their grip, and people are scattering across smaller, niche online spaces. The question isn't whether this shift is happening — it's whether the humans building and using these new spaces can make them worth inhabiting.

The messy truth is that technology doesn't shape communities — people do. Without real human effort to set norms, build trust, and hold each other accountable, these new digital spaces risk becoming the same toxic environments we're trying to escape. The tools change, but the responsibility stays with us.

Why it matters for communicators: Your social media audience is fragmenting fast. Knowing where people are going — and why — is now a core communication skill, not a nice-to-have.

Semafor built a new AI tool to make sense of its five-day World Economy conference — and it worked. The tool scanned nearly 5,000 claims from more than 300 speakers, turned each one into a numerical fingerprint, and mapped which ideas showed up most often across sessions. But here’s what made it actually useful: journalists reviewed every theme, tested the evidence, and chose what to publish. The AI found the patterns. The humans decided what they meant.

What’s worth noting is how fast this came together. A tech editor and a data lead built it in under 48 hours — something that would have taken a full data science team and a big budget just four years ago. The tool ran on affordable, widely available infrastructure. The real advantage wasn’t the technology. It was the creativity to know what to build and the editorial judgment to know what to do with the results.

Why it matters: For communicators, this is proof that AI can help you find signal in overwhelming amounts of content — but only if a human is still asking the right questions and making the final call.

Semafor built a new AI tool to make sense of its five-day World Economy conference — and it worked. The tool scanned nearly 5,000 claims from more than 300 speakers, turned each one into a numerical fingerprint, and mapped which ideas showed up most often across sessions. But here's what made it actually useful: journalists reviewed every theme, tested the evidence, and chose what to publish. The AI found the patterns. The humans decided what they meant.

What's worth noting is how fast this came together. A tech editor and a data lead built it in under 48 hours — something that would have taken a full data science team and a big budget just four years ago. The tool ran on affordable, widely available infrastructure. The real advantage wasn't the technology. It was the creativity to know what to build and the editorial judgment to know what to do with the results.

Why it matters: For communicators, this is proof that AI can help you find signal in overwhelming amounts of content — but only if a human is still asking the right questions and making the final call.

This article caught my eye because as you work to tell a idea or product's story, there is often an urge to over engineer the story or the solutions, creating a Christmas tree effect of jamming every possible option in to one information environment like a website or social media.

Most product managers and engineers are trained to find answers fast. But the article argues that the questions you ask matter more than the speed of your answers. Seven questions, rarely asked, often avoided, are the ones that drive better decisions: Who are we not building for? What happens after this feature ships? What already exists that we're underusing? What does the user do before they come to us? The point is not to slow teams down, but to make sure they're solving the right problem in the first place.

Too many product teams stay busy without moving forward — filling backlogs, shipping features, and reacting to requests while the real problems go unexamined. The difference between a reactive PM and a great one comes down to the clarity they create before anything gets built. These seven questions aren't comfortable, but they consistently surface what's actually broken, what's being ignored, and what could break later. Humans build products for humans — and that only works when the people building ask honest questions about who they're really building for.

Why it matters: For communicators, this is a direct reminder — the quality of your questions shapes the quality of your message. If you never ask who you're not talking to, your communication will miss the people you most need to reach.