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Major League Baseball has officially banned teams from using generative AI tools on the dugout iPads that players and coaches rely on during games. The devices, first introduced through a deal with Apple, were meant to give teams quick access to stats, video, and scouting reports. As some teams started using AI programs to analyze that data in real time, the league stepped in to stop it, worried the technology was moving too fast for the game to control.

Why it matters (communicator's take): This is a clear signal that even fast-moving industries want people, not machines, making the final call in high-pressure moments.

Companies are moving away from expensive, top-tier AI models and choosing cheaper, open-source options instead. Amazon's CTO Werner Vogels says businesses are worried about rising AI bills, so many now pick open-source models that they can download for free and run on their own computers. These models cost less overall, even though companies still pay for the computing power needed to run them.

Why it matters: As a communicator, this shift shows that cost—not just capability—now drives major tech decisions, which means writers and marketers should expect more companies to talk about "value" and "efficiency" in their AI messaging rather than just raw power. It's a reminder that people, not just algorithms, decide what technology gets used and why—human judgment about cost, trust, and need still steers the AI industry forward.

Most organizations still treat communications as a final step—something you do after the strategy is set, the system is built, or the decision is made. Peter Davison flips that order. He argues that communications should function like a bridge or a foundation, something structural that holds the whole system together, not just a message layer on top of it. When communications works this way, it creates alignment across teams with different priorities, gives people clarity when information is incomplete, and builds the trust needed for people to actually adopt new ways of working.

The Human Thread Running Through It

Every outcome in this model depends on people. Systems don't align themselves, decisions don't make sense on their own, and trust isn't automated. Even as organizations lean harder on digital tools and AI to manage complexity, none of that technology can substitute for human judgment about what to communicate, when, and to whom. Technology can move information faster, but only people can decide what that information should mean to the humans receiving it. That's the real infrastructure: human understanding, supported by tools, never replaced by them.

Why It Matters (From a Communicator's Seat)

For communicators, this is a shift from writing messages to designing connective tissue—work that requires sitting inside the systems and decisions themselves, not just describing them after the fact.

When strategy treats communication as infrastructure instead of decoration, decisions get made with better information, teams stay aligned longer, and results actually stick.

AI can make our work faster and better, but new research shows it may be quietly weakening how well we think. Studies from Wharton, Carnegie Mellon, and Anthropic found that people who lean on AI too much stop learning, make more mistakes when the AI is wrong, and lose skills they never got the chance to build. The fix isn't avoiding AI — it's using it wisely: let it handle busywork, but keep the thinking, learning, and decision-making for yourself.

Why it matters: Good communication depends on real understanding, not borrowed answers — if we let AI think for us, we risk losing the judgment and self-knowledge that make our words and decisions trustworthy.

Ukraine's Kyiv Independent covers a war most of its readers will never see in person; 97% of its paying members live outside Ukraine, and two-thirds have no personal connection to the country. To keep that audience engaged, audience development manager Elsa Court feeds hundreds of reader questions into Google's NotebookLM — not to auto-answer them, but to spot patterns: what topics keep coming up, what confuses loyal readers, and where the newsroom needs to dig deeper. That human judgment — deciding what the data means and what to do with it — is the whole point. Machines surface the signal; people act on it.[

But the most important boundary the Kyiv Independent draws is where AI stops entirely. Front-line reporting, the kind filmed under drone fire. stays 100% human. AI can now generate convincing war footage, which means authentic human presence on the ground is the only thing that separates real journalism from fabrication. In a war zone, trust isn't a feature. It's survival. Technology only advances when humans stay in charge of the decisions that matter most.

Why it matters for communicators: Your audience's questions are a data goldmine — but it takes human insight to turn that data into stories worth telling.

Advertising agencies are using AI agents — tools that can plan and buy ads automatically — to work faster and deliver more for their clients. Firms like Dentsu, WPP, and Dept are building these capabilities into their core services, completing work in a fraction of the time it used to take. But the same technology is available to the brands these agencies serve. Hyundai ran its own AI-powered ad campaign and cut online video costs by 67% — without hiring an agency. The tools meant to give agencies an edge are now in everyone's hands.

That's the real story. AI is powerful, but it is not autonomous. The agencies and brands seeing real results are the ones with sharp human thinkers steering the strategy, questioning the outputs, and making judgment calls no algorithm can make. According to the World Federation of Advertisers, 93% of in-house teams plan to invest more in AI over the next two years. That investment only pays off when people stay in control. The technology does not lead; people do.

Why it matters for communicators: Who owns the message is changing. As AI handles more of the execution, communicators who understand how to direct these tools — and when to override them — will be the ones brands trust most.

When people use AI to spot fake news, they get better at it in the moment — but measurably worse when the AI is gone.

A new MIT Media Lab study tracked 67 people over four weeks as they judged real versus fake news headlines. With AI help, participants were 21% more accurate at spotting misinformation — but without it, their performance dropped 15 percentage points below where they started. It's the same pattern seen when GPS weakened our sense of direction: the tool works, but it can quietly erode the skill it's replacing. Researchers call this the "AI dependency paradox," and it's showing up across fields — from journalism to medicine. The good news is that AI designed to ask questions rather than just give answers — using techniques like the Socratic method — helps people actually learn, not just get the right answer in the moment.

Why it matters for communicators: Your audience is increasingly outsourcing their judgment to AI. If you want them to think critically about your message — and trust it — you need to help build their skills, not just deliver answers. Humans must stay in the driver's seat; AI should be the GPS that teaches you the route, not the one that drives for you.

Most people no longer go looking for news — it just finds them. A Montana survey found two-thirds of residents receive news passively, and a national study of 12,000 registered voters found that 40% say "news comes to me" rather than the other way around. That number is almost certainly higher when you factor in the millions of Americans who aren't even registered to vote. The shift is driven by social media feeds, elevator screens, and the sheer exhaustion of a news cycle that often feels hopeless.

This matters because the tools and tech built to reach audiences — newsletters, podcasts, algorithms, AI agents — are largely designed for people who are already paying attention. As passive consumption grows, the "addressable market" for journalism shrinks. Technology can deliver the news, but only engaged humans can decide what it means, act on it, and demand better. The future of an informed public depends on people choosing to stay active — and on communicators fighting to make that choice worth it.

Why it matters for communicators: If your audience is going passive, your message is getting lost. You're not just competing for attention — you're competing against indifference.

Bluesky COO Rose Wang made waves at SXSW London when she said Facebook and X have become "basically AI companies" — no longer the human-centered social networks they once were. Speaking to an audience of journalists, scientists, and everyday users, Wang argued that when one billionaire controls a platform, the rules can change overnight — pushing out the very people who need reliable, verified information. Bluesky's answer is a decentralized model where real communities — not corporate algorithms — decide what they see and how they interact.

Wang's team of just 40 people is betting that putting humans back in charge is not a weakness — it's the future. Rather than using AI to generate content or run the show, Bluesky treats it as a support tool, one that helps independent developers build better experiences for real people. The message is clear: technology only moves forward when humans stay in control of it.

Why it matters for communicators: When platforms become AI-first, the trusted voices — journalists, scientists, and community leaders — get drowned out. Bluesky's model is a reminder that audiences still crave human connection, credibility, and context, and smart communicators should be building their presence where those things are valued.

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.