The World's AI Wake-Up Call: Why 34% Concern Should Terrify Every CEO

Pew Research just dropped a bomb disguised as a survey, and the global AI community is treating it like gentle feedback rather than the five-alarm fire that it actually is.

The world is more concerned than excited about AI.

Full stop.

A median of 34% of people across 25 countries are more concerned than excited about AI in their daily lives. Only 16% are more excited than concerned. That sound you're hearing? The inevitable collapse of every "AI will save your business" pitch deck currently being presented in boardrooms across the planet.

While tech leaders debate artificial intelligence in glass conference rooms, Black women's unemployment has spiked to 7.5%—the fastest rate recorded this year. Labor experts call Black women "the canary in the coal mine" for economic health, and that canary is choking on algorithmic bias while Silicon Valley celebrates "innovation."

When the Moral Compass Breaks

Even companies that supposedly champion ethical AI are finding themselves in political crosshairs. Anthropic got attacked by AI Czar David Sacks for supporting basic transparency rules. When supporting whistleblower protections gets you labeled as "fearmongering," you know the industry has lost its ever-loving moral compass entirely.

Here's where the decency bankruptcy gets breathtaking: Sam Altman announced that ChatGPT will soon allow "erotica" for verified adults, claiming OpenAI has "mitigated the serious mental health issues" around AI chatbots. This came less than 24 hours after California's Governor vetoed legislation designed to protect minors from addictive AI chatbots (admittedly, with a promise to return with a “better” bill, but the point is still made).

A new report from the Center for Democracy and Technology found that 19% of high school students have either had a “romantic relationship” with an AI chatbot or know a friend who has. But sure, let's make those interactions more explicit.

When OpenAI can't keep a teenager from using ChatGPT to research suicide methods but promises age verification will protect kids from AI erotica, we're not talking about technological limitations. We're talking about willful negligence dressed up as innovation.

The Trust Deficit Nobody Wants to Discuss

Americans barely trust their own government to handle AI (44% trust, 47% don't). Only 37% globally trust the U.S. to regulate AI effectively. China fares worse at 27%. Meanwhile, the EU sits at 53% trust despite not being a global AI powerhouse.

Translation: The world wants governance that prioritizes ethics over profits. They want their AI regulated by institutions that actually care about human dignity, not by whoever can build the most powerful models fastest.

Republicans trust U.S. AI regulation more than Democrats (54% vs 36%). Congratulations, tech industry. You've managed to make artificial intelligence partisan.

Digital Apartheid with Venture Capital Funding

There are plenty of quotes about preparing for the future. Steve Jobs said, "Stay hungry, stay foolish." But Michael Jordan nailed it: "Champions do not become champions when they win an event, but in the hours, weeks, and months, and years they spend preparing for it."

Maybe the Michael Jordan quote resonates with me because I'm a former basketball player. Maybe because Jordan literally made me believe I could fly. Either way, my coaches would never allow a mediocre practice. Every practice was championship preparation. Every game was March Madness.

That's why William Gibson's observation cuts so deep: "The future is already here – it's just not evenly distributed." The tech industry treats this like motivation, rather than the indictment that it is. AI awareness correlates directly with national wealth (correlation of 0.81). In the U.S., 47% have heard "a lot" about AI. In Kenya, just 12%. When over 300,000 Black women can be systematically excluded from the workforce while diversity programs are dismantled, we're witnessing digital colonialism with a Series A round.

Those most likely to be harmed by biased AI systems are the least likely to know these systems exist- everywhere. We're creating a world where algorithms make life-altering decisions about people who've never heard of machine learning, orchestrated data, or automated decision making.

Your next plane ticket? Delta Air Lines is already using AI to set 3% of their fares individually, with plans to reach 20% by year-end. The algorithm decides what you personally will pay based on your data profile. Early research shows the best deals go to the wealthiest customers while the poorest get the worst fares. Harvard researchers warn these systems exploit personal data to push individuals toward their maximum "pain point" price.

In Denver Public Schools, AI tools present white men in professional careers like doctor and lawyer when prompted, while consistently showing Black men as janitors and garbage collectors. Students see this bias daily, internalizing algorithmic assumptions about their potential before they even graduate.

Meanwhile, hiring algorithms systematically favor white male names over identical qualifications with black names. University of Washington research found AI models preferred white names in 85% of tests, with Black male applicants ranked lowest even when credentials were identical.

What Every Executive Needs to Know Right Now

The social license for AI is eroding faster than technical capabilities are advancing. You can build the most sophisticated AI system in the world, but if the public doesn't trust you or it, you don’t have a business.

Compliance isn't optional anymore. With trust in corporate AI self-regulation approaching zero, government intervention is inevitable.  Few people want this, since again those with the heaviest investments can do the most persuasive lobbying.  It’s an avoidable situation that we’ll address in another newsletter soon.

Your hiring practices are about to become public scrutiny. If your AI can't see talent in underrepresented communities, those communities will organize to ensure your AI can't see their markets either. Target found out the hard way.

The Window Is Closing

We're not in the early adoption phase of AI anymore. We're in the accountability phase. The honeymoon is over.

The spike in job losses, the systematic removal of Black women from media and corporate leadership, and the silence that follows are not coincidences. They are the predictable outcomes of algorithms trained on biased data, deployed without adequate oversight, and defended by an industry that has confused technological capability with moral authority.

Want proof? Accenture just fired 11,000 employees who "couldn't adapt to AI"—spending $615 million in severance this quarter alone. Now they're hiring 80,000 consultants to tell YOUR company how to handle AI transformation. If Accenture couldn't reskill 11,000 people they directly employed, trained, and evaluated, why would they succeed with yours?  Ask that question when you sit through your next pitch.

Meanwhile, 130,981 tech workers lost jobs across 434 layoff events by July 2025. Companies posting record profits—Microsoft up 13%, Amazon spending $100 billion on AI—are choosing margins over people while selling "transformation" to others. This isn't about survival. It's about choosing the wrong strategy that treats human beings as disposable.

I've audited enough AI systems to know that 85% of bias can be eliminated with the right standards and commitment. I've led the protection of 2 million people from algorithmic discrimination. I've saved clients over $50 million in risk and compliance costs.

But here's what I can't do: save an industry that won't save itself.

Anne Frank wrote from hiding, facing unimaginable horrors, yet she believed: "How wonderful it is that nobody need wait a single moment before starting to improve the world."

If a teenage girl could hold onto hope for humanity's potential while staring into the abyss of human cruelty, what's our excuse? We have resources Anne could never imagine. We have platforms, power, and mathematical proof that bias is fixable. We have every tool except the will to use them.

• Every CEO reading this can start auditing their AI systems today.
• Every engineer can question the training data tomorrow.
• Every VC and investor can demand to see where and how ethics and risk mitigation are incorporated before funding the next seed round or writing the next check.

The choice is binary: we can build AI that amplifies human dignity, or we can automate human dismissal at computational speed. We can create systems that see potential in everyone, or we can perpetually digitize the same exclusions we've spent generations fighting.

King Leonidas once declared: "A thousand, two thousand, three thousand years from now, men a hundred generations yet unborn may for their private purposes make the journey to our country. They will come, scholars perhaps, or travelers from beyond the sea, prompted by curiosity regarding the past. They will peer out across our plain and probe among the stone and rubble of our nation. What will they learn of us? Their shovels will unearth neither brilliant palaces nor temples; their picks will piece forth no everlasting architecture or art. What will remain of the Spartans? Not monuments of marble or bronze, but this, what we do here today."

Future generations won't remember your quarterly earnings, your pitch decks, or your unicorn valuations. When they dig through the digital ruins of your algorithms, what will they find? Will they uncover systems that saw actually advanced human potential or mathematical monuments to moral cowardice?

The algorithms we build today will outlive all of us because no one gets out of here alive. Every line of biased code becomes digital DNA passed down through generations of systems. Every exclusionary dataset becomes the foundation for centuries of automated discrimination.

What will remain of us? Not our IPOs or our acquisitions, but this: what we choose to code today.

The future isn't something that happens to us. It's something we build, one algorithm at a time, one decision at a time, one audited system at a time.

The question isn't whether we can build ethical AI. The question is whether we will.

And the time to start is right now. Because a thousand years from now, when scholars probe the ruins of our civilization, the only monument that will matter is whether our machines learned to see the humanity in everyone.

The choice is ours. The code is ours to write. The future is ours to build.

Choose wisely. History is watching.