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The international conversation on AI is often terribly confusing, since different kinds of AI become fused under the one overarching term. There are three kinds of AI: narrow, general, and super AI, with some grey areas in between. It is very important to clarify these distinctions because each type has very different impacts and vastly different national and international regulatory requirements.

Without national and international regulation, it is inevitable that humanity will lose control of what will become a non-biological intelligence beyond our understanding, awareness, and control. Half of AI researchers surveyed by the Center for Human Technology believe there is a 10 percent or greater chance that humans will go extinct from their inability to control AI. But, if managed well, artificial general intelligence could usher in great advances in the human condition—from medicine, education, longevity, and turning around global warming to advances in scientific understanding of reality and creating a more peaceful world. So, what should policymakers know and do now to achieve the extraordinary benefits while avoiding catastrophic, if not existential, risks?

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Hollywood is really screwing with our heads and our collective mindset.

King Solomon’s wisdom has never been more important: “Without a vision the people will perish” – Proverbs 29:18

If we want a positive future for humanity – for ourselves and our kids – then we need a vision of tomorrow that is hopeful, compelling, and abundant.

Here are four ways we can drive this transformation:

1. Create an XPRIZE for Optimistic Media: Launch a multi-million-dollar competition for filmmakers, writers, and creators who develop compelling, scientifically-grounded visions of an abundant future. Not rose-colored fantasy, but data-driven optimism that acknowledges challenges while showing paths to overcome them.

2. Build a “Media Abundance Index”: What gets measured gets managed. Let’s create a dashboard tracking the ratio of dystopian-to-optimistic content across platforms. Make studios compete for higher scores on the “Abundance Index,” similar to how they now tout diversity metrics.

3. Invest in Exponential Storytelling: Those who want to steer towards a hopeful, compelling, and abundant future for humanity should back productions that showcase how exponential technologies solve humanity’s grand challenges.

4. Leverage AI for Narrative Transformation: Today’s AI systems can analyze story structures and help writers craft compelling narratives around hope, innovation, and human potential. Let’s use these tools to create the next generation of world-building.

For those of you who don’t know me, I teach a class on the history of the digital future. I am finishing a book on the topic as well. So I think I can speak with some authority in saying that there has not been a time in recent memory when the future was quite so unclear as it is right now.

That existential uncertainty comes from two places. (1) We don’t know what generative AI will mean for the types of work you all are setting out to specialize in. And (2) we don’t know what the future of our political system will be.

Piece of advice #2: Find your voice. Never stop finding your voice.

Y’know what most bums me out about generative AI products like ChatGPT? They make everyone sound the same. This is baked into the product itself — it is, at base, a guess-the-next-word engine, a cliche-generator. And whether you think it’s the future or you thinks it’s a hype bubble, it sure seems like we’re going to be awash in the stuff for the next few years.

I consider Harry Law my lead AGI reporter, if such a thing could exist. It’s important we keep debating AGI and ASI because it has ramifications on the global economy and society as a whole. If one day, AI were to become sentient, self-motivated and awaken from the ghost in the machine what would it attempt to do?

The upshot is that the bus is on the road, but its steering is still being worked out. AI firms feel they need to create ever-more capable AI to avoid being left behind by the competition domestically and internationally, while at the same time seeking to understand those systems for safety and policy reasons. This drive is a defining feature of the current moment, as labs must satisfy investors and regulators that AGI is both inevitable and controllable.

Fifteen years ago, Public Benefit Corporations (PBCs) didn’t exist. Today, they have become a popular legal structure for some of the biggest tech companies in the world.

In the 200+ year history of U.S. corporate law, PBCs are a recent legal invention. The first state to pass PBC legislation was Maryland in 2010. Today, 41 states (and the District of Columbia) have laws that enable PBCs.

Unlike traditional corporate structures like C-Corps and S-Corps, which are designed to maximize shareholder value, PBCs promise an alignment between profit and a defined public benefit to society.

PBCs have been making news recently, with OpenAI’s recent decision to convert its for-profit business to a PBC controlled by a nonprofit parent entity.

Becoming a PBC has many benefits:

• Mission alignment: By legally embedding its social mission into its company’s DNA, a PBC structure can help tech firms stay focused on long-term societal impact.
• Public goodwill: A PBC structure can lead to enhanced consumer, employee, and investor trust in the brand. For AI companies responsible for the development of disruptive technologies, becoming a PBC is a step (though a small one) in assuaging the public that those in power have broader societal concerns in mind.
• Greater transparency: PBCs are required to adhere to regular and transparent reporting requirements. However, these requirements do not require AI companies to reveal how their AI algorithms work (a complaint that many have raised). It’s unclear if a shift in legal structure will lead to the type of transparency critics seek.

What happens to a society when intelligence itself becomes a commodity? That is the question posed throughout the National Academy of Sciences 2025 report, Artificial Intelligence and the Future of Work. The work is not prophecy, nor should it be mistaken for one of Silicon Valley’s breathless manifestos. It is, rather, a sober, meticulous reckoning with the ambiguous, disquieting, and often paradoxical forces unleashed by the rise of AI. Strategic, unvarnished, and disturbingly persuasive.

The authors are not alarmists, but their findings demand our attention. The committee, featuring renowned researchers such as Erik Brynjolfsson, David Autor, Tom Mitchell, and others remind us that AI, as a general-purpose technology, joins the ranks of electricity and the steam engine, tools that did not merely make us faster but rewrote the coordinates of productivity.

ITDF Center Director Lee Rainie spoke recently at the Northeast Florida Library Information Network about the future of libraries.

His talk covered two studies released by the Center this spring: one about the universe of large language model users like ChatGPT and Claude, and the other covering the report about being human in the next decade.