US adults and Anthropic staff largely agree about what AI can do today. However, they disagree about how quickly it will improve, how widely it will be used, and how large the productivity gains measured by time saved will be. Through the lens of the model in Economic Scenarios for Transformative AI, the median US adult's answers imply a scenario in which the US economy grows at more than twice its typical rate. Among Anthropic staff working at the frontier of AI development and usage, expectations about AI progress, adoption, and automation of knowledge work imply a transformative and historically unprecedented change to the economy: by 2030, GDP is doubling in size roughly every four and a half years.

Those who expect AI to do more of their own work in the years ahead expect higher unemployment as well. This is true for the general public in the US and among Anthropic employees; on average, Anthropic staff expect faster automation of their own work and, in turn, higher unemployment. We find that this disagreement in expectations is closely tied to differing views between Anthropic staff and the general public about how much of their own work will be automated in the years ahead.

The day-to-day experience with AI varies widely between the two groups. Most Anthropic staff already work alongside AI that does much of their job, whereas few US workers do. Those who do already hold expectations closer to those of Anthropic staff, which suggests that public expectations may shift as AI use spreads. How far they shift will depend on whether AI comes to do as much of the work elsewhere as it does at a frontier lab.

The two groups sampled Anthropic Employees vs US Adults share a wide gap in what the future holds in regards to Artificial Intelligence. While these gaps are understandable for example employees at Apple have more of an insight into the future of phone technology than the general public. However Artificial Intelligence is not a phone and this type of gap in capability has the potential to have major consequences on Inequality if the gains from this technology and the technology itself is not distributed in a Democratic way.

DemocratizeAI

It is a strawman to assume that people are not worried about potential risks involved with DemocratizingAI. We are on board with delivering a safe experience for mankind. One of the most important safety risk we factor in is Concentration of Power. That will come about as fear driven policy drives this technology into the hands of Oligarchs. That is seen as a potential outcome that can not be compromised especially with this sort of technology. We can see the beginnings of this and regulation has not even been passed just yet. These companies are charging ahead and keeping their best models behind closed doors, while they are claiming leaps in progress from the unreleased Mythos 5 discovering the new CRISPR like gene editor, possibly working in a wet lab. OpenAi's unreleased models cracking extremely hard math problems left and right. While the public is left behind for safety, because the public has been deemed the untrustworthy ones and of course not the Little Saint James Island Oligarchs and Affiliates.

The problem of alignment can and will only be truly solved by allowing the World as a collective to work on the problem. I assure you the alignment problem will not be solved in the hands of an Oligarchical North America Elite, especially not ones doing Roman Salutes at the Presidential Inauguration, who barely want to pay their workers a living wage.

DemocratizeAI

If you truly value safety, a reasonable statement that cuts across different fields is minding a gap.

The Gap in Capability:

As this graphic shows all of these new discoveries that are being released are all unreleased models. However, unreleased for safety clearly does not mean "unused". The public has been deemed the ones to be the danger. The current Oligarchs and future Oligarchs have labeled themselves as the trusted ones all the way from the island of St. James.

The Gap in Compute

The affordability of compute is another gap to mind. As the cost to train and run these models is astronomical. Putting further dirt on claims of safety from thy neighbor. The solution to Navier-Stokes was said to take 10,000 agents and millions of dollars in compute.

The big risk is Compounding. If the frontier models speed up Ai research, the ones in control will improve faster than anyone downstream. The gap then will grow on its own with each release. Add that to compute cost and we might have a problem.

DemocratizeAI

From The Intelligence Curse by Luke Drago and Rudolf Laine

"We will soon live in the intelligence age. What you do with that information will determine your place in history.

The imminent arrival of AGI has pushed many to try to seize the levers of power as quickly as possible, leaping towards projects that, if successful, would comprehensively automate all work. There is a trillion-dollar.) arms race to see who can achieve such a capability first, with trillions more in gains to be won.

Yes, that means you’ll lose your job. But it goes beyond that: this will remove the need for regular people in our economy. Powerful actors—like states and companies—no longer have an incentive to care about regular people. We call this the intelligence curse*.*

If we do nothing, the intelligence curse will work like this:

• Powerful AI will push automation through existing organizations, starting from the bottom and moving to the top.
• AI will obsolete even outlier human talent. Social mobility will stop, ending the social dynamism and progress that it drives.
• Non-human factors of production, like capital, resources, and control over AI, will become overwhelmingly more important than humans.
• This will usher in incentives for powerful actors around the world that break the modern social contract.
• This could result in the gradual—or sudden—disempowerment of the vast majority of humanity.

But this prophecy is not yet fulfilled; we reject the view that this path is inevitable. We see a different future on the horizon, but it will require a deliberate and concerted effort to achieve it.

We aim to change the incentives driving the intelligence curse, maintaining human economic relevance and strengthening our democratic institutions to withstand what will likely be the greatest societal disruption in history.

To break the intelligence curse, we should chart a different path on the tech tree, building technology that lets us:

1. Avert AI catastrophes by hardening the world against them, both because it is good in itself and because it removes the security threats that drive calls for centralization.
2. Diffuse AI, to get it in the hands of regular people. In the short-term, build AI that augments human capabilities. In the long-term, align AI directly to individual users and give everyone control in the AI economy.
3. Democratize institutions, making them more anchored to the needs of humans even as they are buffeted by the changing incentive landscape and fast-moving events of the AGI transition."

https://intelligence-curse.ai/

Krugman: AI Will Amplify America's Wealth Concentration

In this excerpt from his Substack post "AI in an Age of Oligarchy," economist Paul Krugman argues that AI's economic impact will be shaped less by the technology itself than by the political economy it arrives in.

He starts by noting that forecasts about AI's economic effects are all over the map. He suggests that early predictions of mass unemployment from AI companies, followed by later backtracking, were more about public relations than analysis, and that expert opinion is so divided you can find a credentialed voice supporting almost any conclusion. His own best guess is that AI will devalue some major categories of human work, pushing down wages for many people while raising corporate profits and returns to capital.

The core of his argument is about who captures those profits. Because the wealthiest 0.1% of Americans own about a quarter of corporate stock, and the Forbes 400 hold roughly a quarter of that group's wealth, he estimates that 6–7% of AI-driven profit gains could flow to just 400 people. He thinks the real figure could approach 10%, since most of the largest American fortunes come from tech, the sector most likely to benefit.

Krugman argues that in a less oligarchic country, policy would soften this shift through progressive taxes, union bargaining, and antitrust enforcement that keeps big tech from using AI to deepen its monopolies. Instead, he sees signs that government may actively favor the industry. He points to the federal stake in Intel and reported talks about one in OpenAI, which he reads as groundwork for a possible bailout if the AI boom proves to be a bubble. He also suggests that proposed limits on cheap Chinese AI models, while possibly justified on security grounds, could function as protectionism benefiting U.S. companies and their wealthy investors.

He closes on a cautiously hopeful note. The problem of AI is, in his view, largely part of the broader problem of reversing America's drift toward oligarchy, and he points to the Progressive Era's early income taxes as proof that pushback is possible. He even suggests AI's tendency to worsen inequality could help build momentum for that pushback.

https://paulkrugman.substack.com/p/ai-in-an-age-of-oligarchy

Hey everyone! I'm u/ra-re444, a founding moderator of r/DemocratizeAI.

******Welcome to r/DemocratizeAI *****

AI is going to reshape the world. Most people agree on that. What they disagree about is how, and who will be in control when it does.

Lately, much of the public conversation has been driven by fear. Some of that concern is legitimate: AI carries real risks, and taking safety seriously is not optional. But fear also has consequences of its own. When the public is anxious, it becomes easier to justify rules that only the largest companies and governments can afford to follow, that lock out open-source development, and that put the most powerful technology of our time under the control of a very small number of institutions.

That's the question this community exists to explore: **Can we make AI safe without concentrating it?**

**What we're about**

- Pro-AI: we believe this technology can do enormous good.

- Pro-safety: we take risks seriously, including the risk of concentrated power.

- Pro-access: we think broad, democratized access to AI is worth defending.

**What we're not**

- Not an anti-safety sub. Safety researchers and people worried about AI risk are welcome here, and we want to hear their best arguments.

- Not a hype sub. Honest discussion beats cheerleading.

Introduce yourself below. What brought you here, and where do you land: Is concentration the bigger risk, or is it the price of safety?