AI Optimism Has a Trust Problem

**Nathaniel Whittemore** (0:00)
Today on the AI Daily Brief, as the political stakes increase, a more positive vision of AI. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
All right, friends, quick announcements before we dive in. First of all, thank you to today's sponsors, KPMG, Rackspace, Blitzi, and HyperAgent. To get an ad-free version of the show, go to patreon.com/aidailybrief or you can subscribe on Apple Podcasts. To learn more about sponsoring the show, send us a note at sponsors at aidealybrief.ai.
Now, one quick note, I had not been intending to do this, but this episode got very long. As you'll see, I think gets to some of the most important conversations that are increasingly being had as AI moves more firmly into the political sphere. This will be a main only episode. We will be back with our normal format and the headlines again tomorrow.
There is no doubt that the political conversation around AI is getting louder and louder. Part of that is the natural consequence of models growing in power, and part of that is the natural consequence of elections coming up. Whatever the proximate causes, however, from the standpoint of both politician and American voter interest, the issue of AI is growing in significance. Alongside that, different companies are staking their claims for the story they want to tell about AI.
Despite being increasingly isolated from the rest of the industry in this, Anthropics seems determined to keep telling us about the potential negative consequences of AI, with the most recent example being their Hope in Hard Questions campaign.
Now, whether that approach to storytelling can survive the IPO process remains to be seen.
OpenAI, meanwhile, has shifted fairly aggressively off this type of messaging. Sam Altman has said publicly on X that he was wrong about his expectations about how AI would interact with jobs, and had been excited to see that AI was primarily a tool for augmenting people rather than replacing them. Then into that space comes Mark Zuckerberg and Meta. For the last year or so, most stories about Meta and AI have been some combination of incredulity at the prices that they were paying to recruit top researchers, or almost schadenfreude-laced commentary about how they hadn't done anything with all that spend yet. Unlike his peers at the other labs, Zuckerberg had never publicly shared the sort of doom and gloom that seemed to be a part of their assessment of the likely future. But over the last several weeks, it's become clear that not only does Zuckerberg not share that perspective, he wants to plant his flag in exactly the opposite place. A couple of weeks ago, the Wall Street Journal published an opinion piece of his called The AI Future is for Everyone, which argued that this power concentrated in a few hands is the worst possible outcome. Then on Monday of this week, August 10th, he published a longer manifesto version of this clocking in at 6,500 words. The title and the core thrust is the same, The Future is for Everyone, the path to a positive AI future. But he goes much farther in this piece to actually lay out some of how he sees it playing out. So let's look first at a few excerpts from the piece, and then we'll get to the reactions. The defining questions of RAAG. Mark writes, Are who will have access to superintelligence and what we will direct it towards? Will it be centralized and restricted to a few institutions? Or will it be a tool that empowers everyone? Obviously, for Meta, the answer is clear. He continues, We propose a philosophy based on individual empowerment as the source of prosperity, invention as the primary purpose of superintelligence, and balance of power as the foundation of safety.
Reiterating a line from the piece that was published in the Wall Street Journal, he says, It is surprising that the discourse for many developing AI is so filled with doom. I do not understand why anyone who believes that AI will eliminate most jobs and much of humanity's relevance would rush to build that future. The notion that AI is so dangerous that the only safe path is an extreme concentration of power seems inherently problematic. Historically, hoping that an absolute power will benevolently provide for humanity of sufficiently enlightened has not led to safe or positive outcomes. So that's the big idea. It was the big idea that he was exploring before, but what are some of the details? First, on job growth in the economy, he writes, People fear that automation will outpace individuals' capability growth, leading to job displacement followed by a difficult period as people learn new jobs. But there is no rule that AI must increase automation faster than it increases individuals' capabilities or demand for new skills. Recent statistics suggest it may be more likely that individuals' capability growth could match or outpace automation, in which case people will gain the ability to do many new things before their current jobs change. This would lead to a healthy balance and potentially even job growth. What's interesting to me about this way of putting it, is that he's actually framing this as a math problem, which happens faster, automation of roles, or the enhancement of individual capabilities and the demand for new skills. What's interesting is that the forces of corporate inertia apply most significantly to the speed of automation question. As in, even things that could be automated in many cases won't be automated because of corporations' slow moving natures. Meanwhile, the speed with which individuals can enhance their capabilities is not necessarily as bound. In terms of other reasons Zuckerberg points to be optimistic about jobs of the future, he points to the fact that there will quote, always be a finite amount of compute and therefore an opportunity cost for how we use it. His argument is that if people can use AI to invent incredibly valuable new things, then it will make more sense to allocate it towards that rather than automating existing jobs. But even within the context of individual jobs, he points to some that don't really exist right now that might in the future. A generation ago, he points out, there were no app developers, social media creators, electrical vehicle technicians, or data center operators. In the near future, there will be new jobs that aren't common today, like one-person product studios designing custom toys, furniture, or clothes, world builders and experienced designers creating games, stories, and adventures, personal biologists using super intelligence to formulate personalized treatments, and much more that we can't yet conceive. Which is not to say that the shape of the economy won't change. Company sizes, he writes, may shrink, just as they did in the transition from industrial giants to tech companies. But, he argues, this doesn't mean fewer jobs overall. It implies a larger number of companies with fewer people each. There are many more valuable companies and services to build than people are able to build today.