Can AI Help Restore the Middle Class?

Today on the AI Breakdown Can AI be a force for decreasing Inequality? The AI Breakdown is a daily podcast and video about the most important news and discussions in AI. Go to breakdown.network for more information about our YouTube, our Discord and our newsletter. Hello friends, back with another long reads episode of the AI Breakdown. This is a really interesting topic and one where I think in some ways AI may break some of the patterns that we've seen in technology in the past. We're going to read some excerpts from an essay and then pair it with an article about a researcher who's come to think very differently about these issues. Before we get into that, I wanted to make one quick note. If you haven't checked it out yet, but you are interested in what we are building around AI education, we are coming right up on some very exciting announcements. You you guys will have no doubt heard that over the last few months we've been running an education beta focused on really, really practical tutorials that get you using AI tools quickly and functionally. If that's something that's interesting to you, go to be super AI. Sign up for the wait list and be the first to hear about what we're building. Again, that's besuper AI. Now the first piece that we're going to read from is an op ed in Inside Higher Ed called Bridging the AI Divide A Call to Action. It's by Adela de La Torre and James Frozi, the President and Interim Vice President and CIO at San Diego State University. SDSU recently opened a center for artificial intelligence and launched a credential program called Academic Applications of Artificial Intelligence. The authors say leaders must take steps to prevent low income and first gen students from falling further behind. They write. AI literacy has already become a gating qualification for participants across America's workforce. In one survey by Amazon Web services, a staggering 73% of employers report prioritizing hiring talent with AI skills. Those employers are willing to pay candidates with AI expertise significantly higher salaries, in some cases almost 50% more. Equipping students for career success and societal mobility therefore requires an immediate, holistic and collective approach to building AI literacy. To do so, we must first begin with access while carefully examining both policy and pedagogy. There is a notable disparity among students perceptions of and openness to AI technology and tools. A fall 2023 survey by San Diego State University captured impressions from nearly 8,000 current college students, revealing that more than 71% agree that AI will become an essential part of most professions. However, survey Results also indicated that students who had more access to technology, those who own more smart devices, were more likely to view AI positively and less likely to find AI tools intimidating or complex. Reinforcing the point when data from the SDSU survey was disaggregated to compare university students living in a populous urban area compared with those living in California's most economically challenged county. The students from the latter community reported far lower use of AI tools, far lower comfort with or understanding of those tools, and far less positive impact from those tools on their educational experience. First generation, low income and underrepresented minority students are already behind and enter higher education with a digital divide in place. Further compounding the threat of divergent access and perceptions of AI technology is a growing trend towards commodification of AI tools. While some tools will remain free, it appears that the most powerful and modern tools will increasingly come at a cost for many students already accumulating student debt and managing the rising cost of living, paying more than $100 per month for competitive AI tools is simply not viable. And finally, despite the increasing integration of AI into coursework, SDSU's recent survey was one of many to highlight that only a fraction of students report encouragement from professors or consistency in policies for use of AI resources. In short, as the need for and value of AI skills continues to increase, there are vulnerable segments of our communities that either feel negatively about it, cannot afford to do it, or do not have clear direction for its acceptable and ethical use and are therefore fearful that their use of AI could cost them their education or career. There is a critical need to address access, understanding and perception issues among our most high needs population to prevent AI from widening the already pervasive digital divide. Universities, and especially public universities that were created to serve their communities are in a powerful position to fill the societal responsibility. They are uniquely positioned and capable of ensuring that as AI drives innovation and progress, it does not simultaneously drive disparity. To this end, there are four key actions that higher education institutions can and should take right away to level the playing field, protect equity, and drive opportunity. First, colleges and universities must forge partnerships for AI affordability and access. An individual institution holds little power or leverage in conducting business with the tech giants leading the AI charge. However, forging partnerships and collaborations among higher education institutions will enable the collective negotiation of fair pricing models with AI vendors that prioritize accessibility for students. Second, higher education leaders must embrace data driven discussions and decision making to inform policies and practices surrounding AI in education. As AI evolves, so too will student expectations and usage. Third, Acknowledging the discrepancy between student and faculty perceptions and inconsistent policies for the use of AI tools in academics, universities must provide training on the acceptable and responsible use of AI technology, including on recognizing bias and the need to keep a human in the loop. Finally, institutional leaders must prioritize the development of comprehensive AI strategies. Input for these strategies must come from heterogeneous stakeholders at all levels of the organization, including students. Along with setting roadmaps and milestones for adoption of AI technology in the classroom, these teams must prioritize equity, affordability, and responsible usage as core pillars of their work. If your university is not already developing responsible use guidelines for AI, then it is choosing to turn a blind eye instead of now is the time to act. As AI continues to reshape the educational landscape, we must prioritize affordability, equity, and responsible usage so that all students have the opportunity to thrive in an increasingly AI driven world. Hello friends. Quick note before we get to the rest of the episode. You have probably heard me talk about the AI Education Beta over the past few months. We've had a ton of you participate, which has been amazing, and now we're almost ready to announce something big and something new. If you want to be one of the first to hear about our new approach to learning AI that is hyper practical, hands on, immediately relevant, continuously upgrading and anchored by community, go to BE Super AI and sign up to be notified when the project goes live. We're getting there in just a few weeks and I want all of you along for the journey. Once again, that's BE super AI. All right, so a clear, simple little piece here, but one that has a very important message. Any new technology, particularly one that comes with the type of cost structure that AI does that rewards people who already have access to advanced devices like AI does, could exacerbate inequality, in this case in the form of a digital divide. However, what I want to pair this with, not because it undermines that argument at all, but because it shows that there is another side of AI which is really quite different. I'm going to read some excerpts from another piece. This one is not an op ed, but a piece from the New York Times called How one Tech Skeptic Decided AI Might Benefit the Middle Class. David Autor, an MIT economist and tech contrarian, argues that AI is fundamentally different from past waves of computerization. The piece begins, David Autor seems like an unlikely AI optimist. The labor economist at MIT is best known for his in depth studies showing how much technology and trade have eroded the incomes of millions of American workers over the years. But Mr. Autor is now making the case that the new wave of technology, generative AI, could reverse that trend, Mr. Autor wrote in a paper published by Noema magazine in February. AI, if used well, can assist with restoring the middle skill middle class heart of the US labor market that has been hollowed out by automation and globalization. Mr. Otter's stance on AI looks like a stunning conversion for a long time expert on technology's workforce casualties. But he said the facts had changed and so had his thinking. Modern AI, he said, is a fundamentally different technology. It can change the economics of high stakes decision making so more people can take on some of the work that is now the province of elite and expensive experts like doctors, lawyers, software engineers and college professors. And if more people, including those without college degrees, can do more valuable work, they should be paid more, lifting more workers into the middle class. In Mr. Autor's latest report, he discounts the likelihood that AI can replace human judgment entirely. And he sees the demand for healthcare software, education and legal advice as almost limitless, so that lowering costs should expand those fields as their products and services become more widely affordable. Until now, Mr. Autor said, computers were programmed to follow rules. They relentlessly got better, faster and cheaper, and routine tasks in an office or a factory could be reduced to a series of step by step rules that have increasingly been automated. Those jobs were typically done by middle skill workers without four year college degrees. AI by contrast, is trained on vast troves of data, virtually all the text, images and software code on the Internet. An AI helper, Autor said, equipped with a storehouse of learned examples, can offer guidance in healthcare. Did you consider this diagnosis? And guard rails don't prescribe these two drugs together. In that way, Mr. Autor said, AI becomes not a job killer, but a worker complimentary technology which enables someone without as much expertise to do more valuable work. So the basic idea here, and I'm not going to read the whole piece, is that what we are starting to see is that one of the most profound impacts of AI initially is bringing people with less skills up to parity with those with more skills. That doesn't mean that people with lots of expertise don't get some benefit from AI, but simply that it seems like it does more to bring the skills of the bottom to the middle. So one part of Auteur's argument is that that reality could improve the economic outcomes for those people who can now do more valuable work. What that's paired with, though, is his assertion, which is one that I've talked about before on this show, that human demand for many things is effectively limitless and constrained only by its cost or by the time we have available to consume. The reason that that matters is that it creates an opportunity for more stuff to be created. In other words, for more of those people whose skills have been risen up to the middle to put them to good, create value that is rewarded. I think it's important not to be Pollyannish about this or to assume that it's just going to happen, but it really does feel to me like the biggest countervailing force of the idea that all jobs are going to be automated away is this idea that AI assistants and AI co pilots can radically change what a huge spectrum of workers are capable of doing. Meaning that more stuff can be done. Now of course I think one of the big places that this starts is with education, which is why I will shill be super AI one more time and I'm excited for you guys to hear later this week what we are up to with that. For now though, I hope you are having a great weekend. Appreciate you listening as always and until next time, peace.