When the Jobs Move - A Tuner’s View of the Future of Work

In this episode, Dr. Rochelle Newton returns after several weeks away to share what she has been building: the AI Tuner Institute. As layoffs accelerate across industries and AI reshapes the structure of work, many people are asking the same questions,  What happens to workers when the jobs move? What does this shift mean for students preparing to enter the workforce? And where do humans fit in a landscape increasingly defined by automation?

Dr. Newton explores these questions through the lens of a Tuner, the emerging role that bridges the gap between AI systems and human teams. She examines why companies are reducing staff, how AI is being deployed inside institutions, and why the future of work will require people who can manage, correct, and guide AI rather than compete with it. This episode offers clarity, steadiness, and a path forward for anyone trying to understand the changing world of work.

Join AI & The Tuners with Dr. Rochelle Newton as she discusses how to pivot as artificial intelligence (AI) swarms the job marketplace!  Life math & Digital Math

Transcript

SPEAKER_00 0:03

Welcome to AI and the Tuners. I am your host, Dr. Rochelle Newton. Thank you for your emails. You mentioned that I have been absent for three weeks, and yes, I have. I have been building the AI Tuner Institute, and I can't wait to tell you more about it. You will learn some today and more in the coming weeks. We are in an interesting time. AI is displacing jobs all across disciplines and throughout the entire hierarchy of work, from the lowest level to the C-suite. Last week, a major tech company laid off more than 20,000 employees and increased its AI deployments. This means more people are going to come into the workplace and more jobs are not coming into the workplace. And as companies, both tech giants and non-technical companies, are reducing their staff, this creates complexities that we were not prepared for. There are not more jobs, and people are in a strange place. Some of the companies say these layoffs are due to overstaffing, and some attribute these layoffs to AI, called AI washing. As we try to make sense of how the job market will handle these layoffs, it is clear jobs are harder to obtain. To make the situation worse, our college students are concerned about their future. They see a marketplace and wonder whether their degree will really matter when they complete college. Today, we will try to dissect these areas from the lens of a tuner. As we look across the landscape of work, one truth is becoming unavoidable. AI is not just changing jobs, it is changing the structure of work itself. And people who are being displaced are not failing. They're caught in a transition that no one prepared us for. We are watching a shift where companies are not simply automating tasks, they're reorganizing their entire workforce around an AI system. And when this happens, the first thing to disappear is not the job title, it is the human content text that wants hell work together. This is where the role of a tuner becomes essential. A tuner is not a programmer, a tuner is not a data scientist, a tuner is the person who understands the work, the real work, well enough to guide AI systems, correct their areas, errors, and protect institutions from the consequences of those areas. Because the truth, AI does not know the institution, it only knows patterns. And I think as companies are running to AI, I think they're assuming that these errors will not be enough of an issue that it makes sense to replace humans with these technologies. And in a lot of ways, there's some truth to that. So for an example, if they were replacing an IT help desk with an AI support tool, yes, AI might know all the intricacies of how to solve a password issue or how to solve a problem with Microsoft Word or all of those kinds of things, but it might not know how the human impact of that era might be, or another question the person may have to ask about how that system works. And we're making judgment calls about what a technology can do when that technology does not have all of the answers. We are known as humans for incompleteness. And let me say what I mean about that. Let's just say we built a project to deliver a new operating system for 10,000 devices. We built our project team, we talked about what we're gonna do, we talked about all the things that go into project management, you know, we did everything we had to do. But in those meetings where we talked about what we were gonna do, we talked about what went wrong in the process of thinking of all the steps of the project, in a team meeting, in a Zoom call, in whatever happened, there are things that are left out. And while we might transfer that entire document to AI, what in what occurred in that deployment, it did not capture all of the conversations, it did not capture all of the short pieces that happened in that project, and yet still we turn that over to AI. And a lot of times AI is built with random information. So, say for example, there's information from Reddit or information from other systems that's not complete or fully accurate, and yet still companies are using that data. We need to attach a human for every deployment under every topic to make sure that AI has concise, accurate information. When patterns are incomplete, AI fills the gaps with something it thinks sounds right. That is what we call hallucinations. And hallucinations are not just technical glitches, they are institutional risk. This can lead to misled information for customers, misinformation for leaders, distorted data, and create false confidence. And for companies in their bottom line, this could mean financial distortions or financial loss, even risking your market share. This is why I built the AI Tuner Institute. Not to teach people how to build AI, but to teach people how to sit in the gaps of AI. Because every institution, every hospital, every university, every bank, every government agency, nonprofit is going to need people who can stand in those gaps between AI and the human system or the human team and say, here's what AI got right, and here's what AI got wrong, and here's what is what it misunderstood, and here's what we need to correct before we deliver or leave that system to itself. I can tell you, as a technology leader, when we would deploy a system, we would turn key over to the users and we say, here's a system, but we were always available to answer questions to make sure that we were there to fill in what we as a team thought was fully deployable, but we may have missed things. We had to be there for the department. The accounting department may have had questions about what we delivered. The payroll department may have had questions. We could not just turn over our system and say, okay, I need department, let's go home. We've done our work for the day. We deployed the system, all is done. And that's what departments are doing now when we're delivering an AI system. We're saying all is done now. That's not right. The tuners are the new stewards of institutional memory, they are the protectors of accuracy, they are the translators between human judgment and machine output. And here is the part that matters most. Tuners are not being replaced by AI, tuners are being created by AI. When I created the institute, the time it took me, I had to go through everything I knew about AI and everything I knew about the gap. And so, as I thought about this, how many courses could I create? Think about every job and every field that's being displaced. That's a lot. I am going to need a lot of help because I don't know all of these industries. I will need help from people to fill in those places that I don't know, to create courses to fill in where your specialization and AI exist. But we will need to make sure that there are places where people can become tuners and help AI and help institutions or organizations fill the gaps where AI is going to have misinformation. And believe me, there's going to be misinformation. We already have examples of that every single day. So let me say this. As you look at my institute, it's A I T U N E R I N S T I T U T E dot org. Go to my site. See what you like about it. See what's wrong and email me. Tell me how I can make this institute work for us all. Because we cannot allow AI to fail because it's too, it's out here now. It's not going away. What we have to do is figure out how to ensure it's successful for those who are being displaced, for those who are wondering how my college degree is going to matter. This Tuner Institute is going to be your partner. And I'm asking you to consider my institute as your partner. So before I close, I always thank you for listening to me. Thank you for considering my thoughts and ideas. So thank you. And consider this podcast and know how we can make AI function fully for what we need it to do. It's not going away. So thank you. I look forward to hearing from you, from you. I am your host, Dr. Rochelle Newton, and you can reach me at aiandetuners at iCloud.com. Thank you for spending this time with me. Have a wonderful day, and I am so glad that you are here with me.