AVP’s Corner

Back in the 1990s there were many breathless news articles posted about how the internet and online colleges were the death knell for the traditional model of Higher Education. I printed out a few of the most alarmist articles and had them hanging on my corkboard for many years as a reminder that fearful prognostications from news media don’t always align precisely with actual outcomes.

It is true that the internet, and MOOCs, etc., didn’t portend the end of Higher Education but they did foretell a massive shift in society and a change in the skills many people would need to be successful. Consider:

• For jobs that require a college degree it is, in many cases, virtually impossible to apply without an ability to use a computer and a web browser.
• Almost every large to midsize college in the US has some level of ongoing online course offerings (most schools went either partially or fully online during COVID for at least some of that time). In many cases, online course offerings are now a substantial portion of the total curriculum.
• The ability to use Zoom or Teams is now an expected skill for most jobs that require a college degree.

This list could continue down the page but the point is that even though the internet didn’t decimate higher education–it certainly did change a great many things. As just one example very close to home, almost the entire graduate school at Ball State is online. We are able to have a substantial positive impact on the training of Applied Behavior Analysis students across the country because we can offer it fully online and that is only one of a list of items that could run across many pages. My point is not to list out all the changes that have occured since the early 90s but rather to highlight that the skills people needed to develop after the advent of the internet were discontinuous with the skills they needed previously.

Today there are many prognostications about how generative AI will replace huge swaths of the labor force and cause mass unemployment. It is difficult to predict the outcomes of a technology this disruptive; I believe that the actual impact of AI is going to be a change in how we work with each other that is going to meet, or even exceed, the changes brought about by the internet. It’s going to take some time before it’s obvious what those changes are. The way that the internet changed our lives is now obvious, with 30 years of hindsight. It’s also clear that people who were prepared for that change had more and better opportunities than those who lagged behind that change. I believe in my own life my early adoption of internet and computer technology provided me with more and better opportunities than if I had been slower to adopt those changes.

It’s possible that generative AI will cause large scale changes in how we interact with each other, and the world more broadly, even faster than the internet did. I don’t think it’s worthwhile to predict what those changes will be and I’m aware of some of the challenges associated with predicting precisely what that path will look like. However, I think this is a technology that will find its way into virtually every interaction we have, in one way or another. I believe it is important that most, maybe all, people become familiarized with, at a minimum, the basics of how AI works and what it can do for you. One of the reasons that I think this current technological shift may go faster than the previous one is there’s very little technical skill required to use AI effectively. AI teaches you how to use it, as you use it. If you want to find out what AI can do, think of something you want and ask the AI if it can do it–it will tell you. But…

If you do, or have done, this you’ll probably become aware of something called “hallucinations”. Hallucinations are currently a real limiting factor in the usefulness of AI. As an example, until fairly recently none of the frontier models could accurately count the number of r’s in the word strawberry (perhaps a silly example but easy to replicate, and some still struggle with it). It’s important to be aware that AI, while impressive, is still evolving and the current parameters are of what AI “can do” and “can’t do” are in a rapid state of change. However, as you become more aware of the technology, and the cutting edge of it, you may be surprised at how fast the “can’t do” category is shrinking.

However, I believe these issues will be worked out before too long and as AI morphs into capable agents we will need to figure out how to leverage it appropriately. “Standing still” on AI is an option but the window for that strategy is rapidly closing. I believe that by the close of 2026 that any entity behind on AI will start to fall behind at an accelerating rate. This means that the effort needed to catch up to AI adoption leaders will be so monumental that some organizations may never be able to do it. I don’t think the outcome of that will necessarily be catastrophic for laggards but I don’t think it will be good either. The ultimate outcome boils down to what it looks like to be on an exponential curve of a technology. As AI advances, there may occur a “takeoff velocity” that will be so large it will be like trying to grab hold of a rocket ship. You can be inside the rocket or you can be outside watching it head for orbit. What can you do to be on the rocket?

• Nudge your employer (or yourself) to at least begin to look into AI and the ways it will impact you and your organization.
• For yourself, if you can afford a paid AI membership fee it could be a very worthwhile investment in your future.
  • If you haven’t, imagine a project, explain it to AI, and see where it goes–you may be surprised.
• Take some time each day to read AI related news. A few good resources:
  • Follow the official social media of leading AI firms and their key leaders. 
  • A few resources can be very instructive, if you want to understand AI better and how it is rolling out into the world.

The transformative nature of this technology will begin to touch everything in the digital world and, before too long, in the real world too. In short, even though everything seems to have a hype cycle; in this case the hype is probably justified.

 

Michael Lane
Associate Vice President, Institutional Research and Decision Support

The preceding post represents current thoughts on a very fast changing topic. AI Content: only the image, I’ve used em dashes since before LLMs existed.