AI surfing: Catch the wave or get lost in the currents?

While AI might seem overexposed in the media, there's a subtopic within AI that's not receiving the attention it deserves. If you're here for the latest buzz on GPT-4o, this isn't the post for you. On the other hand, if you're concerned about the human aspect of AI utilization, you're in the right place.

I'd like to explore why, despite our good intentions, we can unintentionally isolate people from AI, what factors contribute to this, and how we can address it.

Lately, I've noticed a growing number of individuals losing interest in AI, or even developing strong opposition towards it. And these are clever people, who are educated and have accomplished great things in their career. They seem to believe that AI is not relevant to them or that its benefits are exaggerated. They believe that the less AI, the better.

So, what’s going on? Wasn't everyone expected to be fully on board with AI by now?

Despite AI's potential benefits, concerns and misunderstandings still exist, leading to varied reactions from people. I'm going to be bold and say that as we drive towards the AI future, there are already people we've inadvertently left behind. Looking in the rearview mirror, we can see some of these people waving desperately at us, while others have already started walking away from the meeting point. What I'm observing now is a divide among white-collar workers: those who are pro-AI and those who want nothing to do with it.

I've identified three key reasons behind this. Take a look and let me know if you've noticed similar patterns, or if you have another perspective to explore.

1. Fear. People respond differently to the unknown, and AI is arguably one of the biggest unknowns there is. No one knows the extent of the change we're facing and how our lives will be impacted. I've heard a similar concern expressed in various ways, often masked behind humor: "If AI is so capable, is there any value for the work I do?" It doesn't help that we keep emphasizing that AI will enable us to focus on tasks that add more value rather than routine tasks, when people often struggle to distinguish between the two.
2. Technological self-efficacy. The less comfortable you are with technology, the more you might struggle to get started with AI. Despite the availability of user-friendly tools like ChatGPT and MS Co-Pilot, we often overlook the fact that it's not just about accessing them; it's more about obtaining the best output. Achieving optimal results demands proficient prompting skills, which don't necessarily come naturally to everyone.
3. Lack of understandable and engaging information. The major challenge I see in how organizations approach AI is that a one-size-fits-for-all is applied. We either talk about the topic on a very advanced level so that only 1% can follow, or we offer basic training for experts who get bored within the first five minutes of the lecture. With too advanced content you’re excluding beginners from the idea that AI is an accessible tool. With too simplified content you’re boring the experts, who want to go deeper.

In conclusion, overcoming these three topics isn't as complicated as it may seem. Many of these topics center around learning, reskilling, and upskilling, and both individuals and organizations share the responsibility in addressing them. It's about acquiring knowledge to reduce fear, accessing understandable content to demystify AI, and engaging with various AI tools for a better understanding. Moreover, I firmly believe that now is the time to start actively addressing these challenges. Taking a passive stance and waiting to see who adapts and who doesn't will leave our workforce unprepared for the future.

Let's not wait until some of us are left behind by the AI wave indefinitely. It's time to ensure that everyone knows how to ride it, or risk being swept away.