Beyond the Bot Ep. 11 Live: Becoming “Future-Proof” in the Era of AI and Robotics

Tony and Steven recording live for Beyond the Bot Episode 11

In this compelling episode of Beyond the Bot, hosts Tony DeHart and Steven King step away from the Blue Sky Lab and go live from 79 Degrees West. Their conversation, with the help of insightful audience participation, dives deep into the evolving landscape of AI and automation in both physical and digital spaces. They explore how the barriers to entry are dropping, how even small businesses can now leverage AI to drive efficiency and competitiveness, and why AI isn't necessarily taking jobs—but those who use AI certainly are.

The episode is rich with real-world examples, including how AI is transforming traditional roles, empowering educators to rethink curriculums, and allowing companies to scale operations without scaling costs. Tony and Steven also touch on ethical concerns, from algorithmic bias to missteps by major corporations, and they offer thoughtful strategies for risk mitigation, from constitutional AI to better team knowledge sharing. With valuable audience insights and a look into the future of manufacturing robotics, this conversation offers essential context for understanding where we're headed next in the age of intelligent automation.

Transcript:

Tony DeHart: So I'm Tony.

Steven King: And I'm Steven. And for the first time, we're coming to you not from the Blue Sky Lab but from 79 Degrees West. We are live streaming, and this podcast will be available on LinkedIn, YouTube, and all your favorite platforms.

Tony DeHart: Steven, as we're jumping into this—this is a topic that we talk about quite a bit. But we get the sense that it's more important now than ever before. Can you give us a little bit of backstory as to how the conversation is changing and why it's gaining importance?

Steven King: Yeah, well, AI has become a common word across all industries and even in our daily lives—from restaurants to dinner table conversations. It's everywhere. More people are finding new use cases every day, and it's becoming essential for businesses to automate in order to remain competitive.

Tony DeHart: What about adoption? We often hear, "AI is great for others, but maybe not for me." Are we seeing more widespread usage in the business community?

Steven King: Absolutely. Many are using basic tools like ChatGPT. Others are using integrated AI features in the tools they already subscribe to. Some might not even realize they’re using AI. Then there's a group fully embracing it, especially in physical automation—where the savings in labor and materials are significant. Smaller businesses are realizing they need to adopt these tools to compete with larger ones.

Tony DeHart: We often split this into two buckets: physical automation—like robotics in manufacturing—and digital automation. What does AI look like when it’s not robotic?

Steven King: You can automate almost anything. It doesn’t have to be flashy robotics. It could be spreadsheets, finances, email responses—the "back of the house" tasks that eat up time. With the right tools, companies that used to need ten people can now operate with two or three.

Tony DeHart: We’ve seen the barriers to entry drop significantly. On the physical side, components are cheaper. On the digital side, models are more powerful and affordable.

Steven King: Exactly. In 2017, a machine learning project cost us half a million dollars and three months. Today? You can get the same output for $20 a month.

Tony DeHart: That’s wild. And now we see that around 78% of large U.S. companies are regularly using AI. What’s the story with the Shopify CEO and their AI-first approach?

Steven King: I love stories like that. These companies experiment quietly, then go public with bold AI strategies. They test on a small scale, see value, then scale up. That efficiency leads to better margins, new markets, and growth.

Tony DeHart: So instead of asking "How can we use AI?" we’re asking "Why wouldn’t we start with AI?"

Steven King: Exactly. I’ve restructured my syllabus at UNCC. We’re skipping traditional coding and going straight to building with AI tools. Why learn to do something a tool already does better?

Tony DeHart: Show of hands from the live audience—how many of you use AI or automation regularly?

[Audience raises hands]

Tony DeHart: That’s nearly every hand. Let’s hear some use cases. Who wants to share?

Audience Member: I’m on the board of a homeowners association. I’ve used AI to interpret engineering reports, forecast financial decisions, and even rephrase communications to the community based on real estate investment concerns. It’s like a soft skill AI coach.

Steven King: Great example. And tools like Crystal Knows provide personality profiling, suggesting ways to communicate effectively based on public data. It told me I take on too many responsibilities—which checks out.

Tony DeHart: They really do manipulate you with the right phrase, huh?

Steven King: "It’s not a sure thing, but..." works every time on me.

Tony DeHart: Another use case?

Audience Member: I work in industrial automation. We’re using inline instruments with machine learning to optimize processes in real-time, like detecting protein extraction potential in slurries.

Tony DeHart: Fantastic. And it’s not replacing jobs—it’s enhancing them. Steven, how do we see that playing out?

Steven King: It’s not AI taking your job. It’s someone using AI who will. Like how the power drill replaced the hand drill. It’s about efficiency and competition.

Tony DeHart: And your job might evolve. AI enables you to do more, not just faster. Even creative and technical roles are shifting.

Steven King: Right. AI tools are changing how we approach problem-solving and creativity. It’s like electricity—it didn’t give us better candles, it gave us light bulbs.

Tony DeHart: In our own office, we’ve created a chatbot using every technical manual and support question we've ever received. Makes us look like geniuses on calls.

Steven King: For clients, we’re using computer vision for quality control and anomaly detection. Immediate insight instead of end-of-line checks.

Tony DeHart: Of course, there are risks. Like the chatbot hack that led to $1 car offers from a major auto brand.

Steven King: Or Target’s predictive analysis mishap that accidentally revealed a teen’s pregnancy to her family. AI was right, but it wasn’t a good use of the data.

Tony DeHart: So how do we mitigate those risks?

Steven King: Train employees. Vet vendors thoroughly. Understand intellectual property risks, like what happened at Samsung with pasted code into ChatGPT.

Tony DeHart: What about data best practices?

Steven King: Keep humans in the loop, but design around potential human bias. Amazon’s diversity recruiting tool failed because it learned unintended biases. Even word choice mattered: "We did" versus "I did."

Tony DeHart: It’s not just about having one expert. Everyone needs to understand the tools.

Steven King: Right. It’s like a construction site—everyone needs to know how to use the tools, not just rely on the "drill guy."

Tony DeHart: Before we move to best practices, any AI gone wrong stories?

Audience Member: Can we use AI to see what biased the system in the first place?

Steven King: Great question. That’s where constitutional AI comes in. It’s a separate watchdog AI that flags changes violating preset principles. It doesn’t evolve with the same data as the main system.

Audience Member: Couldn’t that watchdog also develop biases?

Steven King: Potentially. But by isolating it from evolving data, we reduce that risk. It’s not perfect, but it’s one of the best guardrails we have right now.

Audience Member: How might generative AI impact robotics, especially with U.S. manufacturing trends?

Steven King: Love that question. With onshoring, automation is essential. We’re combining large visual models with language models so you can say, "Pick up the water bottle," and the robot knows what to do. We're not quite there yet, but we’re getting close. AI is making robots more intuitive and lowering error rates.

Tony DeHart: Amazing. It’s clear that we’re still early, but the light bulb moments are already here. And the future? It’s looking very bright indeed.