On this week's episode of Inside Outside Innovation, we talk about the red pixel in the snow, why MVPs should be delightful, and the robot AI deployment gap. Let's get started.

Inside Outside Innovation is the podcast to help innovation leaders navigate what's next. Each week we'll give you a front row seat into what it takes to grow and thrive in a world of hyper uncertainty and accelerating change. Join me, Brian Ardinger and Miles Zero's, Robyn Bolton. As we discuss the latest tools, tactics, and trends for creating innovations with impact, let's get started.

Podcast Transcript with Brian Ardinger and Robyn Bolton

[00:00:00] Brian Ardinger: Welcome to another episode of Inside Outside Innovation. I'm your host, Brian Ardinger. And with me I have Robyn Bolton. Hello, Robyn. How are you?

[00:00:48] Robyn Bolton: I am great. How are you, Brian?

[00:00:50] Brian Ardinger: We are surviving the cold.

[00:00:52] Robyn Bolton: The sub-freezing temperatures. Yes, I know it's January, but that doesn't mean it has to be as bitterly cold as it is.

[00:01:01] Brian Ardinger: Absolutely. Well, hopefully this conversation will warm people's souls and hearts. As we talk about innovation in its various forms, we'll get right into it. We've gathered a couple of different articles that resonated with us over the last couple weeks.

How AI and Drones Are Transforming Search and Rescue Innovation

So, the first article we want to discuss is titled A Red Pixel In the Snow: How AI Solved the Mystery of A Missing Mountaineer. And this came from the BBC. It's very fascinating article for a couple different reasons, but the basic premise, it's a story about a missing mountaineer. This person was hiking and went missing a 66-year-old hiker and they sent out all the helicopters and that to try to find him. They were unsuccessful, but closer to the spring when some of the snow was melting, they decided to go back out and see if they could actually find the body.

And they used drones and AI, as a way to map the area. And what they found was they could put all that AI pictures into the system and they were able to find a red pixel in the snow that was effectively his helmet, that they were then able to find the person and go and retrieve the body and such.

What I found fascinating about this is, again, in this particular instance, it wasn't successful in finding him and saving him, but just the ability for new technologies like drones, just taking random pictures and then putting that in through the AI and having the AI look for anomalies. They were able to identify something that they couldn't have done in the past, and obviously at a much faster speed than they could have done in the past as well.

[00:02:26] Robyn Bolton: This was such a great story, tragic ending for this hiker, but a phenomenal story of when AI is good, it can be great. And you know, it's an instance of AI doing something that humans are not good at. We're not good at finding a pixel in the snow. We have bias when we see things, and so we're more likely to overlook something red. Because we just don't see it.

So, it was just a great story of how AI is augmenting what humans do. It is taking things that need to get done that we're not good at, and that it's equipped to do better than us. And you know, even though this story didn't have a happy outcome for the hiker, I bet the family is still happy to have him recovered and not be wondering. And as AI gets better, there's probably more people who will be rescued because of it. So, I thought it was just a wonderful story.

Augmenting Human Judgment with AI and Drone Technology

[00:03:25] Brian Ardinger: And it was interesting just to read through actually how the AI worked. The software managed to detect a kind of a red color, even though the helmet was in shade. So again, a human might not have been able to detect it, and it was very good at identifying anomaly.

So, it didn't necessarily say this is exactly where the hiker is, but it was able to go through the mounds of image data and say, here's some possible places. Humans still had to go through and actually find it, but it again, sped up the process.

And then I guess the other interesting point about this is the other technology, if you stack that on top of AI, the drones themselves, being able to get into crevices and places where traditional helicopters couldn't get into.

What's interesting is again all these particular technologies that we're talking about are hitting all at once, and when you start looking at the cumulative effect of how these things can add value or create interesting solutions and that, that's what's accelerating innovation. It's this ability to add on, and it's not just one thing that can make a difference. It's this combination of things.

[00:04:20] Robyn Bolton: And it's the combination of the technology and the humans versus trying to use the technology to replace humans. I mean even the drones, as you mentioned, the drone operators had to go to the sites and train on how to fly the drones so that the drones could see into the crevices and into the shaded areas.

And so. It's and not or when it comes to technology, it's not, okay. AI has replaced the humans, or AI can't do this at all. It's only humans like, no, put 'em together and let everyone do what they're best at.

MVPs, Product Sameness, and the Push for Delightful Experiences

[00:04:53] Brian Ardinger: All right. The second article is titled Why MVPs Should Be Delightful,and it's from the UX Collective.

And this was a great article. MVPs are near and dear to my heart. We do a lot when we're, you know, launching new products and working with startups, and we always talk a lot about the MVP. This particular article by James Skinner. It really talks about the fact that as we're living in a world that AI is now omnipresent. Workflows, you can spin up in a dime at a low cost. It's creating this kind of sea of sameness. And you know, lately products have begun to look the same and feel homogenous. And how do you create new products, new services that delight the user, not just meet the bare minimum of the functionality.

His call to action basically is, you know, stop looking for the good enough or just the functional aspect of your product or service, but how can you inject delight into it?

[00:05:43] Robyn Bolton: I am going to roll out my soapbox on this one. And it comes back to, the reason I have a soapbox is what is an MVP? It started off as a term, a minimum viable product. Literally, minimum viable. A true MVP should just function. We shouldn't be worrying about delight. We shouldn't be worrying about, you know, how does it make the customer feel like should it function?

Solve the problem that we need it to solve. And then there's version two and version three and version four. And then when you get to kind of the quote unquote final version that you are shipping, like, yes, it should delight people. Yes, it should be differentiated. But if we're going to be super strict about language, which I believe is very important because it avoids confusion, a true MVP actually shouldn't be delightful. It should just work. And then what you ultimately launch should absolutely ...

When AI Works and When It Doesn’t with Brian Ardinger and Robyn Bolton