Productivity

Building Custom AI Tools for Travel Planning Problems

Shows how AI can build custom one-time tools in minutes, using a New York trip planner with interactive mapping as an example.

Transcript:

Today I wanted to show you how things have changed a little bit for me when it comes to solving problems. My partner and I are heading overseas shortly. We’ve got about five or six days in New York, and we’ve been trying to plan out our activities. The thing is, I don’t really know much about the York. I’ve never been there. And so trying to get a visual on where everything is has been difficult, working out how far one thing is for another. And so to help what I’ve done is I’ve built a little tool. And the important part here is not the tool, but the approach that was taken. Historically, I would have gone to Google Maps and maybe tried to create a custom map that has all of these pinpoints on it. However, now we’re at the point where we can build these one-time tools in about 15 minutes, and that’s what this tool is. I’d to go through a data collection exercise, we figured out the restaurants we wanted to go to. The shows we’ve already booked where our hotel is all of the different activities that we want to do. And to do that, I just point to AI tools at blog posts for restaurants and at something called the New York Pass for attractions. And rather than me spending time going through and taking that information and copying and pasting it and figuring out coordinates and putting them all on a map, the AI did that for me. The calculation of walking distances is done based on the speed at which we walk. It’s mobile friendly, and so I can host this somewhere and actually have it available for use. And it allows me to then turn things on and off. For example, if we’re seeing a show and we want to go to a restaurant, then you’re aware of the shows are. And here are some of the restaurants that we want to go to. And it’ll tell me how far away it is to walk to these things. My point is that AI is now giving us the power to build these one-time tools in a very short amount of time to solve very specific problems. And even though in this case, the example is personal and travel-related. The concept still applies, whether you’re solving a personal problem or a business problem.

AI Expectations and Human-in-the-Loop Approach at 3DN

Clarifies that AI should augment human workers rather than replace them, emphasizing the importance of human oversight in all AI outputs.

Transcript:

Today’s video is a bit different rather than showing you some practical use of AI. I just wanted to pause and talk a little bit about our expectations for AI. We’ve been using AI internally 3DN for a while now, and it has fundamentally changed the way that we work and the way that we produce output for our customers. And we expect that our customers are going to adopt AI internally or so, and that it’s going to change the way that they provide services to their members. And that chain goes on and on. We would expect that our customers members would be using AI too. However, under no circumstances are we suggesting that humans get replaced. And it was highlighted in the conversation yesterday where an external consultant thought that our approach was to remove humans from the process. And it’s just not the case. Wherever AI is being used, a human needs to assess what’s going on. Hence the term human in the loop. Everything that you’re sending out to your customers needs to be vetted by the right person with the right knowledge. At 3D, our approach is to have our customers augment their staff with AI tools and agents. Ultimately, our goal hasn’t changed. We still want people to be productive and efficient and produce great output. AI makes that considerably easier.