PODCAST TRANSCRIPT

[00:00:00] - Vishal Kumar
We want analysts who can dream and dreamers who can analyze, for the world to be perfect.

[00:00:12] - Doug Foulkes
Welcome to episode 62 of Chaos & Rocket Fuel: The Future of Work Podcast, the podcast that looks at every aspect of work in the future, and it's brought to you by WNDYR and Pattyrn. On this podcast, we speak to industry experts and thought leaders discussing how work is changing and evolving. As always, I'm with the CEO of WNDYR and Pattyrn, Claire Haidar. Claire, how are you today?

[00:00:37] - Claire Haidar
Good. And you? We had spring break across most of the Texas schools last week, and we went and spent a little bit of time on our farm in Virginia and the mountains. And it was really good. Just so good to disconnect. But also see spring blooming, which is the opposite of what's happening with you guys right now.

[00:00:55] - Doug Foulkes
We're towards the end, hopefully, of another very big heat wave, 39 degrees again today, Celsius. I think that's about 107. But anyway, let's leave that behind us because we've got a lot to talk about today. Vishal Kumar is on the podcast for the next couple of weeks. Tell us a little bit about him and why he's on the show.

[00:01:17] - Claire Haidar
Vishal is such an interesting character, Doug. He makes me laugh so much. But the reason why we brought him onto the podcast was specifically because of his company Tao.AI and the role that they're playing in really helping very large organizations to navigate AI. Most importantly, not just navigate it, but actually make it really practical and useful inside companies. You've got access to data, but what do you do to make that data useful inside a company? Looking forward to having this conversation with him.

[00:01:52] - Doug Foulkes
Vishal, very nice to meet you. Thanks very much for coming onto the podcast.

[00:01:56] - Vishal Kumar
Thank you. Lovely to be here and excited for this conversation.

[00:02:02] - Doug Foulkes
Also, AI is something that's interesting on so many levels. Let's kick it off. How are humans working along AI today? How is it different maybe to what we see in the movies, for example?

[00:02:15] - Vishal Kumar
Basically, I'm going to give you a pretty Halloween-ish perspective, so don't get riled up. It's what I do. I don't like to sugarcoat things, which makes it all the more worse to have any conversation with my family. How we're using AI? Sure, there's predicting churn, there's sales outcome, all these fun stuff. And obviously, there's autonomous warehouse bots and whatnot.

[00:02:46] - Vishal Kumar
But that's not where I want to have a conversation or I want to have some conversation about. Many of the aspects where AI could be utilized, currently, it's about making people happier. This is about HR. This is about people. We are conversing around that concept. So where I want to see more AI interact is to make human productivity more human than productivity.

[00:03:17] - Vishal Kumar
Today, if you talk about a lot of these tools and a lot of these platforms, they primarily focus on basically hyper collaboration or focusing on the productivity because they are done by nerds, foreign nerds. And we don't have life as nerds. So we would love for not anyone to have lives. Current AI tool is like our ginormous revenge with the word. Joke aside. But I think, yeah, we need technology to be more human.

[00:03:50] - Claire Haidar
But Vishal, I need you to get really practical. What does that look like? What is human AI look like? Can you walk us through an actual example of what that would look like for somebody where AI effectively makes them more happy?

[00:04:08] - Vishal Kumar
Beautiful question. Basically one of the example, obviously, I don't want to toot my own horn that early in the conversation.

[00:04:20] - Claire Haidar
You can, Vishal. It's totally okay. It's why [crosstalk 00:04:21]

[00:04:23] - Vishal Kumar
Oh, my God. Thank you. Now, where's my sales work? Basically, one of the area that Tao, as a company, we focus on is helping people understand connectivity. We should be more connected than we should work together. Our first challenge that we resolved through AI was, "Is Vishal alone in his pursuit to success?" I hope Vishal is not alone.

[00:04:50] - Vishal Kumar
In practical, we give this capability to the businesses that we're working with. "Hey, you know what? We will take bias away." That's our first role model use case that Vishal will be introduced to, maybe Claire, maybe Doug, diverse point of views, and we have a fun life. And then AI monitors how we are behaving and all that.

[00:05:12] - Vishal Kumar
But we started seeing people again clicking some preconceived patterns. The biases started creeping in, and AI loved it. Now, AI as an AI, it rewards success. Success is people Vishal should talk to—Claire and Doug. But if we happen to have, say, some kind of frequency biases, it just says, "Okay, let's go with it as long as Vishal is happy." So that's still a work in progress.

[00:05:42] - Vishal Kumar
But on the other side, we understand that what makes this company unique is not just Vishal or Claire or Doug, or people like Vishal, Claire, and Doug. It is our individualities coming together. It is basically our diversity that coming together. So we started recommending them, "Hey, Vishal, you have not blah, blah, blah," talk to this guy or talk to this girl.

[00:06:04] - Vishal Kumar
And it's a constant battle. And I think that's something that we never realized we end up finding ourselves in because we thought we'll tell AI, "Hey, we'll reward you if Vishal is happy." But then we realize even the bias is creeping pretty quickly and AI starts getting adapted. And that has been a consistent outcry with many of the business partners that we're working with. Besides this technology, they still see biases, they still see the cultural, basically, undertones.

[00:06:35] - Claire Haidar
Vishal, I want to just go back to real basics here. If bias is one of the problem use cases that you and your team are solving for companies, I'm just thinking through practically, like if we were to hire you and bring you into WNDYR or Pattyrn, would you essentially build your AI into our communication systems, into our hiring platforms, into all of the potential areas where bias could exist? And you're then training the AI to not only recognize the bias but actually direct the humans within that process down a different either form of communication or form of behavior. Is that correct?

[00:07:21] - Vishal Kumar
That's correct. We have two primary products right now. One is focused towards pre-hire and one is focused towards post-hire. We call it "just hiring" and "just hired", two of our product roadmaps. In a "just hired" construct, we have something called say, "just ask". So if I have an issue, I'll type that issue in and it automatically finds someone who can answer that question for this particular gentleman, gentlewoman. And then it says, "Okay. Talk to these six random people who could help you solve your most pressing need." And then there is satisfaction and gamification and all that.

[00:08:04] - Vishal Kumar
If you don't even find anyone locally within your company, there's an option you can switch up and the entire Tao global network lit up. And then, now you are seven people team have access to 300,000 global workforce that can say, "Okay, maybe I can help." And that's one of our way in which we are learning and connecting; and along that journey, we understand the biases and solve that biases.

[00:08:30] - Vishal Kumar
I think this is why I said bias, particularly, is that is one area where we think company creates most value in the diversity of opinions. And that is where the tools are not trained to understand that. Tools are rewarded for more conversation rather than better conversation.

[00:08:50] - Claire Haidar
Vishal for the sake of our audience, okay? Because I know that there definitely are people listening to this podcast who are not versed in AI the way you and I are. You said something in response to Doug's question which is really important. You basically broke down the different areas where AI can play a role in companies. Can we go back to that? And can you basically share literally like a 30,000-foot view, what are the different areas where we're seeing AI playing a big role right now?

[00:09:27] - Vishal Kumar
Where it should. Let me talk about where it should because I'm coming from the technology end. I'm pretty delusional. I come with confused and where the world should be. If I look an organization from someone who understands the nuances of AI and understand the nuances of advanced analytics and what it can deliver to an organization, I think in our least recent conversation, we talked about maturity. That one of the HR leaders said, "Hey, when will the AI be mature? When will we see [inaudible 00:10:02]?" That really sparked a very interesting conversation.

[00:10:06] - Vishal Kumar
I said, "This is a very loaded aspect." What you're talking about has some similarity with what she was asking about. How should we look at AI as a brute force for success, for people leaders? It's all about maturity. Maturity has two angles. One is how technology is getting matured, how I am getting matured with the technology in it. Now basically, when that aspect you start calculating and measuring, we have this very famous saying in our team that we want analysts who can dream and dreamers who can analyze for the world to be perfect.

[00:10:42] - Vishal Kumar
That's where if you're a leader that's data-driven or that claims to be a data-driven leader, time to dream, take a nap, stop drinking that coffee, and imagine how the world will look like because you're already tuned with the idea of data. On the other side, if you are dreaming a lot, maybe time to drink a coffee, try to pick up yourself, and then understand what data can do. When you're looking at AI, don't look at AI as a means or as a brute force to change the world. You still are a people leader. You still have a people problem.

[00:11:16] - Vishal Kumar
Last one and a half years told us, if nothing, that people matter more than technology. That's your core competency. Now as a people leader, you want to empower your workers to be more creative, to create more value. Not to produce more, but to create more value. And these are two different things. As an HR leader, if you understand that from the technology point of view, that's an aha moment when you realize, "Okay, I'm getting familiar with what's going on and the technology is here to serve me and not the other way."

[00:11:49] - Claire Haidar
Got it. I like that a lot, Vishal, the way you've come at it because rather than diving into the specifics of this is where AI is playing a role in sales; this is where AI is playing a role in HR, legal, et cetera; you've actually come with the principle of how we should be thinking about HR as leaders, which is great. Doug, back over to you.

[00:12:12] - Doug Foulkes
I'm going to finish off this section, Vishal, just by asking you to provide two practical industry examples where we can see that AI is working in companies today.

[00:12:23] - Vishal Kumar
I think I just talked about the bias problem. I think that's why, Claire, when I heard about WNDYR, I think I could not appreciate you enough. Because one of the things that I talk a lot about is that businesses already have these technologies that they've been using. And now the AI would come in right in the ecosystem and they say, "Okay, let me duct tape." So all these companies jumped in.

[00:12:44] - Vishal Kumar
They have the 1980s tools that still is relevant. And they said, "Okay, let me put an AI module on top of it. The world will enjoy." But I think having a fresh perspective from AI, that is super critical because the designers were designing AI solution or AI Power, a technology-powered solution today. They don't have those biases creeping them.

[00:13:05] - Vishal Kumar
So that AI for bias... That's one of the areas where we see an opportunity for businesses to get better at. And the other aspect that I'm seeing is learning and development challenge. That's another interesting area. If we talk about disruptions, we talk about industry-shaping and moving around rapidly evolving, how to train worker, how to develop worker for future.

[00:13:29] - Vishal Kumar
If you look at the tools that are available today... "Okay, you want to learn AI? Let me send 17,000 courses right in your face and just learn AI now." But we are not trained that way. We are still human. The time is still linear. If you give me 18 courses, I'm not going to finish 18 now in the same amount of time. Probably I'll take 18 times more. That's another perceived notion of, "Okay, AI is available. It is available for good, but my time is still limited. I still need to produce."

[00:13:58] - Vishal Kumar
Instead of burning me down by this overload of content that AI can deliver on, maybe use AI for empathy, maybe use AI for more human aspect of scenarios. And I think that's another area where we see that AI could really hit home when it comes to delivering the organizations of future; helping understand the human problems through AI, which not many tools are doing. I think you need a fresh approach when it comes to, because AI is still very powerful. It still has all the promises that it delivers on. It's just a matter of doing it right.

[00:14:33] - Claire Haidar
Vishal, again, to get really practical about what you've just shared there is, let's use that example that you started using. I type in a set of courses that I'm interested in, an area that I want to learn in. Instead of the AI suggesting 18 different courses for me to do, what should the AI be doing?

[00:14:54] - Vishal Kumar
With our tool, we started this. In "just ask" if you type in "AI, I have this issue," the tool can easily... We have partners like Udacity, Coursera that are filling in their content with us. But before we inject those and give you the AI perspective of what courses I should give you, Claire, or maybe Doug, talk to them for 5 seconds, 10 seconds. Make it more human. And then Doug says, "Okay, endorsed by blah," because I am different. And while AI is understanding about me, I'm still a people that other people could relate with.

[00:15:31] - Vishal Kumar
So that's why even in our team we have five psychiatrists working on this problem. Again, AI has very interesting promises, but only when you understand the emotional aspect of what makes us special, you can actually deliver on it. I don't know if that makes any sense.

[00:15:45] - Claire Haidar
Yes, it does. It makes a lot of sense.

[00:15:47] - Doug Foulkes
And that's the first part of our conversation with AI specialist Vishal Kumar. Make sure you catch the next two parts of this interesting look into AI in the workplace on Spotify, Google, or Apple podcasts or on WNDYR's website, wndyr.com. From Claire and myself, we'll see you soon.