In short
The episode argues that the public focuses on AI capability benchmarks, but the real question is how AI reshapes human judgment over time—via defaults, attention systems, and “convincing outputs” that feel like thinking. It also covers voice deepfakes, enterprise AI’s weak ROI, and what “understanding” means versus pattern-matching.
Guest
Rana Gujral, CEO of Behavioral Signals; studied how machines read human behavior; serial entrepreneur/investor (also described as an Inc. “entrepreneur to watch”). He discusses building “behavioral mapping and temporal modeling” for detection.
Key claims
AI adoption fails when companies chase substitution and bolt models onto human workflows; harm is more likely “drift” through convenient recommendation pipelines than dramatic takeovers; machine consciousness is unclear, but systems may gain “stakes” only if they learn from consequence; deepfake detection must shift from vocal biomarkers to temporal/person-specific behavioral signatures.
Notable examples
Wall Street Journal story of a mother receiving a synthetic voice call; voice tools like 11Labs/Meta Voice/OpenVoice; detection arms race; enterprise productivity “cliff edges”; equity exercise “70% leaving equity on the table” (system opacity).
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Chapters
Tap a time to open that second in VOMisconceptions About AI
0:34 to 1:30
Explore the common misconceptions regarding AI capabilities and their effects.
“The important question isn't how clever it makes you sound in the moment, it's whether...”
The Real Impact of AI on Human Thought
1:30 to 3:24
Discuss how AI influences human thought processes and instincts.
“So I'll give you the version I noticed in myself, right?”
Challenges in AI Adoption
3:24 to 4:44
Understand the challenges companies face in adopting AI technologies.
“Well, it seemed like we were so excited about AI, specifically generative AI, being able to replace so many tasks, being able to free us up.”
Challenges in AI Adoption
4:52 to 5:07
Understand the challenges companies face in adopting AI technologies.
The Disconnect in AI's Promise
5:07 to 6:28
Examine the gap between AI expectations and the reality within companies.
“yeah i mean the gap between the hype and what what's actually landing inside companies is very real and I think it's healthy that we're finally talking about it honestly.”
The Disconnect in AI's Promise
6:33 to 8:44
Examine the gap between AI expectations and the reality within companies.
“So the company's deployed, measured, and found that productivity gains didn't materialize the way the deck promised.”
The Concept of Machine Consciousness
8:44 to 11:16
Delve into the debate about machine consciousness and its implications.
“Well, I think it's really funny that we told people basically use this tool that we already knew will probably replace you at some point.”
Voice Deepfakes and Detection Technologies
12:16 to 14:01
Learn about the challenges posed by voice deepfakes and detection advancements.
“What are you seeing in terms of voice deep fakes and being able to stop a lot of this?”
The Evolution of AI Detection
14:01 to 16:39
Explore how AI models are improving in detecting realism in generated audio.
“Models like HiFiGAN and Natural Speech 2 are patching those tells one by one.”
Lessons from a Journey of Uncertainty
16:39 to 20:13
Discover insights about embracing unpredictability and trusting intuition.
“You left after undergrad without anything ahead of you, essentially an unknown.”
Show all 15 chapters
Embracing Failure as a Growth Tool
20:13 to 24:20
Understand why failure is essential for personal growth and self-discovery.
“Honestly, I mean, if I had started trusting my own instincts sooner, and I think I mean that in a very specific way.”
The Difference Between Intelligence and Understanding
24:20 to 28:00
Explore the distinction between smart machines and those that truly understand.
“Reading your book, the argument that I got that your book has is machines need more than intelligence.”
The Power of Honesty in Turnarounds
28:00 to 30:14
Learn how radical honesty can unlock potential in struggling companies.
“You had walked into a company that was facing potential bankruptcy, and then you were able to have a huge turnaround and that company would then go on to have a successful IPO.”
The Importance of Employee Ownership and Equity
30:14 to 33:13
Explore the critical role of employee equity and ownership in tech companies.
“So I think, you know, the second is, I think, you know, this is connects to what I sometimes, as I've written about in the book as well, is like you have to give people something to do at every turn.”
What It Means to Be Human in the Age of AI
33:13 to 35:18
Delve into the philosophical question of humanity amidst advancing AI technologies.
“You had a forward in your book that compares AI to bamboo popping up everywhere.”
Transcript
Automatic transcript. May contain errors.0:00We're officially in the era where hearing is no longer believing. Wall Street Journal ran a story about a mother who got a call from someone who sounded exactly like her daughter, panicked, crying, begging for help. It was just not her. This is Rana Gujral. Inc. magazine named him an entrepreneur to watch. He's the CEO of Behavioral Signals. And after years studying how machines read human behavior, he's landed on something uncomfortable. What you're about to hear might change the way you think about AI. The important question isn't how clever it makes you sound in the moment, it's whether... The terrifying part is that it...
0:46What is the biggest misconception that you think people have right now around AI? Yeah, I think the biggest misconception, honestly, is that the debate is about capability. Like, can it do this task? Can it do that task? Will it pass this benchmark? When will it beat humans at X? that is the entire public conversation and I think it's the wrong axis the real story isn't what AI can do it's what using AI does to us over time that's the shift I keep trying to get people to see because once the system sits inside your loop of attention and judgment the important question isn't how clever it makes you sound in the moment it's whether it's building your instincts or quietly just replacing them.
1:39So I'll give you the version I noticed in myself, right? So at some point, I stopped using AI the way I use, say, a calculator, like something you pick up and put down. I started using it in the way I use my own mind, like to draft thoughts, to test arguments, to frame decisions. That felt like productivity, and it is. But there's a second thing happening underneath that nobody talks about. Like, am I accumulating judgment or am I generating a convincing stream of outputs that feel like thinking without actually being it? And I think that distinction matters. Almost no one is asking it because we're all fixated on capability benchmarks.
2:23And the other big misconception related to that is people imagine harm from AI as something dramatic, like a rogue system, a job apocalypse, some rupture moment. That's going to happen. And what I actually worry about is something more dangerous. It's the drift. The most consequential changes AI brings don't arrive as ruptures. they arrive as defaults, like decision pipelines that surface a recommendation before you formed an opinion, like attention systems that learn your psychology with unsettling precision. And none of that is coercive. It's just convenient. And the convenience is more than enough to reshape a life or society without anyone noticing until it's done.
3:13So I think what I would correct one thing in the public conversation, it would be this. It's like, stop asking what AI can do. I mean, start asking what it's doing to shape the human thought. And I think that's the real frontier. Well, it seemed like we were so excited about AI, specifically generative AI, being able to replace so many tasks, being able to free us up. But a lot of the research is showing that many companies are not getting any better. So employees are not really adopting it at a corporate level. And they're not really finding that it's really great at replacing people. even. Many companies are hiring people back.
3:51What are you seeing in terms of this being our savior? I built Founder's Story from a$50 microphone. And the most important thing is I didn't do it alone. For years, I've been using Upwork to hire marketing, editing, branding, you name it. In fact, the editor who cut this very episode and the team behind all of Founder's Story branding found them on Upwork. The quality of people is top notch and paying people is simple. Upwork is a one-stop platform to find, hire, and pay expert freelancers across development, data, marketing, operations, and more. With Business Plus, you can access the top 1 % of talent on Upwork.
4:37And with AI-powered shortlisting, you'll get matched to the right freelancer in under six hours. no endless searching required it's free to sign up and posting a job is easy visit upwork.com right now and post your job for free that is upwork.com to connect with top talent ready to help your business grow that's upwork.com upwork.com yeah i mean the gap between the hype and what what's actually landing inside companies is very real and I think it's healthy that we're finally talking about it honestly. Here's what I see. The initial wave of enterprise AI adoption was driven by what I would say is a fantasy of substitution, right?
5:27Take a workflow, drop in a model, remove headcount, book the savings. And it turns out that almost... I built FounderStory from a$50 microphone. And the most important thing is I didn't do it alone. For years, I've been using Upwork to hire marketing, editing, branding, you name it. In fact, the editor who cut this very episode and the team behind all of Founder's Story branding found them on Upwork. The quality of people is top-notch and paying people is simple. Upwork is a one-stop platform to find, hire, and pay expert freelancers across development, data, marketing, operations, and more. With Business Plus, you can access the top 1 % of talent on Upwork.
6:15And with AI-powered shortlisting, you'll get matched to the right freelancer in under six hours. No endless searching required. It's free to sign up and posting a job is easy. Visit Upwork.com right now and post your job for free. That is Upwork.com to connect with top talent ready to help your business grow. That's U-P-W-O-R-K dot com Upwork dot com You know, that's almost never how work actually flows I mean, real work is full of exceptions Judgment calls, tacit contacts, relationships, etc And the model handles the middle 60 % nicely And then falls off a cliff on the edges And the edges are where the values live, right?
7:02So the company's deployed, measured, and found that productivity gains didn't materialize the way the deck promised. And some of them are now hiring back because they cut into the muscle, not fat. The second thing I point to is that most enterprises try to bolt AI onto processes that were designed for humans doing the whole task. That's like buying a Formula One engine and putting it in a mini WAN. So you have to redesign the vehicle. I mean, the companies I see actually getting value are the ones rebuilding the workflow around a collaboration, not just inserting a chatbot into an existing pipeline.
7:37And I think then there's the adoption piece, right? Which is, I find the most interesting, to be honest. I mean, employees aren't refusing to use these tools because their validity is, right? I mean, they're refusing because nobody's answered the basic question of what's in it for them. If I use this thing and I become twice as productive, does this mean that I get to do more meaningful work? Or does it mean I get more work piled on? What does it mean, you know, or does it actually mean I'm trading my replacement? You know, and until that question is answered, I mean, you're going to get quite resistance.
8:10And you're getting it, you're not necessarily seeing it on the dashboard yet. So, I mean, to your question, I mean, is AI our savior? I don't think so. It was never going to be. It is just a powerful capability that reshapes what's possible. but the returns show up when you rethink the work, invest in people and stop treating it as a cost-cutting shortcut. I mean, the ones that are doing that are winning and the ones that are chasing substitution, I think they're the ones that are writing the disappointed headlines. Well, I think it's really funny that we told people basically use this tool that we already knew will probably replace you at some point.
8:53And then we're shocked that they didn't want to use the tool. It's really funny. As we know, there's always a disconnect from the top executive level down, right? Something you said, though, that stuck with me is that you're worried about AI developing consciousness beyond human control. How real is that? I mean, I'd say, let's be precise about what we're actually talking about, right? So because consciousness is doing enormous work in that sentence, and most people using that word haven't defined it even for themselves. Here's what I think is happening, right? So we're seeing systems that are extraordinarily good at producing outputs that feel conscious.
9:34Stuff like fluent language, empathy, memory, personality. And the human brain is exquisitely tuned to attribute mind wherever it sees those signals. It's the same instinct that makes us name our cars, right? And when a model responds with warmth and nuance, our wiring says, is there something, someone in there? like that's a projection uh not really evident so the harder truth is that we don't really actually have a consensus on what generates consciousness in us um where the nerds neuroscientists are still trying to argue about whether it emerges from specific network dynamics or whether it's a global workspace phenomena whether the brain generates thoughts or receives it and if you can't explain the one working example we have that one working example i mean claiming about how to replicate it in silicon is at minimum, I think, just premature.
10:29So I don't, I mean, I want to be careful. I'm not in the camp that says machine consciousness is impossible. Dehan and others have made a reasonable case that if you replicate the right computational signatures, denying subjectivity to that system becomes just as arbitrary as denying it to other human. That they may come, but there's a big difference between, you know, may come and around the corner. And so what I, you know, I rather focus people on is something I call artificial general experience, you know, not whether the machine is conscious in some metaphysical sense, but whether it starts to have stakes, like, you know, preferences that shape behavior, something that functions like caring about outcomes.
11:15That's a threshold that actually matters for how we treat these systems. Quick break to talk about something I get asked about all the time on this show, Bitcoin. For years, I assumed it was complicated. Turns out it really doesn't have to be. If you've been curious about Bitcoin but haven't made the jump yet, Cash App makes it easy. You can set up automatic purchases with zero fees or buy larger amounts also with zero fees. Start small or go bigger. It's designed to be simple either way. For a limited time, new customers can get$10 added to their balance. Just use code BITCOIN10 when you sign up and don't forget this part.
11:56Send at least$5 to a friend in the first two weeks. Terms apply. Cash App is a financial services platform, not a bank. Banking services provided by Cash App's bank partner. Bitcoin services provided by Block Inc. Brand. For additional information, see the Bitcoin disclosures at cash.app slash legal slash podcast. Much more of a tractable question than the hard problem. What are you seeing in terms of voice deep fakes and being able to stop a lot of this? Because I think we're starting to already see people are calling you or they're calling companies acting like different people and people don't realize it.
12:36I've been called a few times and I'm wondering if this is a human. The funny thing is, every time someone calls me, I ask, are you human or are you AI? Yeah, I mean, I think you're touching on to something that does keep me up at night, honestly. I mean, we're officially in the era where hearing is no longer believing. You know, that phrase is dramatic, but it's just true now. I mean, you know, you've seen examples like, you know, earlier this year, Wall Street Journal ran a story about a mother who got a call from someone who sounded exactly like her daughter, panicked, crying, begging for help.
13:11It was just not her. I mean, it's synthetic voice generated by AI. And the terrifying part is that it isn't that it just happened once. I mean, the tools do it consistently. 11 Labs, Meta Voice, Open Voice, they're openly available. I mean, there's no barrier to entry anymore. I mean, all you need is like three seconds of your voice from a social media clip and you can clone. So on the technology side, on the defense side, most detection has traditionally leaned on what we call vocal biomarkers. So the little imperfections in real speech, stuff like micropauses, pitch variation, throat resonance, tiny jitters caused by breathing or emotion.
13:55And the assumption was synthetic voices couldn't fake those consistently. That assumption is dying fast. Models like HiFiGAN and Natural Speech 2 are patching those tells one by one. So, like, I mean, I actually compare this to the diamond industry. Like, lab-grown diamonds used to be spotted by their lack of natural inclusions. Because chemically, they're still a diamond. Now, manufacturers add synthetic inclusions during the growing process, and you can't tell anymore. I mean, as the same story with voice. So, you know, so I think what we've pushed in the last several years on our end is we pushed on behavioral mapping and temporal modeling.
14:38So instead of asking, does this audio clip look real? We ask, how does this specific person actually speak over time? You know, this is our technology at behavioral signals, right? And so, for example, focused on the cadence, their articulation, co-articulation patterns, the rhythms of how their porosity moves across sentences. I mean, those temporal signatures are much harder to fake, even when a window sounds perfect. But, you know, this is an arms race. Every detection gets studied by the generation side and vice versa. The real answer isn't purely technical. I mean, that's a cultural question at this point.
15:13We need to normalize verification. I mean, like, you know, maybe at some point we'll need a code word with your family, you know, call back to a known number, skepticism as default when emotional pressures are high. I built Founder's Story from a$50 microphone. And the most important thing is I didn't do it alone. For years, I've been using Upwork to hire marketing, editing, branding, you name it. In fact, the editor who cut this very episode and the team behind all of Founder's Story branding found them on Upwork. The quality of people is top notch and paying people is simple. Upwork is a one-stop platform to find, hire, and pay expert freelancers across development, data, marketing, operations, and more.
16:03With Business Plus, you can access the top 1 % of talent on Upwork. And with AI-powered shortlisting, you'll get matched to the right freelancer in under six hours. No endless searching required. It's free to sign up and posting a job is easy. Visit Upwork.com right now and post your job for free. That is Upwork.com to connect with top talent ready to help your business grow. That's U-P-W-O-R-K.com. Upwork.com. We kind of headed there. You have a great story. You grew up in India. You left after undergrad without anything ahead of you, essentially an unknown. You walked into this unknown. you took a big leap.
16:51What did you learn from that? You know, so much, right? I mean, I mean, back to your sort of previous question, this, my interactions with model, you know, and it's like, there's so many different things sort of that have come out in terms of sort of my interactions with my own interactions with AI, like, you know, the back and forth, the model surfaced, an angle that I hadn't considered not a solution, an angle or reframing. In my head, this is the only way I can describe it, like a lock turning and a door open. And I think to me, that's been the epiphany. I think on my own journey, as you sort of said, coming into this new culture, new country, the biggest thing that I've learned is that future is very unpredictable.
17:46You are naive, and I see a lot of young people do this. You're naive if you feel that, you know, success or success is a heavy word. Let's say the outcomes you want, let's go with that. The outcomes you want are driven by a formula. Like you do X, then you do Y, and then you do Z. That results in number 45. life. But that's what we have been culturally taught by our parents, by our society. For example, you have to go to school, you have to get good grades, then you have to get a job, then you have to progress at the job, you have to be a good employee, you have to get along with your colleagues, you have to be all of those things, and then you get that.
18:39The truth is that it doesn't quite work that way. I mean, life is very, very unpredictable. Now, you know, there's a debate about whether, you know, things are happening in a deterministic fashion or everything is all just pure random and how much of what happens you actually control yourself. But to me, like whether you're in this camp or that camp, like, you know, whether in the deterministic or undeterministic camp, whether you believe there's free will or no free will, it doesn't really matter either way. So if you really ponder on that questions carefully and sort of say, well, am I in control or can I affect outcomes or things are going to happen?
19:18The bottom line is it doesn't matter. And so just enjoy the journey. I mean, I think that's one thing that I've learned is that, you know, and that's the thing to it is whether you're doing things that are going to happen in an unpredictable form, Um, and, you know, uh, or it's already destined, uh, in both cases, uh, the, you know, just chill out. I mean, just take it easy, um, and go with the flow and, uh, be in the moment. Uh, and it took me like, uh, decades to get to that realization. I wish like, you know, I wish I had that realization many decades ago. And if I did, I would have made different choices or have done things differently or had lived those years differently.
20:10But I think that's the biggest learning on my end. What is something, when you think back, that if you had done differently, it would have made a positive impact on your life? Honestly, I mean, if I had started trusting my own instincts sooner, and I think I mean that in a very specific way. Like, you know, long stretch of my career, I treated intuition as a lesser cousin of analysis. If I couldn't defend a decision on spreadsheet, I'd second guess it. I'd gather more data, run one more model, get one more opinion. And there's a lot of times weeks later, I'd land exactly where my gut had pointed me on day one.
20:50But that's expensive, right? Not just in time, but in conviction. So every time you override your instinct and it turns out that you've been right, you teach yourself to distrust the same signal. you should be actually strengthening. And there's a thread in the book about this. I mean, humans have two modes of thought, like the fast intuitive one and the slow deliberative one. And we built this whole cultural bias towards the slow analytical reasoning as the serious mode. But the intuition isn't magic. It's accumulated experience compressed into a signal. It's your pattern recognition talking.
21:23And if you've been in an arena a while, that signal is worth listening to, even when you can't fully, uh, article it why, at least in the moment. So, I mean, the thing I tell my younger self is, you know, run the analysis, sure do that, right. But treat it as a check on your instinct, not a replacement. Um, and, uh, and if, if there are two are not lining up, uh, or the disagree, get curious. I mean, don't automatically side with the spreadsheet. Um, so I think that's the big learning. Maybe our intuition is our advanced human brain figuring things out in a very short, quick time. But it's hard for us to fathom that we could come up with that answer because subconsciously we're coming up with something that we didn't really think about.
22:06Now there is a quote, everything you want is on the other side of failure. What does that quote mean to you? Yeah, before I get to the quote, I want to just pick up on what you said, because you're right. Intuition, you know, isn't magic, it's compression. I mean, it's your brain running an enormous amount of pattern matching in the background faster than conscious thought can actually track. I mean, there's a concept called embodied cognition, the idea that thinking isn't just in your head. Your gut, your nervous system, your hormones, they're all processing signals constantly. And most of it is actually below awareness.
22:42That's why a gut feeling shows up as a physical sensation, actually, before you can articulate why. Your body knew before you did. it. So now the quote, like everything you want is on the other side of the failure. For me, that lands in a very personal space. I think we've been sold this with that success is a straight line. I mean, you work hard, you're smart, you win. But that's not how any of it actually works. I mean, every meaningful thing I've built, every insight I've had that mattered came out of something breaking first. I mean, a company that didn't work, a decision I got wrong, a moment where I was pretty sure I'd be embarrassed myself beyond recovery.
23:21And so what I've come to believe is that suffering, failure, the hard stuff, it carries information. It tells you what you value. It tells you what needs protection. It tells you where the edge of your understanding actually is. So if you try to numb it out, and I see a lot of people aiming to do that, I mean, if you optimize around it, you will lose the signal. I mean, you lose the thing that was going to make you remarkable. And I write about this in the book as well. It's like, you know, that my own suffering has helped me make who I am. And I suspect a lot of people feel the same way if they're actually honest about it.
24:00I mean, a life without contrast collapses into just numbness. I mean, you need the low points, not because pain is virtuous, but because that's where the shape of what you actually want become visible. So the quote to me means stop treating failure as a detour. It's not a detour. It is the road. That's the road. Reading your book, the argument that I got that your book has is machines need more than intelligence. They need experience and consequence. What's the difference though between a smart machine and one that understands? The cleanest way I can put it is this. A smart machine gives you the right answer.
24:40A machine that understands can tell you why that answer holds, where it breaks, and what would have to be true for it to be wrong. but so i'm i'm borrowing here from uh david deutch uh who has uh influenced a lot of my ideas and i built upon some of his ideas in the book uh who also also i think has the sharpest lens on this i built founder story from a 50 microphone and the most important thing is i didn't do it alone for years i've been using upwork to hire marketing editing branding you name it in fact the editor who cut this very episode and the team behind all of Founder's Story branding found them on Upwork.
25:25The quality of people is top notch and paying people is simple. Upwork is a one-stop platform to find, hire, and pay expert freelancers across development, data, marketing, operations, and more. With Business Plus, you can access the top 1 % of talent on Upwork And with AI-powered shortlisting, you'll get matched to the right freelancer in under six hours. No endless searching required. It's free to sign up and posting a job is easy. Visit Upwork.com right now and post your job for free. That is Upwork.com to connect with top talent ready to help your business grow. That's U-P-W-O-R-K.com. Upwork.com.
26:15he argues that knowledge doesn't grow through prediction. It grows through good explanations, like explanations that are hard to vary, that connect across domains, that survive criticism. And by that standard, most of what we call intelligent AI today is doing something quite different. It's doing extraordinarily sophisticated pattern matching. I mean, it's finding the shape of the answer in the training data. That's not nothing. I mean, it's quite miraculous, actually. But it's not understanding, right? I mean, so the test I use is take a chess engine that can crush any grandmaster alive. Does it understand chess?
26:54It doesn't know it's playing a game. It doesn't feel the weight of a bad move an hour later. It has no relationship to consequence. It just has competence. And competence without a relationship to consequence is exactly what worries me because we're now embedding those systems inside human decisions where the consequences are real. So the second piece, understanding. in the human sense, isn't just explanatory, right? It's accumulated. You become a different person after you've been wrong. I mean, after you've caused harm, after you've watched a patent play out for years. I mean, your judgments is scar tissue in the best sense.
27:31That's what it is, a judgment. And a machine that outputs brilliant answers is identical before and after every interaction. It hasn't learned anything in the way that matters. It's just been queried. So when I talk about artificial general experience, that's really what I'm pointing at. Like, can the system be transformed by what happened to it? Can it carry forward not just data, but the weight of having been through something? And until we build for that, we're going to keep confusing eloquence with wisdom. And those are very different things. You had walked into a company that was facing potential bankruptcy, and then you were able to have a huge turnaround and that company would then go on to have a successful IPO.
28:14What would you say is a secret unlock that you find when you walk into a company like that, that if you make that switch, it changes everything? I mean, I think I'll be honest, right? I mean, most of the stuff is usually worse than what actually is on the paper. you know like for example you know obviously the cash is an issue morale is an issue there's usually a fog over the whole place and everyone knew something is wrong or was wrong but nobody can actually name it out loud you know so I think what I've seen is that and I've seen this pattern now play out in multiple turnarounds is the secret isn't a strategic insight it isn't a clever pivot It isn't, you know, cutting your way to profitability.
Read the full transcript
29:09Those things matter, but they're downstream. I mean, the unlock is honesty, radical, uncomfortable, name the thing in the room, honesty. So when a company is failing, there's almost always a collective agreement not to look directly at the problem. People protect each other. They protect the founder. They protect their own role. And so the org develops this shared fiction about why things are hard. And everyone quietly just plays along. I mean, it's ridiculous. Like you see this all the time. When slaves blame, the sales will blame the product. The product blames engineering. Engineering blames the roadmap.
29:43And nobody's lying exactly. Everybody's just holding a piece of the truth and refusing to put it on the table. So I think the first thing we did, and I would do this now every time, is like you sit with the people. and I ask them and tell me what they actually thought, not what they'd say in a board meeting, what they say to their spouses at dinner. And you'd be amazed, right? I mean, once one person names a real problem, the dam breaks. Suddenly have like a massive signal instead of noise. So I think, you know, the second is, I think, you know, this is connects to what I sometimes, as I've written about in the book as well, is like you have to give people something to do at every turn.
30:24Like when an org is scared, Now, paralysis is the big thing. It's the enemy, right? So people need the next step. Like even if the plan isn't perfect, having a clear human size action in front of you changes the temperature of the entire building. So, you know, you've got to get the agency back and agency is contagious. So I think, you know, start to compress it is stop managing the story and start facing it and then give everyone a concrete move. And I don't think, you know, there's anything genius here. It's just like, you know, figure out where the oxygen is and unleash that. Sometimes the symbol things are the hardest.
31:05I had a recent guest on, Oren Barzilai, who's one of the founders of Equity Bee. And he told me that around 50 to 70 % of employees never exercise their equity, which is insane because this could be millions and millions of dollars. I know people that recently, through the equity that they earned or stock options, they were able to get millions, life-changing money. So when you think about how important it is for employee ownership around equity and stock options, especially in this crazy world of tech, how important is this going forward? Very. I mean, it's wild and it tracks with what I've seen.
31:48Yeah, 70 % leaving equity on the table. It's a systemic failure of how we communicate ownership. and to be honest, I mean, for the most part, it's because practical matter, they don't have the cash to exercise, is my take, right? It's one of the most powerful alignment mechanisms we've ever invented in business and when done right, it turns employees from labor into partners, changes how people think about decisions, you know, owner just behaves differently, right? And that's true of houses, it's also true of companies. And I also think like a lot of, you know, many times the reasons people don't exercise is the system is generally opaque.
32:30I mean, you get a grant letter with a bunch of numbers. Nobody explains the AMT tax implications. Nobody explains the 10-year expiration window. Nobody explains that a 409 valuation, what it actually means for you. And then you leave your company and you have 90 days to come up with tens of thousands of dollars to exercise and you don't have that liquidity. So you walk away. and the default is loss. I mean, that's a design problem. So I think this definitely needs to be solved because the velocity of value creation in tech is essentially ownership. And if this is broken, this definitely needs to be fixed.
33:13Last question for you is this. You had a forward in your book that compares AI to bamboo popping up everywhere. And I think this sources a question, probably one of the most important questions that we will think about in our lifetimes. What does it mean to be human? That's the question, right? And I'll tell you, I've been sitting with it for years now. Um, and my answer keeps evolving. Um, what I think where I've landed, at least for this chapter of my thinking is like being human has never been about being the smartest thing in the room. If intelligence were the criteria, we'd have surrendered the title the moment a calculator beat us at arithmetic, right?
34:00So what makes us human is something stranger and harder to name. I think it's the capacity to assign meaning. It's to care about outcomes that may or may not benefit us, to feel the weight of a choice, to love something knowing we'll lose it. And I think that becomes clearer, not more confused as the eye gets better, because for the first time, we have a mirror that reflects back everything we are not. The systems can't produce language. They can reason. They can even simulate empathy. But they don't ache. They don't grieve. They don't sit up at 2 a.m. wondering if they made the right call with the kid.
34:41the texture of experience, the fact that things matter to us in a way that costs us something, that's the thing. I think that's the thing. So in the book, I write about not wanting to engineer away the full range of human emotion, eliminate disease, eliminate poverty, eliminate violence, yes, but don't numb us into some flat state of engineered happiness because the sadness, the doubt, the longing, those aren't really bugs. They're the substrate meeting grows out of, right? So my working answer is this. To be human is to be a creature that builds meaning under constraint. Mortality is a constraint.
35:20I mean, limited attention is also a constraint, I guess. I mean, not knowing how the story ends is a constraint. And we make art, love and companies and children inside those constraints. And I think that's the miracle. meaning under constraint wow we didn't even get to talk about quantum next time we'll save that because i i don't even know what's next what's past quantum and asr ag i don't even know what the next one is but i like age what you said i think i think we can adopt that uh i'm less scared now than i was 45 minutes ago so i appreciate that but rana gujarol serial entrepreneur, investor, friend for, I don't know, maybe 10, 12, 12 years.
36:06I'm not even sure. Like we both had more hair when we started hanging out. But that's more hair for sure. You're, you're good. Although I think you went, I think you'd look pretty good if you were bald, Ben. I think you should just shave it up at some point. It's, it's getting there. So I'm hoping I continue to look good because it's definitely getting there. I think you should. I think you have a good head for it. I think you'd be all right. But man, always great to talk with you. And I'm super excited that you came on today. Thank you, Dan. It's always good to talk to you. And thank you for having me.
From the publisher
Daniel and Rana Gujral, CEO of Behavioral Signals, begin with the biggest misconception in AI: that the real debate is about capability. Rana argues that the more important question is not whether AI can write, reason, analyze, or outperform humans on benchmarks, but whether it is strengthening human instinct or quietly replacing it. From there, the conversation explores why enterprise AI often fails when companies use it as a headcount-reduction shortcut, why workers resist tools they fear will train their replacement, and why AI has to be built into redesigned workflows rather than bolted onto old processes. Rana also breaks down voice deepfakes, machine consciousness, artificial general experience, trusting intuition, the role of failure, and why being human is about creating meaning under constraint.
Key Discussion Points
Rana says the public AI conversation is focused on the wrong axis: instead of asking what AI can do, we should ask what using AI does to human attention, judgment, and instinct over time.
He explains that AI harm may not arrive as one dramatic rupture, but through quiet drift: defaults, recommendations, attention systems, and convenience slowly reshaping how people think.
Rana argues that many enterprise AI rollouts failed because companies believed in a “fantasy of substitution,” assuming they could drop a model into a workflow, remove people, and instantly book savings.
He says real work is full of exceptions, judgment calls, relationships, and context, and that AI often handles the middle of the workflow but fails at the edges where the real value lives.
Rana explains that employees may resist AI not because they are illiterate, but because nobody has answered what happens if the tool makes them more productive: more meaningful work, more workload, or replacement.
The conversation explores machine consciousness, with Rana warning that fluent language, empathy, memory, and personality can make systems feel conscious even when that may be human projection rather than evidence.
Rana introduces the idea of artificial general experience, arguing that the more practical question is whether machines develop stakes, preferences, and something that functions like caring about outcomes.
He says we are entering an era where “hearing is no longer believing,” because voice cloning tools can replicate someone’s voice from only a few seconds of audio.
Rana explains that older deepfake detection methods looked for imperfections in synthetic speech, but newer models are learning to patch those tells, making behavioral and temporal patterns more important.
He shares that Behavioral Signals focuses on how a specific person speaks over time, including cadence, articulation, co-articulation, and prosody patterns that are harder to fake consistently.
Rana reflects on leaving India after undergrad and walking into uncertainty, saying the biggest lesson was that life does not follow a clean formula and the future is far more unpredictable than we are taught.
He says one thing he wishes he had done earlier was trust his instincts, because intuition is not magic; it is accumulated experience compressed into a signal.
Rana explains that failure is not a detour from success but the road itself, because suffering and breakdowns reveal what someone values, what needs protection, and where their understanding ends.
He argues that a smart machine gives the right answer, but a machine that understands can explain why that answer holds, where it breaks, and what would have to be true for it to be wrong.
Rana shares his turnaround philosophy: the secret unlock is not a clever pivot, but radical honesty—naming the real problem in the room and giving people a concrete next action.
Takeaways
The biggest AI risk may not be replacement overnight. It may be the slow erosion of human judgment as people outsource thinking, framing, and decision-making to systems that feel helpful.
AI works best when companies redesign the workflow around human-machine collaboration instead of inserting a chatbot into old processes and expecting transformation.
Voice deepfakes are becoming a trust crisis, and Rana believes society will need to normalize verification, including callbacks, family code words, and skepticism under emotional pressure.
Human intuition should not automatically lose to spreadsheets. Rana sees intuition as pattern recognition built from experience, and analysis as a check—not a replacement.
Machines may become more intelligent, but understanding requires consequence, transformation, and the weight of experience—not just eloquent answers.
Closing Thoughts
Rana Gujral’s conversation is less about AI hype and more about what AI forces us to confront in ourselves. As machines become more fluent, more persuasive, and more integrated into our decisions, Rana argues that the real question is not whether they can think like humans, but whether humans will keep building judgment, meaning, and instinct of their own. This episode captures one of the deepest AI conversations on Founder’s Story: a warning about convenience, a framework for trust, and a reminder that being human means building meaning under constraint.
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