What is the Real Value of a Hug?

Every now and then I fantasize about launching a social media channel called Professor Subtext. I, the professor, would publicly decode what people are really trying to say when they post on their favorite platform. (Example: “Happy to participate in this panel” → Subtext: “Look how much of an important expert I am!”)

This fantasy came back to me as I was reflecting on the rather astounding gap between the enthusiastic discourse on LinkedIn—where stakeholders promote AI-powered products—and the deeper concerns about what these same technologies might mean for human society, even if we set aside the usual Terminator-style doomsday scenarios.

I meet psychologists developing AI bots designed to replace psychologists. I meet entrepreneurs using AI to optimize therapists’ workflows. They all talk about how this revolution is not only inevitable, but a net positive. And that’s not surprising—if AI helps you deliver more value to others, of course you’ll champion it.

But as we polish these amazing new tools, I remind myself: their true societal impact won’t be measured by how many people they made rich, or whether they made psychotherapy 30% more efficient. If the same technology ends up doubling the number of people struggling with mental health problems, we’ve actually moved backward.

What really matters is how these technologies reshape the energetic network of value exchange—the invisible web of human acts through which value flows between people. Money is one way value moves, reflecting how much people feel they benefit from what someone else offers. But it’s not the only one. When I hug my child, lean on my partner, smile at a stranger, or give advice to a friend—those are acts that transition value between different people. People who provide meaningful value to others—whose energy is felt and appreciated—tend to experience better emotional well-being. That’s how energy in motion connects to the mental health of a society.

There are two major shifts underway where AI will reshape this energetic network:

1. In our livelihoods.

AI lets us do more with less, reducing our reliance on others for services that don’t require a human touch. Years ago, James Manyika (the former chair of the McKinsey Global Institute) noted that technology can replace the core of certain jobs, lowering the skill needed at the endpoint (1). On one end, we’ll see an increase in providers with fewer qualifications (and lower pay). On the other, a smaller group of super-experts will oversee powerful tools that deliver value at scale.

We already see this dynamic playing out in digital health interventions: Coaches don’t need to be licensed psychologists, so they earn less. Meanwhile, large-scale automated tools—owned by a few companies—are delivering value that used to pass through individual human relationships.

In this system, some people will become even more valuable to others, as they spearhead AI tools. But many more will find themselves sidelined. Empirically, this growing gap in people’s livelihoods has been unfolding over the past 30 years—and the trend appears to be accelerating.

2. In our relationships.

AI products are starting to display what appears to be like genuine empathy—sometimes even more so than humans. Some might even begin to feel like ideal companions. We already have companies who sell romantic relationships with fictional AI women who look and communicate with striking realism. We’ll be forced to ask: What is a real connection? What’s meaningful? What still matters, even when a machine can fake it beautifully?

To make the most of what AI can offer—and to steer it toward a hopeful future—we’ll need to focus less on how it performs, and more on how it supports our ability to be there for one another. To enrich human connection. To help people become more valuable to those around them.

Yes, I’m assuming that this is the most important part of life. And yes, it’s only an assumption—in the absence of a clear moral compass.

Nevertheless – That’s the kind of AI tools I’d like to see in the market. That’s the kind of future I’d like to help build.

Reflective moment: As someone involved in integrating AI into digital health, I seem to have a recurring hobby of sawing off the very branch I’m sitting on. But that’s a topic for another post, and maybe some AI-based therapy.

Be well, Amit

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1.     Manyika, J., Mischke, J., Bughin, J., Woetzel, J., Krishnan, M., & Cudre, S. (2019). A new look at the declining labor share of income in the United States. McKinsey Global Institute Discussion Paper, 1-64.