The Ethics of Understanding People

There’s a strange contradiction sitting at the center of modern marketing. We’ve never had more tools for understanding people, and yet it can sometimes feel like we understand them less.

We can survey them, segment them, listen to what they say online, study what they buy, watch what they click, model what they may do next, and increasingly ask artificial intelligence to find relationships across more information than any team of strategists could reasonably process on its own. For an industry that has spent generations searching for the elusive consumer insight, this should feel like arriving at the promised land.

Instead, it raises a much more interesting question. What are we actually trying to understand?

That question kept surfacing during a recent conversation with Thom Kennon, a professor at New York University and author of The Bigger Leap: An Ethics of NextCapitalism. Thom has spent more than three decades working in strategy, research, advertising, and audience insight. Early in the conversation, he described becoming the person agencies would turn to when they needed a fresh insight, whether that insight was going to inform an audience strategy, campaign, brand, or business decision.

Then, a few years ago, he began to feel like something important was missing.

His answer was not another research tool. It was a different way of thinking about the purpose of the work itself.

For Thom, that shift involved a lot of unlearning. He talked candidly about his own life, including a journey into sobriety that forced him to question a confidence in his own answers that had once gone largely unchecked. He described arriving at something closer to what Zen Buddhism calls a beginner’s mind, a willingness to begin again from the assumption that maybe you do not know as much as you think you do.

That idea of unlearning becomes important when you apply it to business because so many of the systems we operate within arrive already loaded with assumptions. Growth is good. Competition creates progress. Shareholders come first. Customers are acquired. Audiences are targeted. Attention is captured. Market share is won.

We inherit this language so early in our careers that eventually it stops sounding like a point of view at all. It just sounds like business.

Thom’s instinct is to ask why.

One of the central ideas in The Bigger Leap is that businesses might need to shift their focus from growth toward thriving. Growth, particularly when expressed as market share, almost automatically invites a zero-sum relationship with everyone around you. Your gain becomes someone else’s loss. Your strategy begins with the competition because the underlying question is how to take more of what they currently have.

Thriving changes the frame.

During our conversation, Thom talked about Burgeon Outdoor, a New Hampshire company whose founder began thinking about the business through increasingly wide circles of stakeholders. Before worrying about endless expansion, the company focused on whether its employees, suppliers, immediate community, and other people directly connected to the business could thrive alongside it. Only then would the circle expand outward.

That is not the same thing as rejecting profitability. Thom is very clear that businesses still need to make money. The more interesting question is whether money is the purpose of the system or a resource moving through it.

It also leads naturally into one of the distinctions in his book that stayed with us most after the conversation: the difference between fairness and kindness.

Fairness sounds like an unimpeachable business virtue. Most companies would happily describe themselves as fair. But Thom argues that fairness is ultimately procedural. It is a way of assessing whether people are being treated according to an agreed-upon standard. It can exist comfortably inside a meritocracy because everyone receives what the system determines they deserve.

Kindness requires something different.

He connects kindness to empathy, and empathy to a kind of vulnerability. To genuinely empathize with someone, you have to surrender at least a little of your own self-interest and try to experience the world from where they are standing.

That is where a word most business books tend to avoid entered the conversation.

Love.

Thom teaches a course at NYU around social media and brand strategy, and he described finally reaching a point where he began literally writing the word LOVE on the board for his students. His idea of “real social” starts from the premise that social media should actually be social. People interacting with people, not simply brands perfecting increasingly sophisticated ways of distributing messages through a channel.

It sounds almost embarrassingly simple until you start comparing that idea with the machinery modern marketing has built around it.

We talk endlessly about community while designing systems primarily around extracting attention from it. We call people followers and fans, but value them largely according to their probability of converting. We describe brands as participating in culture while carefully tracking how efficiently that participation moves someone down a funnel.

Thom’s idea of the commons offers a different lens.

The commons, in its broadest sense, describes resources and spaces people create, maintain, and participate in together. Thom’s argument is that collaboration, sharing, and mutual creation are not strange alternatives to the way people naturally behave. They are ancient parts of how people have always organized themselves.

Markets came later.

This makes the current obsession with “community” in marketing particularly interesting. A community is not simply an audience with better branding. It depends on some amount of reciprocity. People contribute because they receive something beyond a transaction in return, whether that is identity, belonging, information, entertainment, support, or simply the pleasure of participating with others.

When a business enters that environment, there is a meaningful difference between participating in the community and figuring out how to monetize it.

That difference matters for brand strategy.

A brand can ask, “How do we get these people to care about us?” Or it can ask, “What do these people already care about, and what do we have a legitimate role in contributing to?”

Those questions may lead to very different work.

The same is true in paid media. The prevailing logic of digital advertising has taught marketers to become remarkably good at finding the person while becoming less interested in the environment surrounding them. Once an audience can be isolated and targeted, the place in which we reach them can start to feel interchangeable.

Thom’s thinking around community and the commons challenges that assumption. If people build meaning through relationships with other people, institutions, publishers, creators, and communities, then context is not simply packaging around an impression. It is part of what gives the impression meaning.

This is where the conversation becomes especially relevant in an era of AI.

Thom is not arguing that technology is the enemy of deeper understanding. In fact, some of the work he is developing with students at NYU deliberately combines different forms of research to get closer to a more complete view of people.

He describes three lenses working together. Traditional deterministic research can help identify statistically meaningful patterns in what people say and do. Ethnographic research asks the strategist to spend more time inside the actual discourse of people, reading what they say to each other and immersing themselves deeply enough in the context that their own assumptions begin to change. Stochastic models, including large language models, create another layer by exploring what might happen based on patterns drawn from enormous amounts of information.

Together, those tools can reveal things no single method could see alone.

But there is still a gap.

Thom described traditional quantitative research as having always faced a basic problem. We ask people what they want, how they feel, what they prefer, what they did, or what they believe they might do. Then we quantify those answers and treat them as evidence about human behavior.

Except people are not always reliable narrators of themselves.

There is a gap between what we feel and what we say we feel, between what we do and what we say we do. Ethnography can get us closer to that messiness because it allows researchers to observe people in less structured environments and sometimes encounter things participants would never think to put in a survey response.

Even then, Thom argues that methodology can only take you so far.

Eventually, someone has to see something.

He uses the phrase “insights whisperer” almost jokingly, but the idea underneath it matters. At some point, a strategist has to look at all of this information and recognize something about the human condition hiding inside it. The dataset cannot necessarily announce which pattern matters. A model can reveal relationships, but someone still has to decide whether those relationships contain an insight worth acting on.

That may become one of the most important distinctions in marketing as AI becomes more capable.

Pattern recognition is becoming cheap.

Judgment is not.

And the ethical question does not disappear simply because the model becomes more accurate. It may actually become more important.

If a business becomes extraordinarily good at predicting what people want, what they fear, what attracts their attention, what creates desire, and what is most likely to change their behavior, does that knowledge automatically make the resulting marketing better?

Or does it simply make the business more powerful?

Those are not the same thing.

The advertising industry has always existed somewhere inside that tension. Our job is, at least in part, to influence behavior. We want people to notice something, remember something, feel something, visit somewhere, buy something, or reconsider what they thought they knew.

Thom’s work does not ask us to pretend otherwise. It asks us to think more carefully about the relationship between insight and intention.

Are we discovering something about people primarily so we can trigger a response that benefits us? Or are we learning something that helps us create something more useful, relevant, generous, or meaningful for them?

Again, the same research could lead to either outcome.

That is why this is an ethics conversation, not simply a technology conversation.

One of the most compelling parts of our discussion involved trust. Thom described trust as something capable of counteracting fear, and fear as one of the forces quietly animating an enormous number of business decisions.

Fear of competitors. Fear of losing market share. Fear of missing an opportunity. Fear of giving employees too much freedom. Fear of customers behaving differently than expected.

You can build an entire strategy around that fear without ever putting the word into the presentation.

It appears as competitive response, risk mitigation, market defense, control, optimization, or efficiency.

Thom's challenge is to imagine what changes when trust becomes part of the infrastructure of an organization rather than a soft value sitting on a culture slide.

The implications stretch well beyond organizational design.

Marketing built on trust behaves differently too. It does not necessarily need to force every interaction toward an immediate outcome. It can give people something worth sharing without demanding something in return. It can participate in communities without assuming ownership of them. It can recognize that attention is not something a brand is entitled to simply because it purchased the opportunity to interrupt someone.

That may also be why the answer Thom gave to our final question felt so fitting.

Every guest this season is being asked some version of the same question: what is one thing about human behavior that no algorithm will ever be able to replicate?

Thom paused.

Then he said, “How about wonder?”

He admitted he had never really thought about the answer before. Maybe that is what made it so good.

Wonder is difficult to optimize because it is difficult to define. Thom described it as containing some kind of yearning and some kind of tantalizing allure, but without obvious content. You do not always know what you are looking for when you experience it. Sometimes the experience is valuable precisely because you did not predict where it would lead.

There is something worth holding onto in that.

Marketing is entering an era in which more of our world will be predictable. Models will become better at estimating what works. Creative systems will become better at producing variations based on previous performance. Media systems will become better at identifying where an audience is most likely to respond.

Those capabilities will be incredibly useful.

But perhaps the most important thing strategists can do with them is resist assuming that prediction and understanding are the same thing.

People still surprise us. They contradict themselves. They form communities around things no planner would have predicted. They share something because it made them laugh, cry, think, or feel recognized. They occasionally reject the most rational option for reasons they cannot fully explain themselves.

And sometimes they wonder.

For brand strategists and media planners, that should be exciting rather than inconvenient. Our jobs do not become less valuable as the models improve. The interesting part of the work simply moves.

The question is no longer whether we can find the pattern.

It is what we see when we look beyond it.

Our full conversation with Thom Kennon, The Ethics of Understanding People, opens Season 12 of Responsibly Different™. We get much deeper into his ideas around NextCapitalism, kindness, trust, community, human insight, AI, and the commons than we could possibly cover here.

And throughout this new season, we will keep exploring the same larger tension with researchers, technologists, marketers, and other people studying human behavior: as our tools become better at recognizing us, what will still require us to understand one another?