The Human Behind the Door

There’s an old hotel on a windy corner in Chicago where the front doors shine like brass mirrors. Each morning, before guests even reach the step, a tall man in a gray coat swings one open with quiet precision. He greets them by name, gestures toward the elevator, and somehow makes every traveler feel like a regular. To a cost consultant, he is a line item. To the guests, he is part of the building’s atmosphere.

When management installed automatic doors a few years ago, the entrance became quieter and cheaper, but not better. Guests no longer lingered to chat, taxis stopped less often, and the lobby felt colder. The automation improved the hotel’s bottom line but not its character.

This story captures what British advertising executive Rory Sutherland calls “The Doorman Fallacy,” the habit of mistaking visible tasks for the entirety of a role. In this short video explanation, Sutherland points out that a doorman does more than open doors. He represents safety, care, and ceremony. His presence changes how people feel about a place. Remove him, and you save money but lose meaning.

The Lesson Behind the Metaphor

Sutherland expanded on the idea in his 2019 book Alchemy, arguing that logic alone can lead organizations astray. We typically undervalue the intangible parts of human work because they do not fit neatly into a spreadsheet. For example, the doorman seems redundant only if you assume his job is merely mechanical. In truth, he performs a social and symbolic function. He welcomes guests, conveys prestige, and creates a sense of safety.

Of course, this lesson extends well beyond hotels. In business after business, human behavior is treated as inefficiency. The result is thinner experiences, shallower relationships, and systems that look streamlined on paper but feel hollow in practice.

The Doorman in the Age of AI

In a recent article for The Conversation, Gediminas Lipnickas of the University of South Australia argues that many companies are repeating the same mistake with artificial intelligence. He warns people against the tendency to replace people because technology can imitate their simplest tasks while ignoring the judgment, empathy, and adaptability that define the job.

Lipnickas offers two examples.

The Commonwealth Bank of Australia laid off 45 customer service agents after rolling out a voice bot, then reversed the decision when it realized the employees were not redundant. They were context interpreters, not just phone operators.

Taco Bell introduced AI voice ordering at drive-throughs to speed up service, but customers complained of errors, confusion, and surreal exchanges with synthetic voices. The company paused the rollout and conceded that human improvisation worked better, especially during busy periods.

Both cases reveal the same pattern: Automation succeeds technically but fails experientially. It is the digital version of installing an automatic door and wondering why the lobby feels empty.

Measuring the Wrong Thing

The doorman fallacy persists because organizations keep measuring only what is visible. Performance dashboards reward tidy numbers, calls answered, tickets closed, customer contacts avoided, because they are easy to track. But they miss the essence of the work: problem-solving, reassurance, and quiet support.

When we optimize for visible throughput instead of invisible value, we teach everyone to chase efficiency at the expense of meaning. A skilled agent does not just resolve a complaint; they interpret tone and calm frustration. A nurse does not merely record vitals; they notice hesitation that no sensor can catch. A line cook does not just fill orders; they maintain the rhythm of a kitchen.

The answer is not to stop measuring; it is to do a better job of measuring. Key results should focus on interaction, problem-solving, and support, not just volume and speed. Otherwise, we risk automating away the very parts of work that make it valuable.

Efficiency versus empathy

Sutherland’s insight and Lipnickas’s warning meet at the same point: When efficiency ignores empathy, systems break down. Automation works well for bounded, rule-based tasks such as data entry, image processing, or predictive maintenance. But as soon as creativity, empathy, and creative problem-solving enter the picture, humans remain indispensable.

What looks like inefficiency on paper is often resilience in practice. A doorman who pauses to chat with a regular guest may appear unproductive, yet that moment strengthens loyalty and reputation in ways no metric can show.

Coaching, not replacing

That is why my own work has focused on using AI as a coach or mentor, not as a worker. A well-designed AI coach can prompt reflection, offer structure, and accelerate learning, but it still relies on human curiosity to drive the process. The machine can surface possibilities, but only the person can decide what matters.

When I design an AI coach, I think of it as a partner in thought, closer to Douglas Engelbart’s idea of human-computer partnership than to a substitute employee. The coach asks questions, provides scaffolding, and amplifies creativity. It does not replace the messy, interpretive work that defines human intelligence.

A More Human Kind of Intelligence

The deeper lesson of the doorman fallacy is that intelligence is not a property of isolated systems but of relationships. The doorman’s value emerges in the interplay between person and place, gesture and response. The same is true for AI. Detached from human context, it becomes thin and mechanical. Driven by human purpose, it becomes powerful and humane.

Every generation of innovation faces this tension. The industrial revolution promised to free us from labor but often stripped away craftsmanship. The digital revolution promises connection but frequently delivers distraction. Now the AI revolution promises efficiency, but unless we are careful, it may erode the very qualities that make work worth doing.

As we rush to install the next generation of technological “automatic doors,” let us remember the person who once stood beside them. Not out of nostalgia but because the future belongs to those who still know how to welcome others in.

Read More

AI & ML, Commentary

Radar