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    Home»Machine Learning & Research»The Human Behind the Door – O’Reilly
    Machine Learning & Research

    The Human Behind the Door – O’Reilly

    Oliver ChambersBy Oliver ChambersJanuary 23, 2026No Comments6 Mins Read
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    The next article initially appeared on Mike Amundsen’s Substack Indicators from Our Futures Previous and is being republished right here with the writer’s permission.

    There’s an outdated lodge on a windy nook in Chicago the place the entrance doorways shine like brass mirrors. Every morning, earlier than visitors even attain the step, a tall man in a grey coat swings one open with quiet precision. He greets them by identify, gestures towards the elevator, and someway makes each traveler really feel like an everyday. To a price marketing consultant, he’s a line merchandise. To the visitors, he’s a part of the constructing’s environment.

    When administration put in computerized doorways a number of years in the past, the doorway turned quieter and cheaper, however not higher. Friends not lingered to talk, taxis stopped much less typically, and the foyer felt colder. The automation improved the lodge’s backside line however not its character.

    This story captures what British promoting govt Rory Sutherland calls “The Doorman Fallacy,” the behavior of mistaking seen duties for the whole lot of a job. On this brief video clarification, Sutherland factors out {that a} doorman does greater than open doorways. He represents security, care, and ceremony. His presence modifications how folks really feel about a spot. Take away him, and also you lower your expenses however lose that means.

    The Lesson Behind the Metaphor

    Sutherland expanded on the concept in his 2019 e-book Alchemy, arguing that logic alone can lead organizations astray. We sometimes undervalue the intangible components of human work as a result of they don’t match neatly right into a spreadsheet. For instance, the doorman appears redundant provided that you assume his job is merely mechanical. In fact, he performs a social and symbolic operate. He welcomes visitors, conveys status, and creates a way of security.

    In fact, this lesson extends nicely past accommodations. In enterprise after enterprise, human conduct is handled as inefficiency. The result’s thinner experiences, shallower relationships, and methods that look streamlined on paper however really feel hole in follow.

    The Doorman within the Age of AI

    In a latest article for The Dialog, Gediminas Lipnickas of the College of South Australia argues that many firms are repeating the identical mistake with synthetic intelligence. He warns folks in opposition to the tendency to interchange folks as a result of expertise can imitate their easiest duties whereas ignoring the judgment, empathy, and flexibility that outline the job.

    Lipnickas provides two examples.

    The Commonwealth Financial institution of Australia laid off 45 customer support brokers after rolling out a voice bot, then reversed the choice when it realized the staff weren’t redundant. They had been context interpreters, not simply telephone operators.

    Taco Bell launched AI voice ordering at drive-throughs to hurry up service, however clients complained of errors, confusion, and surreal exchanges with artificial voices. The corporate paused the rollout and conceded that human improvisation labored higher, particularly throughout busy durations.

    Each instances reveal the identical sample: Automation succeeds technically however fails experientially. It’s the digital model of putting in an computerized door and questioning why the foyer feels empty.

    Measuring the Fallacious Factor

    The doorman fallacy persists as a result of organizations preserve measuring solely what’s seen. Efficiency dashboards reward tidy numbers, calls answered, tickets closed, buyer contacts prevented, as a result of they’re simple to trace. However they miss the essence of the work: problem-solving, reassurance, and quiet assist.

    After we optimize for seen throughput as an alternative of invisible worth, we train everybody to chase effectivity on the expense of that means. A talented agent doesn’t simply resolve a criticism; they interpret tone and calm frustration. A nurse doesn’t merely document vitals; they discover hesitation that no sensor can catch. A line prepare dinner doesn’t simply fill orders; they keep the rhythm of a kitchen.

    The reply is to not cease measuring; it’s to do a greater job of measuring. Key outcomes ought to concentrate on interplay, problem-solving, and assist, not simply quantity and velocity. In any other case, we threat automating away the very components of labor that make it invaluable.

    Effectivity versus empathy

    Sutherland’s perception and Lipnickas’s warning meet on the similar level: When effectivity ignores empathy, methods break down. Automation works nicely for bounded, rule-based duties corresponding to knowledge entry, picture processing, or predictive upkeep. However as quickly as creativity, empathy, and artistic problem-solving enter the image, people stay indispensable.

    What seems to be like inefficiency on paper is usually resilience in follow. A doorman who pauses to talk with an everyday visitor might seem unproductive, but that second strengthens loyalty and popularity in methods no metric can present.

    Teaching, not changing

    That’s the reason my very own work has centered on utilizing AI as a coach or mentor, not as a employee. A well-designed AI coach can immediate reflection, provide construction, and speed up studying, but it surely nonetheless depends on human curiosity to drive the method. The machine can floor potentialities, however solely the individual can resolve what issues.

    Once I design an AI coach, I consider it as a associate in thought, nearer to Douglas Engelbart’s concept of human-computer partnership than to a substitute worker. The coach asks questions, supplies scaffolding, and amplifies creativity. It doesn’t change the messy, interpretive work that defines human intelligence.

    A Extra Human Sort of Intelligence

    The deeper lesson of the doorman fallacy is that intelligence shouldn’t be a property of remoted methods however of relationships. The doorman’s worth emerges within the interaction between individual and place, gesture and response. The identical is true for AI. Indifferent from human context, it turns into skinny and mechanical. Pushed by human function, it turns into highly effective and humane.

    Each era of innovation faces this pressure. The economic revolution promised to free us from labor however typically stripped away craftsmanship. The digital revolution guarantees connection however regularly delivers distraction. Now the AI revolution guarantees effectivity, however except we’re cautious, it might erode the very qualities that make work value doing.

    As we rush to put in the subsequent era of technological “computerized doorways,” allow us to keep in mind the one who as soon as stood beside them. Not out of nostalgia however as a result of the longer term belongs to those that nonetheless know how you can welcome others in.

    You’ll find out simply how Mike makes use of AI as an assistant by becoming a member of him on February 11 on the O’Reilly studying platform for his stay course AI-Pushed API Design. He’ll take you thru integrating AI-assisted automation into human-driven API design and leveraging AI instruments like ChatGPT to optimize the design, documentation, and testing of internet APIs. It’s free for O’Reilly members; register right here.

    Not a member?

    Join a 10-day free trial earlier than the occasion to attend—and discover all the opposite sources on O’Reilly.

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