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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 25, 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 previous resort on a windy nook in Chicago the place the entrance doorways shine like brass mirrors. Every morning, earlier than friends 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 by some means makes each traveler really feel like an everyday. To a price advisor, he’s a line merchandise. To the friends, he’s a part of the constructing’s ambiance.

    When administration put in automated doorways a couple of years in the past, the doorway turned quieter and cheaper, however not higher. Visitors not lingered to talk, taxis stopped much less usually, and the foyer felt colder. The automation improved the resort’s backside line however not its character.

    This story captures what British promoting government Rory Sutherland calls “The Doorman Fallacy,” the behavior of mistaking seen duties for everything of a task. 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 which means.

    The Lesson Behind the Metaphor

    Sutherland expanded on the thought in his 2019 guide Alchemy, arguing that logic alone can lead organizations astray. We usually undervalue the intangible elements 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 perform. He welcomes friends, conveys status, and creates a way of security.

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

    The Doorman within the Age of AI

    In a current article for The Dialog, Gediminas Lipnickas of the College of South Australia argues that many corporations are repeating the identical mistake with synthetic intelligence. He warns folks in opposition to the tendency to interchange folks as a result of know-how 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 prospects 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 circumstances reveal the identical sample: Automation succeeds technically however fails experientially. It’s the digital model of putting in an automated door and questioning why the foyer feels empty.

    Measuring the Improper 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 averted, as a result of they’re straightforward to trace. However they miss the essence of the work: problem-solving, reassurance, and quiet help.

    Once we optimize for seen throughput as a substitute of invisible worth, we train everybody to chase effectivity on the expense of which means. A talented agent doesn’t simply resolve a criticism; they interpret tone and calm frustration. A nurse doesn’t merely file vitals; they discover hesitation that no sensor can catch. A line cook dinner doesn’t simply fill orders; they preserve 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 deal with interplay, problem-solving, and help, not simply quantity and velocity. In any other case, we threat automating away the very elements of labor that make it worthwhile.

    Effectivity versus empathy

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

    What seems like inefficiency on paper is commonly resilience in apply. 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, supply construction, and speed up studying, however it nonetheless depends on human curiosity to drive the method. The machine can floor prospects, however solely the particular person can resolve what issues.

    After 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, gives scaffolding, and amplifies creativity. It doesn’t change the messy, interpretive work that defines human intelligence.

    A Extra Human Type of Intelligence

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

    Each technology of innovation faces this stress. The economic revolution promised to free us from labor however usually stripped away craftsmanship. The digital revolution guarantees connection however steadily delivers distraction. Now the AI revolution guarantees effectivity, however except we’re cautious, it could erode the very qualities that make work price doing.

    As we rush to put in the following technology of technological “automated doorways,” allow us to bear in mind the one who as soon as stood beside them. Not out of nostalgia however as a result of the long run belongs to those that nonetheless know easy methods to welcome others in.

    You will discover 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 reside 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 net 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 assets on O’Reilly.

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