Tag Archives: automation

Before Someone Signs Off on the Robots

Have you seen the new robotic parking at Gatwick? It looks quite cool.

It works like this: you drive up into a garage bay, get out, scan a code, take your luggage and wander off to get on a bus to the terminal. Meanwhile, as you bump along the perimeter roads on your way to Pret a Manger and a surly greeting at security, your car is being lifted by a robot and shuffled into a parking space “fully autonomously” and presumably without the clattering of doors into each other or a young lad with a vape doing power slides in a field.

It reminded me of another experience in innovation I recently revisited: Pod Parking at Heathrow.

Ten years or so ago I tried it on a business trip to Scotland. A pre-dawn drop-off in a largely empty car park (back then it was still newish and posh enough to feel business-only), followed by the novelty of a solo ride in a pod to the terminal.

Returning this year with my son on a ski trip, it was slightly less fun.

A busy car park hunting for a space. A long walk with bags to the station. Then the ignominy of sharing a pod with other people similarly bedecked with ski equipment and making inane small talk before setting off on a circuitous, stop-start loop towards the airport.

Notwithstanding the fact that I’m now in my late 40s, travelling with rather more family paraphernalia and rather less wide-eyed consultant enthusiasm for clever infrastructure, the whole thing instead felt like a technically neat attempt to solve the wrong problem.

But before I explain why, let’s return to Gatwick’s robots.

Apparently they’re constrained a little. A fact mentioned almost in passing in the voiceover of what I assume was a press video: there are limits on vehicle weight, wheel size and wheelbase.

Plenty of people wouldn’t think twice about that. I did.

The service is marketed as a premium solution and has a five-day minimum stay. So it seems reasonable to assume a fair proportion of customers will arrive in large, expensive family cars.

Let’s say you own an i7, a Volvo EX90 or perhaps you’ve ordered the Range Rover EV. None of those can use it.

Already this premium, cutting-edge parking solution can’t accommodate a fairly representative selection of premium, cutting-edge family cars. Edge cases, perhaps, but also edge cases sitting at the leading edge of a market that is getting heavier, longer and increasingly fond of enormous wheels. The 21-inch wheel restriction feels particularly egregious.

Of course, the robots can presumably be enhanced. But significant capital has already been sunk into the system. Does the machinery now keep pace with the cars, or do customers eventually discover that their apparently ordinary SUV has fallen outside the parameters of the futuristic car park?

In any event, I started wondering whether robotic parking is actually solving a consumer problem. Or, more accurately, whether it is solving the right consumer problem.

From Gatwick’s point of view it may make perfect sense. Cars can be packed closer together because people don’t need to open the doors. You need less circulation space. There may be fewer staff movements. Less risk of somebody clipping a wing mirror or rearranging the side of a Cayenne against a concrete pillar. Potentially you get substantially more parking capacity out of an extremely valuable piece of land. Those benefits are undeniable.

But you’ll note they are largely benefits to the airport and parking operator. The customer has a rather different problem.

They want to arrive, find where they need to go without circling three times, get kids and bags out, leave the car somewhere they trust is secure, and ultimately reach departures with the minimum possible faff.

Preferably, too, without standing in a bus shelter in horizontal sleet debating whether the matrix display’s ‘6 mins’ has in fact changed at all in ten minutes.

Seen that way, the robot is doing something very impressive several stages after the customer has stopped caring. Once I’ve walked away from the car, I don’t really mind how it gets parked. A robot can carry it above its head while bleeping like a jolly droid. My attention has moved on to the next thing: where is the bus, how long will it take, will there be space for the bags, and how long do I need to stand next to the pseudo-Love Island contestant in coordinated loungewear before I’m actually inside the terminal?

Which brings me back to Heathrow’s pods. The engineering proposition is, or at least was, immediately seductive. Small autonomous vehicles, ostensibly on demand, with a dedicated congestion-free route to the terminal. The PowerPoint similarly likely wrote itself. Judged narrowly as a transit system, it’s evidently clever.

But the judgement should be from the passenger’s experience. Here the journey begins not when the pod moves but when you stop your car: park. Extract luggage. Work out the nearest station. Walk in the rain. Wait. Board. Travel. Sometimes stop — “We will resume your journey shortly”. Get out. Walk again with luggage. Find the terminal entrance.

That is the system and, when closely observed, some fairly boring alternatives instead appear surprisingly competitive.

Put more bus stops alongside parking rows. Increase their visibility and directional signage. Cover the walking routes (maybe even with solar panels). Tell people exactly when the next bus will arrive. Run enough buses that nobody really needs to think about the timetable at all.

And make the bus itself good. Warm in February, properly air-conditioned in August. Comfortable seats. Proper luggage racks designed around what people actually take to airports rather than a grudging shelf above the wheel arch. A driver who says hello, helps someone with a heavy case and knows where they’re going. Give the thing a bit of design attention.

None of that is technologically remarkable, but I suspect the combined effect on the journey could be disproportionately positive.

You’re unlikely to find an architectural visualisation of a man standing happily beneath a bus shelter on the homepage of Dezeen. Or a breathless article about wayfinding signage in Monocle.

But it may produce a better experience.

Perhaps, too, there is another behavioural wrinkle. Five minutes of waiting for something you cannot quite predict can feel substantially worse than eight minutes of movement towards your destination. Walking, as many have observed, gives you a sense of progress and control.

Although luggage complicates the calculation.

A 400-metre walk without luggage can feel like useful progress. The same 400 metres dragging two cases, a ski bag and a slightly recalcitrant child across coarse tarmac is not quite the same behavioural proposition. At some point movement ceases to feel like autonomy and simply becomes work.

Which is why shaving two minutes from the vehicle journey may be almost worthless if the passenger has had to drag their luggage an extra 400 metres to reach it. A beautifully optimised autonomous transit system can quite easily lose to a diesel bus simply because the diesel bus stops adjacent to your car.

So often, sophisticated experience design goes slightly wrong along such lines. Organisations naturally optimise the things they can see, measure and control. In this case: vehicles per hectare, average transfer time, labour requirement, throughput, number of drivers, perhaps even CO₂. All sensible metrics.

People, rather inconveniently, experience the gaps between them. They experience the anxiety of where to go. The extra walk nobody included in the journey-time calculation. The toddler who needs a wee. The suitcase with a wobbly wheel. The bus that pulls away just as you approach the stop. Such things are difficult to measure, don’t align neatly to one system or department and so disappear from optimisation models altogether.

So when we end up with technically excellent things that somehow feel worse, I wonder if there is also an element of theatre at play.

Airports have always been preternaturally good environments for conspicuous modernity. The driverless pods, biometric gates, robots and baggage systems, vast digital screens. They are signals, often at a national identity level, of investment, progress and future-facing willy-waving.

A covered walkway, even with solar panels, is not that. Neither is a bus stop being moved 80 metres. Yet either could improve more journeys, more often, for less money.

None of which is to denigrate the robots too much. They’re far from pointless and if Gatwick can materially increase parking capacity without tearing up more green fields, robotic parking may prove to be quite the investment. Judge it on density, operating cost, reliability and land use and the argument may be very strong. But then call it what it is: clever parking infrastructure.

The more useful question is simply whose problem we’re actually solving. Sometimes installing a fleet of robots that lets you cram more cars onto the same patch of land genuinely does improve the customer experience. Sometimes the customer would get rather more from a bus stop 80 metres nearer their car, an accurate countdown and a warm bus with somewhere sensible to put the cases. The difficult part of experience strategy is having the confidence to work out which before someone signs off on the robots.

AI: I used ChatGPT to tidy up some grammar and that, dear reader, is all.

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I went back to Uni. What I learned on my Human-AI Interaction course.

The bit that mattered was never the screen.

Take this example. You’re looking to buy a used car. You shortlist three cars and start nudging the finance up and down. Nothing dramatic, just enough to see what an additional £30 a month buys you. A slightly newer plate perhaps. Fewer miles. A bit more punch, or practicality.

Then you click through to a retailer. Your shortlist disappears. Your modelled finance examples disappear. You’re on a blank form, being asked questions your behaviour has already answered. Nothing failed in any obvious way. The system simply dropped the ball precisely at the point it needed to hang on to it.

That is still how a great deal of digital experience works.

You can now generate a respectable interface in seconds, in Figma Make or hell even Gemini. It’ll be clean, structured, and broadly acceptable. Enough hierarchy to feel coherent, enough restraint to avoid embarrassment. It looks like design, which is why people are getting carried away and, frankly, why people are being laid off.

There is too a growing belief that interfaces are becoming fluid. Instead of designing fixed screens, we define components and let agents assemble the right interface on demand. Ask for something, get a form. No navigation, no structure, just translate intent directly into interaction.

Concepts like this are gaining column inches, conference talks and LinkedIn views because they’re brief and intelligible. However, as soon as the interaction extends beyond that moment, the weaknesses become apparent. Context isn’t carried forward properly. Earlier decisions aren’t respected. The system produces something plausible but slightly off, and the user ends up repairing it, effectively doing the work we’d hoped to have eliminated. The surface has improved. The underlying behaviour hasn’t.

Over the past eight weeks, I’ve been working through a Human–Computer Interaction and AI course with the University of Cambridge (Advance Online), and it has been mildly uncomfortable in the way good things often are. It stripped things back to a version of UX that feels almost unfashionable: define the problem before you touch a solution; model the system in terms of what it actually does, not how it looks; decide where control sits between human and machine and how that moves about; draw a boundary and accept responsibility for what happens inside it; then prove the thing works rather than just assuming it does.

As I worked through the modules, it was charmingly familiar and obvious that none of this was new. It just hasn’t been particularly visible for a while. The industry has been busy polishing UI surfaces and calling it progress. AI hasn’t changed that per se, but has made the gap harder to ignore. You can now generate something that looks finished without having done any of the thinking that would make it hold together.

That’s also why a lot of current AI design work feels slightly misplaced, and why the obsession with UI product designers irritates me. There are people doing very good work on interfaces and component systems. Zander Whitehurst is one of them, and they look excellent. But that work sits downstream of where the real difficulty now is. You can refine the surface as much as you like; if the system doesn’t carry intent, it won’t survive contact with actual use.

The “democratisation of design” line doesn’t stand up to the faintest scrutiny. Sure, more people can produce interfaces, and there’s been a lifting of all boats in terms of aesthetics. That’s true. Almost none of those interfaces are grounded in any understanding of what the user is actually trying to do. They meet a baseline. They look competent. They solve very little.

What has been democratised is production.

The discipline that underpins it, the work of defining what matters, what to surface, what to hide, what to carry forward, and where the system should stop and ask, has not been automated. It has been skipped.

The shift to intent-based interaction makes that gap more obvious. You are no longer stepping through a process one action at a time. You state an outcome, and the system attempts to get you there. That changes the shape of the problem. The system has to interpret intent, apply constraints, decide what to do next, and show enough of its reasoning that you can tell whether it has misunderstood you. When it gets that wrong, it doesn’t look like a broken interface. It looks like a reasonable answer that doesn’t quite fit, which is both harder to spot and harder to recover from.

This is where the work is moving.

If interfaces can be assembled on demand, the value shifts into what sits behind them: how intent is captured, how memory is handled, what the system is allowed to assume, when it must ask, and how it behaves when it reaches the edge of its understanding.

Friction becomes part of that. For routine actions, speed is fine. For anything with consequence, removing every pause produces something that feels smooth and behaves carelessly. A system that never slows you down also never asks you to think.

There is a second effect that is easier to miss. If the system does more of the execution, the user does less of the thinking that used to go with it. Over time, that changes behaviour. Trade-offs become less visible. Assumptions go unchallenged. Outputs are accepted because they look plausible..

You end up with users who are comfortable approving things they don’t fully understand.

The risk here isn’t replacement. It’s avoidance. If the problem isn’t defined, if the constraints aren’t understood, if the system isn’t designed to carry intent across time, then the speed of output doesn’t help. It just produces more surface, faster, over the same unresolved issues.

That is already visible. The used car journey doesn’t fail because the interface is ugly. It fails because no one took responsibility for the whole. The same pattern is now being reproduced with better tools and more convincing output.

If that continues, the work doesn’t disappear.

It just gets left to the user.

AI: I used ChatGPT to tidy up some grammar and I used Gemini to pick some holes in the piece to strengthen the arguments.

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Time Returned, Time Resold

Rain-blurred motorway at dusk viewed through a windscreen; dashboard lights glow amber in an empty driver’s seat — a quiet image of autonomy and time unclaimed.
Autonomy promised freedom. Instead, it gave us metrics.

Every few years a new invention turns up promising to give us time back. The dishwasher did it, then the calendar app, now the self-driving car. Efficiency, they say, is liberation. But the minutes never come home. They’re quietly re-employed: answering messages that weren’t urgent until we saw them, scrolling through news we already half-read. We don’t get more time. It just comes back wearing a different outfit.

Design now speaks the intoxicating language of generosity. We’ll save you clicks. We’ll make it seamless. Lovely words, but they come with a tempo you didn’t choose. The system nudges, reminds, congratulates you on your streak. Even the oven chirps when it’s done pre-heating. Helpful, yes – in the way a personal trainer is helpful when all you wanted was a walk.

Efficiency was meant to hush the world, not make it chatter. Parcels update you mid-journey, cars suggest faster routes, TV apps interrupt the credits to make sure you don’t go off to bed just yet. You start to feel managed by your own apps and appliances. Is it me, or do they all sound slightly pleased with themselves?

Still, there is a deeper promise in all this autonomy. Because the best thing about a self-driving car isn’t speed, it’s permission. The choice to drive when you want to: for rhythm, for presence, for drivers like me who relish the satisfaction of line and camber, and to switch off when you don’t. The long crawl north to the Lakes. The dawn blast to the airport. The late-night, rain-spray-soaked slog home when you’d gladly hand over the wheel and let the motorway unspool while you exhale, watch the window-light flicker, maybe half-doze through an episode of something forgettable. Control should be optional, not constant.

That’s what the technology could be about: selective surrender or a quieter freedom. But for some unfathomable reason, the marketing and product design departments have decided autonomy is best packaged as constant optimisation. That means another dashboard app full of metrics and prompts and juanty reminders. We built cars clever enough to drive themselves, then gave them personalities that never stop talking.

Real luxury now isn’t speed but discretion: the right to decide how long something should take. To drive when you feel like driving. To look out of the window when you don’t. Technology can make both possible.

Convenience promised to return our hours, but mostly it’s taught us to account for them. Every minute feels spoken for. Perhaps the odd thing is how willingly we’ve agreed to it and the peculiar pleasure we take in shaving seconds off tasks we didn’t enjoy anyway.

Maybe the best thing a self-driving car could do is forget the ETA and let us forget, too.

AI: This piece was refined with AI, for the image prompt, tags, excerpt, and a little sub-editing. The ideas, references, and rhythm are mine.

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