I’m doing it right now. Every time I make my finger press down on one of these keys, it’s like a little instruction: “Computer, please insert the letter ‘r’ into the place where the cursor is.” 

When I take a picture with my smartphone, I’m giving the computer an instruction: “Computer, use your on-board camera to take a photo right now, using the same instructions (zoom, flash, etc.) that I’ve already given to the Camera app.” 

“Zoom in a little bit.” 

“Submit this form.”

“Scroll down.” 

“Send message.” 

We don’t really think about it when we feed these instructions to the computer. We just do it.

People don’t want a drill. They want a quarter-inch hole. 

The product design community loves this quote, but in reality it’s not quite right. We’re a little too preoccupied with the drilling process. People don’t particularly care about making quarter-inch holes. In fact, they’d skip it if they could. What they really want is the happiness they get when they look at a sentimental picture hanging on their wall.

It’s very easy for us to lose sight of why we’re using computers. It’s very easy for us to lose sight of the computer’s place in the world.

We don’t like to think about the computer’s place in the world because it is a boring one. Are you zoomed in 52.1% or 53.4%? Who cares? But that’s an actual job the computer is doing. You just don’t think about it. And it’s a good thing that you don’t have to think about it. That tiny job is one of the many thousands of little jobs the computer is (and has been) doing for you whenever you take a photo! That is computing at its best - saving or modifying millions of zeros and ones that you don’t have to think about in service to your meaningful, human end goal.

You should never have to think about lighting up pixel #13,423. You should have think about if you want to take a picture of your dog, and why or why not. 

People don’t want a quarter-inch hole. They want the happiness they get from a picture on their wall. 

We people feed instructions to computers because of things we have going on in our lives, things we are trying to accomplish, and we are using the computer to accomplish those things. 

“Computer people” often make the mistake of thinking that the computer is an end in itself, because to a computer person, it is! Computer people enjoy computers because they enjoy computers. It’s their hobby. It’s the same thing as how golf people enjoy golf because they like playing golf.

The difference between computers and golf, however, is that you’re not forced to play golf in order to function in society. Non-computer people are forced to use computers to function in daily life.

Computer people are prone to enjoying the process of drilling a quarter-inch hole. Computer people like a good challenge. Writing software code by hand is an example of an instruction that is difficult to give to the computer. For computer people, the difficulty gives them the challenge they’re seeking. It lets them sink more effort into their hobby. 

On the other hand, non-computer people wish they could avoid the process of drilling altogether. They want it to be as easy as possible to give the computer instructions. The instructions are the means to the end. This is the majority of people. For them, it’s a problem if it’s difficult to feed the computer instructions. That wastes their time and energy at the expense of their goal. 

I suspect that LLMs will go down in history primarily as an innovation in the easing of feeding instructions to computers. It’s in the name: “language models”. Language is the medium of communication. When a person is giving instructions to a computer, they’re communicating. “Computer, can you help me find this news article?”

What I see missing from the LLM companies’ thinking is the human end goals. “You should learn AI so that you can use AI more! Why? To use AI!” The Silicon Valley companies are making the same mistake computer people tend to make: they assume that using the computer is the end goal. It isn’t. Not for most people, at least.

Someday, there might be a business leader who dares to ask, “What if we centered our focus on what AI helps people accomplish in their daily lives?” Questions like this have been asked before. But lately, we’ve forgotten about them.

But I’ve come to realize that friction isn’t always a bad thing. In fact, it’s often a great thing.

In your pocket you carry a keychain, because you lock your door when you leave the house. That’s friction: you’re making it more difficult for a total stranger to easily walk into your house.

The reason you have to brake your car at a stop sign or a red light is also friction: you temporarily inconvenience yourself instead of mindlessly zooming through an intersection so that you minimize the chance of a collision. You get a benefit - safety - from this self-imposed friction.

Good friction confers benefits. You exercise (muscular friction) for the health benefits. You study (mental friction) for the educational benefits. You work (economic friction) for the monetary benefits.

When there’s too little friction in your life, you run the risk of losing out on the benefits that come with it. If you’re not careful, it might make you an under-developed, unhappy person. That’s a price too high to pay.

Next time you encounter something that’s “too easy”, ask yourself why is it so easy? Who might benefit from this being so easy? Should it be this easy? If it doesn’t need to be, how would you benefit from a little more healthy friction?

Transcript

There’s something about machine precision that’s unhuman. You can see it, hear it, and sense it. If something’s “too perfect” that really means it’s too precise, too machine-like.

The false negatives are also interesting. For example, personally, I sense this when I hear the world’s best a cappella groups perform. In unison, they hit every note so perfectly that, to me at least, it sounds like an AI. Isn’t that odd? It’s as if too much practice makes you seem less human.

I was watching a Texas Tech football game the other day. Their quarterback flashed a complex sequence of hand signals with such fluidity, it was obvious he was extremely well-rehearsed. This prompted the sports broadcasters to mention how he is often so well-prepared that people will comment that he’s like a robot. There it is again: so much practice that it seems less human.

We see the reverse of this is also true, that imperfections can make something seem human. When we look at a hand-written note, listen to a live amateur performance, look at a painting, or read a hand-painted sign, it’s the imperfections we’re picking up on that make it seem more human. If someone accidentally does something that a machine would never do - like forget to dot an i - we pick up on the humanness of that.

We humans are imperfect. In a sense, allowing imperfections to show through is a form of honesty. In another sense, our human imperfections are simply being filtered about by precise machines.

ChatGPT has a certain writing style that’s not quite human enough. As a result, the #3 app in the ChatGPT store (as of this writing) is a “humanizer” - an extension that attempts to make AI-generated writing sound more human. (As a funny aside, apparently one of the giveaways that some text has been generated by ChatGPT is the inclusion of an em dash. As a detail-oriented technologist, I had previously been using the HTML escape code for em dash, &emdash;, manually in my writing because I like the way the em dash looks. However, all the other humans who don’t know code, won’t do that. Most people just use “-“, because it’s on the QUERTY keyboard. I have since stopped using the em dash in my writing, because I don’t want my writing to be GPT-like.)

Making an AI seem more human turns out to be a difficult software problem to solve. For humans, however, all it requires is being yourself.

There’s lots of opportunities to make software likable too. 

Good experiences are often the result of software acting like a likable person.

I log in to an app and see a message that says, “Good afternoon, Edwin. You’ve got (3) new messages.” That’s helpful. That’s like a person who thoughtfully wants to keep you in the loop. Or, maybe I go to delete something and the interface lets me know once I delete the thing, that action can’t be undone. This is good to know. I’m glad to know that before I choose whether or not to delete. That’s like a person making sure you’re properly informed before you make an important decision.

A likable person…

• Wishes you well, and means it
• Cares about how you’re doing
• Listens
• Proactively offers to help you with things
• Gives you a heads up
• Waits until you’re ready
• Respects your privacy
• Keeps you in the loop

By contrast, bad experiences are often the result of building software that behaves like an unlikable person. 

If you open an app and it immediately badgers you with a popup full of irrelevant information, that’s like a person who rudely interrupts. Or, maybe you log in and see on the top of the screen, “Welcome Customer”. That’s like that guy who won’t bother to learn your name. 

A likable person does not…

• Give you vague or incomplete instructions
• Assume your preferences
• Bark orders
• Repeat the same phrase over and over again
• Creep on you
• Try to be funny when you’re upset 
• Leave you in the dark 
• Let you struggle without offering to help

The thing I find useful about this rule of thumb is that it’s easy to apply to almost anything. You can always ask, “How would a likable person handle this situation?” Asking this will steer you towards all kinds of great practices like feedback, visibility of system status, and error prevention. 

Ultimately, we like likable people. If a company wants us to like them over their competitors, they should be likable too.

Ed Zitron’s Where’s Your Ed At
A skeptical take on AI
wheresyoured.at

Figma’s Newsletter, Shortcut
Product updates from the Figma team
figma.com/blog/newsletter

Jakob Nielsen’s Substack, UX Tigers
Speculative futurism from Jakob Neilsen
uxtigers.com

Nielsen Norman Group Newsletter
UX and usability newsletter from NN/g
nngroup.com/articles/subscribe

One Useful Thing by Ethan Mollick
An optimistic take on AI
oneusefulthing.org

​Sketch Email Updates​​
Product updates from the Sketch team
sketch.com/newsletter

Smashing Magazine’s Email Newsletter
Front-end development newsletter by Smashing Magazine
smashingmagazine.com/the-smashing-newsletter

We know that we’re seeing a rise in mental health problems. The question is… what’s causing them? I’m not prepared to truly answer that question because I believe there’s still lots of research to do to before we figure that out. One intuition I have developed, however, is that junk information exists and it impacts us regularly. 

We have an intuitive sense of what happens to us if we consume too much junk food, but what about junk information? Are there really negative consequences if we consume certain information? If there are, what are they? I suspect that - just like with junk food - if you consume too much junk information, your health will suffer.

Perhaps a definition for junk information would be: content that seems informative or enriching but has been created in such a way that makes it grab a little too much of your attention, ultimately leading to health problems if consumed in large quantities.

The constructive thing about this line of thinking is that it makes the path forward clearer.

We need to:

1. Learn how to separate the nutritious information from the junk information, and
2. Fill the majority of our information diets with the nutritious kind

Some amount of junk information will be okay, as long as it’s held to an appropriate limit.

“It took generations to get nutrition labels on food; it took generations to get speed limits on roads and seat belts and air bags into cars. But food and transportation technology are safer because all of these are now in place. In the case of communications technology, we have just begun.”

-Sherry Turkle

I imagine in the future, we’ll all become much savvier in how we approach the information diet. As the saying goes, you are what you eat. Maybe it’s also true that you are what you read.

1. Searching
2. Stating
3. Fixing
4. Verifying

Searching

No matter the kind of problem you’re dealing with, you always begin by searching. You might look for something that’s obviously wrong. You might search the internet for something written by folks who’ve already solved the problem. You trace and triangulate. As you search, you follow the promising strands while ignoring the distracting ones. Of the four steps, searching is the most difficult and unpleasant for people because the search is often uncertain, unclear, and ambiguous. In a sense, it’s also the most important. It’s nearly impossible to solve a non-trivial problem without thoroughly exploring it first.

As the saying goes, no one trips and falls and accidentally replaces their air compressor. Okay, that’s not really a saying… I just made it up. But it should be a saying, because it’s true and it tells you something about the nature of problem solving. 

Stating

“A problem well stated is a problem half-solved.” -Charles Kettering

It’s of vital importance that once you believe you’ve completed your search and you’ve “found” the problem, you attempt to explain what the problem is. The problem must make enough sense to you for you to be able to explain it. You don’t need a total grasp on the problem, but you must be able to state it in a way that’s somewhat cogent. If you can’t, that’s a sign you’ve got more work to do before you understand it well enough to truly solve it. 

Fixing

Once you’ve found the problem and understand it well enough to state it, there’s some action you must take to fix it. It might require creativity on your part to think of the actions you could take. It might be a matter of stopping something you’ve been doing that’s created the problem. You will likely need to remove something, alter something, or add something that fundamentally alters the situation. There might be more than one legitimate way to fix the problem. At the end of the day, if you haven’t made any changes at all, there’s a good chance you haven’t solved the problem. 

The fix must fit your statement of the problem. It must fit into the theory that you’ve formed. If you can’t explain how your fix addresses the problem (as you’ve stated the problem), then there’s a much lower chance it’ll work as a solution. 

Verifying 

By the time you’ve found and applied the true fix, you’ve solved the problem, but you might not know it yet. If you go back to square one and take a look at the situation after you’ve applied the fix, you should be able to see that the problem is gone. The absence of the problem should correspond to the presence of your solution. You might need to get creative when thinking of ways to verify the fix. You might be able to temporarily remove the solution and see if the problem re-emerges. Or, you might have to be patient. Given enough time and creativity, there’s usually a way to prove you’ve fixed the problem.

When you write something, you need to do your initial research, especially if you don’t know much about the subject. The most important thing you must do (if the thing you’re writing is going to be any good) is consider your target audience. You must have something to say, but you must also understanding who is going to hear it. And you must incessantly cater your message to your audience in every step of the writing process. You brainstorm ideas. Then, you compose an outline. You decide what makes it in the outline and what will be left on the cutting room floor. You toss ideas around and massage the outline. Next, you compose a rough draft, which is inevitably garbage. Then comes a 2nd draft, and a 3rd. If you’re doing it right, your work gets markedly better with each draft. Then, there’s the process of editing. You take what you’ve put on the page and you apply a critical eye. You trim the fat and ask yourself, “What in the world was I thinking?” Mostly the good parts survive. Once you decide you’ve said what needs to be said, you arrive at a mature “final draft”. (Although it doesn’t feel final, because the work is never done. You have to declare it finished nevertheless.)

This is what the process of writing looks like.

The process of UX design is quite similar.

In UX, like in writing, you start with research. You must understand what needs to be done, for who, and why. You must understand your target audience if you’re going to be successful. (Although, we don’t call it a “target audience”; we call them “user personas”.) UX designers also brainstorm. Our low-fidelity wireframes are essentially outlines, as they serve the same purpose: moving things around and figuring out what goes where before sinking time into fleshing out the details. We also have “drafts”, although they go by another name: “iterations”. Then, there’s the process of editing. In UX design, most of the edits come from two places: first, from follow-up research with users where they reveal that something’s not making sense to them. (This is analogous to having someone else read your writing and give you feedback.) Second, you make edits when you do feasibility checks with the engineers. They must be able to actually build what you’ve designed. Perhaps this is analogous to a publisher reading your work and telling you what must change.

In reflecting on this, I’ve also made another realization: that a software user interface is a medium of communication in itself. When you write something, your medium is purely words. When you design a user experience, your medium is the interface: the incorporation of all the buttons, switches, pages, labels, links, and beeps.

And finally, another parallel: while you can make explicit the “steps” of writing (research, outline, rough draft…) and the “steps” of the UX process (empathize, define, ideate, prototype…), it’s very difficult to actually teach the process directly. Creative skills like these are sort of like life. As Kierkegaard put it, “life can only be understood backwards, but it must be lived forwards.” In hindsight, I’d have to agree that the five steps of Design Thinking do in fact resemble the steps you take in UX design. I see that now, looking back on it. But as a beginner, you can’t just formulaically go through the steps and come to a good result. It doesn’t work like that. There’s much more of an art to it, which requires in-the-moment judgment calls that can’t be formulaically prescribed.

The most effective way to learn UX, I think, is to continually practice the art of doing it, while in parallel continually refining your design judgement as you encounter examples of good design and bad design. Always take the time to think about what made a good design good and what made a bad design bad. Over time, you acquire the intuition necessary to make the on-the-spot judgements that you must infuse into every “step” of the design process.

The app allows you to choose your favorite teams and leagues, and then it gives you a simple, well-designed experience that shows you the scores and the live stats of relevant games. You can see textual representations of standings, box scores, and live play-by-plays, but there are no videos, no feeds to scroll through, and no articles. It’s just the pure essence of what the app claims to be: sports scores.

It brought me back to a former age, Apple under the leadership of Steve Jobs.

I felt a feeling of delight reminiscent of when the iPhone first came out. Back then, there was something delightful about having a decent camera on your phone plus the novel simplicity of the design. You could sense that Jobs actually cared about the experience you had using your phone. The proof of this was in the pudding. He was making a product that let you do things - simple things - you previously could not do, things that were self-evidently valuable to you.

It’s easy to understand the value of the Camera app. Or any number of other apps from that first launch: Notes, Books, Calculator, Calendar, Clock, Messages, and so on.

“What would I use this for?” was not a thought in the back of your mind. The thought was, “Wow, that’s great! I’d definitely use this.”

I got this feeling again the first time I used Apple Sports. Apple had truly removed the distractions from the experience of checking the score. Coming from other, more distracting sports apps with news feeds and endless content, it was a breath of fresh air. It delights me to know that I can check the score, definitely not get distracted, and then put the phone back down.

In a word, this is respectful. The experience is respecting my time and attention. And I am responding to it with delight and a better opinion of the company. Here I am, promoting their product without having been paid or incentivized to do so in any way, other than the fact that I am a customer who is satisfied with a product.

I imagine this is what Steve Jobs was going for all along.