- Information architecture isn’t just about making it possible for people to navigate an information environment; it’s also about educating them about their choices, and why they matter. Thoughts on a strategic IA challenge. (Plus, some followup.)
- Brad Stone’s history of Amazon.com, The Everything Store has a great illustration of the lack of a trust in a client-designer relationship. Plus, my notes on The Everything Store overall — TL;DR: I recommend it.
- You can disrupt an industry for one of two reasons: you’re either looking to create value or to extract value. The latter is always a short-term play.
- “The internet was never just a technology or an engine of globalization. It was, at its core, an idea.” That idea is now threatened by the rise of digital nationalism. (WSJ subscription required.)
- Denmark appointed the first ambassador to the tech industry: “These companies have moved from being companies with commercial interests to actually becoming de facto foreign policy actors.”
- On the rise of personal CRM apps, which let you manage and optimize your friendships.
- The Harvard Business Review has a good overview of how bias creeps into AI algorithms and what to do about it.
- One of the challenges of aging is learning how to acquire wisdom without becoming attached to the superficial trappings of the past.
- UX Frameworks, “A resource to find and share frameworks for design research, synthesis, and ideation.”
- An amazing interactive visualization of the history of philosophy.
On the afternoon of January 27, 1967, the crew of Apollo 1 — astronauts Virgil “Gus” Grissom, Ed White, and Roger Chaffee — were killed in a horrific accident. The men were sitting inside the sealed command module of their spaceship during a launch simulation when a fire broke out. Fed by the pure oxygen environment inside the cabin, the conflagration spread quickly. The astronauts didn’t have a chance.
The Monday morning after the accident, NASA Flight Director Gene Kranz — the person responsible for coordinating Flight Control during a mission — addressed his team. This is what he told them:
When a new version of macOS comes out, I usually upgrade my computer relatively soon. I like having access to the latest features, and significant macOS release upgrades are generally trouble-free. That hasn’t been the case with the newest version, Catalina. The trouble stems from the fact that Catalina doesn’t run 32-bit applications. While most major software in the system is now 64-bits, there are still some stragglers — especially legacy apps and drivers that haven’t been (and likely won’t be) upgraded.
That’s why I waited longer than usual before upgrading to Catalina: there was one application in my system that was 32-bits, the driver for my Fujitsu ScanSnap S300M scanner. I knew this driver was incompatible because every time I launched it (under Mojave, the previous version of macOS), I’d get a warning saying that the app would not run in the future. (Here’s a way to learn which apps won’t work: under the Apple menu, go to
About this Mac >
System Report… >
Without this driver, the scanner is useless — even though the hardware is perfectly functional. This device is an important part of my workflow; I use it every other week to digitize most of my paper documents and correspondence. Fujitsu no longer sells this model and has no plans to release 64-bit drivers. So I was stuck. I had two choices: I could hold off on upgrading the operating system (for a while), or I could buy a new scanner. I didn’t like either option. Sooner or later, I’d have to upgrade the OS. And as I said, the scanner itself was in perfect condition; I didn’t need a new one. What to do?
It turns out there was a third option: look for an alternative driver. I found a third-party application called VueScan that works with a range of scanners, including the S300M. It’s been working well for me; the only downside is that it’s a bit slower than Fujitsu’s driver. But given my use of the scanner, it’s not slow enough to merit buying a new device.
Thus far, Catalina has been great. I’m especially enjoying the new Sidecar feature, which allows me to use my iPad as a second screen when I’m on the go. So far, everything is working for me — including my old scanner. The lesson: if you’re contemplating upgrading to Catalina, but are holding back because of legacy software on your system, consider looking for alternatives.
The essence of abstraction in software is that it hides implementation. The implementation is in some ways the opposite of the abstraction; where the abstraction is the gloss that describes how something can be used and what it will do, the implementation is the part under the covers that describes how it will work. If the gas pedal and the steering wheel are the abstraction, then the engine, power train, and steering assembly are the implementation.
Designers often focus on this abstraction of the system — the stuff users deal with. As a result, we spend a lot of cycles understanding users. But for the interface to be any good, designers must also understand the implementation — the system’s key elements, how they interact with each other, its processes, regulation mechanisms, etc.
Sometimes, as with a new (and perhaps unprecedented) system, this implementation itself is in flux, evolving subject to the system’s goals and the needs of the people who will interact with the system. That is, it’s not all front-end: the implementation is part of the design remit; both the implementation and its abstraction are the object of design.
The architecture of information:
Starting with macOS Catalina, Apple deprecated its long-standing iTunes media management app. In its stead, we got three new applications: Music.app, Podcasts.app, and TV.app.
I just upgraded my laptop to Catalina. After cleaning up some random post-upgrade changes, I set out to do some work. Before starting, I thought I’d get some music going in the background. So I did what I always do to play music on the computer: I typed
CMD-space to open the system Spotlight search field and then
itun-RETURN. This sequence of keystrokes usually launches the iTunes application. I’ve done it so many times I now do it reflexively, without even looking at what the system is doing.
Which is why I was confused when I saw an unfamiliar app welcome dialog pop up. I knew iTunes had changed in this release, but the dialog wasn’t what I expected: I was onboarding onto the Podcasts app. My first thought was that perhaps the Music app opened with a description of the new apps that replaced previous iTunes functionality so that I wouldn’t be lost entirely. But the welcome dialog said nothing about Music or TV — it was all about Podcasts. When I closed it, I realized I had actually opened the Podcasts app. I was baffled.
So I typed
CMD-space again and then the word
James Manyika, Jake Silberg, and Brittany Presten writing for the Harvard Business Review:
AI can help identify and reduce the impact of human biases, but it can also make the problem worse by baking in and deploying biases at scale in sensitive application areas.
The phrase “artificial intelligence” is leading us astray. For some folks, it’s become a type of magical incantation that promises to solve all sorts of problems. Much of what goes by AI today isn’t magic — or intelligence, really; it’s dynamic applied statistics. As such, “AI” is highly subject to the data being analyzed and the structure of that data. Garbage in, garbage out.
It’s important for business leaders to learn about how AI works. The HBR post offers a good summary of the issues and practical recommendations for leaders looking to make better decisions when implementing AI-informed systems — which we all should be:
Bias is all of our responsibility. It hurts those discriminated against, of course, and it also hurts everyone by reducing people’s ability to participate in the economy and society. It reduces the potential of AI for business and society by encouraging mistrust and producing distorted results. Business and organizational leaders need to ensure that the AI systems they use improve on human decision-making, and they have a responsibility to encourage progress on research and standards that will reduce bias in AI.
There was a time, many years ago, when I used only one computer for my day-to-day work. It was a laptop, and it was with me most of the time, at least during the workday. I accessed my digital information exclusively on this device: email, files, etc. I kept my calendar on a (paper-based) Franklin Planner. For mobile communications, I used a beeper. I told you it was a long time ago — a simpler time.
Then a new device came on the market, the Palm Pilot:
It was like the paper planner, only digital: it could store your calendar, address book, to-dos, and such. You’d write into it using a gesture alphabet called Graffiti, which you had to learn so you could use the device. But most importantly, you could also sync it with your computer’s calendar, address book, etc. You did this by sitting it on a cradle that came with the device and pushing a button. You connected the cradle to the computer using a serial cable and installed an app on your computer to manage communications between the devices. It was crude and complex, and I loved it. The prospect of having my personal information in digital format with me anywhere was very compelling.
Organizations never exist on their own; they’re part of an ecosystem, a web of relationships that make it possible for things to get done. Your decisions affect the ecosystem, and the decisions of others affect you.
This has always been so, of course, but the internet has made ecosystems more visible and susceptible to disruption. Transacting has become easier and faster. Changes are often immediate, have more impact, and lead to greater network effects. The balance of power shifts: organizations can leverage connections to go straight to consumers. Alternatively, intermediaries can create new roles for themselves, becoming purveyors of information as much as goods.
There are great opportunities for organizations that can affect system dynamics. But there are also risks — to themselves and to the ecosystem. For example, in a recent interview with economist Tyler Cowen, music critic Ted Gioia talked about the impact internet streaming has had on the music industry:
The Everything Store: Jeff Bezos and the Age of Amazon
By Brad Stone
Hachette Publishing, 2013
In a 2013 interview, Charlie Rose asked Amazon’s founder, Jeff Bezos, to define his company. “I would define Amazon,” he replied, “by our big ideas, which are customer centricity, putting the customer at the center of everything we do, and invention.” The Everything Store traces the story of how those ideas — which have been at the core of Mr. Bezos’s vision for Amazon — created one of the great entrepreneurial success stories of our time and transformed the way we shop.
But customer-centricity isn’t the only value that has led to Amazon’s success. Ruthless execution — another central value, and one that the book doesn’t shirk from describing — has allowed Amazon to move faster, smarter, and more aggressively than its competitors. The company’s ability to move quickly has allowed it to exploit strategic advantages it gained due to thinking long-term, another central value.
Alas, Amazon’s relentless pursuit of customer satisfaction has often come at the expense of other actors in the ecosystem, especially employees and vendors. The company’s negotiators don’t aim for win-win, and work-life balance is anathema. The book describes a demanding environment that selects for a particular type of employee, one that’s fully committed to — and willing to make personal sacrifices for — the company: