Facebook’s “On This Day” feature has always felt really strange to me. It’s an algorithm that’s aware of its weirdness, hence the almost apologetic “We care about you and the memories you share here” message that surrounds it. As if it knows it’s bound to get it wrong and show you something you don’t want to be reminded of.

Leigh Alexander provides an interesting perspective on that feature and our social media “memories” in What Facebook’s On This Day shows about the fragility of our online lives:

Part of the palpable dissonance comes from the fact that many of our posts were never intended to become “memories” in the first place. An important question gets raised here: what’s the purpose of all this “content” we serve to platforms, if it’s useless in constructing a remotely valuable history of ourselves? Are we creating anything that’s built to last, that’s worth reflecting on, or have social media platforms led us to prize only the thoughts of the moment? […]

We generally think of social media as a tool to make grand announcements and to document important times, but just as often – if not more – it’s just a tin can phone, an avenue by which to toss banal witterings into an uncaring universe. Rather, it’s a form of thinking out loud, of asserting a moment for ourselves on to the noisy face of the world.

Despite multiple attempts I still don’t understand how Snapchat works, but from what I understand from the Young People this is a big reason for its appeal. There isn’t an expectation that something you post on Snapchat has to be profound enough to become a permanent memory. As one of my friends Simon¹ put it: Snapchat is there to “Share (not remember) moments.” (Side note—if you haven’t done so yet, please read Ben Rosen’s My Little Sister Taught Me How To “Snapchat Like The Teens”. It is absolutely bonkers.)

So Alexander’s point is an interesting one: how do we take control of our online memories? It’s not possible to know for sure, in a moment, if we’re experiencing something we’d like to remember forever. Maybe the best solution is to keep it the way it’s always been: rely on our brains to remind us of things. We can always then dig up those old photos ourselves—without the help of an algorithm—if we really want to relive the moment.

There were some interesting Netflix articles over the past week or so. First, Nathan McAlone writes that Netflix wants to ditch 5-star ratings:

The problem, [CPO Neil] Hunt tells Business Insider, is that people subconsciously try to be critics. When they rate a movie or show from one to five stars, they fall into trying to objectively assess the “quality,” instead of basing the stars on how much “enjoyment” they got out of it.

Here’s an example. Let’s say you had fun watching a crappy movie, but still gave it a two-star rating because you know it’s not a “good” film. That presents Netflix with a problem. The system thinks you hated the movie.

I think embarrassment plays a part in this as well. Even when ratings are private, we’re worried that word might get out. For example, I’d be happy if all my Netflix recommendations consist of “Movies similar to Battleship”, but I certainly don’t want any of you to know how much I liked that terrible movie.

Related to this, McAlone also wrote about Netflix’s most important metric:

That means that the most important economic metric for Netflix is how much a TV show or movie contributes to Netflix’s ability to sign up and retain customers.

The problem is that the current star rating system doesn’t give them that metric because it’s associated with “quality”, not “enjoyment”. So I might rate Out of Africa 5 stars because I objective know it’s a good movie, but if Netflix starts recommending “Boring movies with Meryl Streep” to me, I’m out of there.

Netflix has a very difficult product design challenge ahead of them. They have to change an established user mental model (“stars=quality”) to something different (“tell us what you enjoy watching”) that will help them provide a better and more compelling service.

Matthew Malady has an interesting take on the “I went offline and lived to talk about it” essay. In The Useless Agony of Going Offline he discusses one of the biggest benefits of technology—knowing more things:

At the end of the experiment, I wasn’t dying to get my phone back or to access Facebook. I just wanted to get back to being better informed. My devices and the Internet, as much as they are sometimes annoying and frustrating and overflowing with knuckleheads, help me to do that. If getting outside and taking walks, or sitting in silence, or walking dogs, or talking with loved ones on the phone got me to that same place, I’d be more than happy to change things up.

This is similar to Clive Thompson’s main thesis in his excellent book Smarter Than You Think. Our ability to gain knowledge and collaborate more effectively makes all the negative aspects of being online worth the effort.

This is an interesting story on the topic of algorithmic empathy¹. In Hospitals Employ Email ‘Empathy’ To Help Doctors And Patients Keep In Touch Barbara Feder Ostrov discusses a program that sends patients automated emails to ask them how they’re doing:

Doctors can send daily emails with information timed to milestones in surgery prep and recovery and ask patients or caregivers for feedback on specific issues patients may face during recovery.

The doctors may write their own email scripts, as Newport Orthopedics’ physicians did, or use the company’s suggested content. An online dashboard helps doctors and administrators keep track of which patients are doing well and who might need more follow-up care. Patients can also communicate with office staff about medications and office visits. Their responses to daily emails can trigger a call from the doctor’s office.

A patient might see this message: “How are you? Let me know so I can make sure you’re okay. I have four questions for you today.”

The program has had some promising results, but I’d be interested to know if patients are aware that the messages are automated. To put it another way, is it ethical for doctors to send automated, health-related messages that look like they’re individually crafted?

Erika Hall’s The Secret Cost of Research is a great explanation of why research is essential for products to succeed:

The reason design projects that neglect research fail isn’t because of a lack of knowledge. It’s because of a lack of shared knowledge. Creating something of any complexity generally requires several different people with different backgrounds and different priorities to collaborate on a goal. If you don’t go through an initial research process with your team, if you just get down to designing without examining your assumptions, you may think your individual views line up much more than they do. Poorly distributed knowledge is barely more useful than no knowledge at all.

I can definitely attest to this. It’s exactly why I’m such a big fan of Product Discovery:

This phase always—without fail—produces insights the team finds incredibly valuable. Startups gain clarity about what to say “yes” and “no” to in their product, and large corporations learn how to go beyond customer-centricity buzzwords and discover which benefits they should be selling to their users. As just one of many examples, I was once in a workshop that revealed the executives had a completely different vision for the company than the designers and developers. It was an awkward two hours, but in the end they agreed on the tough but correct decision to suspend their e-commerce plans until some of the content areas on the site had been sorted out. It’s great to see a statement of purpose emerge from these sessions—one that finally gets an organization to agree on what the product’s focus should be.

It’s pretty remarkable how different people’s visions for a product can be, especially since there’s such a simple two-step program to fix that:

1. Understand user needs and business goals.
2. Talk about it, together.

In Jim Brikman’s post A Minimum Viable Product Is Not a Product, It’s a Process he explains the real purpose of following an MVP approach:

An MVP is a process that you repeat over and over again: Identify your riskiest assumption, find the smallest possible experiment to test that assumption, and use the results of the experiment to course correct.

When you build a product, you make many assumptions. You assume you know what users are looking for, how the design should work, what marketing strategy to use, what architecture will work most efficiently, which monetization strategy will make it sustainable, and which laws and regulations you have to comply with. No matter how good you are, some of your assumptions will be wrong. The problem is, you don’t know which ones.

And the crux:

The only way to find that out—the only way to test your assumptions—is to put your product in front of real users as quickly as possible. And when you do, you will often find that you have to go back to the drawing board. In fact, you’ll have to go back to the drawing board not just once, but over and over again.

This is one of the major problems with MVP-thinking as I see it in many organizations today. For many product managers MVP is unfortunately not a learning process, but just a fancy way of saying “v1”. And as we all know, the biggest lie in the enterprise world is “v1”. There’s never a v2. So many hide behind the “MVP” moniker to obscure the fact that they just want to get a thing out the door and move on. We’d do well to remind our teams that the real purpose of an MVP is to learn, not to complete.

In a journal article for Computational Culture Erica Robles-Anderson and Patrik Svensson presents a scholarly critique of PowerPoint, and it is fantastic. It’s long and in-depth and the rare academic article that is a joy to read. From the conclusion of “One Damn Slide After Another”: PowerPoint at Every Occasion for Speech:

PowerPoint is just one example of the oft-overlooked conditioning of knowledge production. The software profoundly shaped basic social expectations, technical conditions, and architectural pre-requisites for speech yet it was uncritically absorbed in nearly every quarter. PowerPoint does not zoom. It does not allow spontaneous comparisons. It does not accommodate several screens, multiple threads, or distributed live collaborations. It makes the analytic move of systematic comparison, so prevalent in late nineteenth and early twentieth century information presentations, extremely difficult to make. Moreover, its expansion has meant that once distinct situations have become more alike. Meetings, sermons, lectures, and talks increasingly employ the technics of commercial demonstration. Twenty-first century occasions for speech are structured by a platform that enforces the paradigm of one-slide-at-a-time.

Jeremy Keith writes about the onboarding process of the site The Session in his post Words of welcome. He shows a series of screen shots of simple messages that teaches users how to be good citizens on the site. Keith closes with this:

No intricate JavaScript; no smooth animations; just some words on a screen encouraging a human connection.

Design words to live by.