Empowered Product Teams is another gem of a post from Marty Cagan. This part stood out to me:

In most companies, technology teams exist “to serve the business.” That is very often the literal phrase you will hear. But even if they aren’t explicit about it, the different parts of the business end up driving what is actually built by the technology teams.

However, in contrast, in strong product organizations, teams exist for a very different purpose. They exist “to serve the customers, in ways that meet the needs of the business.”

The distinction is subtle, but important. If you only serve “the business”, you’re going to make decisions without asking whether something is user-hostile or not (see, for example, scroll-jacking, or Twitter’s tendency to “forget” that you prefer a timeline that shows latest tweets). Bringing customer needs into any conversation about business needs is the way to build something that’s profitable and sustainable.

A lot of words are being written about AI and machine learning these days, so it’s sometimes hard to know what to pay attention to. M.C. Elish and danah boyd’s Don’t Believe Every AI You See is one of those essays that I would consider essential reading on the topic. On the ethics of artificial intelligence:

When we consider the ethical dimensions of AI deployments, in nearly every instance the imagined capacity of a technology does not match up with current reality. As a result, public conversations about ethics and AI often focus on hypothetical extremes, like whether or not an AI system might kill someone, rather than current ethical dilemmas that need to be faced here and now. The real questions of AI ethics sit in the mundane rather than the spectacular. They emerge at the intersections between a technology and the social context of everyday life, including how small decisions in the design and implementation of AI can create ripple effects with unintended consequences.

And on the supposed “neutrality” of machines:

[There is] a prevailing rhetoric around AI and machine learning, which presents artificial intelligence as the apex of efficiency, insight, and disinterested analysis. And yet, AI is not, and will not be, perfect. To think of it as such obscures the fact that AI technologies are the products of particular decisions made by people within complex organizations. AI technologies are never neutral and always encode specific social values.

As Kevin Kelly also pointed out years ago in his book What Technology Wants, technology is never neutral. It possesses the collective values of its creators. And that’s where things so often go wrong. A great resource on this topic is Sara Wachter-Boettcher’s book Technically Wrong: Sexist Apps, Biased Algorithms, and Other Threats of Toxic Tech.

In Filling the Silence with Digital Noise, Kate Moran and Kim Flaherty share some research-based findings on how people use digital background noise to make sure it’s never quiet around them:

While many participants reported feeling the need to have some sort of audio in the background during their silent moments, others reported a more intense version of this phenomenon: the need to fill all the empty moments in their lives with some activity to avoid boredom or downtime. This behavior fills the ‘silence’ in a figurative way — people use their devices to keep their minds constantly occupied.

I read this article with interest, because I also do this—albeit for a different reason. I have a condition called tinnitus, which is a consistent ringing in the ears. There is no cure for it—the only way to deal with it is to learn to manage and be ok with it. For those of us who suffer from tinnitus, silence is torture. Because there is no silence. Your only choices are (1) the sounds/noises you put on around you, or (2) a loud ringing in your head that comes from nowhere and everywhere and never goes away.

Guess which option we usually go for…

The Netflix Data War is a very interesting post about the internal discussions that happen between Netflix’s content team and their data team. In short, data isn’t everything:

[…] in almost any decision-making situation involving data, there is some non-zero percentage of the process that involves “gut”. The reason is because not all information about a process can be incorporated into a data analysis, and it’s important for data analysts to realize that.

That’s an important point to reflect on. It doesn’t matter how complete a data model is. There are some variables that simply cannot be included, because it’s impossible to know what should be included in any particular model.

Apart from that, it’s also just a fascinating look at the internal workings of Netflix.

The Doist team makes some great points in their article Best Practices for Building and Managing a Remote Team, including something we’re embracing very strongly at Wildbit as well:

Managing a remote team effectively is not about monitoring the amount of time your team members spend online (in fact, that’s a great way to kill employee autonomy and motivation). It’s about building and supporting a team that doesn’t need to be micromanaged in the first place.

We wrote more about our approach to remote work here.

In The ‘Future Book’ Is Here, but It’s Not What We Expected, Craig Mod writes that after years of believing books will fundamentally change in the digital age, it’s simply not happening:

I think we can agree that, in an age of infinite distraction, one of the strongest assets of a “book” as a book is its singular, sustained, distraction-free, blissfully immutable voice.

What has changed, instead, is how books are created:

Instead, technology changed everything that enables a book, fomenting a quiet revolution. Funding, printing, fulfillment, community-building—everything leading up to and supporting a book has shifted meaningfully, even if the containers haven’t. Perhaps the form and interactivity of what we consider a “standard book” will change in the future, as screens become as cheap and durable as paper. But the books made today, held in our hands, digital or print, are Future Books, unfuturistic and inert may they seem.

Or, more succinctly:

Our Future Book is composed of email, tweets, YouTube videos, mailing lists, crowdfunding campaigns, PDF to .mobi converters, Amazon warehouses, and a surge of hyper-affordable offset printers in places like Hong Kong.