Steven Levy, writing on Wired around 30 years ago on the rise of spreadsheets:

Increasingly, however, businessmen are not telling but letting their spreadsheets do the talking. Because a spreadsheet looks so authoritative – and it was done by a computer, wasn’t it? – the hypothetical models get accepted as gospel. The spreadsheet presentation is becoming both more commonplace and more sophisticated: not only the numbers but the formats of the sheets themselves are designed to make eloquent points. This use of spreadsheets has less to do with productivity or insightful analysis than with the art of persuasion. “People doing negotiations now sit down with spreadsheets,” Bob Frankston said. “When you’re trying to sell a car, the standard technique is to ask for the other person’s objections, and then argue them away. If two people are in front of a spreadsheet, and one says, ‘Well, the numbers say this,’ the other can’t say, ‘Yes, but there’s something I can’t quite point to.’”

The Baffler:

In a 2017 package titled Understanding People Through Music—Millennial Edition, Spotify (with help from “youth marketing and millennial research firm” Ypulse) set out to help advertisers better target millennial users by mood, emotion, and activity specifically. […]

Spotify specifically wants to be seen as a mood-boosting platform. In Spotify for Brands blog posts, the company routinely emphasizes how its own platform distinguishes itself from other streams of digital content, particularly because it gives marketers a chance to reach users through a medium that is widely seen as a “positive enhancer”: a medium they turn to for “music to help them get through the less desirable moments in their day, improve the more positive ones and even discover new things about their personality,” says Spotify. […]

In appealing to advertisers, Spotify also celebrates its position as a background experience and in particular how this benefits advertisers and brands. Jorge Espinel, who was Head of Global Business Development at Spotify for five years, once said in an interview: “We love to be a background experience. You’re competing for consumer attention. Everyone is fighting for the foreground. We have the ability to fight for the background. And really no one is there. You’re doing your email, you’re doing your social network, etcetera.” In other words, it is in advertisers’ best interests that Spotify stays a background experience.

The goal of Spotify (or Netflix, for what matters) is for you to always be streaming.

Kind of mind-blowing overview of the waste management of a specific item (Christmas tree lights), from Adam Minter.

I would also highly recommend to anyone who wants to understand recycling as a system (that exists outside of our daily reality) to follow Discard studies, which is how I stumbled upon the above:

Structures, not behaviours, uphold norms and practices of waste and wasting. In sociology and other fields, there is a constant tension between agency–what individuals and groups of people are able and want to do– and structure, the cultural norms and values, institutions, infrastructures, and power relations that constrain and even determine that agency. Because of this, we’ve argued against awareness as an ideal method for creating changes around waste and wasting, instead arguing for changes in infrastructure and other scaled up systems. To help understand this tension, we use concepts of scale and scalar mismatch to argue that waste occurs differently within different structures at different scales, and that action must match up with these scales. For example, if we want to address pollution and waste, then focusing 90% of our activist efforts on household waste that makes up less than 3% of a nation’s waste is not going to be effective. Consumer and citizen behaviour cannot impact 97% of the waste that’s out there.

I kind of hate messaging these days.

Over the years different software have imposed on their users FOMO inducing features that lead us to this ridiculous reality in which we all collectively agreed that a response to a text needs to be returned within minutes, no matter the content nor the urgency.

I sometimes choose emails over texts for this reason. I know — I am weird. BUT! Expectations are different with emails. We read less into it if someone takes a day or longer to get back to us (even though some people are trying to make emails obnoxious too).

The online status (last seen at), the typing indicator (is typing), and — worst of all — read receipts somehow ended up being our default, with all which that entails (mostly anxiety). It’s all working exactly as we designed it, as in: it’s all quite shitty:

Privacy remains one of the big and unresolved issues in our industry and while we often worry about data leaks and agonize over how much companies know about us, we often forget that it’s the small and barely noticeable losses of end-to-end user privacy that affect us socially the most. And while turning every privacy related decision into a setting might be enticing, it’s ultimately shortsighted. Designers are well aware that most users won’t bother changing a default. And the act of changing a default ironically always inadvertently reveals something about users, whether they want or not.

So what does a future that respects people’s micro-privacy feel like?

It’s knowing you can go online without having to fear what our online status may reveal about you. It’s about liking someone’s photo without the anxiety of being called out for it. And above anything, it’s about reading a message, without feeling guilty of not sending an immediate response.

Read-Only Memory publishes high-quality books that document videogame history.

A web typography learning game

L.M. Sacasas:

“When I was a child,” the Apostle wrote, “I spoke like a child, I thought like a child, I reasoned like a child.” And, we may add, I looked like a child. Thus the appropriateness of my childishness was evident in my appearance. Yes, that was me as I was, but that is no longer me as I now am, and this critical difference was implicit in the evolution of my physical appearance, which signaled as much to all who saw me. No such signals are available to the self as it exists online.

Indeed, we might say that the self that exists online is in one important respect a very poor representation of the self precisely because of its tendency toward completeness of memory. Digital media, particularly social media platforms, condense the rich narrative of the self’s evolution over time into a chaotic and perpetual moment. We might think of it as the self stripped of its story.

The values change every time the universe changes, and that’s every time we redefine a big enough bit of it. Which we do all the time through the process of discovery that isn’t discovery: just the invention of another version of how things are.

Oona Räisänen:

If you ever connected to the Internet before the 2000s, you probably remember that it made a peculiar sound. But despite becoming so familiar, it remained a mystery for most of us. What do these sounds mean? […]

The first thing we hear in this example is a dial tone, the same tone you would hear when picking up your landline phone. The modem now knows it’s connected to a phone line and can dial a number. The number is signaled to the network using Dual-Tone Multi-Frequency signaling, or DTMF, the same sounds a telephone makes when dialing a number.

The remote modem answers with a distinct tone that our calling modem can recognize. They then exchange short bursts of binary data to assess what kind of protocol is appropriate. This is called a V.8 bis transaction.

Arvind Narayanan:

I will focus the rest of my talk on this third category [predicting social outcomes], where there’s a lot of snake oil.

I already showed you tools that claim to predict job suitability. Similarly, bail decisions are being made based on an algorithmic prediction of recidivism. People are being turned away at the border based on an algorithm that analyzed their social media posts and predicted a terrorist risk. […]

Compared to manual scoring rules, the use of AI for prediction has many drawbacks. Perhaps the most significant is the lack of explainability. Instead of points on a driver’s license, imagine a system in which every time you get pulled over, the police officer enters your data into a computer. Most times you get to go free, but at some point the black box system tells you you’re no longer allowed to drive.

Anton Dubrau does a fascinating overview of existing tunnel boring machine technology:

People tend to think it’s the tunnels that are the most expensive part of underground systems like metros, but thanks to the already existing TBM technology, they often represent only a small portion of the overall cost. Sometimes as little as 10%.

The most expensive parts of subways are the stations. In my view, modern boring technology becomes interesting when we can use it not just for the tunnels in-between the stations, but to build the complete system, including the stations, cheaper.