If the product is free, you are the product:
An antivirus program used by hundreds of millions of people around the world is selling highly sensitive web browsing data to many of the world’s biggest companies.
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Leaked Documents Expose the Secretive Market for Your Web
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Google’s ads just look like search results now
In what appears to be something of a purposeful dark pattern, the only thing differentiating ads and search results is a small black-and-white “Ad” icon next to the former.
Hrm. The resulting change seems to work:
Early data collected by Digiday suggests that the changes may already be causing people to click on more ads. […] According to one digital marketing agency, click- through rates have already increased for some search ads on desktop, and mobile click- through rates for some of its clients increased last year from 17 to 18 percent after similar changes to GoogleĘĽs mobile search layout.
Damn. I may start looking for a new search engine.
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Interference by Sue Burke
# Interference by Sue Burke
[People] tend to ignore outside forces and focus on each other. This comes naturally. They believe they are responsible for everything because they believe they have no limits to the mastery of their fates, a false belief but their central motivation, perhaps good for their mental health, since powerlessness is hopelessness.
If you haven’t heard of Sue Burke’s “Pax” duology, and you like sci-fi, I’m happy to recommend a new favourite book series for you.
The Pax books are about a rebellious attempt to save humanity in which several families build their own ship and escape to a new planet to begin a new colony. Doing that is about as straightforward as it sounds. Sue Burke brings this premise to life masterfully.
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DeepMindĘĽs StarCraft 2 AI is now better than 99.8 percent of all human players
Incredible achievement, but it makes me wonder—what are the .2% of humans doing differently?
These stories of AI achievement are sure to proliferate in the coming years. By focusing on those people who are still able to think around machine learning strategies, we might learn something about how humans and machines can best complement each other.
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Beautiful is good and good is reputable
# Beautiful is Good and Good is Reputable: Multiple-Attribute Charity Website Evaluation and Initial Perceptions of Reputation Under the Halo Effect
The halo effect is essentially how positive—but irrelevant—traits influence our perception of what the thing with the halo actually says or does. These authors explored how charities manifest the halo effect on their websites, and find evidence for four varieties of halo effect.
this study employs charity websites as a multi-attribute donation channel consisting of three attributes of information content quality (mission information, financial information, and donation information) and four attributes of system quality (navigability, download speed, visual aesthetics, and security). Based on the proposed framework, this study proposes four types of halos that are relevant to charity website evaluation —collective halo (attribute-to-attribute), aesthetics halo (attribute-to- dimension), reciprocal-quality halo (dimension-to-dimension), and quality halo (dimension-to-dimension)
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Bad RCS implementations are creating big vulnerabilities, security researchers claim
Scary:
One issue identified on an unnamed carrierĘĽs implementation could allow any app on your phone to download your RCS configuration file, for example, giving the app your username and password and allowing it to access all your voice calls and text messages. In another case, the six-digit code a carrier uses to verify a userĘĽs identity was vulnerable to being guessed through brute force by a third-party. These problems were found after researchers analyzed a sample of SIM cards from several different carriers.
RCS is supposed to be a big deal. It’s fascinating how these system-wide policies can be messed up in microsystem implementations.
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Adam Savage on Lists, More Lists, and the Power of Checkboxes
# Adam Savage on Lists, More Lists, and the Power of Checkboxes
In this Wired article, Adam Savage provides a pragmatic description of how he breaks down complex projects using lists.
In my mind, a list is how I describe and understand the mass of a project, its overall size and the weight that it displaces in the world, but the checkbox can also describe the project’s momentum. And momentum is key to finishing anything.
Momentum isn’t just physical, though. It’s mental, and for me it’s also emotional. I gain so much energy from staring at a bunch of colored-in checkboxes on the left side of a list, that I’ve been known to add things I’ve already done to a list, just to have more checkboxes that are dark than are empty. That sense of forward progress keeps me enthusiastically plugging away at rudimentary, monotonous tasks as well as huge projects that seem like they might never end.
I love the physics metaphor here. There’s lots of other insights to be gained by thinking about how work follows physical principles. For instance, projects also have inertia, friction, and surface area:
- Inertia. The longer a project sits waiting for you—weighing on your mind—the harder it is to get it moving.
- Friction. Inertia is driven by initial friction. In parallel, of course, kinetic friction can make it hard to stop working on something. This is why multitasking doesn’t make sense with most projects.
- Surface area: It can be hard to attack a single, huge project idea, just like how a large ice cube melts slower than many little ones. List making is a key way of breaking up the surface of a project into smaller pieces, making it easier to handle. Increasing surface area also facilitates collaboration: it’s easier to hand off smaller pieces to others, and to put them back together again.
To return to momentum, though, Adam makes an excellent point: breaking down the work helps keep momentum going even when you put the work down.
That may be the greatest attribute of checkboxes and list making, in fact, because there are going to be easy projects and hard projects. With every project, there are going to be easy days and hard days. Every day, there are going to be problems that seem to solve themselves and problems that kick your ass down the stairs and take your lunch money. Progressing as a maker means always pushing yourself through those momentum-killers. A well-made list can be the wedge you need to get the ball rolling, and checkboxes are the footholds that give you the traction you need to keep pushing that ball, and to build momentum toward the finish.
Another point in the article that’s worth emphasizing:
[I]n a project with any amount of complexity, the early stages won’t look at all like the later stages, and [the manager] wanted to take the pressure off any members of the group who may have thought that quality was the goal in the early stages.
I’ve heard this discussed in the context of critique, or “10% feedback”. When sharing work with others, it’s important to disclose the stage the work is at. Typos should be caught at a project that’s basically ready to publish. They shouldn’t even be discussed when a work is being conceptualized. The focus on early stages should be the concepts themselves, and how they fit within the broader context.
Last thing. This is excellent:
There is a famous Haitian proverb about overcoming obstacles: Beyond mountains, more mountains.
🏔
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a ton of people received text messages overnight that were
# A ton of people received text messages overnight that were originally sent on Valentine’s Day
Something strange is happening with text messages in the US right now. Overnight, a multitude of people received text messages that appear to have originally been sent on or around Valentine’s Day 2019. These people never received the text messages in the first place; the people who sent the messages had no idea that they had never been received, and they did nothing to attempt to resend them overnight.
It is incredible to think that this could happen on a scale big enough to hit headlines now, but it wasn’t noticeable on Valentine’s Day originally.
That’s one of the problems with our ever-more-complex technologies. We’re accommodating to the bugs. It gets easier and easier to dismiss weird tech events as glitches and move on without worrying. Unreliability is, itself, unreliable.
But there can be major consequences to seemingly innocent bugs:
… one person said they received a message from an ex-boyfriend who had died; another received messages from a best friend who is now dead. “It was a punch in the gut. Honestly I thought I was dreaming and for a second I thought she was still here,” said one person, who goes by KuribHoe on Twitter, who received the message from their best friend who had died. “The last few months haven’t been easy and just when I thought I was getting some type of closure this just ripped open a new hole.”
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a systemic view of research impact
# A Systemic View of Research Impact
If academia ceases to have an impact it loses its raison d’être. Impact is what differentiates meaningful academic work from mere busywork. It makes the difference between signal and noise.
[…]
Ultimately, the questions that concerns us [are] what role research plays in society and how we can create a research system with impact at its core?
Indeed. We have to be asking (and answering!) questions that matter.
I like this project. Benedikt and Sascha say they’re taking a systemic approach to model the full complexity of academic impact:
academia struggles with creating/measuring/generating impact because it struggles to conceptualise and structurally anticipate it. We are missing a systemic perspective on impact that is grounded in the fact that different forms of meaningful academic work show very different forms of impact.
The work is supposedly semi-open. The authors ask anyone that reads each chapter, released incrementally on Google Docs, to contribute comments, and then they will work to incorporate these insights back into the final output.
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'This is Sticking with Them:' Professor Explores Benefits of Model-Based Learning
Through model-based learning, students use diagrams as a way to think about and reason with systems—and to think about how complex systems interact and change.
“Model-based learning” seems like a reframing of classic teaching practices, but it’s nonetheless a powerful reframing. Emphasizing the model—and encourage students to test and iterate their models—is catchy. It’s also deliberately organizational—it requires students to organize and structure their thinking about a given system, often visually.