- Maintain Separate Github Accounts — simple advice.
- Cooper-Hewitt Pen Data — anonymized data from the Cooper-Hewitt design museum’s fantastic pen.
- Zero Rating’s Problem — Wikipedia was zero-rated for Angola, so Angolans began swapping movies via Wikipedia. Zero rating (“no data charge for this service”) is an incentive to use the site, not necessarily for the purpose intended.
- Motion Design is the Future of UI — Motion tells stories. Everything in an app is a sequence, and motion is your guide. Someone caught the animations and transitions bug.
"money" entries
Four short links: 24 March 2016
Work and Home Github, Museum Data, Bandwidth Incentives, and Motion Design
Four short links: 9 March 2016
Surveillance Capitalism, Spark in Jupyter, Spoofing Fingerprints, and Distributing SSH Keys
- The Secrets of Surveillance Capitalism — The assault on behavioral data is so sweeping that it can no longer be circumscribed by the concept of privacy and its contests. […] First, the push for more users and more channels, services, devices, places, and spaces is imperative for access to an ever-expanding range of behavioral surplus. Users are the human nature-al resource that provides this free raw material. Second, the application of machine learning, artificial intelligence, and data science for continuous algorithmic improvement constitutes an immensely expensive, sophisticated, and exclusive 21st century “means of production.” Third, the new manufacturing process converts behavioral surplus into prediction products designed to predict behavior now and soon. Fourth, these prediction products are sold into a new kind of meta-market that trades exclusively in future behavior. The better (more predictive) the product, the lower the risks for buyers, and the greater the volume of sales. Surveillance capitalism’s profits derive primarily, if not entirely, from such markets for future behavior. (via Simon St Laurent)
- Thunder — Spark-driven analysis from Jupyter notebooks (open source).
- Hacking Mobile Phones Using 2D-Printed Fingerprints (PDF) — equipment costs less than $450, and all you need is a photo of the fingerprint. (like those of government employees stolen en masse last year)
- SSHKeyDistribut0r (Github) — A tool to automate key distribution with user authorization […] for sysop teams.
Four short links: 4 March 2016
Snapchat's Business, Tracking Voters, Testing for Discriminatory Associations, and Assessing Impact
- How Snapchat Built a Business by Confusing Olds (Bloomberg) — Advertisers don’t have a lot of good options to reach under-30s. The audiences of CBS, NBC, and ABC are, on average, in their 50s. Cable networks such as CNN and Fox News have it worse, with median viewerships near or past Social Security age. MTV’s median viewers are in their early 20s, but ratings have dropped in recent years. Marketers are understandably anxious, and Spiegel and his deputies have capitalized on those anxieties brilliantly by charging hundreds of thousands of dollars when Snapchat introduces an ad product.
- Tracking Voters — On the night of the Iowa caucus, Dstillery flagged all the [ad network-mediated ad] auctions that took place on phones in latitudes and longitudes near caucus locations. It wound up spotting 16,000 devices on caucus night, as those people had granted location privileges to the apps or devices that served them ads. It captured those mobile ID’s and then looked up the characteristics associated with those IDs in order to make observations about the kind of people that went to Republican caucus locations (young parents) versus Democrat caucus locations. It drilled down further (e.g., ‘people who like NASCAR voted for Trump and Clinton’) by looking at which candidate won at a particular caucus location.
- Discovering Unwarranted Associations in Data-Driven Applications with the FairTest Testing Toolkit (arXiv) — We describe FairTest, a testing toolkit that detects unwarranted associations between an algorithm’s outputs (e.g., prices or labels) and user subpopulations, including sensitive groups (e.g., defined by race or gender). FairTest reports statistically significant associations to programmers as association bugs, ranked by their strength and likelihood of being unintentional, rather than necessary effects. See also slides from PrivacyCon. Source code not yet released.
- Inferring Causal Impact Using Bayesian Structural Time-Series Models (Adrian Colyer) — understanding the impact of an intervention by building a predictive model of what would have happened without the intervention, then diffing reality to that model.
Four short links: 25 December 2015
Bad Data, Breakout Startups, Drone Economics, and Graph Signs
- Bad Data Guide (Quartz) — An exhaustive reference to problems seen in real-world data along with suggestions on how to resolve them.
- Breakout List — companies where all the action is happening. Read alongside Startup L Jackson’s “How to Get Rich in Tech, Guaranteed.”
- The Economics of Drone Delivery — The analysis is still mostly speculative. Keeney imagines that 6,000 operators who earn $50,000 per year will operate 30,000 to 40,000 drones. Each drone will make 30 deliveries per day. Her analysis ignores depreciation and questions like: ‘How will drones avoid airplanes and deliver packages in Manhattan?’ And there’s another core issue: $12.92 is the price UPS charges to consumers, but its actual marginal cost of delivering one more package along a route they are delivering to already is probably closer to $2. When push comes to shove, will drones be able to compete? (via Chris Anderson)
- 7 Ways Your Data is Telling You It’s a Graph — Network, tree, taxonomy, ancestry, structure – if people are using those words to talk about an organizational chart or reporting structure, they’re telling you that data and the relationships between that data are important.
Four short links: 9 December 2015
Graph Book, Data APIs, Mobile Commerce Numbers, and Phone Labs
- Networks, Crowds, and Markets — network theory (graph analysis), small worlds, network effects, power laws, markets, voting, property rights, and more. A book that came out of a Cornell course by ACM-lauded Jon Kleinberg.
- Qu — a framework for building data APIs. From a government department, no less. (via Nelson Minar)
- Three Most Common M-Commerce Questions Answered (Facebook) — When we examined basket sizes on an m-site versus an app, we found people spend 43 cents in app to every $1 spent on m-site. (via Alex Dong)
- Phonelabs — science labs with mobile phones. All open sourced for maximum spread.
Four short links: 6 November 2015
Media Money, Linux Security, TPP and Source, and Robot Chefs
- Grantland and the Surprising Future of Publishing (Ben Thompson) — writing is good for reach, podcasts and video good for advertising $. The combination is powerful.
- Security and the Linux Kernel (WaPo) — the question is not “can the WaPo write intelligently about the Linux kernel and security?” (answer, by the way, is “yes”) but rather “why is the WaPo writing about Linux kernel and security?” Ladies and gentlemen, start your conspiracy engines.
- TPP Might Prevent Governments from Auditing Source Code (Wired) — Article 14.17 of proposal, published at last today after years of secret negotiations, says: “No Party shall require the transfer of, or access to, source code of software owned by a person of another Party, as a condition for the import, distribution, sale or use of such software, or of products containing such software, in its territory.” The proposal includes an exception for critical infrastructure, but it’s not clear whether software involved in life or death situations, such as cars, airplanes, or medical devices would be included. One of many “what the heck does this mean for us?” analyses coming out. I’m waiting a few days until the analyses shake out before I get anything in a tangle.
- Innit Future Kitchen — robots that cook. Is nothing sacred for these steely-hearted bastards?!
Four short links: 29 September 2015
Indie VC, Robotics Acquisitions, Music Money, and USG Web Standards
- My xoxo Talk (Bryce Roberts) — about indie.vc and the experience of trying something good in the investment world. You won’t believe what happened next …
- 10 More Robotics Companies Acquired (Robohub) — companies of all types and sizes are finding strategic reasons to acquire robotic ventures to add to their arsenal of products and services because they don’t want to be left behind.
- The Past, Present, and Future of the Music Biz — you might not agree with the conclusions, but the numbers are horrifying^W edifying. The U.S. concert industry has nearly tripled since 1999 (when recorded music sales peaked). Yet, what’s typically overlooked by this narrative is that the vast majority of this growth – 83% to be exact – has gone to non-Top 100 touring artists. In 2000, the Top 100 tours (which included ‘NSYNC, Metallica and Snoop Dogg & Dr. Dre) collected nearly 90% of annual concert revenues. Today, that share has fallen to only 44%.
- U.S. Web Design Standards — U.S. Digital Service and 18F put together a reusable component library and style guide for U.S. Government apps.
Four short links: 13 August 2015
Learning Style, Artisinal Cash, Docs at Scale, and Homophily Research
- Elements of Style: Learning Perceptual Shape Style Similarity — code and data for research that helps perceive stylistic similarity between objects that transcends structure and function. For example, we can see a common style such as “Danish modern” in both a table and chair, though they have different structures. Until now, machines have found it difficult to do the same. (That quote cribbed from the phys.org writeup) Our new AI overlords may be cruel and heartless, but they’ll be able to tell Danish Modern from Shaker.
- The Advent of Artisinal Cash (NY Times) — details the rise of local physical currency around the world. Nonetheless, the use of traditional paper money is clearly on the wane. Perhaps these smaller, more attractive artisanal paper notes are merely last bursts of glory before it disappears entirely. Though as Mr. Deller, the artist behind the latest Brixton pound, said, “As long as there are drug deals and criminality, there’ll be a need for cash.”
- Documentation at Scale — 1. Acknowledge that brute force doesn’t work; 2. Make documentation a first class citizen; 3. Make documentation executable; 4. Track the intent.
- Exposure to Ideologically Diverse Information on Facebook (Facebook Research) — Friends shared substantially less cross-cutting news from sources aligned with an opposing ideology. People encountered roughly 15% less cross-cutting content in news feeds due to algorithmic ranking and clicked through to 70% less of this cross-cutting content. Within the domain of political news encountered in social media, selective exposure appears to drive attention.
Four short links: 16 June 2015
Accessibility Testing, Time-Series Graphing, NO BUBBLE TO SEE HERE, and Technical Documentation
- axe — accessibility testing of web apps, so you can integrate accessibility testing into your continuous EVERYTHING pipeline.
- metrics-graphics — Mozilla Javascript library optimized for visualizing and laying out time-series data.
- US Tech Funding: What’s Going On? (A16Z) — deck eloquently arguing that this is no bubble.
- Teach Don’t Tell — what I think good documentation is and how I think you should go about writing it. Sample common sense: This is obvious when you’re working face-to-face with someone. When you tell them how to play a C major chord on the guitar and they only produce a strangled squeak, it’s clear that you need to slow down and talk about how to press down on the strings properly. As programmers, we almost never get this kind of feedback about our documentation. We don’t see that the person on the other end of the wire is hopelessly confused and blundering around because they’re missing something we thought was obvious (but wasn’t). Teaching someone in person helps you learn to anticipate this, which will pay off (for your users) when you’re writing documentation.
Filing cabinets, GAAP, and the accountant’s dilemma
The inability to take advantage of digital technology is as big a threat to financial organizations as any fintech startup.
Learn more about Next:Money, O’Reilly’s conference focused on the fundamental transformation taking place in the finance industry.
There’s plenty of news about the fintech, or financial technology, sector these days. Hundreds of nimble startups are disaggregating the age-old financial systems on which every transaction has relied for decades. There’s little doubt that this will continue — after all, more than four billion humans have a mobile phone, and 1.3 billion know how to use a Facebook feed, but only a billion are what we’d consider “normally banked.” Something’s got to give, and software is eating traditional financial systems one bite at a time.
But the existing financial industry isn’t just under threat from outside. Many of the processes and institutions of finance have been around for centuries, and their processes are tied to physical systems rather than digital ones. As a result, they’re unable to take advantage of digital innovations easily and remain competitive. Read more…