In his “2017 Design in Tech Report,” John Maeda writes that “code is not the only unicorn skill.” According to Maeda, who is the head of computational design and inclusion at Automattic and former VP of design at VC firm Kleiner Perkins, words can be just as powerful as the graphics in which designers normally traffic. “A lot of times designers don’t know that words are important,” he said while presenting the report at SXSW this weekend. “I know a few designers like that–do you know these designers out there? You do know them, right?”
I’ve spent many years referencing Wikipedia’s list of cognitive biases whenever I have a hunch that a certain type of thinking is an official bias but I can’t recall the name or details. It’s been an invaluable reference for helping me identify the hidden flaws in my own thinking. Nothing else I’ve come across seems to be both as comprehensive and as succinct.
However, honestly, the Wikipedia page is a bit of a tangled mess. Despite trying to absorb the information of this page many times over the years, very little of it seems to stick. I often scan it and feel like I’m not able to find the bias I’m looking for, and then quickly forget what I’ve learned. I think this has to do with how the page has organically evolved over the years. Today, it groups 175 biases into vague categories (decision-making biases, social biases, memory errors, etc) that don’t really feel mutually exclusive to me, and then lists them alphabetically within categories. There are duplicates a-plenty, and many similar biases with different names, scattered willy-nilly.
I’ve taken some time over the last four weeks (I’m on paternity leave) to try to more deeply absorb and understand this list, and to try to come up with a simpler, clearer organizing structure to hang these biases off of. Reading deeply about various biases has given my brain something to chew on while I bounce little Louie to sleep.
Despite the phenomenal rise in computing over the last 50 years, the birth of the internet, and our ever increasing reliance on technology, women are still not engaging with computer science at the same rate as men.
The report shows that in 2016 only a minority of schools (29%) entered pupils for GCSE computing – despite it being a foundation subject on the national curriculum. The figure is even lower at A-level, with only 24% of schools entering their students for the qualification.
Things don’t fair any better in further education either, with the Digest of Education statistics revealing the percentage of females who took an undergraduate degree in computer science in 1970-71 was 14%. This rose to 37% in 1983-84 but gradually declined to 18% in 2010-11.
Roughly every ten years there’s a shift to a new computing paradigm. The computer hardware and process optimization of the 80’s gave way to the Microsoft-dominated software and productivity of the 90s. Google-dominated web-based information retrieval of the 00s yielded to the Apple–Android mobile duopoly and the warehouse of apps paradigm of the 10’s.
The maturity of the web, intelligent cloud computing, advances in AI and the mobility of our digital experiences are setting the stage for the next shift to more ambient computing via the Internet of Things. By 2020 the number of connected devices is expected to triple to 34 billion (with a global human population of 7.5 billion).
Trend usually implies that something is short term, like a one-hit wonder on the radio, but when we talk about educational technology, these trends are here to not only stay, but grow. While it is hard to choose the most important educational technology trends, we did our best to craft this list of ten.
The group will serve as an opportunity to connect and engage with researchers and domain experts to drive awareness of Microsoft Research and Windows Azure for Research. We’d like for you to be part of the community and discussions.
What is the Windows Azure for Research initiative?
The Windows Azure for Research project facilitates and accelerates scholarly and scientific research by enabling researchers to use the power of Windows Azure to perform big data computations in the cloud.
Windows Azure Research Award Program
Microsoft Research is soliciting proposals for the use of Windows Azure in research. We welcome research proposals from any branch of scholarly activity. To qualify, applicants must be affiliated with an academic institution or non-profit research laboratory. In addition to individual investigator projects, we are interested in projects that will support access to services and data of value to a collaboration or community. Winning proposals will be awarded large allocations of Windows Azure storage and compute resources for a period of one year.