In the course of getting a job done, we all end up doing a bit of research. Here are some of the projects I’ve contributed to, from artificial intelligence to aircraft design, tissue simulation, human-machine interfaces and Lego Mindstorms! Feel free to check it out. Wherever possible, I’ve added the presentation versions, which are a bit more visual and a lot less text!
In terms of proprietary tools, MATLAB is going to pop up frequently – here is a primer on MATLAB tools and capabilities for computer vision
“People aren’t puzzle pieces, turn-key products, or canned beans. They are investments, copilots, and will form connections within and outside your organization you never would have guessed”
Fuelling People is probably one of the tougher things to do in an organization – training programs, interesting work, mentorship, matched teams, surveys, open door policies, carefully tailored workloads are all a nice set of sliders and controls an organization can play with and optimize, But the most difficult thing is still creating training around an institutional knowledge set that includes some really hard-to-capture aspects – gut feel, interpersonal relations, estimating workloads and performance, turning measurements into decisions, and understanding people’s true capacities and capabilities.
Smashing has an interesting take on setting up technical courses for technical people inside a technical organization. A few key points, which I’ll add a bit to:
- Give context and purpose to what you are teaching. The big picture – how will you be stronger within the organization, and how will it make the organization stronger (i.e. a better place to be!)
- Teach by example. For example, the ‘Cookbook style’ Where a specific need is solved, allowing the learner to auto-generalize (something humans are almost too good at). Check out the micro article on learning as foundations and differences
- Have some awesome homework. Learning is, in the end, doing, and watching someone else cook doesn’t make you a chef. Make the homework rewarding, possibly collaborative, and flexible to meet the motivations and interests of the learner. It’s also a breeding ground for real questions and feedback, not the polite stuff or pile-ons you might get immediately after a presentation
- Learn how the training went – get feedback and get it immediately as well as later on. You have to learn how to teach people, after all, and accurate feedback is more than one datapoint in time – The term, “Let it sink in”, and “experience is the best teacher” have a very good reason to exist!
My favourite techniques in extending technical knowledge are a “Parallels” method and the “Hub Analogy” method.
Parallels Method: For example, if someone knows how to solve a particular problem in Java, map each step over to the target language – say Objective C, and line up the equivalent functionality. Then, differences are much more easily explained, as they stand out from this common basis. This method works great when laterally moving through equivalent topics.
Hub Analogy Method: I recently had the opportunity to do a presentation to new pilots on how airplanes land at an airport. The aviation terms and language really make no sense to a newcomer, especially in 5 minutes, so I started with the idea that landing at an airport is a lot like going through a Tim Horton’s Drivethru: you line up, follow the signs, make a radio call with your request, and keep yourself away from other traffic. This had the benefit of allowing us to ‘hang’ new ideas off this solid mental model which everyone could be familiar with. For example, you can call the Tim Horton’s person the ‘Tower’ and introduce the concept of ‘runway clearance’ as the equivalent of, ‘please drive up to the second window’. A familiar and flexible hub analogy allows better student recall by splitting new learning into Foundation and Connected Differences, i.e. Hub and Spokes. This method works best when introducing less familiar or totally unfamiliar topics. (It is most notoriously misused in science documentaries as the classic units of measure: “Human Hair”, “elephants”, “Golf Ball” and “Football Fields”)
No technique is going to work as well without examples. Popular books from Gladwell and Kahneman are completely saturated with examples because they know that we learn by generalizing, not by making up specifics after memorizing some abstract framework. Humans evolved to think, “I don’t eat that fish because that one time I did was pretty bad, therefore, no yellow-striped fish for me of any kind.”, not, “anything that is sending a signal it is poisonous is highly visible as opposed to camouflaged, therefore I will not try that fish over there.” Examples are also a form of storytelling – which is just a way of conveying a personal experience like, “In and Out: That One Time I Ate That Yellow Striped Yuck Fish”. We love stories because humans are empathy machines, and blur our Specifics into Generalizations.
The stereotypes are true: the boost into space from sea level is a shaky, G-infested carnival ride with every Fourier component you care to name. NASA had a similar problem as part of its problematic Ares 1 project. Some rockets have a dominant resonance frequency in long axis that is termed ‘pogo’ (like the stick) and in human rated vehicles this means a dominant mode vibration passes to the passengers. In the case of the Ares I, this was on the order of 0.7G’s at about 12 Hertz, working out to around 5mm motion. If the computer displays the passenger is looking at do not have the same damping and resonance characteristics as their own eyes and head, motion blur in the displays will make them unreadable as simulated above.
A solution tested was to strobe the display in the same way LED-based displays are dimmed – a square wave duty cycle is applied so that the display is actually off some of time. The duty cycle is synchronized to the main vibrational component of the the pogo motion, removing the worst of the motion blur at the expense of some brightness (This simulated view assumes that brightness can be boosted somewhat to compensate).
When compensating for a single, sinusoidal mode, the loss in brightness is not that great if the duty cycle of the strobing is phase matched to a displacement peak of the motion as shown. A vibration reduction of 90% is possible with a 20% duty cycle, or 80% loss in brightness.
Read the article and see the demo video here:
You never stop learning, which means you never stop studying. Sometimes the hardest things to learn are those that don’t have a concrete test or exam at the end. How do you know how well you did in a race if there are no hurdles, laps, timer or finish line? That’s part of being an adult, and actually a part of a Human Factors model where your “comfort zone” must be stretched into an area where you are uncomfortable, but, as it turns out, competent.
A good way to stretch yourself in the direction of learning something new is not just to read the manual. Humans are designed to learn through doing, so doing examples and writing example exams is generally more effective than just linear reading.
Yes, 3D printer will be taken to the International Space Station on the next Dragon cargo flight (The Dragon 2 capsule will fittingly use 3D-printed thrusters, by the way).
The simplification of user interfaces has been proceeding quickly now that the last vestiges of skewmorphism are gone. Like any new technology, the first iterations of the interface must be familiar to the users. Early cars looked like carriages, early lightbulbs behaved like gaslight, early televisions looked like radios, and the first home computers worked like typerwriters (and still do!).
But any design trend ultimately overshoots the mark, in this case iconography has possibly become oversimlified, and buttons without outlines or contrast fill are being used because retina-class displays support the fine line widths.
Curt Arledge addresses one basic question in this user interface direction: does an outline or contrast button have more usability. Check out his results here
In summary, what seems to matter are two things. First, the users’ familiarity with the icon type: i.e. the common language all interfaces share to a great degree in the iconography alphabet. Second, that user testing is still required, since differences appear in counter-intuitive places, and some design decisions affect usability less than expected.