You all know I love podcasts. One of my favorites, Big Picture Science, held an interview with Nicholas Carr (a journalist) on over-reliance in automation. The entire podcast, What the Hack, also covers computer security. To skip to the HF portion, click here.
+points for mentioning human factors by name
+points for clearly having read much of the trust in automation literature
-points for falling back on the “we automate because we’re lazy” claim, rather than acknowledging that the complexity of many modern systems requires automation for a human to be able to succeed. Do you want to have that flight to NY on the day you want it? Then we have to have automation to help that happen – the task has moved beyond human ability to accomplish it alone.
-points for the tired argument that things are different now. Google is making us dumber. Essentially the same argument that happens with every introduction of technology, including the printing press. We aren’t any different than the humans that painted caves 17,300 years ago.
This is Post 2 in our ongoing series about graduate school in Human Factors. (Post 1)
In this post, we discuss a general to-do list for those considering graduate school in Human Factors. Comments from other faculty welcome!
1. Get Involved in Research as Early as Possible
This can be through a senior project, a class at your university where students do a research project, or (optimally) by working as a research assistant in a lab.
If your university does not have these opportunities, look around (nearby universities). Many professors will take volunteer research assistants, including in the summer, and train you in their lab. This gives you both experience and a potential reference letter.
2. Start Looking for Departments/Mentors and Evaluate Fit
Many programs or labs have information on their alumni. Do they have the kinds of jobs you want? Do their alumni work at places you would like to work?
You will work mainly with a single advisor in an apprenticeship model. However, it’s a good idea to consider programs where you match more than one professor.
Check out the research interests of potential advisors by reading some of their recent publications or look at their curriculum vitae (the academic term for resume; often found online). We often have an area of expertise but work in other areas as well. You don’t want to choose an advisor based on work from 20 years ago that isn’t being continued today.
It is highly unlikely that a potential advisor will initiate a new research area to fit your interests–be flexible in your interests.
Create a spreadsheet listing department, contact information/web address to apply, potential faculty (and their major research areas), application fee, deadline, required materials, and your rating of fit.
3. Contact Prospective Mentors
When you have identified some potential programs, check their website to see which faculty are affiliated with the program and taking students.
Not all faculty take students every year. Some faculty list on their website whether they are taking students. If unsure, a short, formal email to the professor asking if they are accepting new students is appropriate.
Just because they are on a departmental website does not mean that they are affiliated with the HF program (that department may have other graduate programs) or that they are taking students that year. If it is unclear, email and ask. It isn’t helpful if, for example, you are applying to a psychology program but list an industrial engineering professor as your preferred mentor.
If you would like to evaluate potential fit between you and your potential mentor, you can ask if they are willing to meet with you in-person. Opinions vary, but Skype/video conference meetings may work.
Our next post will give an example of the kind of formality expected in contacting a prospective advisor.
This is the first post in an upcoming series about human factors graduate school.
If you have decided that you might want to further your education in human factors and ergonomics by going to graduate school, here is some useful information that Anne and I have collected over the years. While there are many sources of similar information, this one is tailored to potential HF students and answers questions that we’ve received.
First, graduate school will be very different from undergraduate. Yes, you take classes, but the most important experience is in conducting research–that is how you will be evaluated and ultimately what determines whether you are successful.
Most prospective students in HF are interested in the topic because they are interested in design or usability. It is important to realize that graduate school will not be like working in a design studio. Instead, it will be more like being in an experimental psychology program where you take courses in statistics, research methods, cognition, perception, etc.
You will also take specialized courses in usability or other evaluation methods but it will be one of many. The goal is to educate you on the fundamentals of human capabilities and limitations so that you can then use this knowledge in the design or evaluation of artifacts (for those going into applied fields).
In the rest of this series, we’ll discuss researching programs, contacting faculty, and various dos and don’ts.
I became interested in using “big data” for A/B testing after a speaker from RedHat gave a talk to our area about it a couple of years ago. It’s a tantalizing idea: come up with a change, send it out on some small percent of your users, and pull it back immediately if it doesn’t work or isn’t better than the original. Even more amazing when you consider a “small percent” can be thousands and thousands of people – a dream for any researcher. Certainly, this connects to last year’s news on the controversy over Facebook’s A/B testing adventures.
The only con I can think of is that if something works or doesn’t work, you may not know why. We are always fumbling toward success, but maybe it’s not good to encourage fumbling over development of theory.
I enjoyed this article by Matt Gallivan, Experience Research Manager at AirBnB, about the tendency of experts to overgeneralize their knowledge. I try to watch out for it in my own life: When you’re an expert at one thing, it’s so easy to think you know more than you do about other areas.
Because if you’re a UX researcher, you do yourself and your field no favors when you claim to have all of the answers. In the current digital product landscape, UX research’s real value is in helping to reduce uncertainty. And while that’s not as sexy as knowing everything about everything, there’s great value in it. In fact, it’s critical. It also has the added bonus of being honest.
They are specifically looking for someone in Human Factors/Applied Experimental psychology.
MULTIPLE TENURE-TRACK FACULTY POSITIONS AT TEXAS TECH UNIVERSITY
The Department of Psychological Sciences at Texas Tech University announces multiple openings for tenure-track positions at the Assistant Professor level. We seek applications in the areas of clinical (req. #4627BR), human factors/applied experimental (req. #4628BR), and counseling (req. #4626BR) psychology. We are particularly interested in applicants whose program of research, broadly defined, contributes to the department’s emphases on neuroscience, and health and safety. For candidates with an interest in neuroscience, the Texas Tech Neuroimaging Institute houses a research dedicated 3-T Siemen’s Skyra with simultaneous 128-channel EEG, and there are opportunities to collaborate with existing neuroimaging researchers in psychology and across campus.
Candidates are expected to conduct productive and programmatic research, compete for extramural research funding, teach undergraduate and graduate psychology courses, mentor graduate students, and provide service to the department, college, university, and profession. Candidates for our human factors position should have a strong psychology background and a commitment to integrating basic and applied research. Candidates for our clinical and counseling psychology positions must receive their Ph.D. from an APA-accredited program by August 2016 and should be able to supervise graduate students in practicum. The anticipated starting date for all positions is August 19, 2016.
The Department of Psychological Sciences at Texas Tech (http://www.depts.ttu.edu/psy/) has doctoral programs in clinical, counseling, cognitive, human factors, and social psychology. The clinical and counseling programs are accredited by APA and the human factors program is accredited by the Human Factors and Ergonomics Society. We currently have 28 full-time tenure-track faculty, 120 doctoral students, over 1,000 undergraduate majors, our own building with labs and classroom space, and a Psychology Clinic. Our research programs encompass departmental, campus, community, and national/international collaborations. We have effective working relationships with the TTU Health Sciences Center, several large area hospitals, numerous clinics and psychological-service agencies, and other multidisciplinary groups in the region. Texas Tech University is classified as a doctoral “research-extensive university” by the Carnegie Foundation and as a “national research university” by the State of Texas. With a population of approximately 240,000 people, Lubbock is an ethnically-diverse community, with a low cost of living, temperate climate, modern airport and infrastructure, and good school districts.
To apply for a faculty position, candidates must submit a cover letter, vita, statement of research interests, statement of teaching philosophy, sample reprints, 3 or more letters of
recommendation, and any other materials that candidates think will be helpful, to our online application web site, at: http://jobs.texastech.edu, under the above requisition number corresponding to each specialty area. We will begin reviewing applications on October 1, 2015, and will continue to review applications until the positions are filled. Please direct questions about these positions to: Dr. Robert Morgan, Search Committee Chair, firstname.lastname@example.org, 806-834-7117. Texas Tech University is an Affirmative Action/Equal Opportunity Employer and TTU has a sustained commitment to enhancing diversity. We strongly encourage applications from women, minorities, persons with disabilities, and other under-represented groups. We have a successful track record of accommodating the needs of dual-career couples.
I wanted a new helmet that offered some side-impact protection to replace my trusty Petzl Ecrin Roc, especially after a helmet-less Slovenian climber mocked me in Italy for wearing “such a heavy helmet” at a sport climbing crag.
I now own the Petzl Meteor, but after one trip discovered a strange design flaw.
Most helmets clip together the way carseats or backpack buckles clip together:
The Petzl Meteor helmet has a similar clip, but also contains magnets that draw the buckle together. Here is how it should work:
I was climbing at Lover’s Leap in California, a granite cliff. Those of you who know your geology might guess what happens when you combine magnets and iron-rich granite. I put the helmet on the ground while sorting gear, put it back on and heard the buckle snap together. A few minutes later, I looked down (which put some strain on the helmet strap), the buckle popped open, and the helmet fell off my head.
When I examined the buckle, there was grit stuck to the magnet.
Wiping it off seemed to work, except that it moved some of it to the sides rather than just the top. My fingers weren’t small enough to wipe it from the sides. So, the next time I snapped it shut and checked to make sure it was locked, I couldn’t get it off. The grit on the side prevented the buckle from pinching enough to release. I was finally able to get it off the sides by using part of a strap to get into the crevices.
I made some videos of the phenomenon. It was pretty easy to do, I just had to put my helmet on the ground for a moment and pick it up again. Attached grit was guaranteed – these are strong magnets!
The only issue I had with the buckle came after wearing the Sirocco while bolting and cleaning a granite sport route. Some of the swirling granite dust adhered to the magnets, obstructing the clips. It was easy enough to fix: I just wiped the magnets clean, and it has worked perfectly since.
What we found in our tests of both the Meteor and the Sirocco was that the magnet did not always have enough oomph to click both small arms of the buckle completely closed. About one in four times, only one of the plastic arms would fasten and the buckle would need an extra squeeze to click the other arm in. Another thing our testers noticed was that the magnet would pick up tiny pebbles which would prevent the buckle from fully closing. The pebbles can be easily cleaned by brushing off the exposed part of the magnet, but it adds an extra step to applying the helmet. The bottom line is, we prefer the simplicity of the old plastic buckle. We think that the magnet is a gimmick which potentially makes a less safe helmet.
Safety gear shouldn’t add steps to be remembered, such as making sure the buckle is locked, even after getting auditory and tactile feedback when one connected it. Some people may never climb in an area with iron in the ground, but the use-case for a granite environment should have been considered. You know, for little climbing areas such as the granite cliffs of Yosemite.
The field of artificial intelligence is obviously a computational and engineering problem: designing a machine (i.e., robot) or software that can emulate thinking to a high degree. But eventually, any AI must interact with a human either by taking control of a situation from a human (e.g., flying a plane) or suggesting courses of action to a human.
I thought this recent news item about potentially dangerous AI might be a great segue to another discussion of human-automation interaction. Specifically, to a detail that does not frequently get discussed in splashy news articles or by non-human-factors people: degree of automation. This blog post is heavily informed by a proceedings paper by Wickens, Li, Santamaria, Sebok, and Sarter (2010).
First, to HF researchers, automation is a generic term that encompasses anything that carries out a task that was once done by a human. Such as robotic assembly, medical diagnostic aids, digital camera scene modes, and even hypothetical autonomous weapons with AI. These disparate examples simply differ in degree of automation.
Let’s back up for a bit: Automation can be characterized by two independent dimensions:
STAGE or TYPE: What is it doing and how is it doing it?
LEVEL: How much it is doing?
Stage/Type of automation describes the WHAT tasks are being automated and sometimes how. Is the task perceptual, like enhancing vision at night or amplifying certain sounds? Or is the automation carrying out a task that is more cognitive, like generating the three best ways to get to your destination in the least amount of time?
The second dimension, Level, refers to the balance of tasks shared between the automation and the human; is the automation doing a tiny bit of the task and then leaving the rest to the user? Or is the automation acting completely on its own with no input from the operator (or ability to override)?
If you imagine STAGE/TYPE (BLUE/GREEN) and LEVEL (RED) as the X and Y of a chart (below), it becomes clearer how various everyday examples of automation fit into the scheme. As LEVEL and/or TYPE increase, we get a higher degree of automation (dotted line).
Mainstream discussions of AI and its potential dangers seem to be focusing on a hypothetical ultra-high degree of automation. A hypothetical weapon that will, on its own, determine threats and act. There are actually very few examples of such a high level of automation in everyday life because cutting the human completely “out of the loop” can have severely negative human performance consequences.
The figure below shows some examples of automation and where they fit into the scheme:
Wickens et al., (2010) use the phrase, “the higher they are, the farther they fall.” This means that when humans interact with greater degrees of automation, they do fine if it works correctly, but will encounter catastrophic consequences when automation fails (and it always will at some point). Why? Users get complacent with high DOA automation, they forget how to do the task themselves, or they loose track of what was going on before the automation failed and thus cannot recover from the failure so easily.
You may have experienced a mild form of this if your car has a rear-backup camera. Have you ever rented a car without one? How do you feel? That feelings tends to get magnified with higher degrees of automation.
So, highly autonomous weapons (or any high degree of automation) is not only a philosophically bad/evil idea, it is bad for human performance!
First, a disclaimer: this isn’t a full-on review of the Watch. There are more qualified people to review the gadget. The newest one comes from one of the best and most thorough hardware review sites: Anandtech.
One part of the review was particularly insightful:
Overall, I found that the fitness component of this watch to be a real surprise. I often hear that Apple is good at making things we didn’t know we wanted, but this is probably the first time I’ve really believed that statement. Going into the review, I didn’t really realize that I wanted a solid fitness tracker on a smartwatch, but now I’m really convinced that there is value to such features.
This has been my experience as well. I’ve never cared to wear a fitness tracker but i’m surprised at how much I pore over the stats of my standing, activity, and workout levels. The watch also provides a surprisingly effective level of motivation (badges & activity circles).
My activity level (for someone who sits at a desk most of the time) has dramatically increased since the watch (see right; yellow line is when I got the watch).
We used to think that smartphones were the “ubiquitous” technology but there are times I leave it behind. The watch is always-on and there will be interesting use-cases and challenges in the future. I’d love to start my car with my watch!
Some other random thoughts:
The fitness features are great but I wish there was a better way to view my data:
View splits on outdoor runs
View all my workouts instead of looking for them in the calendar view.
Many reviews i’ve read assume the watch will replace the phone. But doing any extended activity really tires the shoulders! My interactions are really limited to much less than 5-10 seconds.
I notice that haptic feedback on the wrist is much less jarring and easier to dismiss (i.e., not as disruptive) as vibrating phones on the body.
The Apple Watch is made for travel:
Most airlines have applets for the watch that make it so easy to keep track of gates, departures, & arrivals.
Boarding a plane with your watch feels very futuristic but most pass readers are on the right side and I wear my watch on the left resulting in very awkward wrist positions. Even when the reader was on the left, it is facing upwards requiring me to turn my wrist downwards.
It is unobtrusive and looks like a watch, not like a gizmo on my wrist.
Apple Pay belongs on the watch. I’ve used Apple Pay on my phone but it is much more seamless on the watch.
Notifications are great if you pare down what can notify you. I only get notified of VIP mail (select senders) and text messages.
Controlling my thermostat, and other electrical devices from my wrist is pretty great.