Musings on success

Traveling back to my native New Jersey usually casts me into a bit of melancholia, and this trip was no different. I guess it’s cliche, but visiting the place of my boyhood makes me want to mark my actual life against the plans I had for it back then. Unsurprisingly, they’re not very similar.

That caused me to further ponder my working definition of “success,” which, perhaps due to an extended soak in Silicon Valley, involves a lot of career advancement and lots of money (or at least a house with an upstairs), maybe inventing something appreciated by millions. However, I left SV because I wanted to work on energy policy be able to say that when it mattered I did something to measurably reduce climate change. So far at least, so much for any of that.

While doing this pondering, two people I knew while growing up kept persistently popping into mind. Both were Scoutmasters from my Boy Scouting days. David Millison was my Scoutmaster when I started Scouting in Troop 7 in Fairfield, NJ. George Berisso was my Scoutmaster in Troop 9 in Caldwell.

I met Dave when I was a wee one, just starting in Scouting. As he told the story, his initial involvement in Scouting leadership was pure coincidence. The local troop was looking to borrow a canoe and he had one. That somehow snowballed into running Troop 7 for 46 years and influencing the lives of hundreds of boys. Dave was the person who first planted in me the seeds of outdoor adventure. He talked in excited tones about Philmont, the scout ranch in the Sangre De Cristo mountains of New Mexico. One of the most profound things I learned from Dave is that discomfort can simply be set aside when necessary. You might be camping in the rain, your tent and sleeping bag soggy, eating cold oatmeal with no fire to warm you. No matter — you can still enjoy fellowship and adventure in such circumstances. You’ll be home to a hot shower in a day or two, so why not decide to carry on and have fun? I can’t say I always live that way, but I try to. Dave also was the master of situational ethics, encouraging us to carefully consider the ethical implications of the most trivial decisions. Are you going to tell the waiter he forgot to put your soda on the bill? Should you let your friend hold your place in line? I still wonder about some of these questions 30 years later.

Mr. Berisso taught AP Biology in my high school and sponsored our Environmental Protection Club. He also ran the troop I was in when I completed my Eagle. He was a demanding teacher and expected students to think carefully and to be skeptical and analytical. As an adult now, I am not quite certain how he could devote so much energy to his day job (science education) and still have energy left over for his family and extracurriculars like scouting. Mr. Berisso was the Scoutmaster who eventually took me to Philmont. Once, when was 17, I think, and rather advanced in Scouting, I did something that should have gotten me kicked out of Boy Scouts for good. Mr. Berisso did kick me out, but provided a path for me to be reinstated. He turned my stupidity into a character building lesson.

I don’t think either of these men were huge successes by the measures mentioned above. They didn’t have fancy cars or big houses or powerful positions. But they were exceedingly successful in other ways, which I now see are just as important, if not more so. They were well respected and appreciated by their communities and loved by their families. Furthermore, they both made indelible marks on hundreds, maybe thousands of young people. I don’t think anyone who knew either man will ever forget him.

It is very sad that both Dave and Mr. Berisso have passed away. I want to introduce them to my family, and to tell them what profound impacts they had on me as examples of character and service. It angers me that I cannot do this. Nevertheless, remembering them helps me to recalibrate my notion of success. I hope I can one day be half as successful as either of them.

Campaigning in an Alternate Universe

I’ve been bouncing around just at the edge of my 2016 presidential campaign overload limit, and the other night’s debate and associated post-debate blogging sent me right through it.

Yes, I was thrilled to see my preferred candidate (Hermione) outperform the other candidate (Wormtail), but all the post-debate analysis and gloating made me weary.

Then, I thought about the important issues facing this country, the ones that keep me up at night worrying for my kids, the ones that were not discussed in the debate, or if they were, only through buzzwords and hand waves, and I got depressed. Because there is precious little in the campaign that addresses them. (To be fair, Clinton’s platform touches on most of these, and Trump’s covers a few, though neither as clearly or candidly as I’d like.)

So, without further ado, I present my list of campaign issues I’d like to see discussed, live, in a debate. If you are a debate moderator from an alternate universe who has moved through an interdimensional portal to our universe, consider using some of these questions:



How do we deal with the employment effects of rapid technological change? File the effects of globalization under the same category, because technological change is a driver of that as well. I like technology and am excited about its many positive possibilities, but you don’t have to be a “Luddite” to say that it has already eliminated a lot of jobs and will eliminate many more. History has shown us that whenever technology takes away work,  it eventually gives it back, but I have two issues with that. First, it is certainly possible that “this time it’s different. Second, and more worrisome, history also shows that the time gap between killing jobs and creating new ones can be multigenerational. Furthermore, it’s not clear that the same people who had the old jobs will be able to perform the new ones, even if they were immediately available.

from Wikimedia

This is a setup for an extended period of immiseration for working people. And, by the way, don’t think you’ll be immune to this because you’re a professional or because you’re in STEM. Efficiency is coming to your workplace.

It’s a big deal.

I don’t have a fantastic solution to offer, but HRC’s platform, without framing the issue just as I have, does include the idea of major infrastructure reinvestment, which could cushion this effect.

Bonus: how important should work be? Should every able person have/need a job? Why or why not?


Related to this is growing inequality. The technology is allowing fewer and fewer people to capture more and more surplus. Should we try to reverse that, and if so, how do we do so? Answering this means answering some very fundamental questions about what is fairness that I don’t think have been seriously broached.

from Wikimedia

Sanders built his campaign on this, and Clinton’s platform talks about economic justice, but certainly does not frame it so starkly.

What has been discussed, at least in the nerd blogosphere, are the deleterious effects of inequality: its (probably) corrosive effect on democracy as well as its challenge to the core belief that everyone gets a chance in America.

Do we try to reverse this or not, and if so, how?



from Wikimedia
from Wikimedia

Speaking of chances, our public education system has been an important, perhaps the important engine of upward mobility in the US. What are we going to do to strengthen our education system so that it continues to improve and serve everyone? This is an issue that spans preschool to university. Why are we systematically trying to defund, dismantle, weaken, and privatize these institutions? Related, how have our experiments in making education more efficient been working? What have we learned from them?


Justice. Is our society just and fair? Are we measuring it? Are we progressing? Are we counting everyone? Are people getting a fair shake? Is everyone getting equal treatment under the law?

from Wikimedia

I’m absolutely talking about racial justice here, but also gender, sexual orientation, economic, environmental, you name it.

If you think the current situation is just, how do you explain recent shootings, etc? If you think it is not just, how do you see fixing it? Top-down or bottom-up? What would you say to a large or even majority constituency that is less (or more) concerned about these issues than you yourself are?



From Wikimedia

Climate change. What can be done about it at this point, and what are we willing to do? Related, given that we are probably already seeing the effects of climate change, what can be done to help those adversely effected, and should we be doing anything to help them? Who are the beneficiaries of climate change or the processes that contribute to climate change, and should we transfer wealth to benefit those harmed? Should the scope of these questions extend internationally?



Rebuilding and protecting our physical infrastructure. I think both candidates actually agree on this, but I didn’t hear much about plans and scope. We have aging:asr-9_radar_antenna

  • electric
  • rail
  • natural gas
  • telecom
  • roads and bridges
  • air traffic control
  • airports
  • water
  • ports
  • internet

What are we doing to modernize them, how much will it cost? What are the costs of not doing it? What are the barriers that are getting in the way of major upgrades of these infrastructures, and what are we going to do to overcome them?

Also, which of these can be hardened and protected, and at what cost? Should we attempt to do so?



Military power. What is it for, what are its limits? How will you decide when and how to deploy military power? Defending the US at home is pretty straightforward, but defending military interests abroad is a bit more complex.

U.S. Soldiers depart Forward Operating Base Baylough, Afghanistan, June 16, 2010, to conduct a patrol. The Soldiers are from 1st Platoon, Delta Company, 1st Battalion, 4th Infantry Regiment. (DoD photo by Staff Sgt. William Tremblay, U.S. Army/Released)
DoD photo

Do the candidates have established doctrines that they intend follow? What do they think is possible to accomplish with US military power and what is not? What will trigger US military engagement? Under what circumstances do we disengage from a conflict? What do you think of the US’s record in military adventures and do you think that tells you anything about the types of problems we should try to solve using the US military?

7-a. Bonus. What can we do to stop nuclear proliferation in DPRK? Compare and contrast Iran and DPRK and various containment strategies that might be deployed.



The future of electrical engineering as a profession

The other day I was watching Dave Jones, a video blogger that I find entertaining and informative. His blog, the EEVblog, is catnip for nerds who like to solder stuff and use oscilloscopes.

Recently he did a short segment where he answered a question from a student who was upset that his teacher told him that EE was perhaps not a great field for job security, and he sort of went on a colorful rant about how wrong the professor is.

The professor is right.

Electrical engineering employment is indeed in decline, at least in the USA, and I suspect, other development countries. It’s not that EE skills are not helpful, or that understanding electronics, systems, signals, etc, are not useful. They are all useful and will continue to be. But I think more and more of the work, in particular, the high paying work, will migrate to software people who understand the hardware “well enough.” Which is fine. The fact is that EEs make good firmware engineers.

I think someone smart, with a solid EE background and a willingness to adapt throughout your entire career, should always find employment, but over time I suspect it will be less and less directly related to EE.

I mostly know Silicon Valley. Semiconductor employment is way down here. Mostly, it is through attrition, as people retire and move on, but nobody is hiring loads of young engineers to design chips anymore. It makes sense. Though chip volumes continue to grow, margins continue to shrink, and new chip design starts are way down, because “big” SOCs (systems on chip) with lots of peripherals can fill many niches that used to require custom or semi-custom parts.

I suspect that the need for EEs in circuit board design is also in decline. Not because there are fewer circuit boards, but because designing them is getting easier. One driver is the proliferation of very capable semiconductor parts with lots of cool peripherals is also obviating a lot of would-have-been design work. It’s gotten really easy to plop down a uC and hook up a few things over serial links and a few standard interfaces. In essence, a lot of board design work has been slurped into the chips, where one team designs it once rather than every board designer doing it again. There might be more boards being designed than ever, but the effort per board seems to be going down fast, and that’s actually not great for employment. Like you, I take apart a lot of stuff, and I’m blown away lately not by how complex many modern high volume boards are, but how dead simple they are.

The growth of the “maker” movement bears this out. Amateurs, many with little or no electronics knowledge, are designing circuit boards that do useful things, and they work. Are they making mistakes? Sure, they are. The boards are often not pretty, and violate rules and guidelines that any EE would know, but somehow they crank out working stuff anyway.

I do hold out some hope that as Moore’s law sunsets — and it really is sunseting this time — there will be renewed interest in creative EE design, as natural evolution in performance and capacity won’t solve problems “automatically.” That will perhaps mean more novel architectures, use of FPGAs, close HW/SW codesign, etc.

Some statistics bear all this out. The US Bureau of Labor Statistics has this to say about the 2014-2024 job outlook for EEs:

Note that over a 10 year period they are predicting essentially no growth for EE’s at all. None. Compare this to employment overall, in which they predict 7% growth.

One final note. People who love EE tend to think of EEs as the “model EE” — someone clever, curious, and energetic, and who remains so way for 40+ years. But let’s remind ourselves that 1/2 of EEs are below median.  If you know the student in question, you can make an informed assessment about that person’s prospects, but when you are answering a generic question about prospects for generic EEs, I think the right picture to have in mind is that of the middling engineer, not a particularly good one.

I’m not saying at all that EE is a bad career, and for all I know the number of people getting EE degrees is going down faster than employment, so that the prospects for an EE graduate are actually quite good, but it is important for students to know the state of affairs.

Inferencing from Big Data

Last week, I came across this interesting piece on the perils of using “big data” to draw conclusions about the world. It analyzes, among other things, the situation of Google Flu Trends, the much heralded public health surveillance system that turned out to be mostly a predictor of winter (and has since been withdrawn).

It seems to me that big data is a fun place to explore for patterns, and that’s all good, clean, fun — but it is the moment when you think you have discovered something new when the actual work really starts. I think “data scientists” are probably on top of this problem, but are most people going on about big data data scientists?

I really do not have all that much to add to the article, but I will amateurishly opine a bit about statistical inferencing generally:


I’ve taken several statistics courses over my life (high school, undergrad, grad). In each one, I thought I had a solid grasp of the material (and got an “A”), until I took the next one, where I realized that my previous understanding was embarrassingly incorrect. I see no particular reason to think this pattern would ever stop if I took ever more stats classes. The point is, stats is hard. Big data does not make stats easier.


If you throw a bunch of variables at a model, it will find some  that look like good predictors. This is true even if the variables are totally and utterly random and unrelated to the dependent variable (see try-it-at-home experiment below). Poking around in big data, unfortunately, only encourages people to do this and perhaps draw conclusions when they should not. So, if you are going to use big data, do have a plan in advance. Know what effect size would be “interesting” and disregard things well under that threshold, even if they appear to be “statistically significant.” Determine in advance how much power (and thus, observations) you should have to make your case, and sample from your ginormous set to a more appropriate size.


Big data sets seem like they were mostly created for other purposes than statistical inferencing. That makes them a form of convenience data. They might be big, but are the variables present really what you’re after? And was this data collected scientifically, in a manner designed to minimize bias? I’m told that collecting a quality data set takes effort (and money). If that’s so, it seems likely that the quality of your average big data set is low.

A lot of big data comes from log files from web services. That’s a lame place to learn about anything other than how the people who use those web services think or even how people who do use web services think while they’re doing something other than using that web service. Just sayin’.


Well, anyway, I’m perhaps out of my depth here, but I’ll leave you with this quick experiment, in R:

It generates 10,000 observations of 201 variables, each generated from a uniform random distribution on [0,1]. Then it runs an OLS model using one variable as the dependent and the remaining 200 as independents. R is even nice enough to put friendly little asterisks next to variables that have p<0.05 .

When I run it, I get 10 variables that appear to be better than “statistically significant at the 5% level” — even though the data is nothing but pure noise. This is about what one should expect from random noise.

Of course, the r2 of the resulting model  is ridiculously low (that is, the 200 variables together have low explanatory power ). Moreover, the effect size of the variables is small. All as it should be — but you do have to know to look. And in a more subtle case, you can imagine what happens if you build a model with a bunch of variables that do have explanatory power, and a bunch more that are crap. Then you will see a nice r2 overall, but you will still have some of your crap pop up.




Nerd alert: Google inverter challenge

A couple of years ago Google announced an electrical engineering contest with a $1M prize. The goal was build the most compact DC to AC power inverter that could meet certain requirements, namely 2kVA power output at 240 Vac 60Hz, from a 450V DC source with a 10Ω impedance. The inverter had to withstand certain ambient conditions and reliability, and it had to meet FCC interference requirements.

Fast forward a few years, and the results are in. Several finalists met the design criteria, and the grand prize winner exceeded the energy density requirements by more than 3x!

First, Congrats, to the “Red Electrical Devils!” Screen Shot 2016-03-09 at 9.56.34 AMI wish I were smart enough to have been able to participate, but my knowledge of power electronics is pretty hands-off, unless you are impressed by using TRIACs to control holiday lighting. Here’s the IEEE on what they thought it would take to win.

Aside from general gEEkiness, two things interested me about this contest. First, from an econ perspective, contests are just a fascinating way to spur R&D. Would you be able to get entrants, given the cost of participation and the likelihood of winning the grand prize? Answer: yes. This seems to be a reliable outcome if the goal is interested enough to the right body of would-be participants.

The second thing that I found fascinating was the goal: power density. I think most people understand the goals of efficiency, but is it important that power inverters be small? The PV inverter on the side of your house, also probably around 2kW, is maybe 20x as big as these. Is that bad? How much is it worth it to shrink such an inverter? (Now, it is true if you want to achieve power density, you must push on efficiency quite a bit, as every watt of energy lost to heat needs to be dissipated somehow, and that gets harder and harder as the device gets smaller. But in this case, though efficiencies achieved were excellent, they were not cutting edge, and the teams instead pursued extremely clever cooling approaches.)

I wonder what target market Google has in mind for these high power density inverters. Cars perhaps? In that case, density is more important than a fixed PV inverter, but still seemingly not critical to this extreme. Specific density rather than volumetric seems like it would be more important. Maybe Google never had a target in mind. For sure, there was no big reveal with the winner announcement. Maybe Google just thought that this goal was the most likely to generate innovation in this space overall, without a particular end use in mind at all — it’s certainly true that power electronics are a huge enabling piece of our renewable energy future, and perhaps it’s not getting the share of attention it deserves.

I’m not the first, though, to wonder what this contest was “really about.” I did not have to scroll far down the comments to see one from Slobodon Ćuk, a rather famous power electronics researcher, inventor of a the Ćuk inverter.

Screen Shot 2016-03-09 at 9.55.00 AMAnyway, an interesting mini-mystery, but a cool achievement regardless.

On BS detection

Coming after my last post, which took aim at Vox, I am hereby directing you to an interesting interview on Vox in which a researcher discusses his work on bullshit. Bullshit, as the researcher defines it is:

Bullshit is different from nonsense. It’s not just random words put together. The words we use have a syntactic structure, which implies they should mean something.

The difference between bullshit and lying is that bullshit is constructed without any concern for the truth. It’s designed to impress rather than inform. And then lying, of course, is very concerned with the truth — but subverting it.

This a pretty fascinating category, no? What is it for? The first thing that springs to mind is establishing authority, which, though distinct from lying, seems to be the basic groundwork for slipping in lies by shutting down critical faculties. Bullshit is like the viral protein coat necessary to deliver some RNA lie payload.

It seems to me that bullshit is particularly rampant these days, but perhaps someone with more knowledge of history will correct me. We live in a very complex, dynamic world, and simple heuristics built into our wetware seem rather outgunned when confronted with modern, well-engineered, state-of-the-art BS. Furthermore, I notice more and more people — not just those in the business of propaganda — who make their living, in part or wholly, by spinning bullshit. Bullshit about guns, vaccines, education, politics, food, religion, terrorism, how your dotcom is helping the world — you name it.

Bullshit arising from the San Bernadino killings angered me over the last few days. Gun control advocates filled my FB feed with pleas for gun control, but the facts of the situation seem to imply that these people would have been able to perpetrate their murder under any conceivable gun control regime, except, perhaps, for a total ban with confiscation. (Which I think we can all agree is not going to happen and probably shouldn’t.) The conservative media, of course, seems aflame with innuendo about Islam and violence, justifying fear of Muslim refugees and discrimination against them. Overall, it’s too early to make much sense of this tragedy, but whether you like gun control or restrictions on refugee immigration, there’s not much in this event to support a serious argument for either. Which is to say, everything on your Facebook feed that links this story to pretty much any cause is 100% pure bullshit.

I believe traditional thinking about bullshit is that, first, people who hear bullshit that confirms their priors just let it go unprocessed because, well, why not? And second, that processing everything you hear critically is work, and most people quite rationally avoid work when they can.

I (and this researcher) wonder, though, because some people have highly sensitive bullshit detectors and can sniff it out instantly, without consulting or WebMD. And I know plenty of people who get angry about bullshit, even when it aligns with what they already believe.

Is this some kind of immunity? Is it natural or can people be inoculated? And if the latter is possible, how do we go about it?


Racket of the day: higher education

A professor at Cal State Fullerton is in trouble for assigning a cheaper textbook than the one assigned by his department. The department-chosen text retails for a whopping $180. It’s also worth noting that the $180 textbook was written by the chair and vice chair of the math department.

Aside from unfortunate conflict of interest, one has to step back and wonder why it is that textbooks are so expensive these days. Has the cost of publishing gone up significantly? Prices in the rest of the book industry would seem to indicate not. Is it harder to recruit authors than ever? Maybe, but it’s worth pointing out that there’s probably not much that has changed in an introductory linear algebra text in the past 50 years.

The only explanation I can’t bat away is that the educational publishing industry learned to assert market power. The students have to buy the course textbook, and that gives publishers who can get in the door strong pricing flexibility, better yet if they are in cahoots with the administration. Furthermore, the ability to pay is bolstered by our good friends, non-dischargeable student loans.

It’s embarassing and sad. One could imagine an alternative universe where a system like Cal State endeavors to create its own teaching materials for free or minimal cost. It’s not like their are a dearth of linear algebra resources for free on the web. But that is not our world.

Finally, as a point of comparison, it just so happens that I still have my linear algebra textbook from undergrad.

What a textbook cost in 1992
What a textbook cost in 1992
Linear Algebra for Calculus, K. Heuvers, J. Kuisti, et al.
Linear Algebra for Calculus, K. Heuvers, J. Kuisti, et al.








$13.35 in 1992 would be $22.64 today. Amazon lists the current edition today for $111. Hmm.