Deferred maintenance

Over the weekend, I found myself with a small block of free time with absolutely no agenda. This luxury usually doesn't happen very often. On most days, I might just plop down in front of the television or a computer screen and while away the time. Today, I decided to do some deferred maintenance on our home.

Leading up to our front door is a stone walkway. My own version doesn't look like this photo below, but it gives you an idea.
 (Photo:  Wikimedia Commons, C.G. P. Grey)

Between the stones is fill made of stone chip. Every year, weed seeds float into the area and germinate. I often get too lazy to do much of anything about it. Unfortunately, it really does look terrible. Since I had the time, I forced myself to address it. Here were the main enemies:
 (Photo:  www.better-lawn-care.com)

About fifteen minutes into the exercise, I started to regret it. After all, the sun was streaming down and it was a humid 90+°. Sweat started dripping into the area I was weeding. My fingers actually started to turn black from a mixture of weed sap, sand, and stone dust. After a bit more than an hour, I was done.

It was certainly gratifying to look at the path after I was done. I felt as if my sacrifice had certainly made my world better in some small way.

I am sure that there are many areas at work that have languished because we've been so caught up in the day to day. The next time you find an odd block of free time at your disposal, I hope that you can also work on similar chores for yourself!

Delaying the inevitable

This morning, I found two gray hairs. There is an odd symmetry--one on each temple just above the ear. Nestled among their jet black neighbors, they certainly stand out prominently when you are looking for them.

While there are many ways to look at it, I suppose I should consider myself lucky. I've generally been able to avoid this for most of my life. Now that I am advancing in years, this is usually the inevitable result.

It's always amusing when you are watching others go to comical lengths to deny or delay the inevitable. It's not so funny when you see it in the mirror yourself.

Oddly enough, I almost feel resigned to my fate. There is no sense in getting upset over it. I could just pluck them out if they bothered me that much. I thought about it as I looked in the mirror this morning after my shower, but decided against it.

Lately, I've been reminded more and more of the slow erosion of my current state of being. As I wander down the hallways at work, the faces around me grow slightly more hazy until they are almost up on top of me. It seems like my sight is narrowing and closing in ever more tightly. I suppose the hair is just another gentle reminder that nothing is permanent.

I'm really glad that I'll get the chance to play ball with my son later today. It will help remind me of better days and the overall joy in being alive.

Context is everything

Near the end of our second hour of shoveling and snow throwing, my wife declared, "We are not going to live in Massachusetts when we are old."

To which I replied, "Define old."

Partial credit?

Original post:  Jan 28, 2015

Yesterday, a major storm system swept through the Northeast. It delivered over 30" of snow to some parts of Massachusetts. My town ended up with over two feet. The Mansfield office is still closed today to clean up.

Despite the wreckage in our area, there are still cries of fury. Most of them are coming from the New York area. In an unprecedented move, the governor shut down the subway (for the first time ever) and banned road travel. There were original predictions of two to three feet in NYC. They ended up with only about a foot of snow. That level is a nuisance, but should not have crippled the city.

Part of the challenge is that weather forecasting is still an inexact science. Weather fronts do not always move in straight lines. While our technology has improved dramatically, we still don't understand all of the variables that go into weather on a moment-by-moment basis. Air pressure near the ground can be very different at 100 feet up and dramatically different at 10,000 feet. All of this compexity means that it isn't humanly possible to make perfect predictions. It turns out that the forecasters were right--they just missed the target slightly. The storm passed fifty miles east of New York and hammered Long Island and New England.

Since NYC is such a major media market, I fully expect this mini-controversy to fill lots of air time on the 24 hour news circuit. There will be fingers wagging and heads shaking--particularly the next time another great storm heads towards that metropolitan area. Still, I am glad that we are taking precautions even if the events fizzle out. I have never personally been stranded on an icy roadside miles from home in impassable traffic. I hope I never have to experience that tragedy.

Would you trust a robot?

Original post:  Jan 27, 2015

Would you trust a robot to pick out a wine for you?

If you did and it picked out a bottle that you didn't like, would you give it a second chance?

As technology is inserted into new areas of our lives, we will have to trust more and more decisionmaking power to fancy algorithms. Are we ready for the loss of control?

A recent study showed that it isn't quite as simple as placing blind faith in our computer overlords:

In a paper called “Algorithm Aversion: People Erroneously Avoid Algorithms After Seeing Them Err,” forthcoming in the Journal of Experimental Psychology: General, the University of Pennsylvania researchers Berkeley J. Dietvorst, Joseph P. Simmons, and Cade Massey asked subjects to consider the challenge of making a difficult forecast: predicting either MBA students’ academic success or states’ airline traffic. They could choose to tie what they earned to either the prediction accuracy of a human (usually themselves) or that of a statistical model. Before making their decision, they first saw the model’s performance on several trial runs, or saw the human’s performance, or both, or neither.

When they had not seen the statistical model perform on the trial runs, the majority of subjects bet on the model being more accurate in the money-earning round—they chose to tie their earnings to its performance rather than the human’s. But if they had seen it perform, the majority bet on the human. That’s despite the fact that the model outperformed the humans in every comparison, by margins ranging from 13 to 97 percent. Even when people saw the performance of both the model and the human in the trial runs, and saw that the model did better, they still tended to tie their winnings in the earnings round to the human over the model. They were more accepting of the human’s mistakes.

These findings surprised the researchers. They had expected people to shy from algorithms at first and then change their minds after seeing their superior performance, Dietvorst says. Instead, he says, they “found completely the opposite.”

One of the study authors speculates that people are less likely to trust computers when it touches on their health or their ego. We may feel that human  judgment can provide superior advice by weighing variables no computer can possibly comprehend. That belief may not actually be supported by the data:

There can be a real cost to this aversion. A 2000 meta-analysis summarized 136 studies comparing predictions made by experts with those made by equations, in areas including medical prognosis, academic performance, business success, and criminal behavior. Mechanical predictions beat clinical predictions about half the time, while humans outperformed equations in only 6 percent of cases. Those are judgments with significant implications for our lives, and it’s a genuine loss to ignore a system that can give us much more accurate answers.

A possible solution might be trying to incorporate some user feedback to help return a level of control to the user:

The researchers at Penn are now exploring why people abandon algorithms so quickly. There may be a hint in the fact that subjects judged the statistical model as worse than humans at learning from mistakes and getting better with practice. Perhaps people could learn to trust algorithms more if they were told that computers can learn. Balfoort says that once you inform customers that WineStein gets better with feedback, “you get a satisfied nod.”

In current work, Dietvorst is finding that giving people the chance to alter an algorithm’s forecast even a trivial amount increases their adoption of it over a human counterpart, from less than 50 percent to more than 70 percent. People “don’t want to completely surrender control,” he says. Ironically, the user’s adjustment usually makes the computer forecast slightly worse, but at least it gets them to use it.

What do you think?

Here is a link to the full article:  Why we need to learn to trust robots - Ideas - The Boston Globe

Like a fresh sheet of ice

Original post:  Jan 26, 2015

Life offers all kinds of unexpected intersections. They often are hidden in plain sight while we go about our daily routines.

Yesterday, our family went ice skating for the first time. While my wife and I had been on skates before, it had been many years ago. Our boys had never actually been on the ice, so we expected a number of falls along the way.

We were there for roughly two hours. It was a bright, sunny day and we were trying to make the most of it. With a winter storm fast approaching (and expected to dump two feet or more of snow on us tomorrow), it might end up being the last outdoor activity for some time.

In order to propel you along the surface, the ice skate actually makes tiny cuts that enable a thin layer of water. This action allows the skater to glide along. It also leaves behind fine ice shavings that eventually accumulate into larger chunks.

Over the course of time, these chunks will continue to build and make it increasingly difficult to sustain your travel. It gets harder and harder to skate because your skate can't slice as effectively for those long, elegant strokes.

About 2/3 of the way into our session, management cleared the ice for the Zamboni. If you have never seen this machine in action, it is actually fascinating to watch. It will scrape off the assorted chop on the top of the ice and spray a fresh, thin layer of water. The water will eventually freeze and form a fresh, glassy surface.

When they let us back out on the ice about ten minutes later, you could notice the difference immediately. It took much less effort to skate. Each step propelled you into an instant glide. I took a few quick spins around the oval. At one point, I carried a little too much speed and my feet went out from under me. I landed with a thud on my right hip. It hurt much more than I expected. Ice, after all, is a fairly unforgiving surface. Luckily, I sustained no more than a slight bruising to both my backside and my ego.

I only fell once; I can only imagine how my boys felt (they were both soaking wet from being covered in ice shavings that eventually melted). Fortunately for us, they never complained. It seems youth does cushion the blow and speed recovery time.

In this first week ahead with our new adventure, I sat back and recognized a number of parallels to our current situation.

Here's wishing you smooth skating with no falls along the way!

Taking a hard look at yourself

Original post:  Jan 20, 2015

We've all done it. We watch a situation unfold and immediately begin criticizing the execution. If only the participants had done this or that, then the outcome would have been incredibly different. We're so sure that we have the answers for others.

The real challenge begins when others apply the same lens to us. Suddenly, we're not so sure that they understand all of the intangibles that went into the decision. If only those armchair judges could sit in our shoes then they would understand all of the complex reasoning that went into our different handling of the situation.

It's so easy to pick out the faults in others. It's really difficult to use the same harsh grading scale on ourselves.

Over the weekend, I spent some time with extended family members. When you are dealing with people you may only see once or twice a year, you don't get a true picture. You only get snapshots and glances that must be extrapolated into a fuller picture. The classic example is the relative's story of meeting a rock star as part of a TV audience. Because they didn't personally greet each and everyone and only gave out a crappy participation gift, this star went from a classy human being to a shady cheapskate. Unfair? Perhaps, but it's what happened.

At this particular event, we had a smaller session with a subset of the family analyzing how we could solve the issues. The loudest voice came from an older relative who calmly explained exactly what should have been done to resolve this really tricky dispute between two other family members. If they would only bring their disagreements out in the open, then they would be able to come to an amicable resolution! True, but getting to that point would be near impossible since the pair weren't speaking to each other at the moment. What made it even more ironic was that this particular relative had a similar dispute with another family member that went for years and was never resolved because they did not speak to each other!

Since it is still January, I resolve to try to use the same judgment on myself that I would first apply to others. I may not always succeed, but I will try to remind myself to tone down the criticism wherever possible.