Software generally gets better over time, but this does not mean it’s getting better and better every day in every way.
Software quality has so many dimensions that it is impossible to make progress along every front with every release of every product. Life’s full of trade-offs. A successful software project will improve over time in the ways that matter to most of its constituents. That doesn’t mean that every user will be better served by each subsequent release, especially if the user base changes.
It’s inevitable that some software will get worse over time, as far as a minority of users is concerned. See, for example, this post about Word Perfect.
Commercial software may disappoint tech savvy users over time as such users make up a diminishing proportion of the software market. One reason programmers often prefer open source software is that they are the target market for the software.
The dynamics of open source software are more complex. Software written by volunteers is driven by what volunteers find interesting. This could result in software becoming wonkier over time, delighting geeks and alienating the general population. However, many volunteer developers find it interesting to make software easy to use for a wide audience.
And not all open source software is developed by volunteers. For example, the majority of work on the Linux kernel is done by corporate employees. The companies paying for the development have a commercial interest in the software, even though they don’t sell the software. Commercial and non-commercial are fuzzy concepts.
A company may sponsor an open source project because they rely on the software. Or maybe they want to undermine a competitor who sells an analogous project. Or maybe they’re sponsoring a project because they want to crow that they sponsor open source projects. Each of these motivations could make a project better for a different constituency.
I’ve read a fair number of business books, but I stopped reading them when they all started to sound alike. I have limited time for reading and so I want to read books that “blow my hair back” as Will Hunting would say.
I made an exception to my abstinence from business books when Guy Kawasaki’s publisher offered me a review copy of his new book Enchantment. The book confirmed my decision to lay off the business literature. I was surprised how much of it I’d already read elsewhere before it arrived. Much of it is a compilation of ideas and stories that were popular on the web last year. Enchantment isn’t a bad book, it just isn’t very original.
This made me think of Robert Ghrist’s quip about new books:
Reading anything less than 50 years old is like drinking new wine: permissible once or twice a year and usually followed by regret and a headache.
I can’t imagine that Enchantment would stand such a test of time. Hardly anyone will be reading it a couple years from now, much less 50 years from now.
Stephen Stigler [1] compares least-squares methods to the iPhone:
In the United States many consumers are entranced by the magic of the new iPhone, even though they can only use it with the AT&T system, a system noted for spotty coverage — even no receivable signal at all under some conditions. But the magic available when it does work overwhelms the very real shortcomings. Just so, least-squares will remain the tool of choice unless someone concocts a robust methodology that can perform the same magic, a step that would require the suspension of the laws of mathematics.
In other words, least-squares, like the iPhone, works so well when it does work that it’s OK that it fails miserably now and then. Maybe so, but that depends on context.
In his quote, Stigler argues that Americans feel that missing a phone call occasionally is an acceptable trade-off for the features of the iPhone. Many people would agree. But if you’re If you’re on a transplant waiting list, you might prefer more reliable coverage to a nicer phone.
It’s not enough to talk about probabilities of failure without also talking about consequences of failure. For example, the consequences of missing a phone call are greater for some people than for others.
Least-squares is a mathematically convenient way to place a cost on errors: the cost is proportional to the square of the size of the error. That’s often reasonable in application, but not always. In some applications, the cost is simply proportional to the size of error. In other applications, it doesn’t matter how large an error is once it above some threshold. Sometimes the cost of errors is asymmetric: over-estimating has a different cost than under-estimating by the same amount. Sometimes you’re more worried about the worst case than the average case. One size does not fit all.
[1] Stephen M. Stigler, The Changing History of Robustness, American Statistician, Vol. 64, No. 4. November 2010. (Written before Verizon announced it would be supporting the iPhone)
Here are a couple variations on the tragedy of the commons, the idea that shared resources can be exhausted by people acting in their individual best interests.
The first is a recent podcast by Thomas Gideon discussing the possibility of a tragedy of the pseudo-commons. His idea of a pseudo-commons is a creative commons with some barriers. He gives the example of open core companies.
The other is Michael Heller’s idea of the tragedy of the anti-commons. If too many people own a resource, the difficulties in coordination may keep the resource from being used effectively. Having too many owners can create problems similar to those caused by having no owners.
If you’re looking for something to blog about, it would be interesting to compare the pseudo-commons and the anti-commons in depth.
Never attribute to malice that which is adequately explained by stupidity.
At first it seems just an amusing little aphorism, something you might read on a bumper sticker, but I believe it’s profound. It’s a guide to understanding so much of the world. Here I’ll focus on what it says about corporations.
I hear a lot of complaints that corporations are evil. Sometimes corporations in general, but more often specific corporations like Apple, Google, or Microsoft. I don’t deny that large, powerful corporations have the potential to do harm. But many accusations of malice are misattributed frustrations with stupidity. As Grey’s law says, any sufficiently advanced incompetence is indistinguishable from malice.
Corporations aren’t evil; they’re stupid. Not stupid in general, but in a specific way: they don’t handle edge cases well.
Organizations scale by creating procedures to replace human judgment. This is mostly a good thing. For example, electronic devices are affordable in part because companies can hire unskilled teenagers rather than electrical engineers to sell them. But if you have a question or problem that’s off the beaten path, you’re out of luck. Many complaints about evil corporations come from outliers, the 1% that corporations strategically decide to ignore. It’s not that that the concerns of the outliers are not legitimate, it’s that they are not profitable to satisfy. When some people say that a corporation is evil, they should just say that they are outside the company’s market.
Large organizations have similar problems internally. Policies written to handle the most common situations don’t handle edge cases well. For example, an HR department told me that my baby girl couldn’t be added to my insurance because she wasn’t born in a hospital. Fortunately I was able to argue with enough people resolve the problem despite her falling outside the usual procedures. It’s harder to deal with corporate rigidity as an employee than as a customer because it’s harder to change jobs than to change brands.
… the so-called demand for simplicity is a myth whose time has passed, if it ever existed.
Make it simple and people won’t buy. Given a choice, they will take the item that does more. Features win over simplicity, even when people realize that features mean more complexity. You do too, I’ll bet. Haven’t you ever compared two products side by side, feature by feature, and preferred the one that did more? …
Would you pay more money for a washing machine with fewer controls? In the abstract, maybe. At the store, probably not.
Donald Norman’s assessment sounds wrong at first. Don’t we all like things to be simple? Not if by “simple” we mean “fewer features.”
A general theme in Living with Complexity is that complexity is inevitable and often desirable, but it can be managed. We say we want things that are simple, but we really want things that are easy to use. The book gives several examples to illustrate how different those two ideas are.
If something is complex but familiar and well designed, it’s easy to use. If something is simple but unfamiliar or poorly designed, it’s hard to use.
In the December 27 episode of EconTalk, Pete Boettke summarizes basic economics as follows: If you don’t have the three P’s, you can’t have the three I’s.
… the whole of economics can be reduced to a single lesson, and that lesson can be reduced to a single sentence. The art of economics consists in looking not merely at the immediate but at the longer effects of any act or policy; it consists in tracing the consequences of that policy not merely for one group but for all groups.
Lately I’ve read several writers critical of popular business books. One oft-repeated criticism is that some of the companies featured in Good to Great aren’t doing so great and therefore the book was wrong.
I’ve never looked at business books this way. I see them as literature. They have stories that may provoke your thinking, but they’re not providing scientific laws. I wouldn’t say Good to Great was “wrong” any more than I’d say To Kill a Mockingbird was “wrong.”
The difference, of course, is that novels don’t aspire to an aura of scientific certainty while business books do. Business books often presume to offer universal laws when they only offer anecdotes. That doesn’t mean these books are not valuable. Anecdotes can be quite valuable. However, the value of an anecdote lies not in what it literally conveys but in the thoughts it stirs in your mind.
Business authors sometimes analyze reams of data. I wish they wouldn’t bother. I prefer business writers who don’t pretend to be scientific. “Here’s what I think. Here’s a story that illustrates my point. Your mileage may vary.”
If someone does produce a high-quality study of some class of companies at some point in time, the study is still an anecdote to a reader in different circumstances. A statistically rigorous study of Fortune 500 companies is not directly applicable to someone running a taco stand. It may not even be directly applicable to someone running a Fortune 500 company a few years later.
The taco stand owner may get as much insight from someone’s memoir of running a single large company as from a rigorous study of hundreds of large companies. (He may also get valuable insight from To Kill a Mockingbird.)
P.S. Although I’m saying business books are like literature, I must add that I hate business parables. The ones I’ve read are just terrible. No one would ever read one of these books for its literary merit, and when you strip away the campy prose there isn’t much content left.
Arnold Kling argues in his interview on EconTalk that knowledge is becoming more decentralized while power is becoming more centralized. Therefore more decisions will be made by people who don’t know what they’re doing.
His strongest point is that knowledge is being decentralized. Jobs have become more specialized, academic disciplines have become more narrow, people have become more interdependent, etc. It’s harder to defend a blanket statement that power is becoming more centralized. Kling gives important examples of power consolidation, but one could also give examples of an opposite trend. It would be easier to argue that at least in some contexts power is becoming more centralized.
If in some context power is becoming centralized while knowledge is being decentralized, it is inevitable that more decisions will be made without adequate knowledge. This sounds like a breeding ground for a sort of antibiotic-resistant strain of the Peter Principle.
The earliest versions of Windows and Mac OS used cooperative multitasking. A Windows program would do some small unit of work in response to a message and then relinquish the CPU to the operating system until the program got another message. That worked well, as long as all programs were written with consideration for other programs and had no bugs. An inconsiderate (or inexperienced) programmer might do too much work in a message handling routine and monopolize the CPU. A bug resulting in an infinite loop would keep the program from ever letting other programs run.
Now desktop operating systems use preemptive multitasking. Unix used this form of multitasking from the beginning. Windows starting using preemptive multitasking with Windows NT and Windows 95. Macintosh gained preemptive multitasking with OS X. The operating system preempts programs to tell them it’s time to give another program a turn with the CPU. Programmers don’t have to think about handing over control of the CPU and so programs are easier to write. And if a program runs into an infinite loop, it only hurts itself.
Computers work better with preemptive multitasking, but people work better with cooperative multitasking.
If you want to micro-manage people, if you don’t trust them and want to protect yourself against their errors, treat them like machines. Interrupt them whenever you want. Preemptive task switching works great for machines.
But people take more than a millisecond to regain context. (See Mary Czerwinski’s comments on context re-acquisition.) People do much better if they have some control over when they stop one thing and start another.
The August 2010 issue of Wired has an interview with Fred Brooks. The interviewer, Kevin Kelly, asks Brooks why he wrote his popular book The Mythical Man-Month. Here’s Brooks’ response.
As I was leaving IBM, Thomas Watson, Jr. asked me, “You’ve run the hardware part of the IBM 360, and you’re run the software part; what’s the difference between running the two?” I told him that was too hard a question for an instant answer but that I would think about it. My answer was The Mythical Man-Month.
I was looking at a word-of-the-day calendar the other day and the word was peripeteia. I didn’t remember what the word meant, but I remembered that I heard someone use it in a presentation.
Eventually I remembered that Mike Rowe had used peripeteia in his TED talk. The word means a sudden or unexpected reversal of circumstances. Rowe begins his talk by describing a peripeteia moment he had while castrating sheep. He uses this story to illustrate how our ideas about work can be very wrong.
Many people with jobs have a fantasy about all the amazing things they would do if they didn’t need to work. In reality, if they had the drive and commitment to actually do those things, they wouldn’t let a job get in the way. Unfortunately, if given a lot of money, they are much more likely to end up addicted to crack, or even worse, World of Warcraft. If you’ve been institutionalized your entire life (school, work, etc.), it can be very difficult to adjust to life on “the outside”.
