Blayne Sucks

Although this was produced a couple months ago now, I wanted to post a link to John Stossel’s Politically Incorrect Guide to Politics. It’s essentially a 45 minute introduction to basic libertarianism (without using big words like libertarianism) and a thought-provoking show about the role government should play in our lives. You can either watch it on the six embedded YouTube videos below or find it here on ABC’s website.

Malcom Gladwell’s recent New Yorker article compares “the quarterback problem” to the challenge of finding a good teacher. It’s an interesting article, but it is, perhaps, too narrow in its focus.

For those who don’t know, the quarterback problem is defined as the extremely difficult task of selecting a quarterback to play in the NFL from the pool of college football quarterbacks. It’s deceptively challenging to do this because there’s so much data available and so many ways to rank college football quarterbacks. However, the college football game is so different from the NFL game that success at the college level seems to have very little correlation, or perhaps no correlation, to success at the professional level.

One of the best examples of this is the comparison of Peyton Manning and Ryan Leaf, who were both extremely successful college quarterbacks drafted first and second in the 1998 NFL draft. Most experts thought it was a toss-up as to which of these two would have a better career. Of course, it’s clear to everyone now that Peyton Manning is a lock for the Hall of Fame while Ryan Leaf is famous for being a complete bust in the NFL.

The key element of the quarterback problem is that past results simply aren’t useful in predicting future success. Gladwell argues that this is also true of selecting good teachers. He claims that the usual metrics used to measure hiring and promotions for teachers, such as master’s degrees, teaching certifications, and other cognitive standards, are just as useless in attempting to determine a good teacher as college football statistics are in trying to determine a successful NFL quarterback.

Another important element of the quarterback problem is that the difference between ‘good’ and ‘bad’ is extremely large, potentially several orders of magnitude. There are very few ‘good’ quarterbacks in the NFL. There aren’t even very many quarterbacks decent enough to serve as an emergency backup. The quarterback position in the NFL may be the single toughest position to play in all of professional sports. Gladwell argues that the same is true of teachers:

Suppose that Mrs. Brown and Mr. Smith both teach a classroom of third graders who score at the fiftieth percentile on math and reading tests on the first day of school, in September. When the students are retested, in June, Mrs. Brown’s class scores at the seventieth percentile, while Mr. Smith’s students have fallen to the fortieth percentile. That change in the students’ rankings, value-added theory says, is a meaningful indicator of how much more effective Mrs. Brown is as a teacher than Mr. Smith.

It’s only a crude measure, of course. A teacher is not solely responsible for how much is learned in a classroom, and not everything of value that a teacher imparts to his or her students can be captured on a standardized test. Nonetheless, if you follow Brown and Smith for three or four years, their effect on their students’ test scores starts to become predictable: with enough data, it is possible to identify who the very good teachers are and who the very poor teachers are. What’s more—and this is the finding that has galvanized the educational world—the difference between good teachers and poor teachers turns out to be vast.

It follows that if you want a school system filled with good teachers, then you have to be willing to identify the poor teachers and get rid of them. This is the only solution to the quarterback problem. It’s a brutal process for both the teachers and the administration. Time Magazine recently had a cover story on Michelle Rhee’s unusual approach to improving schools in the nation’s capital, which is attempting to implement this brutal process.

Rhee wants to solve the quarterback problem the only way possible: by mitigating its effects. Simply put, if you can’t identify good teachers without seeing how they perform in the classroom, then you have to hire a bunch of teachers, watch their classroom performance, identify those that are succeeding, and reward them. Similarly, you have to identify teachers that are failing and eliminate them. Time’s article does a good job explaining why doing these two things is extraordinarily complicated in the teaching industry.

Of course, this is exactly how they solve the quarterback problem in the NFL. On-field performance is everything. Many of the best quarterbacks were identified as such by their play in real NFL games as backups for injured quarterbacks. Matt Cassel is a great example. In college, he never started a game and served as a backup for Carson Palmer and Matt Leinart. He was drafted into the NFL and played as a backup for Tom Brady, who suffered a season-ending injury in the first game of the 2008 season. Brady’s injury made Matt Cassel a starting quarterback for the first time since high school, which would undoubtedly determine his future in the NFL. If he played well, he would likely be rewarded with a starting role for another team during the off season. If he played poorly, he would fall into the nameless abyss of all the other failed NFL quarterbacks.

After reading Gladwell’s article, I had to wonder, how many other professions are like that? Surely the quarterback problem isn’t just limited to teachers and NFL quarterbacks. The first thing that came to my mind was a Paul Graham essay about great programmers, which is really a must-read for anyone in the software industry. In it, Graham talks about the nature of great programmers, and summarizes the problem of identifying them by saying, “The problem is, if you’re not a hacker, you can’t tell who the good hackers are.” Fred Brooks also talks about the vast difference between a great programmer and an average programmer in The Mytical Man-Month. Here’s Fred Brooks on great software designers:

The differences are not minor – it is rather like Salieri and Mozart. Study after study shows that the very best designers produce structures that are faster, smaller, simpler, cleaner, and produced with less effort. The differences between the great and the average approach an order of magnitude.

Clearly, selecting a software engineers fits the definition of the quarterback problem. It would be very interesting to study how the extreme challenge of creating a start-up company performs as a system for identifying great programmers.

Apparently, some people believe there’s a quarterback problem in selecting good lawyers. Although, I have no particular experience with this, I think the environment in which lawyers at big law firms operate is strikingly similar to the ideal solution to the quarterback problem. There’s an incredibly small percentages of lawyers who end up making partner at a big law firm, which indicates to me that there’s a quarterback problem in trying to hire a big law firm partner.

I’ve also seen the suggestion that selecting a mate is a version of the quarterback problem, but I personally think that’s taking things too far. I don’t think that people really have an objective idea of what a good mate is, let alone what metrics to use in measuring potential mates. Furthermore, the role of being a “mate” really isn’t the same thing as having a job.

I believe the quarterback problem is potentially much more prevalent than people currently recognize. I also think that the solution to the quarterback problem is clearly defined. The two important lessons to learn and apply from the quarterback problem:

• Don’t be afraid to give people a chance. They might surprise you.
• Don’t be afraid to make a change when things aren’t working out.

These two steps are the best known solution to the quarterback problem. What other fields could benefit from implementing them? If you have any suggestions for other areas where this problem seems to occur, please mention them in the comments.

If one were to take a national poll on the most important year in United States history, 1776 would easily be a top contender. Thomas Paine published Common Sense in January. Although not an American, Adam Smith published The Wealth of Nations, which had (and continues to have) extraordinary influence on American financial history. The Continental Congress signed the The Declaration of Independence that summer. Perhaps most importantly, George Washington held together the young and inexperienced “rabble” that was the Continental Army throughout the course of that entire year and eventually through the conclusion of the war in 1783. This is the story told by David McCullough’s novel 1776.

Although 1776 is the first book by David McCullough that I have ventured to read, I had most certainly heard of the author before I began reading it. McCullough is one of the most decorated living historians in America, and I would be astonished if more than a few American readers haven’t heard of him. He has twice won the Pulitzer Prize and twice won the National Book Award. He has also received the highest honor bestowed to American civilians: the Presidential Medal of Freedom.

As a result of the author’s fame and previous success, I had extremely high expectations for 1776 in several areas. First, McCullough is known as a fastidious researcher, so I was expecting the book to provide details on the inner workings of the fledgling American Revolution. Second, McCullough is often praised as an exemplary story teller, and with the material he has to work with in the American revolution, I was expecting something amazing. Third, McCullough used many of his notes originally compiled in writing his biography of John Adams, so I was expecting much of the book to deal with the political relationship Washington maintained with the Continental Congress.

In regard to my first expectation, I was quite pleased with the details found throughout the novel. If anything, these details were the most redeeming aspect of the book to those who already know the story quite well. McCullough goes out of his way to drop some now-famous names of people who were at the time merely rising stars, including Alexander Hamilton, James Madison, and Aaron Burr. I was also quite pleased to see many misconceptions dispelled. For example, I grew up learning that the Hessians in the Battle of Trenton were drunk or hungover at the time of the attack. Of course, this has been dispelled in many accounts, as McCullough dispels it here, but it was through this book that I learned the truth of the matter stated plainly.

As to my second expectation, McCullough is certainly a master story teller. Even knowing this beforehand did not prepare me for the fluidity of the book. I was truly surprised at how easy to read it is. It flows so quickly and effortlessly that I found my self reading it in large chunks. One of the primary reasons that I even picked the book up was to find some respite from the large amount of technical reading I have been doing recently, and I am pleased to say that it did not disappoint in the least, even though I was already quite familiar with the major events of the year.

Lastly, I was expecting a focus on Washington’s political discourse with the Continental Congress over the course of the year. This expectation was simply not met. Although there is some discussion of this important relationship, it was certainly not a highlight of the book. Each discussion of the relationship feels unbalanced because the book does not introduce or develop most of the important characters in the Continental Congress. I was left wondering if that is due to the coverage it received in his biography of John Adams, which I will endeavor to read.

My one major disappointment with the book was the artificial framing of the subject. Although 1776 was an extremely important year, it was just one of eight years (1775-1783) that comprised the American Revolution. Quite a few important events are not covered by this book including the winter in Valley Forge, enlisting the aid of France, signing the Treaty of Paris, and George Washington stepping back into the role of a civilian. Perhaps feeling a bit cheated at the missing events was somewhat inevitable. The entirety of the American Revolution itself has been the subject of many books, so I can understand why McCullough would not want to plow the same field all over again. However, I have no doubt that his talents would have made the remaining years and events of the Revolution exceedingly enjoyable stories to read.

On the whole, I can heartily recommend 1776. Owing to its easily accessible nature, it is perhaps best geared towards the average American, but there are certainly details that may interest those more deeply involved in studying history.

As a technologist with a strong interest in computer security, privacy, and public policy, I am naturally drawn to the topic of electronic voting. I have written about electronic voting several times before, including this piece on Ed Felten’s work. Recently, I have seen lists of things things could have gone wrong and some lists of things that actually did go wrong. I have even seen a hilarious account of the worst case scenario, but the most interesting accounts that I’ve seen have been personal accounts of computer science professors who volunteered to operate the polls as election workers.

Avi Rubin, a Professor of Computer Science at Johns Hopkins and director of the ACCURATE Voting center, wrote a post describing his experience working the polls and posted it only minutes before most news outlets announced that Barack Obama will be the 44th President of the United States. Professor Rubin is the author of the book Brave New Ballot, an excellent book on the dangers of electronic voting machines that I have reviewed here. His experience at the polls in Maryland describes the very practical and non-technical aspects of just what a poll worker does during the day.

Steven Bellovin, a Professor of Computer Science at Columbia, also wrote about his experience as an election official. Professor Bellovin is another well-respected authority on computer security whose post focuses on the non-technical details of the responsibilities of poll workers in New Jersey. Andrew Appel, a Professor of Computer Science at Princeton, also wrote about the use of voting machines in New Jersey.

Both New Jersey and Maryland used Direct-record electronic voting machines, which have a myriad of security concerns that have been detailed extensively elsewhere. Essentially, DREs store the official record of an election in an electronic form rather than a paper form. If you are interested in some of the problems with DREs and proposed solutions to those problems, then you should check out the USACM’s page on electronic voting.

You may be asking yourself: Why would a computer science professor volunteer to work a poll as an election official? It’s not like there’s anything technical going on there. Well, any computer security expert will tell you that the first line of defense must be physical access. This means that you can have all technology you want, all the cryptography you want, and spend all the money you have and still not be secure without common sense. There was a great video on No-Tech Hacking at DefCon in 2007 which covers what I’m talking about.

Physical access is one of the key problems with DREs: thousands of people must have physical access to the machines themselves to cast their vote. The environment is filled with opportunities for absolutely simple no-tech hacking. Even if these systems weren’t notoriously bad in terms of the technology used, the physical access alone makes these devices difficult to secure.

The challenges of physical access and the stakes of a Presidential election are both great reasons that computer science professors are interested. It’s a unique opportunity to see how these machines are actually used, and some of their observations are excellent. Their posts are worth reading if you’re interested in electronic voting or computer security: Avi Rubin’s post; Steven Bellovin’s post.

This year’s election has already set early voter turnout records in North Carolina by a 40% increase over the previous records. However, most of the interest in the election is a result of the Presidential race. North Carolina has voted Republican in 9 of the last 10 Presidential elections, but it may be leaning towards electing Democratic candidate Barack Obama this year. For voters in North Carolina, the down ticket races are at least as interesting if not more so than the Presidential race.

First, there’s an incredibly competitive race for the Senate. Incumbent Elizabeth Dole was once thought to be a invulnerable in her reelection campaign, but challenger Kay Hagan may actually win the seat. The race becomes even more important because the Democrats may be able to obtain a filibuster-proof majority of 60 senate seats if Hagan wins.

Second, there’s another incredibly close race for governor, which is truly amazing considering that 27 of the last 30 governors of North Carolina have been Democrats. (Yes, North Carolina historically favors Democrats as Governors and Republicans as Presidents.) The string of Democrat governors dates all the way back to reconstruction after the civil war. Popular Charlotte Mayor Pat McCroy is the Republican nominee trying to overcome this history, while current Lieutenant Governor Beverly Perdue is trying to become the first female governor of North Carolina. There’s also a Libertarian candidate for Governor that is doing well for a third party candidate: Michael Munger, who is currently the head of the political science, economics, and public policy departments at Duke University.

If you live in North Carolina and are at all interested in the Governor’s race, then I would urge you to watch the hour-long debate on YouTube by all three candidates. (There are six parts to the debate: Part 1, Part 2, Part 3, Part 4, Part 5, and Part 6.) At the very least, you should check out this summary of the debate.

There are many other important down ticket races. Usually, these down ticket races don’t even register in the minds of voters, but if all politics is local, then why are so many of these important races unkown? I urge you, wherever you live, to go online and at least find the names of all the people who will appear on your ballot in November. Take the time to Google them. You might find it more interesting than you thought, and either way some of these people will have the power to control a part of your life.

[Update: The New York Times has a brief editorial on a strange quirk in the North Carolina ballot. Even though North Carolina voters can vote using a single straight-ticket option, they still have to separately vote for President. This has resulted in unusually high numbers of North Carolina voters who simply do not have a recorded vote for President.  If you are curious what a North Carolina ballot looks like, you can find one on the State Board of Elections website. For more information on North Carolina voting, take a look at the 2008 Voter's Guide.]

[Update 2: Zach has an excellent post about the lack of attention paid to down ticket races over at In the Agora.]

Martin Fowler recently wrote something with which I found myself jarringly disagreeing. The post is about a concept called observed requirements.

Although I strongly disagree parts of his recent post, I did want to say upfront that I really like Martin Fowler’s work. Ever since I read Martin’s book UML Distilled, I have been a fan. For something that is meant to simplify understanding, UML always appeared overly complicated to me and his book does a nice job of focusing on making it useful. Martin is also a big proponent of Agile Methods and Extreme Programming, both of which have improved software development practices by turning software development on its head.

Martin’s post starts with this quote from the book “Mastering the Requirements Process,” which I read last spring. (Note: I read the first edition of this book, which contains the quote Martin uses. I have not seen the second edition. Then again, I only have the second edition of UML Distilled. Such is the life of a grad student.) Here’s the questionable quote:

Requirements are the things that you should discover before starting to build your product. Discovering the requirements during construction, or worse, when you client starts using your product, is so expensive and so inefficient, that we will assume that no right-thinking person would do it, and will not mention it again.

Suzanne and James Robertson

When I first read this quote, I had pretty much the same initial, gut reaction that Martin had. It advocates an extreme position in a field where many different development methodologies have been successful. However, Martin’s post takes a position at the other extreme and is equally questionable.

Martin seems to think that the word “requirement” itself is a bad word, and that requirements are incompatible with agile methods. He claims that web sites developed using agile techniques violate the “waterfallish” requirements process and suggests four specific ways that such web sites can observe requirements throughout development:

• Look at what people are trying to do with the site and provide easier ways for them to do it.
• Look at where people are abandoning doing something, and look for ways to fix whatever was frustrating them.
• Build a new feature and see if people use it.
• Build an experimental feature and make it available to a subset of the user base. Not just can you see if they like it, you can also assess how much load it puts on your servers.

He goes on to say that web sites should monitor how their users actually use their site because what a user really does is much more accurate than what a user says they do. First, let’s get this out of the way. Suzanne and James Robertson dedicate a significant portion of their book (about half a chapter) to requirements elicitation through observing users! Let’s look at two more quotes from the first edition of their book.

First quote:

It is unlikely that many users can explain what they do in enough detail for the developer to completely understand the work, and thus capture all the requirements.

Second quote:

For example, one of our clients, [...], had 20 different products. [...] The way the users handled each of these products at first looked to be different. However, a common pattern emerged as we studied the structure of the work – we were looking for similarities, not differences. We observed that each product was in fact a different way of [...]. The end result was that we found a common set of requirements, and were able to make a single core implementation, and then dress it differently for each of the products.

I have edited the second quote to remove project-level details and focus on the “observed requirements” concept. Quite simply, I don’t understand how these quotes are irreconcilable with Martin’s four suggested approaches to observing requirements. In fact, they seem to be quite compatible. The jarringly disagreeable part of his post is that Martin paints requirements as a software artifact that can only be used in Waterfall development, which is completely untrue.

Second, let’s talk about requirements. Requirements can, and should, be a part of any agile method of development. They answer a critical question: “why?” In the case of an observed requirement, the answer is obvious: “Because that is, by definition, exactly what the user wants or needs!” In fact, requirements are even easier to integrate into the agile process than other software development processes. The regular meetings with customers provide a great opportunity for requirements-based techniques, but agile proponents typically eschew actually documenting any of the contextual information involved in these meetings in favor of self-documenting code and UML.

Self-documenting code has always seemed a bit silly to me. Just as an author can’t write to two audiences at once, a programmer can’t satisfy the compiler and provide complete documentation at the same time. Martin Fowler writes in UML Distilled (2nd Edition):

The fundamental reason to use the UML involves communication. I use the UML because it allows me to communicate certain concepts more clearly than the alternatives. Natural language is too imprecise and gets tangled when it comes to more complex concepts. Code is precise but too detailed. So I use the UML when I want a certain amount of precision but I don’t want to get lost in the details.

Many agile proponents like UML and in particular, use cases. Unfortunately, use cases, and other UML artifacts, typically don’t offer enough contextual information to answer “why” questions. (Though, they are excellent for answering “how” questions.) It is possible to augment use cases with contextual information. Later in UML Distilled, Martin says that developers should feel free to modify UML to meet their needs. Of course, once you have added the needed contextual information, you’re effectively just writing requirements.

Any agile proponent would find a lot of Suzanne and James Robertson’s book useful if they went into it with an open mind. Many of the techniques for discovering customer requirements could improve the efficiency of regular customer meetings in an agile development process. Conversely, many proponents of detailed requirements specs would find a lot of useful information in agile-based books like Martin Fowler’s Refactoring book and Kent Beck’s Extreme Programming Explained book.

Third, and finally, let’s talk about the current use of user interaction data as an “observed requirement.” The one thing in Martin’s post with which I completely agree is that observed requirements are extremely useful and haven’t been fully explored. As a privacy researcher, I think there are some unresolved issues for user data protection, but as a developer it is clear that this data can improve the product. The often cited example in this is Amazon.com’s book recommendation service, which I enjoy. For the moment, let’s set aside the privacy concerns because that could be a whole post in and of itself.

Martin mentioned at the end of his post that he hasn’t found much advice on leveraging customer website use for the express purpose of improving their systems. I don’t think the idea is being used as well as it could be, but it is out there. John Musa has been talking about Operational Profiles, which are effectively a set of observed requirements, for years as a way to improve software development. He’s even got his own book out there on the subject.

That’s the only work that I know that gives extensive, useful guidance on how to take user interactions with a software product and directly tie it back into the development process. I certainly don’t have all the answers here. If anyone knows another place where this concept has been studied, I would love to hear from you.

ABC News has an article on the eavesdropping of Americans that answers any remaining questions regarding the FISA Amendments passed this past summer. Essentially, the article details the use of surveillance systems to spy on ordinary Americans. Here’s a quote from the article:

“These were just really everyday, average, ordinary Americans who happened to be in the Middle East, in our area of intercept and happened to be making these phone calls on satellite phones,” said Adrienne Kinne, a 31-year old US Army Reserves Arab linguist assigned to a special military program at the NSA’s Back Hall at Fort Gordon from November 2001 to 2003.

Kinne described the contents of the calls as “personal, private things with Americans who are not in any way, shape or form associated with anything to do with terrorism.”

The article goes on to describe the nature of some of the phone call as pillow talk or phone sex. Some of the individuals involved were from the US Military, the International Red Cross, and Doctors Without Borders. Naturally, the Senate is investigating. The article further states that some especially juicy clips were saved by employees of the NSA.

Unfortunately, abuse of surveillance systems by insiders is nothing new. Bruce Schneier has shown us that surveillance cameras are abused and ineffective. Six well-known security and privacy researchers have warned about this sort of abuse with telephone surveillance as well (pdf).

The only thing that is remotely surprising about this is that we have specific details from whistleblowers, who are risking their careers and livelihood to tell us about this abuse. In this case, it is even more surprising that not one, but two independent whistleblowers came forward simply because the agency involved was the notoriously secretive NSA.

The GCHQ, which is the British equivalent of the NSA, recently dealt with its own whistleblower: Katherine Gun. In this case, Gun was a translator asked to favorably translate documents as evidence to garner support for the Iraq war. Her case was dropped at trial almost immediately. Speculatively, the decision to drop the case was due to the calculated decision that producing the evidence required to prosecute her would have been more embarrassing for the GCHQ than simply letting her go.

Many whistleblowers find the ethics of betraying their employer for the greater good an excruciating ethical dilemma. Check out this BBC News interview of Katherine Gun if you are interested in how she weighed the decision. (There’s a book about her if you are more ambitious.) For these reasons and many more, whistleblowers like Mark Klein in the AT&T case that prompted the FISA Amendments and now David Murfee Faulk and Adrienne Kinne in this more recent case with the NSA shouldn’t be our last line of defense.

Essentially, lesson from this ABC News article is simple: surveillance tools will be abused. It is human nature for power to corrupt. The Founding Fathers of the United States recognized this and tried to limit the power of the government explictly for this reason. They built checks and balances into our government because they knew that hoping for whistleblowers to highlight problems was not reliable. Why does the current US government not seem to comprehend this?  How many more whistleblowers and ABC News stories will it take for our government to catch on?

I recently was without my computer for some time and stumbled upon al3x’s Rules for Computing Happiness shortly after getting back online.  My time away from my computer gave me the opportunity to think about my own computer usage.  I thought I would go ahead and post my own short lists of rules.  For the sake of brevity, I will limit myself to five tips per category.

Obviously, the goal of using a computer is to improve your “happiness” through making work easier or making play more fun.  Although measuring happiness is hard, there is a clear divide between how computer power users (geeks) and the average person (non-geeks) uses a computer.

The first group has different objectives when they use their computer.  People in this group are more interested in hardware and software that gives them choice and control.  They are willing to put in the time to weigh their options and make the decision they feel is appropriate.

Geek Software:

1. When looking for a piece of software, always consider using an open source alternative.
2. Use software that stores data in open file formats.
3. Learn how to use a Unix-based operating system.  Good options include Mac OS X, Linux, or OpenSolaris.
4. If you travel, be sure to encrypt your data.  I almost put this into the Non-Geek category, but I think full disk encryption may still be a little bit out of the range of things that Non-Geeks are willing to learn how to use.  Either way, this is incredibly important if you travel and have any personal information on your laptop.
5. Don’t be afraid to use proprietary software when it is simply the best tool for the job.  I think potential examples of this are Photoshop and TextMate.  Both of these programs have good open source alternatives (Gimp and vim or Emacs respectively), but the bottom line is that you should use whatever makes you most productive.  Just don’t forget point #2 in this list.

Geek Hardware:

1. Buy hardware with open source software support. This hardware will almost invariably have good closed source support as well, but open source support will give you more options and more control if you want it.
2. Do not skimp on your monitor, keyboard, or mouse.  If you are going to be using your computer heavily, the quality of the interfaces you use is very important to your health.
3. If you use more than one computer, get a KVM.  It will save you a ton of space on your desk.
4. If you use a router, get a dd-wrt compatible router.  The feature set will blow you away.
5. Conduct extensive research on every piece of hardware you are considering buying.  Good places to start are the Ars Technica Buyer’s Guide or Tom’s Hardware.

The second group consists of a wide variety of people in all kinds of professions that want nothing more than to use it to complete some task or to have fun.  They explicitly do not care about learning how computers work.  My mother falls into this category.  Here are the rules that I would give anyone in this group to help them achieve computer happiness:

Non-Geek Software:

1. Think twice before installing any piece of software.  Could an already-installed application do what you need?
2. Find and use software that will help you back up your data.  Apple’s Time Machine is a good way to do this.  (See Non-Geek Hardware #4.)
3. Keep a written record of all the software you install/remove and the time you install/remove it.
4. Use a password manager that allows you to select stronger passwords.
5. Do not use web applications unless the things you use them for aren’t sensitive.

Non-Geek Hardware:

1. Do not buy top of the line hardware.
2. Do not buy ultra cheap hardware.
3. Hardware features are less important than the software support.
4. Buy an external hard drive and use it to back up your important data.
5. Avoid expensive hardware service plans.

Once is an anomaly.  Twice is a coincidence.  Three times is a trend.  The US Government has not once, not twice, but three times bailed out a financial company that was facing the consequences of their risky business decisions.  The most recent incarnation of this is AIG, the world’s largest insurance company.  ABC has a great quote in their piece on the AIG bailout that pretty much sums up the core problem in all three of these bailouts:

“They called it insurance, but they were gambling,” said Nobel Prize-winning economist Joseph Stiglitz. “In a market economy, there has to be a sense of accountability. You can’t come running to the government every time you have a problem.”

This is pretty simple cause and effect.  In fitness, this is summarized by the catch phrase “No Pain, No Gain.”  In sports, there’s a common saying that “most games are won or lost before they are played.”  Another common saying, though I have had difficulty finding its origin, is this:

“Capitalism without bankruptcy is like Christianity without hell.”

— Frank Borman

I have seen this modified to “Capitalism without failure is like religion without sin” as well.

The point is that these bailouts are the most fundamental of errors.  Capitalism depends heavily on fair risk and rewards.  If someone takes a business risk that pays out, then those who didn’t take the risk shouldn’t be granted the benefit of regulations limiting the entrepeneurs who did.  If someone takes a business risk that crumples underneath them, then those who didn’t take the risk should be rewarded by not seeing the government swoop in and “save” the now-failing company that did.  The rules of the game shouldn’t change while it is being played.

Now having said that, there may be some circumstances where letting everything go would be worse than some government intervention.  The problem is identifying those circumstances is incredibly hard.  We were told that the Bear Stearns bailout was the mother of all bailouts.  We were told that the $29 bn we spent there would prevent a domino effect.  (Pretty effective, eh?)  Then we were told that the Fannie Mae and Freddie Mac needed the world’s largest bailout.  They said that the $200 bn we spent there essential to our economy.  Now we are being told that AIG is too big to fail.  They are saying that the $85 bn we spend there will save a cornerstone of our economy.  How is this fair to “small” businesses like Lehman Brothers?  What key characteristics were missing in those circumstances?  These arbitrary interventions in the market are bad for all businesses.

Now I’m not an economist.  I don’t claim to be an expert in this area.  I do find it interesting that many of the companies that are failing now are doing so because of prior government intervention in the market.  Fannie and Freddie were a government sponsored duopoly in the market.  AIG was exercising a massive loophole created by the government.  Why aren’t politicians trying to solve these root causes?  Why are they so busy trying to wash away the effects?

Instead, the Bush administration wants to spend another $700 bn on bad debt in an effort to “save” our economy.  Add this to the $314 bn we’ve already spent on bailouts this year and we would break the $1,000,000,000,000 mark.  You can see the trend continuing.  It’s great to know that my tax dollars are violating the most basic principle of economics by purchasing a product known to be bad.  I want my money back.

Edited to add: Looks like the $700 bn deal could be even worse than I originally thought:

Sec. 8. Review.

Decisions by the Secretary pursuant to the authority of this Act are non-reviewable and committed to agency discretion, and may not be reviewed by any court of law or any administrative agency.

Hat tip: Tim Lee.

As you may have noticed, I have updated the Wordpress theme used on this site.  I have also made a few changes under the hood.  For example, I have enabled user registration and comments.  Users can register using OpenID.  If you haven’t heard of OpenID, it’s basically a way for you to log in to this site without a password.

This means that you can log into BlayneSucks and comment on posts using any of the following popular blogging credentials:

• AOL — openid.aol.com/screenname
• Blogger — blogname.blogspot.com
• Flickr — www.flickr.com/photos/username
• LiveJournal — username.livejournal.com
• Technorati — technorati.com/people/technorati/username
• Yahoo — http://openid.yahoo.com
• WordPress.com — username.wordpress.com

All you have to do is put the URL listed into the OpenID box on the BlayneSucks log in page.  Furthermore, I have enabled Gravatars for users.  A Gravatar is a globally recognized avatar.  Basically, it’s a picture that follows your comments around from blog to blog.  You can sign up at http://en.gravatar.com/.

I hope you enjoy the new site look and feel as well as the ability to comment!