jriddycuz's comments

I mean, it's a tiresome task to even attempt to enumerate all the ways in which I feel college failed to live up to the hype they feed you before you go in. And perhaps it's because I went to a big, run-of-the-mill state school, but I typically refer to college as an extortion racket now.

I welcome any and all attempts to disrupt what I consider a corrupt and ineffective system.

This seems to be a reasonably good description of what the word means and what it is commonly associated with. You can call practically any young firm a startup, but it does most commonly refer to PG's definition. Like DHH said in the post, "starting a business" just does not have the near-mythical connotations "startup" has, but those connotations are result of the stories that typical startup culture provides. I don't think there's a way to make "starting a sustainable business" sound sexy because it's not a very sexy idea. And perhaps people with a spouse and kids shouldn't worry too much about how sexy an idea is, but rather how valuable it is.

Now those firms and their ilk may not fit your definition of "startup", but they are still ex nihilo undertakings that have been able to supply some very demanding consumers. They'll never be as sexy as the Valley kids, but their continued existence serves as ample evidence of their validity. And in that sense, it is a myth that startups must be all-consuming.

Wait, since when aren't they? I would have thought basic regex skills were a baseline shibboleth of a programmer. I even know several non-technical people that are proficient.

Language changes. People sometimes still complain about "hopefully" being used as a sentence modifier, as in, "Hopefully language mavens will see their role in speech communities as custodians and curators of beneficial older conventions, rather than as guardians and protectors of acrolectic law." However, the etymologically literal sense of this word ("in a manner full of hope") has so little use that the non-standard meaning predominates.

I am near the start of my career (3 years in or so) as a programmer, and I spent much of the first part of that working remotely. Though I enjoyed not having to get dressed and drive in traffic to be at the office by 8am, this severely stunted the development of my work skills. Now, when I was working for a startup, I would spend hours and hours at home on projects and remained fairly disciplined, but that was due to the passion I felt for my work. When that startup folded I had to enter the regular workforce for financial reasons, and I found it much harder to be motivated about what I was doing. When working remotely, I found myself constantly distracted and unfocused, and even though I felt I had fairly strong communications skills, my ability to communicate with co-workers did not develop.

There are numerous problems with younger employees working remotely, but the way it stunts one's development as a professional is probably the worst. Now that I'm in an office, I am constantly exposed not only to people more knowledgeable than I, but also people who have learned how to be a professional and how to work in a team.

One thing in particular that struck me is that I didn't really know how to behave in an office. True, there are a lot of ways that the modern office is kind of depressing, but developing decent working relationships based on mutual respect with your co-workers does a lot to make a workplace tolerable and even enjoyable. This respect is not developed in most cases unless you actually observe and learn some office behavioral norms.

Working remotely can be awesome, and stodgy companies should learn that flexibility has its advantages. But these advantages are often strongest for experienced employees who know how to organize themselves and motivate themselves to get a job done wherever they are for little reason other than professional pride and a paycheck.

[1] http://en.wikipedia.org/wiki/Reification_(fallacy)

If survey classes actually connected the dots, it would promote intelligent students without challenging them to persevere, and ultimately favor the development of bright but undisciplined generalists.

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While I relate to some of the cynicism of the essay, I think this is an emergent sociological phenomenon rather than something that the designers of curricula necessarily intend to do. Sure, there's a need to weed out students who can't hack it later due to a lack of intelligence or persistence, but the idea that course designers set out to build people into student-drones who blindly memorize information because "that's what society needs" is hogwash. This is a result of a need to serve a broad range of students with a limited supply of teaching talent.

I'm confident most college departments would love to get highly intelligent students intensely interested in their field of study. Showing them how to connect all the dots could open a window towards a genuine love for the field at hand, turning a jaded generalist into a dedicated scholar. While persistence may still be an issue with some of these students, showing them how amazing and connected a field can be could encourage them to specialize in this fascinating study. Few things inspire as much persistence as deep fascination. The crappy survey classes probably do more harm than good in turning away potentially excellent students from the material.

I mean, it might even be clearer-looking to output strings. Not saying that outputting string programs is good, but it is a good lower limit for how complex the code for your macro system can be in order for it to be useful.

This can be avoided by not treating skepticism as an identity, but rather a name for a collection of tools. Like the OC said, it's being skeptical about things rather than being a skeptic.

This was my impression exactly when I first read about Dart. This is the language that Google wants to replace Javascript? Please. Javascript may have some strange design quirks (or outright flaws, depending on who you talk to), but at least it has the sense to have a meaningful boolean context. I understand that you can't try to revolutionize everything if you're targeting a wide audience, but this just looks like decaffeinated Java.

I am not saying that empiricism is inherently flawed, or that we should stop collecting economic data. And I I do not intend to advocate any particular school of economic thought here. All I'm advocating is that students be taught how to think critically about what they are being taught. So much of a modern economics education consists of looking at the changes in figures over time that very little is spent focused on a more general kind of reasoning.

The kind of reasoning I'm calling for is not easy to define. This is one of the tremendous advantages numbers have over argument in most minds. This kind of reasoning takes into account the notion that most of the information we obtain is not perfect or complete, and that many of our determinations are really judgment calls on what is more likely to be true. If empiricism is reasoning with your eyes, this is reasoning with your nose. It is a trained skill that allows you to recognize dubious premises and unspoken assumptions. When refined, it allows you to distill the essence of arguments down to a set of axioms that you can use to build a coherent model of the situation at hand. It is this theoretical side that allows you to understand how to construct experiments that test hypotheses, or whether that is even possible in each case.

To demonstrate the importance of gaining an understanding of the theory and rules behind something before testing it, I offer a parable:

The commissioner of the NFL once decided that teams were punting too much and he hired an econometrician (economic statistician) to study the situation and provide a solution to this problem. The econometrician applied his skills to the task at hand, aggregating data from several seasons to find correlations. He noted that there is an incredibly strong correlation between forth downs and punting, and he recommended that the commissioner ban fourth downs. In the next season, offenses were only given three downs. To the econometrician's surprise and the commissioner's chagrin, teams actually punted more frequently, as the fewer number of downs dramatically limited offensive opportunities.

The econometrician's misunderstanding was based on something rather obvious (if you understand American Football): a failure to separate correlation and causation due to an ignorance of the rules of the game. And compared to a global economy, football is a very simple game, with very simple rules. Applying reasoning to the example is very straightforward, but applying the same thing to a world of dynamic human behavior is much more subtle. Which is why students ought to be trained to question assumptions and sense where logic and math have separated themselves from the reality they are supposed to help us describe.

People will disagree about when things correlate to reality, and about what things make sense in parables. But almost anyone can learn to recognize when a number seems too specific, just like most decent coders learn to recognize "code smell." Just the other day, someone told me confidently that 65% of communication is non-verbal. Now, while I almost agree intuitively, I immediately asked where they heard that, and how someone could have arrived at that figure, which seemed oddly specific for something (communication) that I don't think is frequently quantitized. Every student of a soft science needs to have this skill strongly developed, or they will begin to take these kinds of things at face value.

While I enjoy math tremendously, part of my deep dissatisfaction with economics as a field is its incredible over-reliance on math as a tool for analysis. I'm speaking as someone who dreamed of being an economist all through high school and early college. Classically, economics had very little to do with (numeric) math, and much to do with reasoning about how people behave.

However, as modern statistics (and math as whole) began to develop rapidly in the early 20th century, and as logical positivism became a dominant philosophy (http://en.wikipedia.org/wiki/Logical_positivism), economists took note and begin applying these tools liberally to their field. They started collecting and compiling tons of data on anything they could measure. Data is compelling: numbers give a sense of precision and clarity that mere reasoning does not. But this appeal is also what makes numbers dangerous. Though rigorous empirical testing of hypotheses in science is clearly one of the greatest advancements of the last 200 years, it has often been misapplied to other fields where the same controls are hard to apply. And experiments without controls can produce essentially meaningless data. Economic data is particularly complex, and there is still much debate as to how to calculate even very basic oft-quoted economic figures like inflation, unemployment, and GDP.

Though there was significant debate about the usefulness of these new tools, they became enshrined by the two dominant mainstream schools of the 20th century: Keynesianism and Neo-Classicalism. This bastardization of the field has made economics into a cargo cult science, where researchers regularly base their knowledge on data that is only slightly more controlled and scientific than corporate accounting.

This is not a trifling academic concern. So much of our lives is affected by what economists do and say. The bigger concern I have for young economics students is that their lack of mental math skills will make them more inclined toward the kind of overly precise large number manipulation that computers and calculators make so easy. I hope, for all of our sakes, that these less mathematically-inclined students will instead be wary of the numbers and critically apply reasoning to the models and assumptions they have been taught.