Editorial

Editorial — 3 Comments
20
Jun 09

Resume Writing Tips

resume_pileI’ve spent some time over the last week looking at resumes. I’ve had about 100 or so cross my email inbox from a variety of job posting sites, and I was reminded of a few quirks that people tend to fall into that are not at all helpful for getting yourself a job. I’ve been on both sides of the hiring manager divide, and I thought I would relate some resume writing tips. There are a few examples given below that are IT-centric, so feel free to fill in your own examples as you’re reading.

  1. Do not include an objective section: Objective lines are always generic; they say nothing that differentiates you from others who are applying. I would much rather that a person has an overview section that includes your career highlights or technical capabilities. Telling me that you’re “interested in using your skills in an innovative and challenging environment” says nothing and wastes precious space. Rather, tell me that you “have 5 years experience in data warehousing technologies, including the deployment of 3 large scale data cubes.” The former is a statement that tells me nothing specific. The latter gives me a much better idea of who you are professionally and what you’re capable of accomplishing.
  2. Proofread: Your resume is the first piece of work you’ve created that I see. Do you really expect me to trust your level of conscientiousness if you’re not capable of adequately proofreading your public facing professional document? The answer should be no. This includes not only spelling and grammar, but consistent formatting.
  3. Do not use a generic resume template: Again, when a hiring manager is looking at stacks of resumes, differentiation makes a difference. If your resume blends in with 50 others, it’s a safe bet that I’m not going to remember yours. It’s worth your while to spend some time planning out the formatting of your resume for uniqueness.
  4. Tell me what you’ve done; tell me what it accomplished: Most people do the former, but few do the latter. I oftentimes read resume blurbs like “program effectively in C#.” A sentence like this relates to me your skill set, but it doesn’t tell me what you’ve done with this skill. A blurb like “programmed a replacement CRM system in C#, increasing application performance and saving the company $50K over the previously licensed CRM system” not only relays your skills, but it tells me what your skills have accomplished.
  5. Use white space: White space is capable of focusing the attention of the reader on particular pieces of the resume. More often than not, I receive what I refer to as “machine gun” resumes. These are resumes that use 8 point font, have 0.15in margins, and have full lines of text on every line. The thinking here seems to be that if you’re able to throw every possible thing you’ve ever done or read about (or whatever) at the manager, they’ll be impressed. Actually, it’s quite the opposite. If it’s difficult for me to focus on your resume, and there’s no indication of what pieces of the document you’d like for me to focus on, sensory overload takes over and it’s nearly impossible for me to remember anything about your resume.
  6. Do not refer to yourself in the third person: It sounds ridiculous, but I’ve seen this in a lot of resumes. You cannot vouch for yourself. By referring to yourself in the third person you sound silly. Do not do this.
  7. No images: Please don’t include any images. I’m sure some people will disagree with this one, but I don’t think that it’s appropriate. For tech resumes, I understand that people are sometimes interested in including graphics that represent certain received certifications. While these certifications should certainly be listed in the resume, please exclude the graphics. There have been several times where people have included graphics for certifications that have NOTHING to do with the position they’re applying to. And this tells me that they’re simply blanketing job sites with resumes rather than to tailor their search to specific positions.

There are a lot of other recommendations I could give, but others have already done a great job of this. Please check out these other resume tip sites:

Resume Tips from Taos
44 Resume Writing Tips from Daily Writing Tips
12 Important Resume Tips (YouTube)

(Photo by woodleywonderworks)

Editorial — 1 Comment
29
May 09

The Consequences of Trusting Computers

Computers were created in large measure to solve problems. And the programs that run on computers are designed to solve these problems. And those programs generally run to do exactly what we tell them to do. And much of what we tell them to do is straightforward in the sense that the problems they solve follow the law of non-contradiction, i.e. an answer provided by a computer for a specific problem is either true or not true, but never both simultaneously.

I can program a computer to answer for me the question, “What is three factorial?”
The answer provided, hopefully “six”, is either true or not true, but is quite obviously not both.

I’m ignoring some gray areas here, particularly in the places where problems are solved by computers learning, a la genetic algorithms in the case of Roger Alsing’s EvoLisa program or neural nets in the case of GNU Backgammon. But even in these arenas, computers are programmed to perform specific tasks that solve (or approximate) particular problems. For the rest of this post, I’m generally referring to the simpler class of problems, though I will touch on how decisions made within the financial sector over the last several years have in part caused our current global economic situation based on solutions to incomplete mathematical models.

I really started thinking about this issue in relation to the now famous Verizon Math site and associated videos that show just how hapless humans can be when we depend entirely on computers to return the correct answer. What I’m saying here is that we’ve more or less reached the point where we believe that computers will always return the correct answer, and forget that while computer programmers aim to have their programs answer on the “true” side of the law of non-contradiction, sometimes this unfortunately isn’t the case.

If you’d like a poignant example, please watch this video, where several Verizon employees fail to recognize how their computer system has overcharged the customer on the phone. I don’t bring this video up to pick on Verizon specifically, but this is an issue that has gained a lot of attention over the last several months:

Now, here’s the point: Though Verizon is in the wrong, the employees are not willing to recognize the error. And why is this the case? I can think of several reasons.

  1. Verizon employees are used to hearing customers complain about how they have been mischarged, and generally speaking the customer is wrong.
  2. These Verizon employees do not understand the math being explained to them by the customer.
  3. These Verizon employees are trusting what their computer system is telling them without fail.

And I think that all three issues played a part in the lack of understanding of the employees. But the issue that bothers me the most is the third, that the employees infallibly trust their computer system. What bothers me most about this story is that even in the face of blatant mathematical reasoning, the belief of the employees was to side with the answer provided by the computer. And the computer was incorrect. Due to a variety of circumstances, the math provided by the computer program did not match the price quote delivered by Verizon. And rather than viewing the computer as the product of human intellict, they viewed the computer as the objective arbiter.

Using the computer as an objective arbiter is a dangerous business for a variety of reasons, including most notably that the program returning the answer can be incomplete or incorrect. In the case of the recent financial meltodown, at least part of the blame can be placed on mathematical models that viewed sets of risk transactions (e.g. credit default swaps) as indepdent events. As it turns out, these events were NOT independent. Here’s an article about this. But an assumption of the program was to treat them independently. So was the computer wrong? Practically speaking, in retrospect, yes. But I don’t think that’s the right way of looking at it. The computer was answering the question based upon the programmer’s intent. And it was answering the question correctly in that sense.

What’s the moral of the story? Basically, it’s that computers answer problem in EXACTLY the ways they are programmed to do so. No more and no less. Computers are designed to be “right”, but it doesn’t mean that it will always pan out this way. Treating them as flawless objective arbiters is farming out your intellect. And while I’m certainly not saying that computers and their programs can’t be trusted (hell, it’s what I do for a living), I’m also saying that it’s a good idea to treat them as if they’re a product of humanity.

Editorial — No Comments
28
May 09

G-20 in Pittsburgh and Hockey

PittsburghByNightIt’s not very often that I blog about my hometown of Pittsburgh, but today is one of those days. Congratulations to Pittsburgh, which will be hosting the G-20 summit this coming September. Good stuff. You can read the AP version of the story here. Of course, when the White House made the announcement today the media’s response was along the lines of “Whaaaaaat?!” But as a person whose lived in Pittsburgh for a long time, I’m very excited for this positive attention. We have a lot to offer in this city, and I’m glad that to show that to the world.

In addition, I must say that I’m ridiculously excited to see the Pittsburgh Penguins back in the Stanley Cup finals for the second year in a row. Sports, of course, are one of the major reasons people know about Pittsburgh, and between the Steelers and the Penguins, the city has had a good run as of late. The Pens didn’t pull it out last year, but I’m feeling good for this year.

LET’S GO PENS!

Editorial / Logic/Math — No Comments
14
Jan 09

Reflections on the Anniversary of Kurt Gödel’s Death

godelKurt Gödel died 31 years ago today. From the little I’ve read of his life, and from the even smaller amount that I truly grasp from his work, I believe that only in reality could such a fantastic and somewhat lamentable figure come to be. He was included in the infamous Vienna Circle, but was himself a Platonist. He was shy, reclusive, and prone to illnesses both physical and mental. He was a friend to Albert Einstein. And he shook the world of mathematics in a way that destroyed the Hilbert program. In simple terms, he showed that the mechanization of mathematics could not be fully automated, or that mathematics was not something that could be neatly placed in a box and tied up with a bow.

John W Dawson Jr. explains the first of Gödel’s Incompleteness Theorems by saying, “In his 1931 paper Gödel showed that, no matter how you formulate the axioms for number theory, there will always be some statement that is true of the natural numbers, but that can’t be proved. (That is, objects that obey the axioms of number theory but fail to behave like the natural numbers in some other respects do exist.)”

John Von Neumann, certainly one of the greatest mathematicians of the 20th century, had the following to say in a letter shortly after the publication of the Incompleteness theorems:

Thus today I am of the opinion that 1. Gödel has shown the unrealizability of Hilbert’s program. 2. There is no more reason to reject intuitionism (if one disregards the aesthetic issue, which in practice will also for me be the decisive factor). Therefore I consider the state of the foundational discussion in Königsberg to be outdated, for Gödel’s fundamental discoveries have brought the question to a completely different level.

Another way of summing this up is to say, “this work has changed the way we must view mathematics.” I have to imagine that the fame of the majority of famous people peaks in the prime of life, only to wane with time and death. Only the smallest number of people see their influence grow with time, as reflection shows their achievements to be truly monumental. Gödel, I believe, sits comfortably in the latter group.

Obviously, I have a bit of a crush.

Editorial — 2 Comments
29
Sep 08

Basic Calculators and Overkill

calculatorI really enjoyed reading this post about the physicality of a calculator over at Social Mathematics. The idea of having a simple calculator available to you in your workplace or home office setting is intriguing to me. I must admit that I do enjoy having a basic little calculator at my disposal. I know that I can open up a spreadsheet on my computer to take care of some maths, or that I can simply use my brain, but there’s something about using a calculator for basic arithmetic that is appealing to me. I tend to use the calculator as a sort of extension to my short term memory.

Of course, it’s quite possible to take this idea to the extreme. Many moons ago at a previous job, there was an individual who worked there that was not the sharpest crayon in the box. We’ll call this individual “Slowbe”, and we will assume for this story that Slowbe was a man.

Slowbe was well known for his occasional mental lapses, and I remember hearing a story about him sitting in a meeting with several others, going over various numbers in a spreadsheet. This was a spreadsheet that Slowbe had created himself. As the group was looking at the numbers, Slowbe decided that he wanted to add up several numbers in the spreadsheet. So he left the conference room, walked around 300 meters round trip to his desk, and returned with a pocket calculator.

Now, I’m not sure if you, the reader, are familar with Excel. But when you have a spreadsheet open, and there are several numbers within this spreadsheet which you’d like to add up, doing this requires about 0.4 seconds worth of work. In essence, Excel can act quite easily as a really stinkin’ powerful calculator. Everyone in the meeting (most of whom were IT people), sort of looked at one another with “What just happened?” kind of faces.

This, my friends, is overkill.

(Picture by draggin of a Little Professor Calculator created by Texas Instruments in 1976.)

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