The acronym STEM - science, technology, engineering, mathematics. It shows up everywhere. Some ungodly fraction of new jobs will be in STEM fields. We need more STEM majors in college.
As general statements, these are true. The economy is becoming more knowledge-based, with knowledge of technology necessary to perform basic tasks - use of spreadsheets for accounting, computer-generated presentations, and even fancy espresso machines in the coffee industry. (An aside: I know that my colleagues will hate me for stating this fact, but use of most equipment used by scientists - mass spectrometer, PCR machine, thin film deposition chamber, to name a few - is not any more difficult that using the espresso machine at Starbucks. As a result, this has obvious implications for what defines "skilled" versus "unskilled" work, and resulting prestige and salaries.) We therefore do need more people trained on certain equipment, with the appropriate backgrounds.
(I will note: One problem I have with the STEM categorization is that it encompasses a huge range of positions, from glass cleaner at a pharmaceutical company to PhD astrophysicist. Not all positions are truly creative or thinking-based - in fact the vast majority are not.)
Where does this training needs to occur? Currently colleges are the bridge between high school and good jobs in the STEM sectors. However, a college degree requires more than background for a certain job, and much more that simply training on a certain piece of equipment (what many people do at a given job in STEM). As such, there is an argument that can be made to get rid of such "waste" - general education classes - and streamline the process to produce more employment-ready individuals. The implication is that understanding subjects like literature, history, and touchy areas such as systemic racism and sexism is pointless if one wants employment in the modern economy.
Is this true? If one's only goal in life is to be a drone, then it probably is true. And it is true that most employers simply want drones, who know one thing and are trained to do one task (but can be retrained if necessary for a different task) and do not think about their place in the world, in the economy, and might therefore complain. Employers also do not want to be reminded of their own systemic "-isms" which are generally taught in colleges in the US at this point in time (not necessarily true in the past). As such, they are less likely to encourage broad-based studies. But just because something is good for the business community, is it good for everyone else? It is true that some individuals are not interested in learning extraneous topics and are only interested in a decent-paying job, no matter how boring. This is fine, but these people should not be encouraged to attend a traditional college.
What is required here are vocational schools - training centers for specific jobs that take little time to complete and do not require general education. These need to be funded by businesses (who directly benefit from the training) either directly or through corporate taxes. We also need better career paths for intellectually curious college graduates - having them sit inputting numbers into a spreadsheet is boring and a waste of human capital. I do not know if I have a solution for that problem. The modern economy requires a certain amount of labor that is not automatable yet, but also does not require much intellectual skill (leading to some 70% of employees not being engaged at work, including myself in my supposedly high-quality science position at NIST).
(In an ironic twist, there are claims that certain STEM jobs are less likely to be automated, unlike paper pushers, burger flippers and such. This is not true. The unautomatable jobs and careers are all creative - author, artist, historian, museum curator, etc. - and outside of STEM. At least until we develop true artificial intelligence.)
Thursday, May 29, 2014
Wednesday, May 28, 2014
Is Economics Science?
The most recent issue of Science magazine (from May 23, 2014) focuses on economic inequality. Most likely this is a response to Thomas Piketty's book Capital in the 21st Century, which purports to explain economic inequality in terms of return on capital investment relative to labor. The question we will address here is whether or not this subject belongs in a publication titled Science.
For something to be scientific, it must predictively explain phenomena, hypotheses must be experimentally testable, and one must be willing to discard hypotheses that clearly do not match or predict experimental data. Hypotheses and explanations for experimental data that continue to predict future data are considered to represent reality. In some disciplines (notably physics) the explanations are written as mathematical expressions, which are often extrapolated into domains not yet probed experimentally and yield predictions that can be further tested. As a note, the quality of a given description is determined by its accuracy relative to measurement accuracy and certain descriptions (known as "theories" in the physics community) can only be considered accurate within a given experimental space (e.g. low velocity, small mass, long time scale).
At some level, modern economics is attempting to be like physics - economists attempt to write down rigorous mathematical formulas that describe the flow of money, ideas, commodities, etc. The mathematical predictions can then be compared to what has actually happened to test for accuracy. Experiments can be devised to test these "theories"in small scales, with limited resources and individuals, and such results are often extrapolated to populations at large. This is fine, as science goes, and economics can be considered science under these circumstances.
The problem arises when economists treat economics as a deductive philosophy: given certain assumptions (sometimes mathematically rigorous, sometimes not), one can use deductive logic to predict what will happen in the future. If the assumptions are correct, and the mathematics accurate enough, the future can be predicted. Much of modern economic commentary resides in this treatment. When we read about, for example, how changing the minimum wage will affect the labor market, the conclusion is often based on deductive logic given a premise and a few assumptions. The problem is often that the assumptions are not based on any experimental evidence but are essentially made-up axioms (e.g. the "people act rationally" assumption), used to make predicting easier or to appeal to some basal desire for humanity to be predictable.
We can see the effects of this type of thinking in modern day economic analyses. One would hope that economists would understand the weaknesses of their assumptions and mathematical descriptions (most physicists certainly do), but this often does not seem to be the case. This brings us back to Piketty's book, which relies on actual long-term macroeconomic data to make statements about the past, and possibly predict the future. This is scientific - developing predictions and hypotheses which can be tested (though the test will be how the actual economy behaves over the upcoming years). We do not know if the predictions will be accurate (given that most previous predictions of large-scale economic behavior, for example those of Malthus, Karl Marx, and others have failed, I am not optimistic for Piketty), but we will see. Somewhat problematically (but interestingly), we cannot devise controlled macroeconomic experiments - society in the past, right now, and into the future is one ongoing experiment with parameters continually changing. Perhaps one day we can write down a good description (even if only statistical predictions are possible).
For something to be scientific, it must predictively explain phenomena, hypotheses must be experimentally testable, and one must be willing to discard hypotheses that clearly do not match or predict experimental data. Hypotheses and explanations for experimental data that continue to predict future data are considered to represent reality. In some disciplines (notably physics) the explanations are written as mathematical expressions, which are often extrapolated into domains not yet probed experimentally and yield predictions that can be further tested. As a note, the quality of a given description is determined by its accuracy relative to measurement accuracy and certain descriptions (known as "theories" in the physics community) can only be considered accurate within a given experimental space (e.g. low velocity, small mass, long time scale).
At some level, modern economics is attempting to be like physics - economists attempt to write down rigorous mathematical formulas that describe the flow of money, ideas, commodities, etc. The mathematical predictions can then be compared to what has actually happened to test for accuracy. Experiments can be devised to test these "theories"in small scales, with limited resources and individuals, and such results are often extrapolated to populations at large. This is fine, as science goes, and economics can be considered science under these circumstances.
The problem arises when economists treat economics as a deductive philosophy: given certain assumptions (sometimes mathematically rigorous, sometimes not), one can use deductive logic to predict what will happen in the future. If the assumptions are correct, and the mathematics accurate enough, the future can be predicted. Much of modern economic commentary resides in this treatment. When we read about, for example, how changing the minimum wage will affect the labor market, the conclusion is often based on deductive logic given a premise and a few assumptions. The problem is often that the assumptions are not based on any experimental evidence but are essentially made-up axioms (e.g. the "people act rationally" assumption), used to make predicting easier or to appeal to some basal desire for humanity to be predictable.
We can see the effects of this type of thinking in modern day economic analyses. One would hope that economists would understand the weaknesses of their assumptions and mathematical descriptions (most physicists certainly do), but this often does not seem to be the case. This brings us back to Piketty's book, which relies on actual long-term macroeconomic data to make statements about the past, and possibly predict the future. This is scientific - developing predictions and hypotheses which can be tested (though the test will be how the actual economy behaves over the upcoming years). We do not know if the predictions will be accurate (given that most previous predictions of large-scale economic behavior, for example those of Malthus, Karl Marx, and others have failed, I am not optimistic for Piketty), but we will see. Somewhat problematically (but interestingly), we cannot devise controlled macroeconomic experiments - society in the past, right now, and into the future is one ongoing experiment with parameters continually changing. Perhaps one day we can write down a good description (even if only statistical predictions are possible).
Wednesday, May 21, 2014
Scientists (and nerds, geeks) in modern media
Do we really need another post tackling inaccuracies in the media? Maybe, since some issues I will discuss are rarely discussed elsewhere (possibly because journalists are often not ensconced in scientific culture).
The most famous, though not only, example of scientists on a TV sitcom, currently producing new episodes, is The Big Bang Theory (TBBT). Medical and investigative dramas (e.g. CSI, Numbers, Bones, X-Files) often include scientists and doctors in various roles, but this is rare in sitcoms. Growing up, I remember no sitcoms with scientists or people interested in science as major characters (the closest might be Steve Urkel from Family Matters, who was nothing more than a caricature, or possibly Frasier Crane, who though a psychiatrist no longer does or discusses scientific research). If anyone knows of other characters from the early to mid 1990s, please let me know. I did enjoy the X-Files, which discussed a lot of science (often in the context of the paranormal), but that did not really portray scientists as scientists.
As a note, I generally enjoy TBBT. It has intellectual humor, employs irony effectively, and the characters are by and large good, relateable people. We can compare to other shows featuring educated individuals, such as Nip/Tuck, where the characters are, by and large, awful people. Or Frasier, with intellectuals who, though generally good people, are portrayed overwhelmingly as snobs. (Sheldon can be condescending - "I know more than you" - which may superficially seem snobby, but does not have the cultural snobbiness - "I'm into art and classical music just because it's what cultured people do" - portrayed on Frasier. I would argue that these are different.) However, TBBT is not without its misleading and inaccurate portrayals. The most glaring is the inconsistency of the show with the realities of academia. All of the characters (except Bernadette, who works at a pharmaceutical company) seem to be independent researchers. None are described as postdocs or faculty, i.e. they seem not to have bosses (or are their own bosses) but also have no full-time teaching and advising duties. They also seem to have some semblance of job security (though not complete job security). In US research universities, such positions are rare to nonexistent. Compare to Numbers, with a more accurate labeling of individuals as assistant and tenured professors, department chairs, and students with the proper duties required of each.
However, both Numbers and TBBT, along with Bones, suffer from a different problem - that of heightened expectations for scientists. Leonard, Sheldon and Charlie all graduated from college and received PhD degrees significantly younger than average (Leonard the oldest at 24). Sheldon, Charlie, and Brennan, Hodgins and Sweets from Bones all have multiple doctoral degrees. First, the average PhD recipient in the US is about 28-29 years old. Second, almost none will get a second (or more) doctorate. This sort of portrayal is not only inaccurate, it may be harmful to potentially interested young people who might get turned off from studying science because of the perception that one must be a super-genius, in college at age 14, to be successful. As an anecdote, I personally do not know anyone in real life with such credentials.
Are such portrayals harmful? I do not know. Realistically, it will take years of sociological data -following children who watch such shows - to find out.
This is all for now - I may write more in the future discussing the "-isms" and diversity if the time and popularity of this blog require it.
The most famous, though not only, example of scientists on a TV sitcom, currently producing new episodes, is The Big Bang Theory (TBBT). Medical and investigative dramas (e.g. CSI, Numbers, Bones, X-Files) often include scientists and doctors in various roles, but this is rare in sitcoms. Growing up, I remember no sitcoms with scientists or people interested in science as major characters (the closest might be Steve Urkel from Family Matters, who was nothing more than a caricature, or possibly Frasier Crane, who though a psychiatrist no longer does or discusses scientific research). If anyone knows of other characters from the early to mid 1990s, please let me know. I did enjoy the X-Files, which discussed a lot of science (often in the context of the paranormal), but that did not really portray scientists as scientists.
As a note, I generally enjoy TBBT. It has intellectual humor, employs irony effectively, and the characters are by and large good, relateable people. We can compare to other shows featuring educated individuals, such as Nip/Tuck, where the characters are, by and large, awful people. Or Frasier, with intellectuals who, though generally good people, are portrayed overwhelmingly as snobs. (Sheldon can be condescending - "I know more than you" - which may superficially seem snobby, but does not have the cultural snobbiness - "I'm into art and classical music just because it's what cultured people do" - portrayed on Frasier. I would argue that these are different.) However, TBBT is not without its misleading and inaccurate portrayals. The most glaring is the inconsistency of the show with the realities of academia. All of the characters (except Bernadette, who works at a pharmaceutical company) seem to be independent researchers. None are described as postdocs or faculty, i.e. they seem not to have bosses (or are their own bosses) but also have no full-time teaching and advising duties. They also seem to have some semblance of job security (though not complete job security). In US research universities, such positions are rare to nonexistent. Compare to Numbers, with a more accurate labeling of individuals as assistant and tenured professors, department chairs, and students with the proper duties required of each.
However, both Numbers and TBBT, along with Bones, suffer from a different problem - that of heightened expectations for scientists. Leonard, Sheldon and Charlie all graduated from college and received PhD degrees significantly younger than average (Leonard the oldest at 24). Sheldon, Charlie, and Brennan, Hodgins and Sweets from Bones all have multiple doctoral degrees. First, the average PhD recipient in the US is about 28-29 years old. Second, almost none will get a second (or more) doctorate. This sort of portrayal is not only inaccurate, it may be harmful to potentially interested young people who might get turned off from studying science because of the perception that one must be a super-genius, in college at age 14, to be successful. As an anecdote, I personally do not know anyone in real life with such credentials.
Are such portrayals harmful? I do not know. Realistically, it will take years of sociological data -following children who watch such shows - to find out.
This is all for now - I may write more in the future discussing the "-isms" and diversity if the time and popularity of this blog require it.
Tuesday, May 20, 2014
Introduction
One could ask whether there is truly a need for another science news and analysis blog. This question is difficult to answer. Is there already enough information available? Probably. Could we always use more information and different opinions and analysis? Certainly. Will the extra information add enough to overcome the cost of storage to create this blog? I do not know - that is to be determined based on readership and interest. Do we need more scientists to engage the public, present and interpret results of new studies? Almost definitely.
A little bit about myself: I have a Ph.D. in physics. My research specialty is magnetism and spin dynamics in solid-state systems. I worked at an industrial research lab for a spell, then I had a fellowship working at the National Institute of Standards and Technology (NIST), until the money ran out (or so that is the official statement). Currently, I am searching for the next opportunity and doing a lot of reading and thinking.
I think that part of being a good scientist is disseminating knowledge not just to one's bosses and narrowly-defined colleagues (the people working in the same narrowly-defined subfield, such as one encounters at conferences) but to society at large. Many scientists, including former and current colleagues, do not agree, which is why I think it is important for me to pursue this outreach.
A little bit about myself: I have a Ph.D. in physics. My research specialty is magnetism and spin dynamics in solid-state systems. I worked at an industrial research lab for a spell, then I had a fellowship working at the National Institute of Standards and Technology (NIST), until the money ran out (or so that is the official statement). Currently, I am searching for the next opportunity and doing a lot of reading and thinking.
I think that part of being a good scientist is disseminating knowledge not just to one's bosses and narrowly-defined colleagues (the people working in the same narrowly-defined subfield, such as one encounters at conferences) but to society at large. Many scientists, including former and current colleagues, do not agree, which is why I think it is important for me to pursue this outreach.
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