As the economy continues to chart its own tortuous, uncertain course, there seems to have been a fair amount of much-needed discussion on the kinds of skills new grads should possess. These skills of course have to be driven by market demand. As chemist George Whitesides asks for instance, what's the point of getting a degree in organic synthesis in the United States if most organic synthesis jobs are in China?
Upcoming grads should indeed focus on what sells. But from a bigger standpoint, especially in the sciences, new skill sets are also inevitably driven by the course that science is taking at that point. The correlation is not perfect (since market forces still often trump science) but a few examples make this science-driven demand clear. For instance if you were growing up in the immediate post-WW2 era, getting a degree in physics would have helped. Because of its prestige and glut of government funding, physics was in the middle of one of its most exciting periods. New particles were literally streaming out of woodwork, giant particle accelerators were humming and federal and industrial labs were enthusiastically hiring. If you were graduating in the last twenty years or so, getting a degree in biology would have been useful because the golden age of biology was just entering its most productive years. Similarly, organic chemists enjoyed a remarkably fertile period in the pharmaceutical industry from the 50s through the 80s because new drugs were flowing out of drug companies at a rapid pace and scientists like R. B. Woodward were taking the discipline to new heights.
Demand for new grads is clearly driven by the market, but it also depends on the prevalence of certain scientific disciplines at specific time points. This in turn dictates the skills you should have; a physics-heavy market would need skills in mathematics and electronics for instance, a biology-heavy market would mop up people who can run Western blots and PCR. Based on this trend, what kind of skills and knowledge would best serve graduates in the twenty-first century?
To me the answer partly comes from an unlikely source: Stephen Hawking. A few years ago, Hawking was asked what he thought of the common opinion that the twentieth century was that of biology and the twenty-first century would be that of physics. Hawking replied that in his opinion the twenty-first century would be the "century of complexity". That remark probably holds more useful advice for contemporary students than they realize since it points to at least two skills which are going to be essential for new college grads in the age of complexity: statistics and data visualization.
Let's start with the need for statistics. Many of the most important fields of twenty-first century research including neuroscience, synthetic and systems biology, materials science and energy are inherently composed of multilevel phenomena that proliferate across different levels of complexity. While the reductionist zeitgeist of the twentieth century yielded great dividends, we are now seeing a movement away from strict reductionism toward emergent phenomena. While the word "emergence" is often thrown around as a fashionable place-card, the fact is that complex, emergent phenomena do need a different kind of skill set.
The hallmark of complexity is a glut of data. These days you often hear talk of the analysis of 'Big Data' as an independent field and you hear about the advent of 'data scientists'. Big Data now has started making routine appearances in the pharmaceutical and biotech industry, whether in the form of extensive multidimensional structure-activity relationship (SAR) datasets or as bushels of genomic sequence information. It's also important in any number of diverse fields ranging from voter behavior to homeland security. Statistical analysis is undoubtedly going to be key to analyzing this data. In my own field of molecular modeling, statistical analysis is now considered routine in the analysis of virtual screening hits although it's not as widely used as it should.
Statistics was of course always a useful science but now it's going to be paramount; positions explicitly looking for 'data scientists' for instance specifically ask for a mix of programming skills and statistics. Sadly many formal college requirements still don't include statistics and most scientists, if they do it at all, learn statistics on the job. For thriving in the new age of complexity this scenario has to change. Statistics must now become a mandatory part of science majors. A modest step in this direction is the publication of user-friendly, popular books on statistics like Charles Wheelan's "Naked Statistics" or Nate Silver's "The Signal and the Noise" which have been quickly devoured by science-savvy readers. Some of these are good enough to be prescribed in college courses for statistics non-majors.
Along with statistics, the other important skill for students of complexity is going to be data visualization and formal college courses should also reflect this increasingly important skill set. Complex systems often yield data that's spread over different levels of hierarchy and even different fields. It's quite a challenge to visualize this data well. One resource that's often recommended for data visualization is Edward Tufte's pioneering series of books. Tufte shows us how to present complex data often convoluted by the constrains of Excel spreadsheets. Pioneering developments in human-computer interaction and graphics will nonetheless ease visual access to complicated datasets. Sound data visualization is important not just to simply understand a multilayered system or problem but also to communicate that understanding to non-specialists. The age of complexity will inherently involve researchers from different disciplines working together. And while we are at it it's also important to stress - especially to college grads - the value of being able to harmoniously co-exist with other professionals.
Hawking's century of complexity will call upon all the tools of twentieth century problem solving along with a few more. Statistics and data visualization are going to be at the forefront of the data-driven revolution in complex systems. It's time that college requirements reflected these important paradigms.
First published on the Scientific American Blog Network.