Early last month, Michael White’s Adaptive Complexity on Science 2.0 had a useful critique of the citizen scientist. It is very important to consider these things, and the future of citizen science opportunities will be dependent on how valuable their efforts will prove to be.

The role of the citizen scientist is certainly still an evolving one, and will likely eternally be in flux. Before the era of professional scientists comfortably sitting at respected universities and industrial businesses, which is now commonplace, the majority of scientific exploration was accomplished by the non-professional, or “natural philosopher”. In fact, the term “scientist” wasn’t even used until William Whewell coined the term in 1833. These days, not everyone can–nor should–follow a career path into professional research, but there is no reason why someone interested in learning about and even participating in scientific exploration should be excluded from the opportunities.

There is certainly a difference between data processors and pure scientists. One person plugs and chugs through data using a pre-defined set of rules and regulations. The other actually develops those rules, thoroughly thinks about how to use them, and makes conclusions about the results with skill. But, the inherent sensation in this comparison–that one somehow is less interesting than the other–misses the real purpose and excitement of citizen science efforts.

We certainly don’t need everyone to be converted into fundamental science researchers to profess at ivy league institutions. There are certainly many of them out there already, and the job market these days for new hires offers some slim pickings. The point, rather, of citizen science is to inspire and generate a broad appreciation for science and the universe in which we live.

Involving a wider spectrum of the population with accessible, fun, and interesting projects–even if they “only” require human-level data processing, which, by the way, in the realm of pattern recognition, is still so much more impressive than computer-based data processing!–can only positively support everyone involved. In addition, a culture with a greater population who has increased levels of science appreciation will also benefit in long-term sustainability, assuming you believe that a more clear understanding of science across the majority of individuals can only bring about good things.

So, although the “crowd sourcing” and citizen science projects in effect right now (GalaxyZoo being a primary example) might not require each participant to be a full-scale experimentalist, it seems like absolutely nothing is lost. If fact, it seems that because of this non-requirement, even more is gained for the larger picture, since the hurdles for participation are not insurmountable for nearly everyone

The more non-professionals involved in doing real science–even if it is “just” data processing–will bring a greater appreciation to these non-professionals, which will only help support the professionals down the road (say, through successful data analysis resulting in new discoveries, or the increased willingness of citizens to pay those higher tax dollars into the NSF and NIH).

MORE:

“Citizen Science Isn’t Enough Science For Citizens” :: Michael White’s Adaptive Complexity, Science 2.0 :: June 8, 2010 :: [READ]

“Experts Weigh in on Crowd Science Trend” :: genomeWeb’s The Daily Scan :: June 4, 2010 :: [READ]

“The Growth of ‘Citizen Science’” :: The Chronicle of Higher Education :: June 3, 2010 :: [READ]