Ariel Waldman writes and speaks about “democratized science”, advocating radical DIY “science”, as she says, “Massively Multiplayer Science”. Recently she has been interested in “hacking space” (as in outer space), but her writ includes lots of citizen science and DIY science. (I’ll come back to SpaceHack in a future post.)
One of her earlier contributions was the “Democratized Science Instrumentation” Guidebook (2012), which cataloged 25 low cost instruments and systems that “that are breaking down barriers by enabling open, accessible, cheap and citizen-led science.” (p. 2)
This work is motivated by her understanding that “[t]he cost, size and accessibility of instrumentation are often some of the main barriers to entry in scientific exploration.” (p. 2) More generally, “[t]hose working outside of scientific institutions often lack access to professional-grade instrumentation” and this “lack of democratized instrumentation…hinders multidisciplinary exploration, timetables for discovery, distributed knowledge and contributions by those outside of the science industry.” (p. 3) If science is important, then it is important that everyone wit a contribution has a chance to make it.
I’m not sure I completely buy the premise here (access to instrumentation may or may not be the key barrier in a given case), but she is surely correct that this ethos has merged with the roaring river of DIY that is our Great Age or Making. “The maker/hacker community is a collective of people who have become empowered by creating, modifying or tinkering with hardware and software to create clever and more accessible solutions to a wide variety of problems.” (p. 3) In our community maker spaces and fab labs, we are putting the tools in the hands of the workers.
Waldman notes the importance of these communities and other social structures, she has little to say really. If you reject formal scientific institutions, you are left with Hackathons and, nowadays, Kickstarter. I’m not sure these are enough. We need persistent, long term, non-profit scientific communities.
Setting aside Waldman’s strategic analysis, the guidebook has a collection of interesting tools, ranging from online data analytics such Galaxy Zoo to various DIY DNA processing instruments. The common theme is that “anyone can do it”.
With her focus on instrumentation, it isn’t surprising that the list is heavy on data collection and light on analysis or interpretation (theory). Having some formal training, and knowing a lot of really smart scientists, I know that most of the formal training of scientists is not about how to operate cool instruments, but how to understand the data that comes out of them, and what inferences can validly be drawn. Scientists do not just turn on the microscope, get the read out, and send it off to the “gatekeeper” journal to get points. Scientists have to understand how to sample, how to check, cross-check, and re-check for errors, and how to make valid inferences from data.
Just as a for instance, consider the first gizmo in the guidebook, the Air Quality Egg http://airqualityegg.com/, now in use all over the planet. This device lets you collect and amass CO and NO2 concentrations “right out there” in your yard. The website has data from more than a thousand of such devices.
The idea is that this data will help you “to understand or change the local dynamics of pollution that affect you.” It certainly “gives people a way to participate in the conversation about air quality.” But is this “science”? Is the data even meaningful?
With little information about where the device is located, how can you interpret the readings? I mean, an Egg that is sitting near a major road will see a lot more emissions than one in a large park. Outdoor readings will change rapidly as the wind shifts. Readings on the ground will be different from readings on a tenth floor balcony of the same building. And so on. What do all these difference mean? It’s complicated, and the readings form the Egg are scarcely sufficient to parse out what is going on.
f readings from a single Egg are difficult to interpret, what can be made of readings from a thousand Egg’s all around the world?
I’m not saying no one should make or use DIY instruments. But I am saying that just collecting data is scarcely “science”. It may or may not engender “conversation” about scientific topics, but who knows if such a conversation will be better or worse for the DIY data?
My own view is that it is vastly more important to try to understand what our best science tells us, and what we do and don’t know (and why). I.e., study science. Putting on a lab coat and collecting some data might lead to an important discovery, but it probably won’t. And the odds on producing junk data are very high. Ask any scientist about that.
That said, many of these gadgets are quite seductive. Who wouldn’t love to have his own PCR and gel box, so I could dink around with DNA? What would I do with one? I have no idea!
- Ariel Waldman, Democratized Science Instrumentation. Science and Technology Policy Institute Occasional Papers in Science and Technology Policy, Washington, 2012. http://arielwaldman.com/wp-content/2014/06/OP-7-2012-DemocratizedScienceInstrumentation-v1.pdf