My rating: 5 of 5 stars
Okay, who took part in SETIhome? Raise your hand… I did for a couple of years and it’s in here. I have way too many reading obligations (ARCs and borrowed) but this popped up and I… let myself be sidetracked with this advance review copy received from the publisher from NetGalley, due out in February 2020. Fortunately, it is a very fast read. It comes off targeted to youth/young adults, but Mses. (I know Messrs. is the plural of Mr., but had to look up the plural of Ms.) Cavalier, Hoffman, and Cooper talk early on of “[e]xposing your children to citizen science…”
The authors give “fifty-plus” programs to participate in and they range from things seemingly obvious like bird/animal watching/observing to mushrooms, monarch butterfly migrations, or trash on beaches, Alzheimer’s observations and selfies at streams to help map all of the streams, even reporting infrequent events like landslides. They tell the reader how to find the project, what’s required (simple as a clipboard or a computer, perhaps needing special software or specific collecting materials), how broad the scope is (localized or global), the goal, task, outcome and their opinion why they like the project.
Most importantly, the authors affirm the value of citizen science. You don’t need scientific credentials. You do need to “review all of the instructions, training modules, and information” before beginning. And for it to work…you need to participate. Rightly, the authors advise that the project needs to fit you as much as you fit it. You may not have the time, resources or maybe passion to commit, and we all know sifting bad data is a necessary burden, but responsible limiting of bad data is so, so welcome.
Cringe when reading it moment: An MIT project called DeepMoji is designed to teach Artificial Intelligence systems about emotions, but requires a … [cringe again as I type this}…Twitter account. Oh, MIT, Twitter? Really? Sifting the sludge, I guess, has some value.
Really cool eye opener when reading it moment: One project (Foldit) has teams solving folding puzzles to help predict protein structures (and gathering data on pattern recognition and general puzzle solving to teach computers how to solve better), used in genetics and drug targeting. The eye-opener./..teams that successfully solve protein folding puzzles become coauthors on the scientific papers!
Five stars for being a novel book on something extremely important, particularly as the US slips backwards on the science front. Check out SciStarter for more information and opportunities.