Category Archives: Interests

The Field Guide to Citizen Science: How You Can Contribute to Scientific Research and Make a Difference by Darlene Cavalier

The Field Guide to Citizen Science: How You Can Contribute to Scientific Research and Make a DifferenceThe Field Guide to Citizen Science: How You Can Contribute to Scientific Research and Make a Difference by Darlene Cavalier

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.

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What I learned in 2017 from The Teaching Company’s Great Courses

As I’ve said before, I have a 22-40 minute morning commute to work (the longer time often due to absolutely no reason at all except … drivers.)gettyimages-55743523_1472835076262_5913880_ver1-0

I used to listen to NPR, then classical music, but after stepping up my audio learning in 2016, last year I continued listening to lectures from The Teaching Company. Quite a few of them, as it has turned out: Continue reading

What I learned this year from The Teaching Company’s Great Courses

I have a 22-40 minute morning commute to work, the longer time often due to absolutely no reason at all except … drivers.gettyimages-55743523_1472835076262_5913880_ver1-0

I used to listen to NPR, then classical music, but this past summer I started listening again to lectures from The Teaching Company. Quite a few of them, as it has turned out: Continue reading

In all probability…

NPR’s All Things Considered is talking this week in a special series Risk and Reason about how people interpret probability . Yesterday, they talked about weather  – as in … What does a 20% chance of rain mean? Do you know?

Today, they looked at the CIA using words rather than discrete numbers to assess the probability of something happening. “Likely”, “not likely” are encouraged instead of “67% chance” or “25% chance”. The three comments I saw on the page linked (there may be more when you check) were inane, but one commenter said

It’s a little disconcerting to be reminded that many of our policy makers can’t handle numbers, or apply critical thinking to them. […]

Silly. Nobody can handle numbers. Not as far as probability is concerned. I happen to think that the word approach is more meaningful in the CIA analysis context than a numerical score. People latch onto numbers and attribute not necessarily warranted credibility to them. I say “not necessarily” because there are legitimate cases of credible probability (coin flips, dice rolls), but those are few. And the more precise seeming of the numbers, the more they believe.

Something called the fallacy of false precision comes into play in these cases. The fallacious part is that you can’t have more precision than your least precise component. The necessity for words instead of numbers is simple: any time you have an opportunity to interpret data, the least precise component is a human being. Five analysts in a room …five different answers. Ten analysts…well. you know.

There are many, many examples of people falling to the lure of numbers and not in a good way (math geek here…there is a good way, even if you don’t think so). A quick look at an unfiltered Facebook feed will surely reveal at least one “97% of the people won’t…” But, words require justification, reasoning. Numbers do, too, but pulling the thread on the data is challenging. And on the analyst’s side, how do you explain precision when you’re assessing a terrorist threat? That’s only slightly more possible than guessing the likelihood that you’ll get a booth the next time you eat out.

Mark Twain popularized and attributed to Disraeli (unconfirmed):  “There are three kinds of lies: lies, damn lies, and statistics.” (I also add NRA gun safety propaganda, but to the point I’m trying to make here…) Assigning a precise numerical probability to a chaotic situation – and if it involves humans, it’s chaotic – is ludicrous. Using words like “likely” or “unlikely” begs further questions so that the decision maker can make an informed decision.

The decision makers can handle numbers fine, and do apply critical thinking. But it’s the right kind of critical thinking for the data being assessed. “Why do you think that?” “Why do you think [Bob] has a different recommendation?”

Probability can be consciously or unconsciously manipulated by interpretation. It can also be 100% accurate and totally meaningless. Think about it: If your parents didn’t have any children, there’s a very high probability you won’t either.

And in case you are wondering, the 20% chance of rain means that in weather situations like those predicted, measurable rain occurred 20% of the time.