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Casey Fiesler, PhD, JD, geekD Profile picture
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31 May, 5 tweets, 2 min read
I'm often struck by how much the foundation of science relies on individual integrity. And typically I feel it's pretty solid. But this kind of garbage is a result of publish-or-perish, bean counting, and the general incentive structures of academia. cacm.acm.org/magazines/2021…
Also when this situation came to light a year ago I went on a whole lengthy tweet-rant about it so I won't repeat myself but here you go. :)
Also to clarify: "is a result of" above should probably be "exacerbated by" because obviously it's a result of when there is a breakdown of individual integrity. Awful people gonna be awful, but there are incentive structures dictating the particular form of awful.
I'm also feeling especially annoyed over bean counting re: incentives as I put together my tenure materials. I mean, the number of beans in my jar right now is totally fine, it just seems weird for number of papers to be a useful metric for anything.
I bring this up because a review collusion ring probably results in bad papers being published. And if *number of papers* didn't matter so much, this behavior would not be incentivized because it would be more important to write good papers that would get published anyway.

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More from @cfiesler

Casey Fiesler, PhD, JD, geekD Profile picture
27 May
We read 700+ Reddit papers, analysis described in this (open access!) @SocialMedia_Soc article (led by @moduloone, with @_sgilbert_ @NaiyanJones & @michaelzimmer). Here are some things we know about research that uses data from Reddit! 🧵 journals.sagepub.com/doi/full/10.11…
Unsurprisingly, Reddit as a site of study or data source is on the rise. The first 2 papers we encountered were published in 2010, with a jump to 17 in 2013, and 230 in 2019.
I also think it's really interesting that though computing and related disciplines make up the largest number of journals represented in our dataset of Reddit papers, medicine and health is next - even (just) above social science. Computer Science, Engineering and Math constituted 33% of pu
Read 9 tweets
Casey Fiesler, PhD, JD, geekD Profile picture
9 May
I'm increasingly frustrated with "I don't know enough about ethics to include it in my class."

My take: If you e.g. teach an ML class & you actually don't know ANYTHING about ML ethics... learn. Ethics is part of ML. I'm sorry your education was lacking, but now time to learn.
Like, professors should be constantly continuing to learn. I learn new things so that I can teach them all the time. If you say "I don't know enough about ethics" what you probably mean is "I don't care enough about ethics."
I'm not suggesting that if you teach an ML class you need to go read Kant. I'm suggesting go read about ethics IN YOUR FIELD. Ethics is part of that field. So go learn it in the same way you keep up to date on ANYTHING that is new or you don't know!
Read 7 tweets
Casey Fiesler, PhD, JD, geekD Profile picture
15 Apr
In honor of PhD application season winding down, here's a tweet-thread-that-should-probably-be-a-blog-post on things I have observed through hearing from a LOT of PhD applicants in many different fields over the past eight months. TL;DR this process can be better. 🧵
Consider things admissions committees or faculty might expect to see in an application: LORs from certain types of people that mention certain things, statements of purpose with certain elements (faculty mentioned, why this program, etc.)

Are applicants TOLD these expectations?
As one critical example, are you in a field where it is common or there is even an expectation that applicants reach out to potential advisors before they submit an application? Is there any reason applicants would know this if they don't already have mentorship in that field?
Read 8 tweets
Casey Fiesler, PhD, JD, geekD Profile picture
19 Mar
This thread is for live-tweeting the ethics session at #SIGCSE2021. FIVE papers at @SIGCSE_TS this year about ethics in computer science education! 🧵
First up: "How Students in Computing-Related Majors Distinguish Social Implications of Technology" by Diandra Prioleau et al. at University of Florida.

They presented students with scenarios about AI technology (e.g. recidivism algorithms)...
... and found that their participants could spot social implications, but frequently missed issues of systemic discrimination. But surprisingly: About half of students had never heard of these issues, which points to a gap in computing curriculum. dl.acm.org/doi/10.1145/34…
Read 14 tweets
Casey Fiesler, PhD, JD, geekD Profile picture
9 Mar
As you know, I am a fan of @tiktok_us these days, but I need to put them on blast for a bad design choice. Folks interested in content moderation/platform safety, buckle up. This is a story about bad people exploiting a loophole for harassment. We can learn from this. [Thread 🧵]
TikTok has a "block" feature that works similarly to Twitter. If you block someone, you can't see them and they can't see you. This includes comments.

So now we have A (person being harassed) and B (awful person who thinks it's fun to e.g. leave death threats in comments)...
B has figured out that they can comment on A's post and then immediately block A, which then means that A can't see that comment - and in fact doesn't even know it's there since it doesn't show up in their notifications.
Read 8 tweets
Casey Fiesler, PhD, JD, geekD Profile picture
7 Mar
Some thoughts on why this news - the potential for next gen watches (both Samsung Galaxy and Apple) to provide blood glucose readings - could be game-changing (not so much for #T1D folks but for everyone else). macrumors.com/2021/03/05/app…
This tech would almost certainly not be an improvement over existing continuous glucose monitors like what I use, but (I think?) it's rare for people with Type 2 to have insurance coverage for CGMs, especially if you're not on insulin and don't have to worry about lows.
The beauty of continuous monitoring over finger sticks is that you can get DATA. Unless you waste a lot of (expensive!) test strips to try to experiment, you're not going to know e.g. exactly when and how much your blood sugar spikes after meals.
Read 6 tweets

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