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If "engagement" shouldn't drive media algorithms, what should?
@PartnershipAI held a workshop with 40 recommender system professionals, researchers, and critics and here are our answers.https://www.partnershiponai.org/beyond-engagement-aligning-algorithmic-recommendations-with-prosocial-goals/ …Thanks. Twitter will use this to make your timeline better. UndoUndo -
A better headline might have been: "CDC study shows vaccines don't protect against Delta as well as earlier variants, underscoring the importance of herd immunity."
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If you want to get serious about this, you could compute the risk ratio between vaxxed and unvaxxed, using a base rate of 69% vaxxed for the county (as the CDC paper notes). I've seen similar cases of failure to use a risk ratio in journalism beforehttp://jonathanstray.com/what-data-cant-tell-us-about-buying-politicians …
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Part of the journalistic challenge here is there are two key messages to get across, that seem to pull in opposite directions: - you can still get infected even if vaxxed - but vaccines really cut down the risk Together, this is the reason why everyone needs to get vaxxed.
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If this isn't clear to you, consider: when 100% of the population is vaccinated, then 100% of the COVID cases will be in vaccinated people. There is no information about the effectiveness of the vaccines in this headline, even though it sounds like there is.
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This is an awful, awful, headline. I've been teaching stats to journalists for years but I never thought it would be life or death (base rate fallacy). Should have gone with "Roughly 97% of new hospitalizations and 99.5% of deaths in the U.S. are among unvaccinated individuals"https://twitter.com/CNBC/status/1421178119747162114 …
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This is one of those rare cases where an understanding of Bayes' Theorem is actually critical. "% infected people who were vaxxed" is really, really not the same as "% of vaxxed people who were infected." If 90% are vaxxed, most infections will be vaxxed. https://en.wikipedia.org/wiki/Base_rate_fallacy …https://twitter.com/CNBC/status/1421178119747162114 …
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Platform recommender engineer told me today: yes, we could turn up the diversity so no one's feed gets too specific. But then a lot of people would miss out on finding all the other folks who are into whatever their thing is, and people get a lot of joy and connection from that.
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Sometimes people are like "why is polarization bad?" and I'm like, well, I reeallly don't want to go any further up this escalation curve.pic.twitter.com/Ix7r55vB8i
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Jonathan Stray Retweeted
Still, these data paint a starkly different picture from the CrowdTangle dashboard that Kevin Roose regularly tweets. Seehttps://twitter.com/jon_m_rob/status/1386798266667372545?s=20 …
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Remember when I said that the White House might be the worst possible messenger for trying to get people vaccinated? This backfire effect has been confirmed.https://twitter.com/CaulfieldTim/status/1420429315443990529 …
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We just aren’t there yet with basic recommender controls.https://twitter.com/heratylaw/status/1420233961733713921 …
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Jonathan Stray Retweeted
I am awestruck at this combo of fluent data analytics for non-coders plus training for data journalists. Kudos
@adamhooper,@pierreconti,@jonathanstray for advancing what I first saw in DabbleDB (@avibryant) and OpenRefine (http://davidhuynh.net ). https://app.workbenchdata.com/courses/en/intro-to-data-journalism …Thanks. Twitter will use this to make your timeline better. UndoUndo -
I see this correlation too. This thread picks apart potential reasons for that, but more importantly how this cultural fact might bias guesses about what types of AI social impacts will prove most significant.https://twitter.com/Miles_Brundage/status/1419077027022336001 …
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Jonathan Stray Retweeted
I'm going to repeat this -- please read this whole thread, which is one of the smarter things I've read on this issue. Whether respect is useful as a strategy for deniers depends almost entirely on your location in the network.https://twitter.com/EBHarrington/status/1418317295278084100 …
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The tweet it composed for me was pretty good, actually. Full points for self-reference. https://twitter.com/theJohnHerrick/status/1418260277217296387 …pic.twitter.com/vTbBCfLc5c
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Jonathan Stray Retweeted
Good. I’m sick and tired of classic artists being exempt from the attention economy. They should feel the dehumanizing pressure of engagement metrics just like the rest of us.https://twitter.com/CityLab/status/1415835106338615296 …
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Jonathan Stray Retweeted
Instagram, which is owned by Facebook, is now targeting me with ads about the awesomeness of targeted adspic.twitter.com/am9Lp1kNJO
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My takeaway: this is a very cool algo auditing method. But it’s recsys 101 stuff. The hard question is not whether a recsys responds to your interests — it does! — but what's happening with the humans, and what kinds of media diets are healthy. Bot audits can’t answer that. /FIN
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To close, a word on transparency. I’d love the reporters to publish their code so we can see exactly what they did, and how to build on it. The deeper problem is it should be possible for outsiders to run audits on real platforms. Perhaps like this. https://cdt.org/insights/overview-of-transparency-obligations-for-digital-services-in-the-dsa/ … 15/
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The reporters also found it surprising that only one signal — watch time — was enough to establish each bot’s interests. I don’t find this surprising. Both theory and practice show that a single reward signal can produce incredibly complex behavior. https://deepmind.com/research/publications/Reward-is-Enough … 14/
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