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25 Jun, 5 tweets, 3 min read
Noise is a remarkably insidious form of pollution: a 10db noise increase (from dishwasher to vacuum) drops productivity by 5%. But the kicker is you don't notice: noise hurts your ability to think, not your effort. You work as hard but do worse! And poorer areas have more noise.
Here's a link to the paper, which makes the point that policy is really needed to regulate noise, since people don't realize how much they are impacted by it, and so don't value quiet as much as they should: joshuatdean.com/wp-content/upl…
Also other forms of pollution also impact cognition in subtle ways. More 👇
Noise cancelling headphones don’t solve the noise problem, as this study shows. They don’t significantly improve our ability to concentrate in office environments. And again, it’s a bit of a trap: we feel that they help us, even though they don’t! pub.dega-akustik.de/ICA2019/data/a…
Since people are asking about music, results have been a bit contradictory, but this 👇 paper uses multiple experiments to find that, for tasks that involve memory or writing, music hurts performance.

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More from @emollick

Ethan Mollick Profile picture
14 Jun
A profound understanding of technology is found in Historian Melvin Kranzberg's 6 Laws of Technology. Here they are in a 🧵

1st Law: “Technology is neither good nor bad; nor is it neutral,” many problems occur when benign technologies are used at scale. Think DDT (or Facebook) Image
2nd law: “Invention is the mother of necessity” - new technologies, as they scale, require their own suites of innovations. Self driving cars have pushed development of new sensors, phones ever better cameras, etc. This is a good rule for entrepreneurs looking for new markets.
3rd law - “Technology comes in packages, big and small” Technology is all about systems, you can’t study individual things in isolation. One issue with blockchain is that it doesn’t fit well into the social, organizational, and technical systems that it is supposed to replace.
Read 6 tweets
Ethan Mollick Profile picture
6 Jun
A thread on the science of stories:

Stories are persistent: this paper traces back fairy tales across languages & cultures to common ancestors, arguing that the oldest go back at least 6,000 years. One of the oldest became the myth of Sisyphus & Thanatos in ancient Greece. 1/
That may be the start: this paper argues some stories may go back 100,000 years. Many cultures, including Aboriginal Australian & Ancient Greek, tell stories of the Plaeades, the 7 sisters star cluster, having a lost star- this was true 100k years ago! 2/ dropbox.com/s/np0n4v72bdl3…
Stories share similar arcs: Analyzing 1.6k novels, this paper argues there are only 6 basic ones:
1 Rags to Riches (rise)
2 Riches to Rags (fall)
3 Man in a Hole (fall rise)
4 Icarus (rise fall)
5 Cinderella (rise fall rise)
6 Oedipus (fall rise fall) 3/
epjdatascience.springeropen.com/articles/10.11…
Read 8 tweets
Ethan Mollick Profile picture
4 Jun
One of my favorite scientific figures is this one of the entropy levels of 100 world cities by the orientation of streets. The cities with most ordered streets: Chicago, Miami, & Minneapolis. Most disordered: Charlotte, Sao Paulo, Rome & Singapore. Paper: appliednetsci.springeropen.com/articles/10.10…
To illustrate, here is how the maps look for Minneapolis (most ordered) & Charlotte (most disordered), rendered with this amazing tool for showing maps of roads by @anvaka: anvaka.github.io/city-roads/?q=…
Here's the cities organized by alphabetical order from the paper (by @gboeing )
Read 6 tweets
Ethan Mollick Profile picture
1 Jun
Challenge in social science posts: indicating when claims are causal in papers. Many papers find relationships without trying to show causality- a useful start for more research! But readers may think a causal argument is being made & complain. Good intro: alexedmans.com/blog/corporate…
Academics tend to be very careful about this language. If something is “linked” or “associated” with something else, that is not making a claim that one causes another. Neither is “predicted by” in many cases. This thread 👇 on Hill’s Criteria can help you think through claims.
And don’t get me started on “correlation isn’t causation.” Correlation could be:
✅Nothing
✅Causation or reverse causation
✅Confounding factors or omitted variables
✅Both factors lead to group selection (more men are 👩‍🚒, more 👩‍🚒 get hurt in 🔥, but 🔥doesn’t burn men more) Image
Read 4 tweets
Ethan Mollick Profile picture
4 May
For May 4th, a lesson on how to sell new technology from Star Wars (& Edison). The key to the look of Star Wars ships are greebles: glued-on bits from off-the-shelf model kits of WWII tanks, planes etc. They make a connection with current tech, making Star Wars feel familiar. 1/ Image
To sell electricity, Edison used the same technique as the Star War's greebles by using skeumorphs (a design throwback to an earlier use) connecting his new scary tech to a familiar one: gas. Gas lights gave off light equal to a 12 watt 💡so Edison limited his 💡 to 13 watts. 2/ ImageImage
As another example, lampshades weren't needed for an electric light, since they were originally used to keep gas lamps from sputtering. But Edison added them anyhow. While not required, they are comforting and, again, made a greeble-like connection to the older technology. 3/ Image
Read 7 tweets
Ethan Mollick Profile picture
19 Apr
I think many lean startup founders do far too many customer interviews- 100 or more in many cases! Diminishing returns kick in pretty fast & there are other startup experiments, too. So how do you know how many to do? Look for “theme saturation” when <5% of information is new 1/2 Image
Ways of calculating this are in the article, but there is evidence that 92% of key themes are identified within 12 interviews. Even cross-cultural studies often require only 20-40 interviews. Interviews can help but you need to progress to other tests! 2/2 journals.plos.org/plosone/articl…
In general, founders should separate the vital parts of the lean startup method (experiments & hypotheses!) from the dogmatic parts (too many interviews, business model canvas). That doesn’t mean the dogmatic parts can’t be useful, but they are limiting. hbr.org/2019/10/what-t…
Read 4 tweets

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