Please try the URL privacy information feature enabled by clicking the flashlight icon above. This will reveal two icons after each link the body of the digest. The shield takes you to a breakdown of Terms of Service for the site - however only a small number of sites are covered at the moment. The flashlight take you to an analysis of the various trackers etc. that the linked site delivers. Please let the website maintainer know if you find this useful or not. As a RISKS reader, you will probably not be surprised by what is revealed…
https://www.msn.com/en-us/news/us/the-results-are-in-for-remote-learning-it-didnt-work/ar-BB155PAl
The problems began piling up almost immediately. There were students (without computers and] Internet access. Teachers had no experience with remote learning. And many parents weren't available to help. In many places, lots of students simply didn't show up online, and administrators had no good way to find out why not. Soon many districts weren't requiring students to do any work at all, increasing the risk that millions of students would have big gaps in their learning. “We all know there's no substitute for learning in a school setting, and many students are struggling and falling far behind where they should be,” said Austin Beutner, superintendent of the Los Angeles Unified School District, in a video briefing to the community on Wednesday.
Many in tech cheered when Twitter added labels to President Trump's tweets. But civil libertarians caution that social media companies are moving into uncharted waters.
https://www.nytimes.com/2020/06/05/technology/twitter-trump-facebook-moderation.html
After work on the Golden Gate Bridge's sidewalks to bolster their wind resistance, nearby residents of San Francisco are complaining that the 1.7 mile-long structure makes a creepy droning noise when it's windy. The mysterious and unsettling tone is heard in videos posted by Alberto Martinez, Mark Krueger and @reedm. It's a spectacular example of engineering neglect.
https://boingboing.net/2020/06/06/engineering-screwup-turns-gold.html
https://sg.yahoo.com/news/robot-dog-hounds-thai-shoppers-keep-hands-virus-074643214.html
“I think the execution, like the robot itself, is a bit scary,” the 29-year-old said, though she admitted that giving out hand sanitiser is a “good idea”.
Muzzle the mandible-equipped model.
Singapore plans to give a wearable device that will identify people who had interacted with carriers of coronavirus to each of its 5.7 million residents, in what could become one of the most comprehensive contact-tracing efforts globally.
Testing of the small devices, which can be worn on the end of a lanyard or carried in a handbag, follows limited take-up of an earlier smartphone-based system and has further fueled privacy concerns about contact tracing technology.
The tiny city-state, with one of the highest COVID-19 caseloads in Asia, is one of many countries trying to use technology to allow them to safely reopen their economies.
Singapore will soon roll out the device, which does not depend on a smartphone, and “may then distribute it to everyone in Singapore,” Vivian Balakrishnan, the minister in charge of the city-state's smart nation initiative, said on Friday. […]
https://gizmodo.com/even-scientists-funded-by-zuckerberg-are-dragging-faceb-1843945011
Rodney Parkin should remember Hanlon's razor.
My experience of various governments (the administrative parts) consistently demonstrated “stupidity” when designing systems. This word is better characterised as: “ignorance of the reality” and “inability to consider ‘out-of-the-box’ situations”. Government projects, especially where computer programs are involved, provide a rich seam for RISKS' contributors to mine.
Shapir's excellent comments connect to research on “news finds me”, e.g.,those people who say
> “we know better because we have read an Internet post!”
Recent research papers tell us that the people most likely to believe conspiracy theories are those who don't read (on paper, online, etc.) articles about a topic. They believe that anything that matters will find them, via channels such as social media groups, rather than their having to look for news at all. One paper that is available online is by Michael Wagner and John Foley. Once you “know” that reports contrary to your beliefs derive from conspiracies, no amount of presenting facts and rational arguments will change those beliefs. https://www.brookings.edu/techstream/how-media-consumption-patterns-fuel-conspiratorial-thinking/
Since the early days of social media I have been making the point that Amos Shapir echoes. Headlines, in both mainstream and social media have become increasingly hyperbolic, seldom more so than when a “cause” or disaster is involved. With no apologies to the coronavirus pandemic, there is a long-standing saying in the media, that the headline: “Small Earthquake In China, Not Many Dead” does not sell newspapers. Consequently, editors have always chosen snappier phrases, which sometimes misrepresent the real story.
That seems to have become somewhat of the norm these days, especially so on social media such as Facebook, Twitter and even LinkedIn.
Contributors (I would not demean the role of an Editor by giving the authors that title) now trade on their readers (and I hesitate to use that description) not looking beyond the headline. Only a vanishing few now read below the fold.
Anecdote: many moons ago I found myself seated next to the retired British Prime Minister, Sir Ted Heath on a Concorde flight to Miami (he was going to watch the Superbowl, I was heading to Bogota in a hurry). He read the broadsheets from masthead to imprimatur and I commented to him that he must now have a Catholic view of the news. His reply was at the same time both stunning and bleedin' obvious, so much so that I recall it verbatim, and is highly relevant in this context.
He said: “It has been my delight since leaving office, to read the newspapers for myself. When I was Prime Minister, I received two digests of the news: one prepared by the Cabinet Office [the Civil Service digest of relevant news - MB] and one prepared by my PPS [Parliamentary Private Secretary, giving the Conservative Party's digest of relevant news - MB].”
“You know, I could have been Prime Minister of two different countries!”
Unless the variance is infinitely large (and extensive scientific evidence gathered over the last few months proves this not to be the case), then the concept of R0 is indeed well-defined and R0 does indeed have a precise value for a given data set: “superspeaders” notwithstanding. The value of R0 is analogous to the “expected value” in probability theory: the actual wins and losses in a game of chance may vary wildly, but the concept of “expected value” is still valid.
There is no point in continuing to argue that the infection process “might” have such a wide variance that the outcome is completely random and undeterminable and uncontrollable, and that therefore any model is worthless. The data is in: as I wrote in RISKS-31.90, a number of countries have taken various actions (those supported by the models that Baker is still trying to discredit) and these are beating COVID-19. Other countries have failed to take effective action and these still do not have the virus fully under control.
If the model is faulty because the situation is completely random and unpredictable (in the chaos theory sense), then there would be no corollation between actions taken and outcomes. But by now the corollation is plainly there to see in the data:
https://www.endcoronavirus.org/countries
The Law of Holes: “If you find yourself in a hole, stop digging!”
[If the experts who read RISKS are having trouble with these concepts, then we're all in deep yogurt! Derek Bok, a president of Harvard University, said “If you think education is expensive, try ignorance”. Between the trillion dollar bailout in the Great Recession, and the trillion dollar bailout in the Great Pandemic, I'd say that we all just paid the highest tuition in history to learn the cost of our ignorance regarding heavy/fat tailed distributions. HB]
Statisticians came up with the terms ‘mean’, ‘median’, and ‘mode’ because the term ‘average’ was ill-defined.
For ‘normal’ distributions, ‘mean/expected’, ‘median’, and ‘mode’ coincide, so there is less need to disambiguate.
For (ab)normal distributions, mean/median/mode can vary widely from one another, or may not even exist—e.g., the pathological, but not unusual, ‘Cauchy’ distribution (“applications of the Cauchy distribution … can be found in fields working with exponential growth” [Wikipedia]), which has neither a mean/expected value, nor a variance, nor a standard deviation, thus for the Cauchy distribution (and many other commonly occurring distributions) Arthur's phrase “the size of the standard deviation” is nonsensical.
Takeaway: when some distribution is not ‘normal’, then our INTUITION FAILS US. The sign on an abnormal distribution should read: “Abandon all intuition, ye who enter here”. Something is dreadfully wrong when the variance/standard deviation or even the mean/expected value does not exist. Even when the mean/‘expected value’ does exist for such an abnormal distribution, it is almost always misleading and/or useless. Perhaps it would be more appropriate to call such a mean ‘the SUSpected value’! :-)
Indeed, Nassim Taleb has written entire books about the differences between ‘mediocristan’ (‘normal’ distributions) and ‘extremistan’ (heavier-tail-than-normal distributions), and has had unrelenting criticism of the financial regulators for their inappropriate use of ‘normal’ instead of ‘fat-tailed’ distribution models in the run-up to the Great Recession. One of Taleb's books has the name ‘Fooled by Randomness’, which I loosely translate as ‘Fooled by Ab-Normality’.
The whole point of the terms mean/median/mode/average is to attempt to characterize the ‘ordinary/typical/expected’ behavior of a system. For many systems having ‘normal’ distributions, these attempts often succeed, mostly because the bulk of the density of the distribution is confined within a relatively narrow band around the mean/median/ mode/average, and the ‘tails’ of the distribution fall off extremely fast, so the percentage of ‘out-liars’ (pun intended) is negligible.
Thus, e.g., classical thermodynamics works beautifully, because many/most of the variables are normally distributed, and with Avagadro's number of ‘independent’ variables, these normal distributions are incredibly smooth and accurate. Traditional differential equation models are therefore appropriate.
Getting back to ‘reproduction rate’, we find that in the presence of superspreaders, this rate is NOT normally distributed—indeed, it has exceedingly high variance due to its heavier-than-‘normal’ tail. If such a random variable occurred by itself, discussions of ‘average’ behavior might be excused. However, when a symbol like ‘R0’ appears as the BASE of an exponential function—e.g., (R0)^n—any attempt to describe an ‘ordinary/typical’ behavior is nonsensical, because the variance of (R0)^n is amplified to effectively infinite proportions (variances nearing the magnitude of Avagadro's Number qualify as ‘effectively infinite’ IMHO).
We all agree that these pandemic R0-based models are ill-conditioned, and I have simply pointed out that one of the causes of this ill-conditioning is the high variance of the distribution for a ‘reproduction number’, which variance is then amplified by its appearance as the base of an exponential function.
An aside on “policy prescriptions”:
I have studiously avoided any discussion about which policy prescriptions should be followed, but I would merely make the comment that if one bases one's decision about whether to follow some policy prescription on the validity of some scientific statement, then if that statement is shown to be false/inaccurate, then such a prescription becomes illogical and unsupported.
Indeed, from a false premise, one can deduce a true conclusion, but in that case, all false premises are logically equivalent, e.g., “we would predict approximately 510,000 deaths in GB” is logically equivalent to “Iraq had weapons of mass destruction” is logically equivalent to “the Moon is made of green cheese”. But NASA didn't spend $1 trillion on the lunar exploration program because some ‘scientist’ swore that the Moon was made of green cheese.
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