I find the (short) video easiest to follow:
Best of all, it is incentive-compatible. The founder Po-Shen Loh, a mathematician from Carnegie Mellon, wrote to me:
…for each positive case, don’t just ask the direct contacts to quarantine; instead, tell everyone how many relationships away COVID just struck (e.g., “3” is a contact of a contact of a contact). Then animate this over time like a weather radar…Keep everything anonymous.
Suddenly, the main purpose of the intervention is no longer to protect others from you (quarantining after being exposed). Instead, it is to directly protect you from others, because that early warning of approaching COVID lets you know it’s a good time to wear a better mask, or to be more vigilant about distancing, because the situation is getting hot. This appeals to self-protection instincts instead of altruistic instincts. Since this app is already in deployment, we know anecdotally, for example, of a person who installed the app because his kid was going to a university that was using the app. Why? So that he could be alerted in case COVID started spreading his way from the university via his kid.
Here is his associated preprint. As economists, ought we not to feel that appealing to self-interest and love of family sometimes works?
ThreadHelper is a browser extension that finds you the tweets you need. It shows as a sidebar on the right hand side of your Twitter timeline and instantly and automatically searches bookmarks, retweets, and your past tweets for tweets that are semantically relevant to the tweet being composed. It can be used as a specific search that’s faster than Twitter’s or as a fuzzy search tool.
Alex is very very highly rated by those who know him, but still in the broader scheme of things significantly underrated as a Bay Area tech and finance thinker. Here is Alex on SPACs:
If the best fundraise (IPO included) aggregates as many potential buyers as possible to raise money at the highest price with the least dilution and lowest fees, it’s hard to understand how a SPAC represents an improvement against those constraints. When a SPAC merges with a target (“de-SPACs”), it’s tantamount to an IPO. The SPAC (already publicly traded, with lots of cash on its balance sheet) and the target company agree on a pre-money valuation for the target; the money sitting in the SPAC becomes the “money raised” (IPO equivalent) with typically a PIPE (Private Investment in Public Equity, a further institutional fundraise / large block sale) done at the same time. As an example, a $500M SPAC might merge with a private company, ascribing a $4.5B valuation to the private company, meaning a $5B post-money valuation of the combined entity. How do we know *this* is the fair price? Should a company meet with one SPAC? Two SPACs? Three SPACs or four? Where is the price discovery?
And while the fee structure of SPACs will likely change, right now it is indisputably a more expensive option with less price discovery. Bankers are paid 5%+ for taking the SPAC public; SPAC investors typically get warrants with their investment; the SPAC sponsor typically gets 20% (of the pre-merger value of the SPAC) for finding a target, so 2% in the above example; a banker is normally hired and paid to handle the merger; a mini-roadshow happens to get approval from the SPAC shareholders AND to potentially secure more cash in the form of a PIPE, for which a banker is also paid.
Most of the post is on why IPOs are less inefficient than you might think, informative and interesting throughout.
From a GitHub repository:
This GitHub repository is a back up of my FAERSFix scripts.
The FDA Adverse Effect Reporting System is a horrifically dysfunctional quagmire of shockingly bad data. The data is not just bad for severe epistemological reasons, it is also poorly organized and riddled with flagrant absurd errors.
These scripts smooth over the very messy process of acquiring and basic debugging of the data. At the end of the process a user can arrive at a local repository of the FAERS data that is sane enough to begin to think about some kind of sensible analysis. To understand the disastrous state of the original source data, see the source code of the scripts which is designed to be a readable self-documenting manual demonstrating how to correct this mess.
Since the FDA’s gremlins never rest, these scripts will become obsolete. If you would like to contribute updates or fixes, feel free to send me a patch or a pull request. Good luck!
I thank Chris E. for the pointer.
I’ve tried it a few times, and I think it will become “a thing.” You can read about it here, though it is time someone did a more current article. It is the best forum invented to date for mid-size, friendly, intellectual chats. Broadly speaking imagine a Zoom call, with competing topic-named rooms, the video turned off, and better queuing and calling upon people procedures. It doesn’t seem to induce fatigue the way Zoom calls do. The software has a fluidity and ease of use that I hardly ever see, as usually I hate new apps that people tell me to try.
I don’t know that it will ever be “my thing,” mostly because I can read so quickly, which raises my opportunity cost of consumption. (Though you can read with it on in the background — is it ever the case that no one in the audience is listening? Would that even matter?) In any case, I suspect it will take some real mind-share away from Twitter and Facebook, and now is the time for you to start learning about it.
So far it is invite-only, though I assume it will be opening up more broadly. Furthermore, an invitation is not so difficult to get. Arguably there is a problem with who gets invited or deplatformed, though so far this seems to bother the (non-participating) people on Twitter more than it disturbs anyone performing on Clubhouse itself.
It is much more Tiebout-like than Zoom, so someday this also may be an incredible data source on what leads to useful conversations, which are the best governance rules, and so on.
Fleetwood Mac’s Rumours is a top 10 album this week — more than four decades after its release — thanks to a viral TikTok video that’s had everyone vibing along to “Dreams.” Rumours now ranks seventh on the Billboard 200 chart, the publication announced last night, the album’s first appearance in the top 10 since 1978, a year after it debuted.
Rumours’ newfound popularity is thanks to a viral video from Nathan Apodaca, who goes by 420doggface208 on TikTok, that shows him skateboarding down a road and sipping cran-raspberry juice straight from the jug, while “Dreams” plays over top. It’s been viewed more than 60 million times since being posted at the end of September, and it’s even inspired both Mick Fleetwood and Stevie Nicks to sign up for TikTok over the past two weeks. Fleetwood recreated the viral video himself, while Nicks posted a video of herself lacing up roller skates and singing along. They have a combined 35 million views.
Here is the full story, via Fernand Pajot.
This seems unconfirmed, and do note some sources in the story do not believe this account, but here goes:
AstraZeneca, whose Phase 3 coronavirus vaccine clinical trial has been on hold for more than a month, did not get critical safety data to the US Food and Drug Administration until last week, according to a source familiar with the trial.
The FDA is considering whether to allow AstraZeneca to restart its trial after a participant became ill. At issue is whether the illness was a fluke, or if it may have been related to the vaccine.
The source said the root of the delay is that the participant was in the United Kingdom, and the European Medicines Agency and the FDA store data differently.
“They had to convert data from one format to another format. It’s like taking stuff off a PC and putting it onto an Apple. They had to spend a lot of hours to get what they wanted,” the source said.
On Friday, a federal official hinted there might be some word this week on the trial’s future.
Or maybe they just fooled CNN with it?
Otherwise, good thing we are kept safe from such dangerous data formats! Would it really not be better to move to reciprocal recognition procedures? Not to mention a unified data format, or perhaps some FDA methods to read data produced for the EU?
For the pointer I thank Jackson Stone.
“If quantum computing actually materializes, in the sense that it’s a large scale, reliable computing option for us, then we’re going to enter a completely different era of simulation,” Davoudi says. “I am starting to think about how to perform my simulations of strong interaction physics and atomic nuclei if I had a quantum computer that was viable.”
All of these factors have led Davoudi to speculate about the simulation hypothesis. If our reality is a simulation, then the simulator is likely also discretizing spacetime to save on computing resources (assuming, of course, that it is using the same mechanisms as our physicists for that simulation). Signatures of such discrete spacetime could potentially be seen in the directions high-energy cosmic rays arrive from: they would have a preferred direction in the sky because of the breaking of so-called rotational symmetry.
Telescopes “haven’t observed any deviation from that rotational invariance yet,” Davoudi says. And even if such an effect were to be seen, it would not constitute unequivocal evidence that we live in a simulation. Base reality itself could have similar properties.
Here is further discussion from Anil Anathaswamy. Via Robert Nelsen. As you may already know, my view is that there is no proper external perspective, and the concept of “living in a simulation” is not obviously distinct from living in a universe that follows some kind of laws, whether natural or even theological. The universe is simultaneously the simulation and the simulator itself! Anything “outside the universe doing the simulating” is then itself “the (mega-)universe that is simultaneously the simulation and the simulator itself.” etc.
Not a CWT, as he will be interviewing me, but likely a discussion too, who knows what I may fling back at him?
What do you all recommend I read to prepare? I prepared a great deal for my CWT with Vitalik a few years ago (one of my favorite episodes), but what is new with Ethereum and blockchain and other matters since then?
I thank you all in advance for your usual wise counsel and advice.
It would seem so, now there are lots of them, here is one part of my Bloomberg column:
The Nobel Peace Prize this year went to the World Food Programme, part of the United Nations. Yet the Center for Global Development, a leading and highly respected think tank, ranked the winner dead last out of 40 groups as measured for effectiveness. Another study, by economists William Easterly and Tobias Pfutze in 2008, was also less than enthusiastic about the World Food Programme.
The most striking feature of the award is not that the Nobel committee might have gotten it wrong. Rather, it is that nobody seems to care. The issue has popped up on Twitter, but it is hardly a major controversy.
I also noted that the Nobel Laureates I follow on Twitter, in the aggregate, seem more temperamental than the 20-year-olds (and younger) that I follow. Hail Martin Gurri!
The internet diminishes the impact of the prize in yet another way. Take Paul Romer, a highly deserving laureate in economics in 2018. To his credit, many of Romer’s ideas, such as charter cities, had been debated actively on the internet, in blogs and on Twitter and Medium, for at least a decade. Just about everyone who follows such things expected that Romer would win a Nobel Prize, and when he did it felt anticlimactic. In similar fashion, the choice of labor economist David Card (possibly with co-authors) also will feel anticlimactic when it comes, as it likely will.
Card with co-authors, by the way, is my prediction for tomorrow.
I will be doing a Conversation with him. So what should I ask?
Here is his um…Wikipedia page, presumably it is fairly accurate!
This started in the late 1980s, and was led by GMU economist Don Lavoie, who earlier had been a computer programmer. Here is one bit from Don’s extensive essay, co-authored with Howard Baetjer and William Tulloh:
The market for scholarly ideas is now badly compartmentalized, due to the nature of our institutions for dispersing information. One important aspect of the limitations on information dispersal is the one-way nature of references in scholarly literature. Suppose Professor Mistaken writes a persuasive but deeply flawed article. Suppose few see the flaws, while so many are persuaded that a large supportive literature results. Anyone encountering a part of this literature will see references to Mistaken’s original article. References thus go upstream towards original articles. But it may be that Mistaken’s article also provokes a devastating refutation by Professor Clearsighted. This refutation may be of great interest to those who read Mistaken’s original article, but with our present technology of publishing ideas on paper, there is no way for Mistaken’s readers to be alerted to the debunking provided by Clearsighted. The supportive literature following Mistaken will cite Mistaken but either ignore Professor Clearsighted or minimize her refutations.
In a hypertext system such as that being developed at Xanadu, original work may be linked downstream to subsequent articles and comments. In our example, for instance, Professor Clearsighted can link her comments directly to Mistaken’s original article, so that readers of Mistaken’s article may learn of the existence of the refutation, and be able, at the touch of a button, to see it or an abstract of it. The refutation by Clearsighted may similarly and easily be linked to Mistaken’s rejoinder, and indeed to the whole literature consequent on his original article. Scholars investigating this area of thought in a hypertext system would in the first place know that a controversy exists, and in the second place be able to see both (or more) sides of it with ease. The improved cross-referencing of, and access to, all sides of an issue should foster an improved evolution of knowledge.
A potential problem with this system of multidirectional linking is that the user may get buried underneath worthless “refutations” by crackpots. The Xanadu system will include provisions for filtering systems whereby users may choose their own criteria for the kinds of cross-references to be brought to their attention. These devices would seem to overcome the possible problem of having charlatans clutter the system with nonsense. In the first place, one would have to pay a fee for each item published on the system. In the second place, most users would choose to filter out comments that others had adjudged valueless and comments by individuals with poor reputations. In other words, though anyone could publish at will on a hypertext system, if one develops a bad reputation, very few will ever see his work.
Miller and Drexler envision the evolution of what they call agoric open systems–extensive networks of computer resources interacting according to market signals. Within vast computational networks, the complexity of resource allocation problems would grow without limit. Not only would a price system be indispensible to the efficient allocation of resources within such networks, but it would also facilitate the discovery of new knowledge and the development of new resources. Such open systems, free of the encumbrances of central planners, would most likely evolve swiftly and in unexpected ways. Given secure property rights and price information to indicate profit opportunities, entrepreneurs could be expected to develop and market new software and information services quite rapidly.
Secure property rights are essential. Owners of computational resources, such as agents containing algorithms, need to be able to sell the services of their agents without having the algorithm itself be copyable. The challenge here is to develop secure operating systems. Suppose, for example, that a researcher at George Mason University wanted to purchase the use of a proprietary data set from Alpha Data Corporation and massage that data with proprietary algorithms marketed by Beta Statistical Services, on a superfast computer owned by Gamma Processing Services. The operating system needs to assure that Alpha cannot steal Beta’s algorithms, that Beta cannot steal Alpha’s data set, and that neither Gamma or the George Mason researcher can steal either. These firms would thus under-produce their services if they feared that their products could be easily copied by any who used them.
In their articles, Miller and Drexler propose a number of ways in which this problem might be overcome. In independent work, part of the problem apparently has already been overcome. Norm Hardy, senior scientist of Key Logic Corporation, whom we met at Xanadu, has developed an operating system caned KeyKOS which accomplishes what many suspected to be impossible: it assures by some technical means (itself an important patented invention) the integrity of computational resources in an open, interconnected system. To return to the above example, the system in effect would create a virtual black box in Gamma’s computer, in which Alpha’s data and Beta’s algorithms are combined. The box is inaccessible to anyone, and it self-destructs once the desired results have been forwarded to the George Mason researcher.
There is really quite a bit more at the link, noting that at the time Don had assembled a group of about ten people working on these ideas. As for the hyperlinks, I recall thinking at the time something like: “People don’t value reading so much, so making reading better with hyperlinks won’t have a huge marginal value!”
A further Covid-19 India Prize goes to award winning journalist Barkha Dutt for her reporting on the Covid pandemic and related crises in India.
Because of the Covid lockdown (March-June 2020), Indian news reporting and broadcasting faced severe disruptions in March-April 2020. For the first 50 days, as television networks remained studio-bound, Dutt and her small team traveled across India to report from the ground, producing over 250 ground reports. All the videos and reports are available on the MoJo youtube channel.
One of the world’s most severe lockdowns unleashed a massive internal migration from the cities to the villages in India. Dutt’s team was one of the first to shed light on the erroneous state policies concerning economic migrants in India during the lockdown,, often while walking alongside migrants. Her sustained coverage eventually led other stations and newspapers to follow and report similar stories and invoked a policy response from the government.
Another Covid-19 India Prize goes to award winning data journalist Rukmini S, for The Moving Curve Podcast, covering the data issues in India. She is currently an independent journalist writing for Mint, The Print, India Today (where she is tracking the pandemic daily) and India Spend (she is tracking Covid mortality) and writes occasionally for The Guardian, SCMP and The Hindu.
She distills all the information, data, and her daily insights into a 5-7-minute audio update in the form of a free podcast, now at 92 episodes. The episodes range from getting to the heart of India’s death statistics, interviewing a rural doctor about what it’s like waiting for Covid to hit, to attempting to cut through India’s public/ private healthcare binary, and they have had significant influence on many state governments. The Moving Curve podcast is produced by a small team of two – Rukmini S and sound engineer Anand Krishnamoorthi. The podcast is available on the major platforms as well as on medium.
For me one of the most fun episodes, here is the audio, video, and transcript. And here is the longer than ever before summary, befitting the chat itself:
Audrey Tang began reading classical works like the Shūjīng and Tao Te Ching at the age of 5 and learned the programming language Perl at the age of 12. Now, the autodidact and self-described “conservative anarchist” is a software engineer and the first non-binary digital minister of Taiwan. Their work focuses on how social and digital technologies can foster empathy, democracy, and human progress.
Audrey joined Tyler to discuss how Taiwan approached regulating Chinese tech companies, the inherent extraterritoriality of data norms, how Finnegans Wake has influenced their approach to technology, the benefits of radical transparency in communication, why they appreciate the laziness of Perl, using “humor over rumor” to combat online disinformation, why Taiwan views democracy as a set of social technologies, how their politics have been influenced by Taiwan’s indigenous communities and their oral culture, what Chinese literature teaches about change, how they view Confucianism as a Daoist, how they would improve Taiwanese education, why they view mistakes in the American experiment as inevitable — but not insurmountable, the role of civic tech in Taiwan’s pandemic response, the most important remnants of Japanese influence remaining in Taiwan, why they love Magic: The Gathering, the transculturalism that makes Taiwan particularly open and accepting of LGBT lifestyles, growing up with parents who were journalists, how being transgender makes them more empathetic, the ways American values still underpin the internet, what he learned from previous Occupy movements, why translation, rotation, and scaling are important skills for becoming a better thinker, and more.
This bit could have come from GPT-3:
COWEN: How useful a way is it of conceptualizing your politics to think of it as a mix of some Taiwanese Aboriginal traditions mixed in with Daoism, experience in programming, and then your own theory of humor and fun? And if you put all of that together, the result is Audrey Tang’s politics. Correct or not?
TANG: Well as of now, of course. But of course, I’m also growing, like a distributed ledger.
COWEN: You’re working, of course, in Taiwanese government. What’s the biggest thing wrong with economists?
TANG: You mean the magazine?
COWEN: No, no, the people, economists as thinkers. What’s their biggest defect or flaw?
TANG: I don’t know. I haven’t met an economist that I didn’t like, so I don’t think there’s any particular personality flaws there.
COWEN: Now, my country, the United States, has made many, many mistakes at an almost metaphysical level. What is it in the United States that those mistakes have come from? What’s our deeper failing behind all those mistakes?
TANG: I don’t know. Isn’t America this grand experiment to keep making mistakes and correcting them in the open and share it with the world? That’s the American experiment.
COWEN: Have we started correcting them yet?
TANG: I’m sure that you have.
That is the title of my latest Bloomberg column. Here is one excerpt:
The larger question is how to know when this great stagnation is ending. Counterintuitively, the answer might be when people are most upset — because that’s generally how most humans react to change, even when it proves beneficial in the longer run. These feelings arise in part from the chaos and disruption brought about by some pretty significant changes.
People, here is the good news and the bad news: Change is upon us. We are entering a new era of crises — in politics and biomedicine, with climate and energy, and not incidentally, about how prudently we spend our time.
The regretful truth is that progress is never going to be easy. The great technological advances of the late 19th and early 20th centuries, remember, were followed by two world wars and the rise of totalitarianism. Innovations such as radio and the automobile improved countless lives but also broadcast Hitler speeches and led to destructive tanks.
I’m not predicting the same catastrophe for today. I’m only saying that when the discontent is palpable, as it is right now in America, keep in mind that true breakthroughs may already be underway.
The examples are in the longer text. Recommended!