Category: Miscellaneous

Source: Risk Bow-Tie Method, by Julian Talbot

Bow-Tie method is a structured approach to risk identification and management. It focuses on causal chains between sources, controls, events, post-event controls, and consequences.

Source: TikTok and the Sorting Hat | Remains of the Day, by Eugene Wei

I like to say that “when you gaze into TikTok, TikTok gazes into you.”

One can debate the semantics of what constitutes a social network forever, but what matters here is realizing that another way to describe an entertainment network is as an interest network. TikTok takes content from one group of people and match it to other people who would enjoy that content. It is trying to figure out what hundreds of millions of viewers around the world are interested in
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The idea of using a social graph to build out an interest-based network has always been a sort of approximation, a hack. You follow some people in an app, and it serves you some subset of the content from those people under the assumption that you’ll find much of what they post of interest to you. … But what if there was a way to build an interest graph for you without you having to follow anyone? What if you could skip the long and painstaking intermediate step of assembling a social graph and just jump directly to the interest graph? And what if that could be done really quickly and cheaply at scale, across millions of users? … Now imagine that level of hyper efficient interest matching applied to other opportunities and markets.

the three purposes which I used to distinguish among networks

Apps like Facebook, Instagram, and Twitter are built on social graphs, and as such, they amplify the scale, ubiquity, and reach of our performative social burden. They struggle to separate their social functions from their entertainment and utility functions, injecting an aspect of social artifice where it never used to exist.

That an app launched out of China could come to the U.S. and sprint into cultural relevance in this attention marketplace should be a wake-up call to complacent U.S. tech companies. Given how many of those companies rely on intuiting user interests to sell them things or to show them ads, a company like TikTok which found a shortcut to assembling such an interest graph should raise all sorts of alarm bells.

in many situations when people ascribe causal power to something other than culture, I’m immediately suspicious.
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It turns out that in some categories, a machine learning algorithm significantly responsive and accurate can pierce the veil of cultural ignorance. Today, sometimes culture can be abstracted.
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TikTok has figured out the hardest piece, the algorithm. With it, a massive team made up mostly by people who’ve never left China, and many who never will, grabbed massive marketshare in cultures and markets they’d never experienced firsthand. To a cultural determinist like myself, that feels like black magic.

Source: The TikTok War | Stratechery, by Ben Thompson

• Humans prefer video to photos to text
• TikTok makes it easy to create videos, ensuring a massive supply of content (even if most of the supply is low quality)
• TikTok relies on the algorithm to surface compelling content, and is not constrained by your social network

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The point, though, is not just censorship, but its inverse: propaganda. TikTok’s algorithm, unmoored from the constraints of your social network or professional content creators, is free to promote whatever videos it likes, without anyone knowing the difference. TikTok could promote a particular candidate or a particular issue in a particular geography, without anyone — except perhaps the candidate, now indebted to a Chinese company — knowing. You may be skeptical this might happen, but again, China has already demonstrated a willingness to censor speech on a platform banned in China; how much of a leap is it to think that a Party committed to ideological dominance will forever leave a route directly into the hearts and minds of millions of Americans untouched?

Again, this is where it is worth taking China seriously: the Party has shown through its actions, particularly building and maintaining the Great Firewall at tremendous expense, that it believes in the power of information and ideas. Countless speeches, from Chairman Xi and others, have stated that the Party believes it is in an ideological war with liberalism generally and the U.S. specifically. If we are to give China’s leaders the respect of believing what they say, instead of projecting our own beliefs for no reason other than our own solipsism, how can we take that chance?
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In short, I believe it is time to take China seriously and literally: the Communist Party is not only ideologically opposed to liberalism, it believes that only one of liberalism or Marxism can prevail. To that end it has been taking action for over 20 years to control information within its borders and, over the last several years, to control information outside of its borders. It is time for the U.S. to respond, both on the government level and corporate level, and it should do so in a multi-faceted fashion.

Source: How Big Tech Monopolies Distort Our Public Discourse | Cory Doctorow’s craphound.com, by Cory Doctorow
RE: How Big Tech Monopolies Distort Our Public Discourse | Electronic Frontier Foundation: Deeplinks, by Cory Doctorow

In a nutshell, my dispute with the “surveillance capitalism” hypothesis is that I think it overstates how effective Big Tech is at changing our minds with advanced machine learning techniques, while underplaying the role that monopoly plays in allowing Big Tech to poison and distort our public discourse.

I think this is a distinction with a difference, because if Big Tech has figured out how to use data to rob us of our free will, anti-monopoly enforcement won’t solve the problem – it’ll just create lots of smaller companies with their own Big Data mind-control rays. But if the problem rests in monopoly itself, then we can solve the problem with anti-monopoly techniques that have been used to counter every other species of robber-baron, from oil to aluminum to groceries to telephones.

Source: Everything I’ve learned about solar storm risk and EMP attacks, by Chris Said
RE: “An assessment of threats to the American power grid” | Energy, Sustainability and Society volume 9, by Matthew Weiss & Martin Weiss

When I read this paper, I was stunned. Is the risk of prolonged grid collapse really that high? And is it true that, just as the CDC failed to stockpile masks for a pandemic that we were all warned about, we are equally unprepared for a grid failure that could lead to societal collapse and mass starvation?

To answer these questions, I did some homework. I read congressional testimony, think tank technical reports, a book, academic papers, insurance company assessments, several industry technical reports, and multiple reports in the trade media. What I found was at times contradictory. Somewhat troublingly, both sides of the issue accused each other of bias from financial incentives. Overall, my view is that while some of the EMP and solar storm risk is overhyped, it remains a serious issue, and one of the main tail risks we should be preparing for.
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My own view is that while the ‘mainstream’ view is probably correct, and while there certainly has been some fearmongering, I am philosophically aligned with the alarmists. The mainstream belief at NASA in 1986 was that the Challenger was safe. The mainstream belief at Chernobyl in 1986 was that the reactor core could never rupture. The mainstream belief on Wall Street in 2007 was that mortgage-backed securities were safe.

Now that we have seen our preparedness level for Covid-19, who are you going to believe: The people saying “Don’t worry, we have this unpredictable and complex system under control” or the people waving their hands and shouting “correlated risk!” I’m with the people shouting “correlated risk!”, even though they’ll probably end up being wrong.