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NOTE: I am continuing to post excerpts from my book World After Capital. The following is on the Knowledge Loop. Unfortunately I am dealing with a gitbook issue, so this revised text is not yet live on the book website.The Knowledge Loop
Already today knowledge has made possible something extraordinary: by means of the innovations of the Industrial Age we can, in principle, meet everyone’s basic needs. But we cannot stop here. We need to generate additional knowledge to solve the problems we have introduced along the way, such as climate change. Knowledge is powerful, but only if we have enough of it. Where will that additional knowledge come from?
New knowledge does not spring forth in a vacuum. Instead it emerges from what I call the Knowledge Loop. In the Knowledge Loop, someone starts out by learning something, then uses that to create something new, which is then shared which in turn is the basis for more learning. And so on.
The Knowledge Loop is not new. Given my definition of knowledge, it has been around since humans first developed written language, some five thousand years ago. Before that humans were able to use spoken language, but as I have noted previously that puts tight limits on both time and space for learning and sharing. Since the invention of written language we have had breakthroughs that have helped accelerate and broaden access to the Knowledge Loop. Those include moveable type (about one thousand years ago), the printing press (about five hundred years ago), and then more recently the telegraph, radio and television. Now we are in the middle of another fundamental breakthrough: digital technologies, which can connect all of humanity to the Knowledge Loop at zero marginal cost and are allowing machines to participate in the Knowledge Loop.
It is easy to underestimate the potential of digital technologies for further accelerating and broadening access to the Knowledge Loop; to many, it seems as if these innovations have under-delivered. As a line on the Founders Fund website once complained, “We wanted flying cars and all we got was 140 characters.” Since that lament we have made great progress on flying cars in no small part because digital technologies, including the maligned Twitter, have already helped accelerate the Knowledge Loop.
There is a healthy debate going on now about the role of Twitter, Facebook, and others (Google, Apple, …) with regard to moderating speech on their platforms. Rather than writing something entirely new, I decided to go back and look at what I have written and whether my opinion has changed since then. As I did that I was happy to find that I have had a fairly consistent approach based on who has power.
Over the years I have written a lot about keeping the government out of regulating content on the internet. For instance, in a post from 2010 titled “We Need an Internet Bill of Rights (And Fast)” I wrote:
If you care about freedom and democracy you do not want to give the government a wholesale way to shut down access to sites on the Internet. The potential downside from abuses of such as system far outweigh the upside to copyright holders.
Much of my writing about various content bills, most recently about FOSTA, has been around limiting government power to interfere with speech on the internet. Government has a monopoly on hard power within a country (e.g. throwing you in jail) and so government intervention in speech is particularly problematic.
What about the platforms themselves? Here I have written for some time that they have a responsibility to society to moderate content. Here is a quote from a post that I wrote shortly after Trump was elected President, titled “We Must Talk About the Role of Facebook, Twitter in Society.”
Imagine a system that at the push of a button allows its users to deliver a physical object into the homes of hundreds of millions of other people. Now imagine the operator of that system saying: “we don’t ‘edit’ what people send via the system.” You could put in a hand grenade with the pin removed or a bouquet of flowers. “We just deliver it. We are only in the delivery business.”
We would find this position preposterous. As society we would have none of it. Yet we have exactly that when it comes to information. The system operators are making no distinction between uplifting content and propaganda. They allow for “mind grenades” to be lobbed into millions of homes.
So how to square the positions from the first and the second post? I don’t want government regulating speech on online platforms but I also want online platforms to take responsibility. The answer is take power away from the platforms so that competition is possible. Rather than antitrust, which is an industrial age tool, I would like to see the large platforms become programmable via APIs. Again I have written about this extensively, for instance most recently in a post titled “We Need Mandatory Enduser APIs for Social and Search Systems.”
[…] with an API key I can have an intermediary software layer that operates on my behalf. And that layer can connect me with friends and family that are split up across multiple social networks. This would allow for real competition to Facebook to arise. And once there is competition there is a strong check on behavior as a future #DeleteFacebook campaign would be far more impactful.
Even just the potential of competition (known as “contestability”) will allow users to exert real power over what kind of behavior is acceptable on a platform.
Of course much of the work on decentralized systems is meant to provide alternative platforms that do not have a central point of control. While I am supportive of this and have invested in a number of projects, such as Blockstack and Algorand, It would be a mistake though to think that these kind of systems will automatically lead to good outcomes for speech (or for anything else). Here is a talk I gave at Blockstack Summit making that point
In a follow up post I will write more about the problems with speech that we can already tell will arise with decentralized networks. While they do have the potential to guard against government power, they will definitely invite the kind of manipulation I flagged as problematic in the context of the election.
Have you watched television recently? Eaten food that had been stored in a refrigerator? Accessed the Internet? Played games on your smartphone? Driven in a car? These are all things that billions of people around the world have access to and often use daily (there are over 2 billion smartphone users). Many of us take these capabilities for granted and rarely do we ask where they come from. And while these are produced by different companies using a wide range of technologies, none of them would be possible without the existence of knowledge.
Knowledge, as I use the term, is the sum total of all information humanity has recorded in a medium and improved over time. There are two crucial parts to this definition. The first is “recorded in a medium” which allows information to be shared across time and space. For instance, stone tablets were some of our earliest ways of recording information. The second is “improved over time” which separates knowledge from mere information, provided that the process of critical inquiry is allowed to operate (we first encountered this process in the chapter on Humanism).
A conversation I had years ago but didn’t record cannot be knowledge. However, if I write down an insight from that conversation, or even the conversation verbatim, and publish it on my blog, I’ve potentially contributed to human knowledge. The conversation isn’t accessible to anyone who wasn’t there at the moment it happened. Even my own recollection of the conversation will fade. The blog post, by contrast, is available to others across space and time. Some blog posts will turn out to be important and become part of human knowledge. As another example, the DNA we carry in our cells isn’t knowledge by my definition, whereas a sequenced and recorded genome can be. Every person’s DNA sequence is ephemeral, i.e. disappears with our bodies. Recorded sequences though can be maintained over time, shared and analyzed. Ones that turns out to be medically relevant, such as the BRCA mutation that increases breast cancer risk, become part of human knowledge.
This definition of knowledge is intentionally broad and includes not just technical and scientific knowledge but also art, music, literature. But the definition is also narrow in that it excludes anything that is either ephemeral or not subject to improvement. Computers these days produce tons of recorded information, such as logs of activity on a system, that are mere information, unless they are subsequently analysed.
I started this section with examples of everyday technologies that would not exist without the power of knowledge. An even stronger illustration of its power is that without knowledge many of us would not be here today. As we saw in the chapter on population, Malthus was right about population growth but wrong about its most dire consequences because he did not foresee technological progress powered by knowledge. It is useful to go through one specific example to show just how powerful knowledge is and how it improves over time.
Humans breath air. But for the longest time we did not know what air consists of. Both oxygen and nitrogen, the two primary components of air, were not identified and isolated as elements until late in the 18th century (around 1770). Separately the systematic study of manure as a fertilizer, which had been used in agricultural practice dating back to Egyptian and Roman times, didn’t start until the early 19th century. That study led us to understand that ammonia, which consists of nitrogen and hydrogen, is a powerful fertilizer. Progress in chemistry and industrial processes eventually resulted in the so-called Haber process for nitrogen fixation, which means converting atmospheric nitrogen into a form that can be available to plants. The Haber process, which was invented in the early 20th century, became a crucial ingredient in raising agricultural yields globally and thus averting the Malthusian dystopia.
How successful has this been? For most humans today, about half the nitrogen in our bodies has been touched by the Haber process on its way into plants and animals that we subsequently ingest. Put differently: knowledge is so powerful that we are now made from knowledge.
What my much compressed history of nitrogen fixation doesn’t capture are the many false starts along the way. It seems hilarious to us now, but at one point a leading theory as to why some materials can burn had nothing to do with oxygen but was attributed to the material containing “phlogiston” which was thought to be the part of the material that “disappears” into the air when burning. Without the improvement of knowledge over time, we might have remained stuck at that theory.
When thinking about the power of knowledge, we must remember that a year, or a decade, or even a hundred years are all trivial in the time scale of humanity, and in turn, humanity’s time scale is trivial compared to that of the universe. When considering longer time frames, we should regard as possible all speculative propositions that don’t explicitly contravene the laws of physics—a line of thinking inspired by a new theoretical foundation for science called Constructor Theory .
Consider for a moment what knowledge might allow humanity to do in the future. We might, through further discovery, rid ourselves of fossil fuels, cure any disease, take care of every human’s basic needs, and travel to other planets in our solar system (organizations like SpaceX and NASA are already working toward this goal ). Eventually we might even travel to the stars. We could, of course, also blow our own planet to bits before any of that can happen or be struck by a massive asteroid (this is why allocating our collective attention properly is so crucial). Now, you might say: “Travel to the stars? That’s impossible.” Actually, it isn’t. Extremely difficult? Yes. Requiring technology that doesn’t yet exist? Yes. But impossible? No. Interstellar travel is definitely not imminent, but with the further accretion of knowledge, it will become possible.
Knowledge is the essential human project. We are the only species on planet earth that has created knowledge. This is also why I include art and music in my definition of knowledge. Art has allowed humans to express our hopes and fears, and its accretion into culture has helped motivate the large scale coordination and mobilization of human effort. We can broadly think of technical component of knowledge as underpinning the “how” of our lives and the artistic component the “why” And if you have ever doubted the power of the art portion of knowledge, just think of the many times throughout history and the present when dictators and authoritarian regimes have banned and destroyed works of art.
The internet was around for about two decades before the arrival of the web supercharged its growth. The ease of using a web browser made broad consumer adoption possible. Mobile payments were around for at least a decade before they started to take off. Again the key factor to adoption was ease of use – this time in the form of wallets that are actually integrated with in-app payments and widely accepted at the point of sale such as Google and Apple Pay (in other parts of the world adoption was driven by carrier billing or pre-payment – again questions of convenience).
Similarly crypto is approaching a decade of existence. And we are still looking for the massive increase in the ease of use that will enable broad adoption. It is possible that clinging to the browser and wallet metaphors may be holding us back. The browser is strongly associated with content. The wallet is strongly associated with payments. But crypto is so much more than both: it is a new infrastructure for decentralized systems.
Lots of smart people are working on browsers and wallets that are crypto enabled. And I am glad that’s happening, as the right answer may come from that work. But it would also be good to see experimentation with a new metaphor. Candidates that come to mind are: agent, proxy, and authenticator. A piece of software that I, the enduser, control and that represents me vis-a-vis the decentralized infrastructure.
What would be included in such a “representation” app? Authenticating myself and granting/revoking access to my data. Storing and managing my private keys (possibly in a highly abstracted manner, where I don’t even need to know what a key looks like). What does representation *not* have to include? The UI/UX of decentralized applications can be separate and handled by each app, including payment and investing applications. Some of the apps can be web based and others native (or the same app can have a web and a native experience). The closest thing we have to this representation concept today are password managers.
If you are aware of any projects that are explicitly pursuing this direction, I would love to hear about them.
Despite making progress on the recovery from my shoulder surgery, I have not been blogging and today will be another missed Uncertainty Wednesday.
I have been spending the last few weeks of summer reading more which has been enjoyable. I am learning about Zero Knowledge Proofs from various blogs, including Vitalik Buterin’s excellent posts on the topic. I am also nearly finished with Michael Pollan’s “How to Change your Mind” about psychedelic drugs. And I am halfway into Judea Pearl’s “The Book of Why” and about a third into Kurt Andersen’s “Fantasyland.” All three of these are interesting reads.
As for updates on World After Capital: I am stuck on a section that I am unhappy with but am hoping to get that resolved by next Monday, so I can continue posting excerpts. I have also received a large number of emails with comments on the book and am slowly getting back to people. My thanks to everyone who has written and apologies for the slow replies.
Wishing everyone a good summer and if you have topics you would like me to write about, please let me know.
Facebook is in the unique position today to face both the problems of centralization and decentralization. On its centralized core platform it is confronted with making content decisions, while on WhatsApp it struggles with slowing down the spread of rumors and calls for violence. Just to be clear, I have no sympathy for Facebook which has been arrogant about these issues and has put growth above anything else. Nonetheless everyone who is building new decentralized platforms would do well to think about these issues NOW.
The Internet itself is quite decentralized relative to Facebook. That’s of course why InfoWars and many other conspiracy websites are out there. Facebook has long wanted to convince people around the world that it is effectively the Internet (after all time spent outside of Facebook is a lot harder to monetize). But of course it is not and it can easily censor content on its network. That is quite obvious based on its long suppression of even vaguely sexual content. So of course now it needs to rightly answer the question as to why it lets Holocaust denial be spread through its connections.
But Facebook also already has a foot in a semi-decentralized future due to its acquisition of WhatsApp which provides end-to-end encrypted messaging. Here content travels in a way that cannot be observed or censored. That is of course what many people building new decentralized systems are dreaming of. But that dream too has a nightmare version of it which played itself out in Sri Lanka and Myanmar among other places, where WhatsApp was used to spread rumors and calls for violence that amplified bloodshed. Here Facebook is reduced to trying to diminish the viral coefficient by limiting the number of forwards.
In a fully decentralized system neither type of intervention will be possible. There will be no central censor (Facebook) and no obvious throttle for virality (WhatsApp). That is the explicit goal of building such systems and that is great to the extent that the censor is asserting market or political power to the detriment of competition or the voice of the people. But it would be a mistake not to anticipate that these systems will also be used to spread conspiracies and incite violence.
So what is to be done? Unfortunately there is no simple answer. There is not “just add some AI” quick technical fix. Instead we need a massive transformation. We need to shed the Industrial Age and enter the Knowledge Age. That requires changing pretty much everything about how we live and how our societies work (just like we changed pretty much everything when we went from the Agrarian Age to the Industrial Age). If you want to read my take on all of that, you can find it in my book World After Capital.
The last few Uncertainty Wednesdays had us look at how to model beliefs using probability distributions and then update those with a specific example of using the beta distribution. You may have noticed something odd about the way we updated the parameters of the beta distribution: add 1 to α when we observe heads and add 1 to β when we observe tails. This wipes out any and all ordering information. So let’s say you have a total of 100 observations. With this update rule the only thing that matters is the total count of heads and tails respectively. Let’s say that happens to be exactly 50 each, which gives us this beautiful looking distribution:
Which is quite tight around the probability 0.5 for heads.
Yet clearly there is a huge difference between observing some fairly random sequence of heads and tails versus say first 50 heads and then 50 tails, or maybe 5 heads, followed by 5 tails, followed by 5 heads and so on. Say for the last one if we had observed this 20 times in a row, our belief for the next toss – expressed as a distribution – surely shouldn’t look like the picture above. Instead, we would probably put a very high probability on the next toss being heads (the last 5 were tails and so we are due for a reversal).
Why does our current approach not detect that at all? The reason is that embedded in our updating approach was the assumption that the coin tosses were independent of each other. If we wanted to allow for tosses to be influenced by prior tosses (or, more likely, by some underlying system that determines the tosses) we would have to use a more complex initial setup and updating procedure. In a future post I will show how to do this.
NOTE: Today’s excerpt from World After Capital rounds out the section on limits of capitalism. We already saw the issue of missing prices, the problem of power laws and today talks about how the self-conservation of capitalism through the political system keeps attention trapped in the job loop.Self-Conservation
Toward the end of the Agrarian Age, when land was scarce, the political elites came from land ownership. Their influence really wasn’t substantially diminished until after World War II. Now we are at the end of the scarcity of capital, but the political elites largely represent the interests of capital. In some countries, such as China, this is the case outright. Senior political leaders and their families own large parts of industry. In other countries, such as the United States, politicians are influenced by the owners of capital because of the constant need to fundraise.
A study conducted at Princeton analyzes how much public support for a policy influences the likelihood of that policy being enacted  in the United States. It turns out that for the bottom 90% of the population their preferences have no influence on outcomes. Only the preferences of the wealthiest 10% of the population matter. Even within the 10% whose preferences matter, there is a huge concentration. For instance, over a 5 year period the 200 most politically active companies alone spent nearly $6 Billion on lobbying.
Individual and corporate lobbying results in policies favorable to owners of capital, such as low capital gains tax rates (or in the case of venture capital and buyout funds the taxation of General Partner profits as capital gains instead of income). Low corporate tax rates with lots of loopholes, including the accumulation of corporate cash in low tax countries is also favorable to owners of capital. So in 2018 we are finding ourselves with some of the lowest corporate tax rates, the highest stock prices and the highest share of profits in national income.
In addition to preserving and creating benefits for owners of capital there are also outright attacks on the sharing and creation of knowledge. I have written more about these in the chapter on Informational Freedom, but want to give one example now. Corporations lobbied heavily over the years to lengthen copyright and strengthen copyright protections. Scientific publishers such as Elsevier have used these protections to make access to knowledge so expensive that even universities as wealthy as Harvard can no longer afford the subscriptions. 
The existing political and economic system thus acts to conserve the scarcity of capital past its expiration date. As long as that is the case we will not be able to solve the attention allocation problem outlined above. We will heavily over-allocate attention to the job loop (work and consumption) and under-allocate attention to the individual need for purpose and the collective growth of knowledge.
How then do we overcome these limitations? That is the subject of Parts Three and Four of World After Capital. But first we will take closer look at the power of knowledge and the promise of the digital knowledge loop.
While I am working on my book World After Capital, I am also collecting ideas for an important project that I want to tackle afterwards: a compendium of principles. Before you think, oh Albert is going full on Ray Dalio, let me provide the definition of “principle” the Oxford Dictionary:
(1) A fundamental truth or proposition that serves as the foundation for a system of belief or behaviour or for a chain of reasoning.
(2) A general scientific theorem or law that has numerous special applications across a wide field.
I am interested in principles that represent a “fundamental truth” that serves as the “foundation” of all knowledge and hence has “numerous special applications.”
What is an example of such a principle? Feedback: entity A influencing entity B, which in turn influences entity A. There are quite a few truths we have figured out about both positive feedback and negative feedback.
Once you understand the principle of feedback you can see it pop up in lots of different contexts, from Jimmy Hendrix’s guitar play to the working of the cruise control in your car. That happens to be the point of compiling principles. They are incredibly powerful. And if you understand them you have that power at your disposal as you try to understand other knowledge or help contribute new knowledge.
In addition to general principles which are the foundations of all knowledge, I believe that major fields of knowledge, such as business, also have a limited number of powerful foundational principles. What is an example in business? Financing: any activity for which cash outflows precede cash inflows requires financing (unfortunately Wikipedia only has an entry for Funding, which doesn’t neatly capture this principle).
Again, once you understand the principle of financing there are a great many other things about business that you can understand faster and deeper, including venture capital.
I am always surprised how little attention is given to principles in most teaching, given how powerful they are. Hence my plan for a compendium. Going forward, I will periodically post some other principles. If you have suggestions for principles, please make them in the comments.
Last Uncertainty Wednesday, I introduced the beta distribution to model our prior belief about the probability of Heads in a coin toss. We saw that for the parameters α = β = 1 the beta distribution gives us a uniform prior, which expresses the highest degree of uncertainty (you may want to revisit the earlier post on entropy for that).
Now I will toss an actual coin while writing this post. Wait. It came up tails (i.e. not heads). What should our new values be for α and β?
As it turns out the updating formula is super simple. If we observe heads we increment α and if we observe tails we increment β. Here is what the Beta distribution looks like for α = 1 and β = 2, i.e. after we have observed tails:
What does this picture tell us? Going from a uniform prior, the observations of tails has shifted a fair bit of probability towards lower values of θ. Remember that θ is the parameter we are interested in. It is the probability that the coin will come up heads. Since we have seen only one outcome and that outcome was tails, we are updating by assigning a lot more probability to values of θ below 0.5 (on the horizontal axis). This is our updated belief.
Is this the only possible update we could have made? Well, if we use the Beta distribution to model our beliefs and the thing we observe has a binary outcome (such as a coin toss), then this is the precise updating as determined by Bayes’ Theorem. If you are so inclined you can find a very accessible derivation of this result here, which also shows how the simple updating rule results.
So let’s keep tossing our coin. I just did and as it turns out got heads. So our updated values are now α = 2 and β = 2 and our new distribution looks as follows
This is symmetric, which shouldn’t surprise us as we have observed both head and tails. It is also starting to shift probability away from the extremes and towards the middle.
Now if you want to play this game by yourself and see how the beta distribution changes after each toss, you can just head over to this query on WolframAlpha. Just add 1 to the value of α (alpha) each time you toss heads and 1 to the value of β (beta) each time you toss tails. Watch the distribution update!
I have just tossed my coin 30 times and observed 17 heads and 13 tails. Here is what the Beta distribution looks like for α = 18 and β = 14
So the beta distribution is starting to bunch up around 0.5, but we can see that the average is slightly above 0.5, in line with having observed more heads rather than tails (making heads somewhat more likely). Next Wednesday I will talk more about what we have learned at each step and also some of the limitations of this approach.
NOTE: Last week’s excerpt from World After Capital described how prices cannot exist for many of our most important attention allocation decisions. Today I describe how production functions with network effects result in power law distributions that have bad social and economic implications.Power Laws
Economics is not normative when it comes to the distribution of income and wealth. Many different outcomes are possible and what is realized depends a lot on the underlying production functions. Consider first a fairly manual production function such as was common pre-industrialization. If you were a cobbler making shoes by hand, there were only so many shoes you could produce. I don’t know if such data is available, but the output of cobblers likely formed a normal distribution, with even the most productive cobbler making only a small multiple of the number of shoes of the average cobbler.
Then along came industrialization and with it economies of scale. If you made more cars you could make them more cheaply and that was true until you got to a fairly large number of cars relative to total demand. That’s why, over time, we wound up with relatively few car manufacturers around the world and the owners of the surviving largest ones wound up with large fortunes (e.g., the Ford or the Piech families). It turned out that many service businesses have relatively small economies of scale (e.g., a hair salon). That has allowed a great many service businesses to exist. The biggest exception to this has been financial services in which a few large banks, insurance companies, and brokerage firms tend to dominate.
Now, however, with digital technologies we are seeing a shift to power laws for many more situations. For instance, on YouTube the most watched video has been watched billions of times compared to the vast majority of videos which have been watched just a few times. Or in ecommerce, Amazon is an order of magnitude larger than the next biggest competitor and several orders of magnitude larger than most ecommerce companies. The same goes for apps in the appstore. The leading apps have hundreds of millions (and some even billions) of users. But the vast majority of apps has just a few users.
Digital technologies are driving these power laws because of network effects combined with zero marginal cost. As I explained in the chapter on digital technology this means that in principle we need only one medical diagnosis systems to serve the entire world (in practice we would want several). So far we have seen one social network by far dominate all others. We have one search company dominate all others. Protected markets, such as Russia and China, have their own search and social network companies, but their size also follows a power law distribution.
This shift to power laws everywhere is driving a huge increase of wealth and income inequality to levels that are now beyond the peak of the early 1900s. At that time it was undone by two world wars, which destroyed much of the accumulated existing wealth as well documented in Thomas Piketty’s book “Capital in the Twenty-First Century.” Inequality beyond a certain level is socially corrosive, as people effectively start to live in different world that is disconnected from the problems faced by large parts of the population. There is no self-corrective to this kind of excessive, power-law driven, inequality built into capitalism.
Beyond the social implications of such inequality, the largest digital companies also wield undue political and market power. A recent example of that was the dramatic drop in the market capitalization of pharmacy chains when Amazon acquired a relatively small online pharmacy, such signaling its intent to compete in that market. Historically market power was bad because it produced inefficient allocations due to excessive rents (and such artificially low quantity). In digital markets powerful companies have often pushed prices down or made products free entirely thus causing seemingly no harm to consumers. The harm here comes via reduced innovation as companies and investors stop allocating capital to trying to bring better alternative products to market.
The purported self-corrective in capitalism for market power is “creative destruction” as first described by Joseph Schumpeter. And indeed if you look at the dominant companies today they are quite different from those of the Industrial Age. But going forward this may be quite a bit harder, if not impossible. Why? During the Industrial Age machines served a specific purpose. This meant when a new product or a new manufacturing technology became available, the installed base of machines became essentially worthless and was a weight on the incumbents. Today, however, the new incumbents operate general purpose computers, which take information as one of their key inputs. They can easily implement a new product, or add a feature to an existing one, or adopt a new algorithm. Production functions with information as a key input have a property known as super-modularity: the marginal benefit of additional information is higher the more information you already have. This gives the digital incumbents tremendous sustained power as they get more marginal value from a new product or service than a new entrant.
Independence Day is a cheesy summer action blockbuster. And yet, after watching it one can’t help but feel good about humanity defeating an existential threat using courage, technology and science (and doing so under American leadership). The irony today is that we face such a species level threat. It just happens to be invisible and slow moving. I am talking about the greenhouse gases that are slowly but steadily warming up our planet (in particular our oceans) and our atmosphere. Climate change is the defining threat to humanity and we should be fighting it using all the courage, technology and science we can muster.
Here is the latest reporting from the Washington Post on all the heat records being broken in the last week leading up to this 4th of July. And here is a chart I just generated using the University of Maine Climate Reanalyzer, which shows departures from the 1979-2000 temperature average. You can see big heat bubbles over the US, Europe and especially over Antarctica:
Antarctica is especially troubling because it now appears that ice there is melting three times faster than before.
Seeing how the current president doesn’t even believe climate change is a real phenomenon and has someone heading the EPA who thinks it could all be a good thing, I give you instead a rousing speech by a cheesy movie president
This is also a good time to resurface the post I wrote last year on 4th of July. In it I rewrote the beginning of the Declaration of Independence to make it address what I believe we need for a World After Capital:
We hold these truths to be universal, that all humans are created equal; that they are endowed qua their humanity with certain unalienable Rights, that among these are Life, Liberty and the pursuit of both Happiness and Knowledge; that they have Responsibilities towards each other and other species, that among these are Tolerance, and the Application and Furtherance of Knowledge for the Benefit of All.
Happy 4th of July!
PS Uncertainty Wednesday will continue next week.
Capitalism has been extraordinarily successful. So much so that even communist countries like China, that had long sought a different path, have embraced it. But capitalism cannot solve the scarcity of attention without significant changes in regulation and self-regulation. That’s due to three important limitations. First, there are prices that will always be missing for things that we should be paying attention to. Second, capitalism to date has limited mechanisms for dealing with the power laws arising from digital technologies. Third, capitalism acts to preserve the interests of capital over those of knowledge. Put differently: we need to make changes now, precisely because capitalism has been so successful. The important problems that are left over are the one’s it cannot solve.Missing Prices
Why won’t capitalism help us allocate attention? Because the great strength and the great weakness of capitalism is that it relies on prices determined in markets. Prices are amazingly powerful because they efficiently aggregate information on consumer preferences, producer needs, etc. But not everything can be priced. And increasingly the things that cannot be priced are becoming much more important than those that can—think of the benefits from space travel, the cost of climate change, or even an individual’s sense of purpose and meaning.
There are foundational issues that prevent the existence of prices for many things. This is not just a question of a missing market that can magically be created by assigning property rights.
The first foundational issue is zero marginal cost for copies and distribution in the digital realm. From a social perspective, we should make all the world’s knowledge, including all the existing music, videos, educational materials available for free at the margin. That’s not just true for content but also for services that can be provided at essentially zero marginal cost, such as medical diagnoses. As long as we are relying on the price mechanism, we will—by definition—under-produce free resources. Another way to think about this is as follows: the Industrial Age was full of negative externalities, such as pollution, which resulted in over production; the Knowledge Age is full of positive externalities, such as learning, which implies under production. So for instance, relying on the market mechanism we will not pay nearly enough attention to the creation of free educational resources.
The second foundational issue is extreme uncertainty. Because prices aggregate information, they fail when no such information can exist. There are events that are so rare or have not occurred at all yet that we have essentially no information on their frequency or severity. This is especially true around the kind of societal event horizon that we are currently dealing with. Nassim Taleb’s work on tail risk is highly relevant here. The price mechanism cannot work when forecast error is infinite. For instance, large asteroid impacts on Earth occur millions of years apart. There is no price that can help us allocate attention to detecting such asteroids and building systems for deflecting them. As a result we are currently paying a trivial amount of attention to this problem relative to the potential damage to humanity from an impact.
The third foundational issue is new knowledge itself. The further removed the knowledge is from creating a product or service that can be sold, the less the price mechanism is of use. That is quite obvious for basic research, but is even true in applied settings. Consider early aviation pioneers, for example. They did not pursue flight because there was an obvious market with clear prices for air travel. Instead, they were fascinated by solving the challenge of heavier-than-air flight. Take the early days of quantum computing when any actual machine was still decades away. The price mechanism would not allocate attention to quantum computing at that time.
The fourth foundational issue is the deeply personal. For markets and prices to exist there have to be multiple buyers and sellers. So there is no market and hence no price for you to spend time with your children. Or for you to figure out your purpose in life. Ironically, it has been an ad campaign for a commercial product that got this idea right: Master Card’s long running series of “Priceless” ads. In the first of these from 1997 a father takes his son to the ballpark. The text reads “Two tickets, $28; Two hotdogs, two popcorns, two sodas, $18; autographed baseball, $45; real conversation with 11-year old son: priceless, there are some things money can’t buy.” Capitalism and the market mechanism cannot help us allocate attention to anything that is deeply personal.
It’s been six weeks since the last Uncertainty Wednesday, so I strongly suggest you go back first and read that post which provides an introduction to the idea of updating. Take your time, this new post won’t go away!
The distribution that we will use for modeling our coin is the Beta distribution. Why choose that one? Because the beta distribution when combined with likelihood function for a coin toss gives us another beta distribution. This is known technically as a so-called conjugate prior. That all sounds very technical but the idea is simple: when our prior is a beta distribution and the observations are of the 0 or 1 (head or tails) variety, then our posterior distribution after updating is once again a beta distribution.
Now the beta distribution has two parameters, which are commonly referred to as α and β. These parameters can take on lots of values, but there is straightforward choice for initial parameters. We will pick α = β = 1 because for those values, the beta distribution coincides with the uniform distribution. All the plots in this post are generated using Wolfram Alpha.
As a refresher: the x axis on this chart is the parameter θ for which we are expressing our belief. In the coin toss example θ would be the probability that the coin comes up Heads on any one toss (in which case 1 - θ is the probability that it comes up Tails). We know nothing about the coin right now so that probability θ could be anything between 0 (never see Heads) and 1 (every toss comes up Heads).
At this point you may be thoroughly confused. How do the parameters from the beta distribution relate to the parameter for the coin toss? Sometimes people call the α and β hyper-parameters, but I think a better term would have been meta-parameters or belief-parameters. Put differently α and β determine the shape of our belief about θ.
So now what remains to be done is to figure out how we should update α and β after we have observed some outcomes. We are looking for new values of α and β after we have observed either Heads or Tails. As we will see next Wednesday the updating of these values turns out to be super simple.
NOTE: I am resuming publishing excerpts from my draft book World After Capital. Today’s section continues the discussion of why attention is scarce. Since it has been five weeks, I recommend first rereading the prior section which introduces attention scarcity.Collective Attention Scarcity
At the same time our collective attention is also scarce. How so? Humanity as a whole is not devoting nearly enough attention towards moving knowledge forward with regard to a variety of threats and opportunities.
On the threat side, for example, we are not working nearly hard enough on how to recapture CO2 and other greenhouse gases from the atmosphere. Or on monitoring asteroids that could strike earth, and coming up with ways of deflecting them. Or containing the outbreak of the next avian flu: we should have a lot more collective attention dedicated to early detection and coming up with vaccines and treatments.
Climate change, “death from above,” and pandemics are three examples of species level threats for humans. As I wrote earlier, we can only sustain the present number of humans on this planet due to our technological progress. Each one of these risk categories has the potential to fundamentally disrupt our ability to meet the basic needs of millions, potentially billions and possibly the entire human species. That’s why our collective attention is scarce in the precise sense of scarcity provided earlier.
On the opportunity side, far too little human attention is spent on environmental cleanup, free educational resources, and basic research (including the foundations of science), to name just a few examples. There are so many opportunities we could dedicate attention to that over time have the potential to dramatically improve quality of life here on Earth not just for humans but also for other species.
As in the individual case, much of our collective attention, instead of being applied to these threats and opportunities, is absorbed by having to earn a living, with our leisure time increasingly consumed by watching entertainment on the internet.
The result is that we are not investing nearly enough attention in generating more knowledge. And if we don’t have enough knowledge, we may not be able to solve some of the threats we are currently facing, such as climate change. The climate change threat is not a hypothetical concern, but has repeatedly led to the downfall of prior human civilizations, such as the Rapa Nui or the Mayans. Now, however, we are facing the climate change threat on a truly global scale. We should be using a few percent of all human attention to fight this but I suspect the actual number is two to three orders of magnitude smaller.
I am proposing this as a (possibly new) explanation for the Fermi Paradox, which famously asks why we have not yet detected any signs of intelligent life elsewhere in our rather large universe. We now even know that there are plenty of goldilocks planets available that could harbor life forms similar to those on Earth. Maybe what happens is that all civilizations get far enough to where they generate huge amounts of information, but then they get done in by attention scarcity. They collectively take their eye off the ball of progress and are not prepared when something really bad happens such as a global pandemic.
But why exactly is attention so poorly allocated? One key reason is that we are currently attempting to use the market mechanism to allocate attention. The next chapter explains why that cannot work.
Yesterday, I tweeted that I considered Sarah Sanders tweet about being asked to leave the Red Hen restaurant an abuse of government power. Since I got quite a few questions on Twitter about that I want to elaborate the argument in a blog post.
Sarah Sanders is currently the White House Press Secretary. This is a role that she has chosen voluntarily. In this role she has time and again repeated and defended the many lies of President Trump, most recently the lie that separating children at the border was a law for which the Democrats were responsible, when in fact it was a policy decision by the White House.
Sarah Sanders was asked by the owner of the Red Hen to leave. She was at the restaurant as a private citizen and not on any government business. She then used her official United States government account to complain about her treatment. The official account has over three million followers and is supposed to be used for White House communications. Using it to complain about how she was treated personally therefore constitutes a clear abuse of government power. She could and should have used her personal account, which, by the ways, has over two hundred thousand followers, so it’s not like she wouldn’t be heard.
It is completely perplexing to me how people think that they can be associated with the administration and not have any personal responsibility. On Twitter someone actually rolled out a version of the “she is just doing her job” defense. I don’t think I need to provide the historical context for why that should not be allowed to stand. She has actively chosen to do this. And continues to do so every day that she remains the Press Secretary. Just to be clear: the same has been true for anybody working in any prior administration. It is a voluntary action and hence comes with personal responsibility.
A business should be perfectly free to not provide service to someone on the basis of the actions they have taken. The “No shirt, no shoes, no service” sign at businesses in beach towns is perfect example of this. As is the case of my asking someone to leave our office years ago after being incredibly rude to one of our assistants. Not wearing shoes, making rude remarks, acting as the Press Secretary, these are personal actions that can and should form the basis for a legitimate decision not to do business with somebody. It is crucial to note that this is not discrimination based on beliefs, e.g. being a Republican, but entirely based on actions.
And because several people have brought it up: this is also different from discriminating on the basis of someone’s identity, such as the color of their skin. Now there is not necessarily a bright line at all times between actions, beliefs and identity. For instance, I tend to be critical of some action resulting from religious beliefs and think people have some personal responsibility in those matters, but I also recognize that a lot of people see their faith as an integral part of their identity. Quite clearly being Press Secretary is not part of Sarah Sanders’s deep personal and difficult/impossible to change identity. That is an action she has chosen.
So in summary: Your actions should have personal consequences (that, by the way, is the meaning of “skin in the game”). Being ejected from a restaurant is one of those possible consequences. And using an official government account (instead of a personal one) to complain about such consequences constitutes an abuse of government power.
If you feel the same way about this as I do, I encourage you to support the Red Hen by purchasing a gift certificate.
After nearly four weeks of not posting due to shoulder surgery I am almost back. I am saying almost because even though I can type very well again, I am spending a fair bit of time every day on physical therapy. That is time I would have spent writing and, well, something has got to give. So for now I am planning on one post per week instead of the usual three, but let’s see where it goes.
In the meantime though I want to thank everyone who kindly reached out, inquired how things were going, and wished me a speedy recovery. I appreciated every note! Hearing from friends and strangers helped a lot, especially in the early days post surgery when I was quite miserable. If you ever consider shoulder surgery for rotator cuff, just mentally prepare yourself for a really rough first week. You may wind up questioning whether it was a good idea, I certainly did. And while I am only four weeks out now I can feel improvements every day which makes me optimistic.
If you care for a bit more background here is what happened. We went skiing in March to Verbier, Switzerland. On the first day in poor visibility I misjudged the distance from an off-piste run down to a cat track and there were about 5 feet of vertical. I hit the cat track hard, double ejected and pancaked into some very hard packed snow. I could hear a group of people standing near by go “Ouch.” I got up put my skis on an skied off but my left wrist and right shoulder definitely hurt. I skied the rest of the day but got fairly little sleep at night as my shoulder was throbbing. Given the great conditions though, I just took a lot of Advil the next morning and wound up skiing the entire five days we were there.
When I got back to New York my shoulder continued to hurt and I had fairly limited range of motion when trying to lift my right arm. I was hoping the whole thing would just go away with time but after six weeks without improvement I finally caved decided to see a doctor. Easier said then done because my insurance company wanted me to first get an x-ray before approving an MRI. The medical reasons for this are dubious at best and I decided to pay for the MRI out of pocket (you can get a much better rate when paying on the spot, one of the great distortions of our medical system).
With MRI in hand I went to two different doctors and got the same feedback: a mostly torn Supraspinatus tendon and a bunch of damage to the Glenoid labrum. Both required surgery to fix. The procedure itself was done at an outpatient facility and I was able to spend the night in my own bed (mostly not sleeping). Pro-tip: start taking the pain killers right away and don’t wait for the nerve block to wear off. Because of the nerve block you don’t feel any pain but when it wears off the pain is excruciating and pain killers take some time to work (file under: important note to self, should I have to do this again some time).
Now off to do my physical therapy exercises. And: Happy Father’s day to all fathers who made it to the end of this post!
No Uncertainty Wednesday today. I had shoulder surgery yesterday to repair a rotator cuff injury. That means I won’t be able to type for quite a few days. I am creating this post using Voice on my Android phone. Impressively I did not have to correct a single word.
NOTE: Today’s excerpt from World After Capital is about attention. It argues why attention is scarce in the sense of scarcity introduced earlier in the book. This section sets up the demands on attention and then talks about scarcity of attention for the individual (next time will look at scarcity of attention for society as a whole).Attention
There is a limited amount of human attention in the world. We have 24 hours in the day and we need to spend some of that time eating and sleeping. For many people in the world much of their waking time is occupied by the job loop (both the earning and the spending parts). That leaves relatively little time for attention that we can freely allocate. This hard limit also exists in the aggregate, since—as I have argued earlier—we are headed for peak population.
At the same time that our attention is limited, we are using the Internet to dramatically increase the amount of available content. The increase in content is well documented to be exponential, which means that most of the content that has ever been produced by humanity has been produced in the last few years . For example, YouTube alone is adding 100 hours of new video content every minute .
As a result, it is easy today to be completely overwhelmed by content. Our limited attention can readily be absorbed by ever refreshing content. Humans are maladapted to the information environment we now live in. Our brain evolved in a world where when you saw a cat, there was an actual cat. Now we live in a world of infinite cat pictures. This is analogous to our maladaptation to sugar for an environment that is now sugar rich (largely artificially so). Checking email, Twitter, Instagram, watching yet another YouTube clip or Snapchat story, or episode of one’s favorite show on a streaming service—these all provide quick “information hits” that trigger parts of our brain that evolved to be stimulated by novelty. As of 2017, the average person spends roughly two hours on social media every day .
The limited availability of attention has become the key new source of economic rents. Companies such as Google, Facebook and Twitter are valued in no small part based on the amount of attention they have been able to aggregate, some of which they then resell in the form of advertising. As a result they invest heavily in algorithms designed to present ever more captivating content to their end users in order to monopolize their attention. Sites like Buzzfeed and Huffington Post that are nominally news sites do the same.
Now even if you think this is problematic, does it mean attention is scarce in the precise meaning of scarcity that I defined earlier? That would require for us to not have enough attention to meet humanity’s basic needs. Is that really the case?Individual Attention Scarcity
Let’s first consider attention at the individual level. All over the world people have constructed their identities around work and around firmly held core beliefs, whether religious or worldly. Both of these are undermined by digital technologies. We saw earlier how digital technology is putting pressure on labor. It is also putting pressure though on firmly held beliefs. Content is no longer easily contained in geographic boundaries and people are being exposed, many for the first time, to opinions and behaviors that diverge from their core beliefs.
In combination, this pressure is leading to a large scale crisis of individual identity and rising aggression both online and offline. This crisis takes many different forms, including increased teenage depression, growing adult suicide rates—particularly among middle-aged white males, and drug overdose deaths. In the US, these have increased almost 60 percent, 20 percent and 40 percent, respectively, between 2006 and 2015 [need more up-to-date statistics]:
This is not dissimilar from the beginning of the Industrial Age, when people had to leave the countryside and move to big cities. They were forced to give up identities that had been constructed around land and a historical set of professions. They were confronted with people from other regions who held different beliefs.
Just as with the transition into the Industrial Age it is therefore not surprising that there is a rise in populist leaders with simplistic messages, such as Donald Trump in the United States and Viktor Orban in Hungary. A recent study found that throughout Europe, populist parties are receiving more than double their average share of the vote in national and parliamentary elections compared with the 1960s . People whose identity is shaken want to be reassured. They want to hear that things will be OK and that the way of getting there is simple. “Make America Great Again” is an example of that. So is ISIS. In both cases the message is retrograde. Instead of a new identity that has to be built, requiring time and effort, these backward movements promise an easy return to a glorious identity of the past.
Our attention to our most basic need, the existential need to make sense of the world as an individual by finding a purpose that makes our life meaningful, is scarce. Instead we let our attention be occupied by our job or by yet another video or worse by propaganda. This individual scarcity of attention is not confined to any one demographic. Definitely people who have to work multiple jobs just to make rent and feed their families are impacted. But so are many people in high paying jobs who are often working more hours today than they ever have.
I do a fair bit of counseling for young people who want to work for a technology startup or who want to enter venture capital. Most of them are looking for tactical advice, such as how to apply to a specific position. After discussing that for some time, I usually switch gears and ask them a much more open question. “What do you want from your next position?” That often elicits answers such as learning a new skill, or applying a skill that they have recently learned. Sometimes people answer with a desire to contribute to some cause. I then get to the point by asking directly “What is your purpose?” Shockingly few people have an answer to that.
Purpose is an individual need for which the Industrial Age had little use. Somebody with a strong sense of purpose does not fit readily into the job loop either as a worker or as a consumer. Instead work and consumption have become the de facto purpose for most people. Both the cultural and religious narratives adjusted from the Agrarian Age to the Industrial age to support this re-definition of purpose.
With digital technology we can now exit the job loop and redirect attention to finding other sources of purpose. Instead though we are using digital technology to aggregate attention primarily for resale (advertising) and for entertainment. We do not identify this as a fundamental problem of the largest platforms, focusing instead on areas such as privacy and moderation of speech. That’s because we continue to see the world through the lens of capital scarcity instead of attention scarcity.
Now that we have spent the last few Uncertainty Wednesdays on modeling beliefs as probability distributions, we can now get to the topic of updating. Updating is what we are supposed to do with our beliefs when we have new observations. We first encountered a similar idea in the extensive example of a cancer test which we used to derive Bayes’ theorem.
In that post I wrote that “[Bayes’ theorem] relates the probability of the world being in state B *before* we have observed a signal to the probability *after* we have observed signal H.” Now in that quote and in the example we used probabilities and not probability distributions. We had found the following formula, which is known as Bayes’ rule:
P(B | H) = [P(H | B) / P(H)] * P(B)
As a reminder P(B) is the probability of event B before we have observed anything, so in the case of cancer this would be the rate at which this cancer occurs in the relevant population. P(B | H) is the updated probability conditional on having received a positive cancer test (H as in high). We saw that the updating occurs through the factor P(H | B) / P(H) which consists of the sensitivity of the test P(H | B) divided by the total probability of seeing a positive test P(H).
What we are looking for now is to come up with a similar version of Bayes’ rule for beliefs expressed as probability distributions. We want something that looks roughly like:
posterior belief = update factor * prior belief
where again the update factor captures the likelihood of the observations, keeping in mind here that we are now dealing with distributions. The beliefs and the update factor are both functions which makes the formula for this quite daunting looking. We will write it – with some abuse of notation – as follows to keep things simple
p(θ | x) = [p(x | θ) / p(x) ] * p(θ)
where θ is the parameter we are interested in, such as the probability of Heads for our coin, and x denotes our observations. We see the numerator of the update factor now is p(x | θ) – this is a function, the so-called likelihood function, which maps θ into p(x | θ). The denominator is p(x) which is the probability of the observations. That in turn is quite complicated if we unpack it, since it is an integral over all the possible values of θ and their probabilities (what comes out though is a scalar, meaning just a number, not a function).
So what we are really doing is multiplying two functions: the likelihood function and the probability density function of our prior belief which gives us a new function that represents our updated or posterior belief. This is complicated for the general case and along with calculating p(x) by evaluating the integral will require numerical approximations.
Thankfully though it turns out that there are elegant and simple solutions for some types of probability distributions, such as the Beta distribution which I had introduced as an example of a possible belief. If you have a Beta distribution as the prior belief for the probability parameter in a coin toss then the posterior belief also takes the form of a Beta distribution! Next Wednesday we will use this fact to show how we can easily update our beliefs on a coin toss (provided we buy into using the Beta as the shape of our prior).