Dr. Jorge Pérez, an evolutionary biologist from the University of La Paz, and several companions, were exploring the Andes Mountains when they found a small valley, with no other animals or humans. Pérez noticed that the valley had what appeared to be a natural fountain, surrounded by two peaks of rock and silver snow.
Pérez and the others then ventured further into the valley. “By the time we reached the top of one peak, the water looked blue, with some crystals on top,” said Pérez.
Pérez and his friends were astonished to see the unicorn herd. These creatures could be seen from the air without having to move too much to see them – they were so close they could touch their horns.
While examining these bizarre creatures the scientists discovered that the creatures also spoke some fairly regular English. Pérez stated, “We can see, for example, that they have a common ‘language,’ something like a dialect or dialectic.”
Dr. Pérez believes that the unicorns may have originated in Argentina, where the animals were believed to be descendants of a lost race of people who lived there before the arrival of humans in those parts of South America.
While their origins are still unclear, some believe that perhaps the creatures were created when a human and a unicorn met each other in a time before human civilization. According to Pérez, “In South America, such incidents seem to be quite common.”
However, Pérez also pointed out that it is likely that the only way of knowing for sure if unicorns are indeed the descendants of a lost alien race is through DNA. “But they seem to be able to communicate in English quite well, which I believe is a sign of evolution, or at least a change in social organization,” said the scientist.
Click here for the rest of the story.
AI’s are better than humans at Chess and Go, why shouldn’t they also be better at the game of collusion? Calvano, Calzolari, Denicolò and Pastorello show that they are (here quoting a VOXEU summary by the authors):
[In Calvano et al. 2018a] we construct AI pricing agents and let them interact repeatedly in controlled environments that reproduce economists’ canonical model of collusion, i.e. a repeated pricing game with simultaneous moves and full price flexibility. Our findings suggest that in this framework even relatively simple pricing algorithms systematically learn to play sophisticated collusive strategies. The strategies mete out punishments that are proportional to the extent of the deviations and are finite in duration, with a gradual return to the pre-deviation prices.
Figure 1 illustrates the punishment strategies that the algorithms autonomously learn to play. Starting from the (collusive) prices on which the algorithms have converged (the grey dotted line), we override one algorithm’s choice (the red line), forcing it to deviate downward to the competitive or Nash price (the orange dotted line) for one period. The other algorithm (the blue line) keeps playing as prescribed by the strategy it has learned. After this exogenous deviation in period , both algorithms regain control of the pricing.
Figure 1 Price responses to deviating price cut
Note: The blue and red lines show the price dynamic over time of two autonomous pricing algorithms (agents) when the red algorithm deviates from the collusive price in the first period.
The figure shows the price path in the subsequent periods. Clearly, the deviation is punished immediately (the blue line price drops immediately after the deviation of the red line), making the deviation unprofitable. However, the punishment is not as harsh as it could be (i.e. reversion to the competitive price), and it is only temporary; afterwards, the algorithms gradually return to their pre-deviation prices.
…The collusion that we find is typically partial – the algorithms do not converge to the monopoly price but a somewhat lower one. However, we show that the propensity to collude is stubborn – substantial collusion continues to prevail even when the active firms are three or four in number, when they are asymmetric, and when they operate in a stochastic environment. The experimental literature with human subjects, by contrast, has consistently found that they are practically unable to coordinate without explicit communication save in the simplest case, with two symmetric agents and no uncertainty.
What is most worrying is that the algorithms leave no trace of concerted action – they learn to collude purely by trial and error, with no prior knowledge of the environment in which they operate, without communicating with one another, and without being specifically designed or instructed to collude.
Tacit collusion isn’t actually illegal since it’s virtually impossible to prove, at least among humans. Tacit collusion by AIs is going to be much more common but perhaps also easier to prove if the antitrust authorities can demand access to the algorithms. No need to torture the data when you can torture the AIs. It’s going to be a strange world.
Hat tip: Ankur Delight.
Our first episode in the Women in Economics series is an introduction to Elinor Ostrom, the first woman to have won the Nobel Prize in Economics. Elinor Ostrom and Vincent Ostrom have long been a part of the intellectual foundations of “Masonomics”. Both the Ostroms were past presidents of the Public Choice Society, for example, as were Jim Buchanan, Gordon Tullock and Vernon Smith. The Mason Economics department was thrilled when Ostrom won the Nobel as there has been and continues to be fruitful interaction between public choice, experimental economics and institutional analysis.
At the Women in Economics website you can also find Ostrom’s Nobel Prize address, more on the tragedy of the commons, and other resources.
Since climate change and what to do about it are in the news it’s time to re-up an underrated idea, buy coal! Carbon taxes increase the price of carbon and induce economic and technological substitution towards lower-carbon sources of fuel in the countries that adopt them. As carbon-tax countries reduce fuel use, however, non carbon-tax countries see the price of their fuel decline. Thus, unless all countries join the tax-coalition, there is leakage. Supply-side policies are an alternative to demand supply policies. The United States, for example, could buy out and close coal mines, including giving the workers substantial retirement/reallocation bonuses, thus reducing the world supply of coal which is still the largest source of C02 emissions.
You can get rich by hitting an oil gusher, but coal is relatively expensive to mine and to transport. Thus, it’s relatively cheap to buy out coal mines because you aren’t buying the coal, you’re buying the right to leave the coal in the ground. Cutting the supply of coal raises its price which will increase the quantity supplied in other countries. Thus, there is the potential for supply leakage as well as demand leakage. It’s probably easier to use more coal when the price of coal falls (electricity, for example, can be generated in a variety of ways) than it is to mine more coal when the price rises. In other words, the elasticity of the demand for coal is greater than the elasticity of supply so supply leakage is probably less than demand leakage. Furthermore, supply leakage can be handled by buying out supply in the non-coalition countries. As Noah Smith pointed out with the graph at right (data) US CO2 emissions are actually falling while the rest of the world keeps rising (as they catch up in per-capita terms) so addressing the CO2 emissions problem requires bringing countries like China and India on board.
Coal use in China is very high and increasing. India has been canceling coal plants as solar becomes cheaper but coal is still by far the largest source of power in India. Thus, there is plenty of opportunity to buy out, high-cost coal mines in China and India.
It might seem odd to buy Chinese and Indian coal mines but we buy Chinese and Indian labor, why not a coal mine? Moreover, it’s important to understand that the policy is to buy only up to the point that it benefits both parties. Buying coal isn’t foreign aid, it’s a pollution reduction plan just like a carbon tax or R&D investment and because we can buy barely-profitable coal mines and avoid the problem of leakage this is a low-cost method to reduce CO2 emissions.
Collier and Venables worry that foreign voters won’t like foreign investors buying up coal mines, although foreign investment is hardly uncommon and foreigners do protect rainforests by buying the right to cut them down. In any case, Collier and Venables suggest a cap-extract and trade program. Under cap-extract there is a cap on global extractions of carbon (not use) but rights to extract can be traded. Since it’s more valuable to extract say oil than coal what this would mean is that payments would flow from mostly developed countries to developing countries which makes it clear that we are all in the boat together.
Even without a cap-extract and trade program, however, there are other factors that make buying coal attractive to people in selling countries, namely coal is killing them even putting aside the dangers of climate change.
NYTimes: Burning coal has the worst health impact of any source of air pollution in China and caused 366,000 premature deaths in 2013, Chinese and American researchers said on Thursday.
Coal is responsible for about 40 percent of the deadly fine particulate matter known as PM 2.5 in China’s atmosphere, according to a study the researchers released in Beijing.
India’s air quality is even worse than China’s and is responsible for some 1.2 million early deaths annually. A 25% cut in pollution in India could increase life-expectancy by 1.3 years and in some highly polluted cities such as Delhi by 2.8 years. Not all pollution comes from coal but a substantial amount does.
Buyers might worry that a foreign government will take their money and later renege on the deal. There are lots of ways to deal with this problem–turn the coal fields into a national park, for example, or develop them for housing. But let’s turn a problem into a solution. Instead of buying coal, we could rent it. In other words, buy the right to delay mining the coal for say 10 years. Given the rate of improvement in solar, many coal plants will be uneconomic in 10 years and given the rate of improvement in living standards and the consequent increased demand for clean air, many coal plants in India and China could well be unpolitical in 10 years. Thus, it is true that some solutions are naturally in the offing, but for exactly this reason some coal plants are going to be working extra hours in the next decade to squeeze out what profit they can while they still can. We can avoid this last push of CO2 into the atmosphere by buying up the right to extract and holding it for a decade.
A program to leave coal in the ground could easily pay for itself in lives saved and climate stabilized.
And Jesus said, Behold, two men went forth each to buy a new car.
And the car of the first man was good and served its owner well; but the second man’s was like unto a lemon, and worked not.
But in time both men grew tired of their cars, and wished to be rid of them. Thus the two men went down unto the market, to sell their cars.
The first spoke to the crowd that had gathered there, saying honestly, My car is good, and you should pay well for it;
But the second man went alongside him, and bearing false witness, said also, My car is good, and you should pay well for it.
Then the crowd looked between the cars, and said unto them, How can we know which of ye telleth the truth, and which wisheth falsely to pass on his lemon?
And they resolved themselves not to pay for either car as if it were good, but to pay a little less than this price.
Now the man with a good car, hearing this, took his car away from the market, saying to the crowd, If ye will not pay full price for my good car, then I wish not to sell it to you;
But the man with a bad car said, I will sell you my car for this price; for he knew that his car was bad and was worth less than this price.
But as the first man left, the crowd returned to the second man and said, If thy car is good, why then dost thou not leave to keep the car, when we will pay less than it is worth? Thy car must be a lemon, and we will pay only the price of a lemon.
The second man was upset that his deception had been uncovered; but he could not gainsay the conclusion of the market, and so he sold his car for just the price of a lemon.
And the crowd reasoned, If any man cometh now to sell his car unto us, that car must be a lemon; since we will pay only the price of a lemon.
And Lo, the market reached its Nash equilibrium.
Your challenge: Explain an economics principle the King James Way.
Women in Economics highlights the groundbreaking and inspiring work of female economists – not only to recognize the important work they’ve done but to also share their inspirational journeys.
Our first major video on Elinor Ostrom will be released on February 12 followed by videos on Janet Yellen (featuring Christina Romer and Ben Bernanke), Anna Schwartz (featuring Claudia Goldin), Joan Robinson and more. We also have some more informal “mini-testimonials” discussing the work of some major contemporary economists who have been inspirational. In the video below I discuss the work of Petra Moser. (I should have cleaned my office.)
Tyler and I also want to take a moment to thank the fantastic team at MRU for a huge amount of creativity, inspiration and hard work in putting this series together. Lots of thanks and appreciation to Roman Hardgrave, Alexandra Tooley, Mary Clare Peate, Brandon Davis, Justin Dile, Lindsay Moss and William Nava. You too can join the team!
After Independence, India adopted a single time zone for the entire country. India spans as much 1,822 miles in the East-West direction or 29 degrees longitude. If India followed the convention of a new time zone every 15 degrees it would have at least two time zones. With just one zone the sun can rise two hours earlier in the East than in the far West.
In an original and surprising paper, Maulik Jagnani, argues that India’s single time zone reduces the quality of sleep, especially of poor children and this reduces the quality of their education. Why does a nominal change impact real variables? The school day starts at more or less the same clock-hour everywhere in India but children go to bed later in places where the sun sets later. Thus, children in the west get less sleep than children in the east and this shows up in their education levels and later even in their wages!
I find that later sunset causes school-age children to begin sleep later, but does not affect wake-up times. An hour (approximately two standard deviation) delay in sunset time reduces children’s sleep by 30 minutes. I also show that later sunset reduces students’ time spent on homework or studying, and time spent on formal and informal work by child laborers,while increasing time spent on indoor leisure for all children. This result is consistent with a model where sleep is productivity-enhancing and increases the marginal returns of study effort for students and work effort for child laborers.
The second part of the paper examines the consequent lifetime impacts of later sunset on stock indicators of children’s academic outcomes. I use nationally-representative data from the 2015 India Demographic and Health Survey (DHS) to estimate how children’s education outcomes co-vary with annual average sunset time across eastern and western locations within a district. I find that an hour (approximately two standard deviation)delay in annual average sunset time reduces years of education by 0.8 years, and children in geographic locations with later sunset are less likely to complete primary and middle school.
Addendum: The importance of sleep and coordination of sleep with circadian rhythms is also illustrated by the phenomena of teenagers who get more sleep and do better in school when school opening is better timed with adolescent sleep patterns. As a result, we are seeing a movement to push school opening times later for teenagers. Perhaps India will adopt a second time zone.
European germs killed 90% of the population of the Americas in the century after 1492 causing millions of hectacres of farm land to revert to forest which increased the uptake of carbon and reduced the planetary temperature. That is the upshot of a new paper that joins together previous estimates of population decline, farm land and carbon sequestration to push the onset of the Anthropocene to before the industrial revolution.
Abstract: Human impacts prior to the Industrial Revolution are not well constrained. We investigate whether the decline in global atmospheric CO2 concentration by 7–10 ppm in the late 1500s and early 1600s which globally lowered surface air temperatures by 0.15∘C, were generated by natural forcing or were a result of the large-scale depopulation of the Americas after European arrival, subsequent land use change and secondary succession. We quantitatively review the evidence for (i) the pre-Columbian population size, (ii) their per capita land use, (iii) the post-1492 population loss, (iv) the resulting carbon uptake of the abandoned anthropogenic landscapes, and then compare these to potential natural drivers of global carbon declines of 7–10 ppm. From 119 published regional population estimates we calculate a pre-1492 CE population of 60.5 million (interquartile range, IQR 44.8–78.2 million), utilizing 1.04 ha land per capita (IQR 0.98–1.11). European epidemics removed 90% (IQR 87–92%) of the indigenous population over the next century. This resulted in secondary succession of 55.8 Mha (IQR 39.0–78.4 Mha) of abandoned land, sequestering 7.4 Pg C (IQR 4.9–10.8 Pg C), equivalent to a decline in atmospheric CO2 of 3.5 ppm (IQR 2.3–5.1 ppm CO2). Accounting for carbon cycle feedbacks plus LUC outside the Americas gives a total 5 ppm CO2 additional uptake into the land surface in the 1500s compared to the 1400s, 47–67% of the atmospheric CO2 decline. Furthermore, we show that the global carbon budget of the 1500s cannot be balanced until large-scale vegetation regeneration in the Americas is included. The Great Dying of the Indigenous Peoples of the Americas resulted in a human-driven global impact on the Earth System in the two centuries prior to the Industrial Revolution.
TechnologyReview: In July 2016, someone using the name Tom Elvis Jedusor (the real name of Lord Voldemort, the main villain in the Harry Potter universe, in the French edition) posted a link to a text file in a chat room frequented by Bitcoin researchers. Voldemort’s document described MimbleWimble, a blockchain system that would hide the identifying information associated with Bitcoin transactions.
…The person who started Grin [one of the first new currencies built on a blockchain that implements MimbleWimble] is also pseudonymous, going by the name Ignotus Peverell (the original owner of Harry’s invisibility cloak), and has never been seen. Peverell recently used a text-to-speech program to address attendees at a Grin conference.
So to sum up, Grin is a new currency on the MimbleWimble blockchain imagined by Lord Voldemort and implemented by the invisible Ignotus Peverell.
…Eric Meltzer, an investor for crypto-focused Primitive Ventures, recently estimated that $100 million of “mostly VC money” has already been invested in Grin mining operations.
Bloomberg: In a novel approach for the biotechnology industry, small-cap company Agenus Inc. is aiming to raise $50 million to $100 million by issuing digital securities backed by future sales of an experimental cancer drug.
The digital securities will allow investors to bet on future sales of single products and will have a limited impact on shareholders’ equity, the company said. Agenus plans to offer at least 25 million of what it calls biotech electronic security tokens, or BESTs, to certain high-net-worth individuals and institutional investors starting Feb. 15.
I find this puzzling. First, why break out one drug from the rest of the firm? Investors generally want diversification and this is the opposite. Agenus is basically saying the rest of the firm is a value suck. Second, one of the virtues of the blockchain is that it allows for easy trade but the SEC requires that to buy these securities you must be an accredited investor and as such there are typically encumbrances on transfer. Thus, putting the securities on the blockchain doesn’t lower transaction costs, the way it could for other assets.
A lot of assets will be tokenized (i.e. securitized on the blockchain) in the future so this is an area to watch but to succeed tokenization must increase diversification and reduce transaction costs and this tokenization does neither.
In this clip professional money manager Ben Griffiths approvingly quotes fellow-trader Larry Williams, “If you get one thing right in your career it is to learn to be a slow buyer and a fast seller”. “If you can master that”, Griffiths continues “you will be well down the way to being a successful manager of money.” Using a huge database of 783 portfolios averaging $573 million in size and covering 4.4 million trades over 16 years, Akepanidtaworn, Di Mascio, Imas, and Schmidt show that professional money managers follow exactly this advice and it is exactly wrong.
Professional money managers do well on their “slow”, buy decisions–somewhat surprisingly, well enough to beat benchmark portfolios. It’s on their “fast”, sell decisions that money mangers significantly underperform the market. Remarkably, the authors show that on average professional money managers would have done better had the chosen what to sell randomly. Why? On their buy decisions money managers put in effort–you can tell they are putting in effort because their buy decisions cannot be explained by simple heuristics based on past returns (such as buy past winners or buy past losers). On their sell decisions, however, managers do appear to follow a heuristic of selling their big past winners or past losers. See the graph where the blue buy decisions are independent of past returns while the red sell decisions show a clear preference to sell positive or negative return outliers. The authors show that this bias reduces return (just as you would expect). When you sell fast you sell what comes to mind quickest, an availability bias, and that’s often a past winner or a past loser even if greater thought would convince you that these are not the best stocks to sell. The sell fast bias, however, is pretty easy to fix. I expect that institutional investors will induce money managers to take a second look at sell decisions, much as computer systems now ask physicians to check branded prescriptions when generics are available.
Addendum: In related news, Deep Mind’s Alpha Star trounced human players of StarCraft II, a game of imperfect information that is much more complicated than chess. Amazingly, Alpha Star made fewer actions per minute than the human players. As with GO the AI developed new long-range strategies never before seen.
The history of Aleppo is terrible stuff; a long succession of massacres and sieges disappearing into the mists of Syrian pre-history. First held by the Hittites, it was captured in turn by the Philistines, Assyrians, Babylonians, Persians, Greeks, Romans, Persians (again), Byzantines, Arabs, Mongols and Ottomans, each of whom vied to outdo the carnage of their predecessors. The Assyrians were the most imaginatively sadistic: they impaled the town’s menfolk on their spears and feasted for two days while their victims groaned to a slow death.
In between invasions Aleppo was ruled by a succession of aristocratic thugs who exacted outrageous taxes and perfected ingenious ways of bankrupting their burghers.
In all the town’s history there are only two cheering anecdotes. The first tells of the Arabs who captured Aleppo by dressing up as goats and nibbling their way into the city; the second concerns Abraham, who is supposed to have milked his cow on the citadel’s summit. It is not much in ten thousand years of history, especially when the one story ends in a massacre…and the other is a legend, and untrue. It is the result of a misunderstood derivation of the town’s (Arabic) name Haleb, which comes not from the Arabic for milk (halib) but a much older word, possibly Assyrian, connected with the mechanics of child abuse.
From William Dalrymple’s In Xanadu written in 1989…things have not since improved.
We are Canada’s Air Navigation Service Provider (ANSP) managing 3.3 million flights a year for 40,000 customers in over 18 million square kilometres – the world’s second-largest ANSP by traffic volume.
Our airspace stretches from the Pacific West coast to the East coast of Newfoundland and out to the centre of the North Atlantic, the world’s busiest oceanic airspace with some 1,200 flights crossing to and from the European continent daily. It also stretches from the busy U.S-Canada border with major international airports to the North Pole where aircraft fly polar routes to reach Asia.
We are also the world’s first fully privatized civil air navigation service provider, created in 1996 through the combined efforts of commercial air carriers, general aviation, the Government of Canada, as well as our employees and their unions.
Our revenues come from our aviation customers, not government subsidies. By investing in operations and controlling costs, we strive to keep customer charges stable, while improving safety and flight efficiency.
In addition to Canada, New Zealand, Germany, Australia, and the United Kingdom have moved in recent decades towards a more private system based on user fees rather than government funding. See also my earlier post on European airports.
In 2015, I documented that crime in Baltimore was rising rapidly as police resources became stretched as they dealt with riots and anger following the death of Freddie Gray. I warned that the city could tip into a permanently higher crime rate.
It’s now become clear that is exactly what happened as an investigative report by The Trace reveals:
Instead of getting backup, detectives were pulled from their cases, sometimes for days at a time, to help quell the violence. By 2016, homicide investigators cumulatively spent 10,000 hours working riot duty and patrol rather than tracking down murderers…
In the ensuing months, Baltimore’s closure rate for shootings dropped to 25 percent, the lowest in recent history. More than 1,100 cases from 2015 and 2016 alone remained unsolved by the following summer.
As the closure rate fell, the number of shootings increased (see data at right).
It’s not just Baltimore, however:
The crisis of unsolved shootings isn’t confined to cash-strapped cities like Baltimore, but also hits some of America’s most affluent metropolises. In 2016, Los Angeles made arrests for just 17 percent of gun assaults, and Chicago for less than 12 percent. The same year, San Francisco managed to make arrests in just 15 percent of the city’s nonfatal shootings. In Boston, the figure was just 10 percent.
Crime is lower today than in the past but we are in danger of becoming complacent. The rate of unsolved crimes is very high and in some cities it is soaring. Any city with an arrest rate for assaults of 15% is primed for a crime wave.
We need more police as well as better policing.
Addendum: I wonder how many of these cities are still devoting significant resources to marijuana busts?
Cryptocurrencies, GPS, drones, and cheap beacons are driving a new evolution in illegal markets:
…[A] major change is the use of “dead drops” instead of the postal system which has proven vulnerable to tracking and interception. Now, goods are hidden in publicly accessible places like parks and the location is given to the customer on purchase. The customer then goes to the location and picks up the goods. This means that delivery becomes asynchronous for the merchant, he can hide a lot of product in different locations for future, not yet known, purchases. For the client the time to delivery is significantly shorter than waiting for a letter or parcel shipped by traditional means – he has the product in his hands in a matter of hours instead of days. Furthermore this method does not require for the customer to give any personally identifiable information to the merchant, which in turn doesn’t have to safeguard it anymore. Less data means less risk for everyone.
The use of dead drops also significantly reduces the risk of the merchant to be discovered by tracking within the postal system. He does not have to visit any easily to surveil post office or letter box, instead the whole public space becomes his hiding territory.
…Classically, when used by intelligence agencies, dead drops relied on being concealed. This lead to dead drops being hard to find even by the intended recipients without costly preparation and training. One of the results of this was that dead drops were often used repeatedly, which increased the probability of both sender and recipient being identified by surveillance.
An ideal dead drop is however used exactly once. Only then can the risks of using it be reduced to pure bad luck.
This challenge is met by Dropgangs in various ways. The primary one is that the documentation of each dead drop is conducted in minute detail, covering GPS coordinates, photos of the surrounding and the location, as well as photos of the concealment device in which the product is hidden (such as an empty coke can). The documentation however increases the risk for the Dropgang since whoever creates it would be more easy to identify by surveillance. In addition, even great documentation still requires the customer to understand it and follow it precisely, which can lead to suspicious behavior around the dead drop location (staring at photos, visually comparing them to the surrounding, etc).
A first development to mitigate the problem of localizing is the use of Bluetooth beacons. In addition to the product, the dead drop contains a little electronic device that sends a signal that can be received by a smartphone, which in turn can display the direction and approximate distance to the device. In addition to the GPS coordinates, the customer requires only a smartphone with the correct App. Beacon devices like these are available on the open market for under ten dollars.
They do however pose the risk of a non-authorized party to discover the dead drop, simply by searching an area suitable for hiding dead drops with their own smartphone.
There are first reports of using beacon devices that are not constantly sending a signal, but have to be activated first. The activation usually happens by establishing a WiFi hotspot on the customer’s phone (by using the WiFi tethering feature). Only if the beacon sees a WiFi hotspot with a specific, merchant provided, unique name will it start to send a homing signal itself. Devices like these are very cheap (<15 USD) and have gained traction in the field, but they pose risks to the customer: His smartphone becomes identifiable by observers, even over considerable distance. This can lead to tracking the customer.
…A plausible next step would be the development of markets for dead drop operators that make their living by picking up product from one dead drop and placing it in another, working as a proxy for the customer to increase his safety and to reduce his efforts. This would also make this distribution model wider spread and available to more products, which will blur the lines between the black and the legal market. On this blurred line new services and technologies will establish themselves, inherently dual use services like lock boxes that can be paid by peer-to-peer cryptocurrencies.
Looking even further into the future, it seems plausible that the whole urban environment might find itself integrated into a dynamic landscape of very short-lived dead drops that are serviced by humans and cheap drones (unmanned aerial vehicles), which are already cheaply available and likely only require one market actor to develop and spread a mechanism to pick up and drop goods. Both merchant and customer could use drones, that are available for rent through dedicated Apps, to deliver product to a meeting point on a roof, where another drone would pick it up. Chaining multiple exchanges like this will make the tracing of the delivery extremely hard, essentially leading to mixing techniques so far used only in anonymizing digital communication.
Read the whole thing.
Hat tip: Eli Dourado.