If you pay attention online you might have heard of “The Current Thing.”
What’s The Current Thing? The Current Thing is any concept that grabs hold of public attention, sometimes out of nowhere, and which demands an answer: are you for or against?
I also like Marc Andreessen’s explanation.
If not supporting it gets you disinvited from the dinner party, it’s the current thing.
This post is about the UAP (Unidentified Aerial Phenomenon) “sightings” that have gained attention over the past few years and especially in the past few months. If you haven’t heard of this before or seen some of the (admittedly grainy) videos, it’s a tell of how a potentially big (and weird) story doesn’t get as much attention as it probably should.
Unlike previous UFO (Unidentified Flying Object) sightings from the past half century, the UAP situation is different. Rather than random individuals or conspiracy theorists, witnesses include fighter jet pilots. Interested parties include the military and senior government officials. The US government has established the Unidentified Aerial Phenomena Task Force. We went from oddballs claiming that they saw UFOs to people with a lot of credibility to lose claiming that they have either observed UAPs or believe that the question deserves serious attention.
No matter your opinion of what the reality is, there are few main outcomes we can expect the more we learn about this topic. These outcomes all seem to portend a change of some sort. Continue reading “Unintended UAPs”
I’ve written multiple times about basic values, technology trends, and how they can be causes of unintended consequences.
Today I’m exploring the topic of autonomous weapons, reasons behind their development, and potential outcomes. This is a big topic that I will certainly return to multiple times.
Autonomous weapons are characterized by understanding battlefield goals and finding ways to achieve these goals without human action. Such weapons are currently being researched, developed, and tested as intelligent wingmen for fighter pilots, as support vehicles carrying supplies and fuel, and as offensive weapons. Continue reading “Onward, Robot Soldiers?”
Apart from the US presidential election, another well-funded campaign from 2020 was California ballot measure Proposition 22. If you live outside of California, you may have never heard of Prop 22, even though it could come to impact you.
Prop 22 was a California referendum that dealt with a question specifically addressed to rideshare and app delivery companies. Namely, should rideshare drivers legally be considered contractors or employees?
Now that attention to the presidential election and inauguration has past, let’s go back to look at Prop 22, its Yes vote, and how its implementation led to a system change.
The Fallout
Less than a month after Prop 22 came into effect, related companies took the following actions:
Political Action Committees have formed to bring Prop 22-style legal changes to New York, Illinois, and perhaps nationwide. And possibly globally.
This is just the beginning, but each of the above outcomes have been met with some amount of shock and outrage. Why now?
The Ballot
What Proposition 22 actually said on the voter guide:
“Prop 22: Exempts App-based Transportation And Delivery Companies From Providing Employee Benefits To Certain Drivers. Initiative Statute.
“Summary: Classifies app-based drivers as “independent contractors,” instead of “employees,” and provides independent-contractor drivers other compensation, unless certain criteria are met. Fiscal Impact: Minor increase in state income taxes paid by rideshare and delivery company drivers and investors.”
As with many ballot propositions, it took lengthy explanations to show what voters were actually choosing. Rather than list all the listed arguments and rebuttals here, see the lengthy voter guide for the full details voters received.
Set aside the reality that few voters may actually read propositions carefully. Also set aside the issue that common knowledge of Prop 22 probably came more from ad campaigns than language listed on the voter information guide. To me, the most noticeable information was the information missing from the information provided. How would rideshare and related systems change if Prop 22 received a Yes or No vote?
The Campaign
Prop 22 put the business models of rideshare and delivery companies at risk as well as threatening to change gig worker treatment. The risk for either side was in their relative change. What followed were ad campaigns in support of either side.
But a ballot initiative doesn’t require that both arguments would be heard equally or presented just as well. Rideshare and delivery companies (Uber, Lyft, Postmates, DoorDash, and Instacart) spent approximately $200 million promoting a Yes vote. The opposition spent only $20 million.
How should we judge spending on Prop 22? To compare, in the last couple decades, we’ve seen dramatic increases in fundraising for presidential campaigns. In 2000, Bush and Gore together raised around $450 million. Another contentious presidential campaign in 2004 saw the campaigns raise $1 billion for the first time. For the record-breaking 2020 campaign, Biden and Trump collectively raised $1.7 billion (counting all the other candidates would double that amount).
Of all the 2020 presidential campaign money, $288 million came from donors in California. That gives us some perspective.
So perhaps the $220 million spent on Prop 22 in California makes this single issue similarly important to a presidential campaign. The financial support is different though. Companies backing the proposition can model their own benefit to the point that they know what a win is worth. That’s harder to do with a presidential campaign.
App companies also had distribution on their side. That is, they already had a direct line to customers and gig workers and could push messages like this.
Is it possible that 72% of drivers supported Prop 22? With that majority, shouldn’t voters follow the drivers?
This is where you might use the phrase “lies, damned lies, and statistics.” Uber drivers have different needs. Few regularly work over 15 hours a week just for Uber (the minimum needed to qualify for the Prop 22 benefits) while many work fewer hours and also split their time between other gig companies. Those in the second category would likely lose their ability to drive for Uber in the event of a No vote that classifies app workers as employees. That could explain why so many Uber drivers and delivery people supported the proposition.
The vote passed 58% in support of Proposition 22.
Comparisons
We need to back up a moment to an earlier bill. Prop 22 was itself a follow-up to Assembly Bill 5 (AB5), a 2019 bill which provided a three-part test to whether someone is an employee or a contractor.
“The person is free from the control and direction of the hiring entity in connection with the performance of the work, both under the contract for the performance of the work and in fact.
“The person performs work that is outside the usual course of the hiring entity’s business.
“The person is customarily engaged in an independently established trade, occupation, or business of the same nature as that involved in the work performed.”
AB 5 also granted numerous business-type exemptions, but not to app companies.
Exempted businesses were notably not individually well-funded or from Silicon Valley, though they may have held political sway with California legislators. These AB 5 business exceptions include doctors, dentists, lawyers, architects, engineers, accountants, commercial fishermen, designers, artists, barbers, and more.
They political sway was most allegorically seen in business awards a legislator bragged about for writing exemptions into AB 5.
I never imagined that my only “gold record” would be a thank you from the Recording Industry Association for working to right-size Dynamex & AB5 for musicians. But, I’ll take it! (Have you heard me on Karaoke though??) pic.twitter.com/OUfiDcPD4i
AB 5 threatened the gig economy business model where drivers, delivery people, and other workers did not receive employee benefits. That threat was bound to receive a response from the companies that had the most at risk.
“The ballot measure would require the companies to provide an hourly wage for time spent driving equal to 120% of either a local or statewide minimum wage. It would not pay drivers for the time they spend waiting for an assignment. It also requires that drivers receive a stipend for purchasing health insurance coverage when driving time averages at least 15 hours a week, a stipend that grows larger if average driving time rises to 25 hours a week.”
This is an example of where it’s difficult to assess outcomes from a quick read.
15 hours might sound like a low bar, but this is active driving time. Potentially double that amount of time to include driver wait time between fares. Also, the active driving time is tracked per company. That is, 10 hours driving for Uber and 5 hours driving for Lyft do not qualify as 15 hours. Just meeting that 15 hour minimum will prove difficult for many drivers.
Further, an earlier analysis of Prop 22 by the UC Berkeley Labor Center reassessed the 120% of minimum wage benchmark ($15.60) and claims that drivers with more than 15 active hours per week would actually earn only $5.64 per hour.
Why would drivers choose to work if their pay declines? There could be a number of reasons, including that they prefer driving to other work and can’t find other work. A distinction of gig economy work is that you typically don’t need to commit to a fixed schedule. In the case of driving for rideshare delivery businesses, gig workers can work just about any hours they want. That flexibility may make up for their ability to earn more doing something else.
Rideshare companies are famous for having basing their distribution model on moving into new municipalities in advance of any legal right to do so. Uber entered the New York City market without a license to operate as a transportation company. As a result, taxi drivers felt both their fares and medallion values fall and riders benefitted from lower fares and more supply.
A No vote on Prop 22 was supposed to challenge not the distribution part of rideshare businesses, but their cost structure.
But after the Yes vote, some fees have also been passed on to customers. For Uber and Lyft, the fees depend on location and range from $0.30 to $1.50 per ride. Postmates now charges a driver benefits fee of between $0.50 and $2.50, depending on location.
Prop 22 Paradox
Why did we see public shock and outrage in January when affected companies fired workers, changed policy, and added fees? Surely Proposition 22 voters would have expected some type of negative outcome, however they happened to vote.
It’s probably more likely that many Prop 22 voters didn’t really think about negative outcomes. Either because their chief concern was on what positive outcomes they would see, that they didn’t believe themselves negatively affected by potential changes. or they just didn’t have the habit of thinking about trade-offs.
A look at Prop 22 outcomes.
Yes (drivers classified as contractors). Rideshare companies start to provide some benefits. Drivers continue to set their own hours. Price increases passed on to customers.
Other potential outcomes: Slower driving? Drivers have an incentive to reach 20 hours of active driving time. That’s the point at which benefits kick in. If the value of the benefits is greater than that from driving fewer hours, then drivers may slow down or at least not speed.
No (drivers classified as employees). Drivers receive pay increases. Drivers have to work fixed hours. Driver supply falls. Fares rise. Ride demand falls. Rideshare companies have difficulty operating in California. Price increases passed on to customers.
In the case of a No vote, affected companies estimated needed price increases of 25% to over 100%. Outside researchers estimated 5% to 10%.
Alison Stein, Uber’s economist makes this series of public projections for price increases, trips lost, and work opportunities lost.
By Alison Stein, Economist at Uber (link to larger version above)
Given Stein’s role we perhaps need to take the projections as one perspective. Notably, price increases are most extreme in the less populated parts of California (more inactive driver time between rides). But these price increases also stand out because Uber had subsidized rides to become a less expensive option than legacy taxis.
Trying to present the way a system change could have other outcomes is not unattainable. Especially in something like Proposition 22, which is relatively straightforward. I say relatively because unlike say electing an individual to political office, who might say one thing and do entirely something different, Prop 22 was more limited in scope.
It’s also not to say that putting out that systems map might produce one single correct answer. People can still weigh different outcomes differently. I just don’t like shock and outrage after a legal change goes into effect and companies act. The shock and outrage should have happened with the outcome of the vote itself.
Societies have long valued information control but methods of control have changed over time. What systems drive these changes? And where do undesirable outcomes occur?
Using any of these methods doesn’t imply bad intentions. In some cases, there are good reasons for wanting to control information. But if we’re thinking only of intentions, we’ll lose our focus on outcomes. Good intentions can lead us down bad pathways.
Four major types of control information are destruction, banning, debauching, and blocking.
These methods are applied to recorded information as well as what we carry in our memories and pass down verbally.
Some systems look like one-way roads. Here I’ll call one-way system roads those which seem inclined to move in one direction, even if the endpoint is difficult to predict, and where it is difficult to return to the earlier state. In some cases an intervenor slows movement down the one-way road or lengthens the road itself.
Let’s look at depletion of forests to make charcoal, the search for oil, the possibility of world wars, opioid and social media addiction, and presidential election cycles.
Last week we learned that customers of Garmin, maker of GPS-enabled tech for sports, automotive, aviation, and other use cases, couldn’t fully use their devices, sync, or connect for updates. As the story unfolded and the company eventually announced that this was the result of a ransomware attack, it reminded me of a pattern I’ve written about before — the trade-off between operational improvements and additional systemic risk.
Garmin, and many other companies, provide what has become essential technology. This article is an exploration of unintended consequences related to system dependence, navigation, international differences, hacker ambitions, and potential future outcomes.
A snapshot of Garmin’s recent uptime for its aviation service flyGarmin.
Today I was reminded of the first post I ever wrote on this blog (Voice AI, Telecom, Scams, and Co-evolution), back in 2018. My first article was focused on second-order effects of emerging voice AI capabilities and projected a number of scams that the technology would enable.
While this tech also has many positives, I always try to get a fuller picture by looking at the system.
The world is full of trade offs. In the case of voice AI in the article, we have the ability to scale up scams that historically worked, but only in small does. The “hey grandma” scam was one example. As I wrote back then:
“An older scam that this tech will scale is what’s known as the “Hey, Grandma” scam, where a grandparent gets a call from a “grandchild” in distress. There are different flavors of this. For US grandparents the story is often that the grandchild got into legal trouble and needs money wired. In China and Taiwan, it’s often that the grandchild has been kidnapped and is being beaten up. Again, wire the money.”
We usually think of speed as good. Getting somewhere faster or finishing something sooner are typically positives. Completing an action or a project shouldn’t prioritize slowness. In fact, slowness is often paired with unsuccessful and over-budget projects. But are there breaking points where increased speed makes a system worse and harms the project itself?
There are several ways in which increased speed can change a system for the worse. Let’s look at how increased speed skips past unknown needed steps, pushes work elsewhere in the system, and adds risk.
Skipping Unknown Steps
Systems are not cleared bounded. We (at least as a non-expert) often don’t know or understand all the steps necessary to produce something.
As an example of the first way increased speed leads to problems, I was reminded of this quote, from Zorba the Greek.
“My indiscreet desire of that morning to pry into and know the future before it was born suddenly appeared to me a sacrilege. I remembered one morning when I discovered a cocoon in the bark of a tree, just as the butterfly was making a hole in its case and preparing to come out. I waited a while, but it was too long appearing and I was impatient. I bent over it and breathed on it to warm it. I warmed it as quickly as I could and the miracle began to happen before my eyes, faster than life. The case opened, the butterfly started slowly crawling out and I shall never forget my horror when I saw how its wings were folded back and crumpled; the wretched butterfly tried with its whole trembling body to unfold them. Bending over it, I tried to help it with my breath. In vain. It needed to be hatched out patiently and the unfolding of the wings should be a gradual process in the sun. Now it was too late. My breath had forced the butterfly to appear, all crumpled, before its time. It struggled desperately and, a few seconds later, died in the palm of my hand.
That little body is, I do believe, the greatest weight I have on my conscience.”
Those steps, like the gradual unfolding of a butterfly’s wings, can remain hidden in the chrysalis or with time they can be teased out. Something like a kind of natural phase change — a butterfly emerging from a cocoon — is complex but probably already as minimal as it could be. Not necessarily so for processes we create.
At the opposite extreme of beauty, I was once at an organization that instituted an ISO standardization process. Once that was implemented the goal was maintaining the standards, not efficiency, for we had unintentionally institutionalized some processes that served no purpose. The people knew which ones were useless, but still needed to do them. This is one of the small sadnesses of work life in large organizations.
Pushing Work Elsewhere
I used to want to be a photojournalist.
I had multiple cameras and lenses, developed and printed my own film, and worked as a photographer. I have photographed high-profile delegations at the top of the Capitol dome, and in a less security obsessed age, in the depths of the Pentagon. I’ve also had film confiscated (long story, another time).
Before high-quality digital cameras, professional photographers shot film. Because I could only carry maybe 10 rolls in a camera bag, no matter how interesting the subject matter, there was a limited number of exposures I could take. With 36 exposures in a roll of 35mm film, 10 rolls gave me 360 shots, max. (This number itself is a huge increase over older formats like the large glass photographic plates that Ansel Adams used almost a century ago.) 360 pictures was a huge number to shoot in a day and I probably only did it once.
Today, it’s normal for photographers to shoot that many in an hour.
Photography was more difficult, more expensive, and slower in the past. I couldn’t take as many pictures and had to wait hours at least (finish the roll, develop, and print) to finally see what images I captured. Often, I had to wait days. But looking at the prints I was able to recall what lens I used, what exposure settings, and how I held the camera. The difficulty of taking pictures made each one more memorable.
Unlike in the case of the butterfly, once digital cameras improved, there was no need for photography to continue to be slow, as it was with film. So as the results of photography appeared faster, much of the work that took place while shooting was pushed to the proofing and editing phase.
The more pictures I could take — an increase in speed supported by ease and large camera storage — the more careless I was during the photo taking phase. This is a positive feedback loop. Instead, I pushed the care to the final selection process.
Risk Adding
A goal, especially one not well thought out can result in second-order effects that act against the purpose of the goal in the first place.
“In the late 1960s, the Ford Motor Company was losing market share to foreign competitors that were selling small, fuel-efficient cars. CEO Lee Iacocca announced the specific, challenging goal of producing a new car that would be ‘under 2000 pounds and under $2,000’ and would be available for purchase in 1970. This goal, coupled with a tight deadline, meant that many levels of management signed off on unperformed safety checks to expedite the development of the car—the Ford Pinto. One omitted safety check concerned the fuel tank, which was located behind the real axle in less than 10 inches of crush space… Investigations revealed that after Ford finally discovered the hazard, executives remained committed to their goal and instead of repairing the faulty design, calculated that the costs of lawsuits associated with Pinto fires (which involved 53 deaths and many injuries) would be less than the cost of fixing the design.”
The Pinto had the shortest automotive product timeline from design to delivery — 25 months when the industry average was 45 months.
The internal reaction to the Pinto’s design flaws was itself a choice of speed. Given the data, the needed calculations could be performed quickly. The redesign and fix of the Pinto gas tank would take much longer.
“The costs of implementing the rollover portion of the amended Standard has been calculated to be almost three times the expected benefit, even using very favorable benefit assumptions. The yearly benefits of compliance were estimated at just under $50 million, with an associated customer cost of $137 million.”
There are many examples from financial services of speed adding to risk, but I’ll pull out this example (also from Goals Gone Wild) from Continental Illinois Bank in the 1970s and 1980s. Continental was at the time a regional bank.
In 1976, Roger Anderson, the bank’s chairman publicized his plan for fast growth. In only five years the bank more than doubled its portfolio of loans.
“To reach this stretch goal, the bank shifted its strategy from conservative corporate financing toward aggressive pursuit of borrowers. Continental allowed officers to buy loans made by smaller banks that had invested heavily in very risky loans.”
Additionally, improper due diligence and kickbacks for loan approvals compounded until defaults and a run on the bank led to a government bail out of Continental Illinois Bank in 1984. That government bailout led to the popularization of the phrase “too big to fail.”
Antidotes to These Outcomes?
While the casual feeling may be that things are moving too quickly, that might just be part of the human condition. Many have actually written about the way speed — at least measured by technological progress — has slowed down over the past century.
The book The Rise and Fall of American Growth, Robert Gordon itemizes the innovations that appeared between 1870 – 1940 (electricity as a utility, communications, electric lights, home appliances, the telephone, recorded sound, radio, television, the automobile, the airplane, and more). These innovations led to greater productivity, health, education and a world so changed as to be unrecognizable to those who lived earlier.
By Gordon’s (and many others’) measure, innovation speed has since slowed.
Another way to look at speed is to compare the completion time of large building projects (both physical and digital) to the modern day. Patrick Collison, co-founder of Stripe, keeps a list of such projects that finished in what today seem like unnaturally short times. For example:
The Empire State Building (410 days); the Pentagon, at the time the world’s largest office building (491 days); the Alaska Highway spanning 1,700 miles (234 days); the Boeing 747 from start to finished first plane (747 days); and the New York Subway first 28 stations (4.7 years); the prototype of JavaScript (10 days); first version of Unix (3 weeks); the first GUI computer, the Xerox Alto (3 months); the iPod first shipments (290 days)…
Proposed reasons for the slowdown include increased conflicting interests and regulation, but not studying second-order effects. Such slowness presents its own problems.
Consider
“Chesterton’s Fence” as an example of second-order thinking: “I don’t see the use of this [useless fence]; let us clear it away,” brings the retort “If you don’t see the use of it, I certainly won’t let you clear it away. [W]hen you can come back and tell me that you do see the use of it, I may allow you to destroy it.”
As Vaclav Havel wrote in 1992: “I had wanted to make history move ahead in the same way that a child pulls on a plant to make it grow more quickly.” Social change may happen in fits and starts.
Sometimes slowness across minutes is what’s needed. Stanislav Petrov of the USSR’s Air Defense Forces was on shift in 1983 to monitor for nuclear warhead launches from the US. When a new satellite system sounded an alarm, he paused for 15 minutes to determine that the Soviet Union’s missile warning system had reacted in error (later shown to be sunlight glinting off clouds above North Dakota).
Years ago, when I was in college, I spent a couple hours a day reading the New York times in print. I would go to my favorite library, get one of the two copies of that day’s paper, and probably go through half of it. I then read three or four other papers too. The feel and even the smell of the newsprint was something I looked forward to. I started my days that way. When I couldn’t start my days that way, I missed it.
One of my goals at the time was to do something in journalism. I wrote for a handful of college publications. But journalism ended up not being for me, and I have no regrets about that today. In the meantime I still looked forward to reading the paper.
But more often I ended up reading less news in focused hour-long chunks in the morning and more news in quick scattered clips throughout the day, often delivered via social media. This change gave me awareness of new developments but also distracted me incredibly from longer-term projects. You’ve probably gone through that change too.
