Tech vs. Telecom

Are the big telecom companies like AT&T, Comcast, and Verizon tech companies? Or are they giant, lumbering change-averse utilities of yesteryear? Well, they’re sort of in-between. I would like to see Comcast succeed because they are a major employer and providing support to local startups in my city. And yet, I have had awful experiences with them and just dropped them in favor of Verizon. I’ll be happy with Verizon until my introductory promotion runs out.

These companies are not good enough. They are not providing the kind of internet we need at a price we can afford. This article in Wired says Apple, Google, and Facebook will end up eating them alive, by accident.

These tech titans didn’t plan to take down the telcos. But they depend upon you having fast, reliable internet, so they’re bringing everything in-house. This promises to make things drastically better for you as a consumer, so if you hate big telecoms, you’ll feel schadenfreude at their demise. But you might end up with more of the same as the new guard becomes the old guard…

You’ve probably heard about Google Fiber and its shift toward wireless Internet over fiber-optic cables. Google Fi mobile service could be even more radical. Instead of building cell towers, Google resells access to Sprint and T-Mobile networks. Companies like Cricket and TracFone do this too, but Google-Fi lets your phone use the best signal available at any moment…

As new technologies and expanded access to the wireless spectrum drive down the cost of operating cell services, Google and other wireless brokers will be able to create nationwide–even worldwide–networks. That would make wireless service a commodity and shift the balance of power from incumbents like AT&T to companies like Google.

I wonder what major industry will be the next to go down. Will it be the fossil fuel industry challenged by renewables (the coal industry is already close to collapse), the finance industry challenged by upstart new financial tech companies (if they don’t shoot themselves in the foot again first), or the traditional telecoms falling to the new tech giants?

Magic Leap

According to this article in Wired, the “world’s hottest startup” is virtual reality company Magic Leap.

Virtual reality overlaid on the real world in this manner is called mixed reality, or MR. (The goggles are semitransparent, allowing you to see your actual surroundings.) It is more difficult to achieve than the classic fully immersive virtual reality, or VR, where all you see are synthetic images, and in many ways MR is the more powerful of the two technologies.

Magic Leap is not the only company creating mixed-reality technology, but right now the quality of its virtual visions exceeds all others. Because of this lead, money is pouring into this Florida office park. Google was one of the first to invest. Andreessen Horowitz, Kleiner Perkins, and others followed. In the past year, executives from most major media and tech companies have made the pilgrimage to Magic Leap’s office park to experience for themselves its futuristic synthetic reality. At the beginning of this year, the company completed what may be the largest C-round of financing in history: $793.5 million. To date, investors have funneled $1.4 billion into it.

That astounding sum is especially noteworthy because Magic Leap has not released a beta version of its product, not even to developers. Aside from potential investors and advisers, few people have been allowed to see the gear in action, and the combination of funding and mystery has fueled rampant curiosity. But to really understand what’s happening at Magic Leap, you need to also understand the tidal wave surging through the entire tech industry. All the major players—Facebook, Google, Apple, Amazon, Microsoft, Sony, Samsung—have whole groups dedicated to artificial reality, and they’re hiring more engineers daily. Facebook alone has over 400 people working on VR. Then there are some 230 other companies, such as Meta, the Void, Atheer, Lytro, and 8i, working furiously on hardware and content for this new platform.

you can sue your city for unsafe streets

According to Streetsblog NYC:

The Court of Appeals, New York’s highest court, ruled that New York City and other municipalities can be held liable for failing to redesign streets with a history of traffic injuries and reckless driving…

“This decision is a game-changer,” says Steve Vaccaro, an attorney who represents traffic crash victims. “The court held that departments of transportation can be held liable for harm caused by speeding drivers, where the DOT fails to install traffic-calming measures even though it is aware of dangerous speeding, unless the DOT has specifically undertaken a study and determined that traffic calming is not required…”

Vaccaro said the decision “will create an affirmative obligation on the DOT’s part to — at the very least — conduct studies to determine whether infrastructure can reduce traffic violence, and unless such studies indicate otherwise, to install the infrastructure.”

Lawsuits are not the ideal way to do urban planning or protect public safety. They are a last resort. But I support them as one tool in the toolbox when engineers, planners, and public officials are ignoring their ethical obligation to protect the public when they know (or, if they don’t know, are ignorant of knowledge they are ethically obligated to acquire to be a competent professional in their chosen field) there are better, proven alternatives out there.

ride pooling can (maybe) reduce traffic by a lot

Here’s a new study from MIT that says ride sharing and pooling algorithms could theoretically reduce Manhattan rush hour traffic drastically.

On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment

Ride-sharing services are transforming urban mobility by providing timely and convenient transportation to anybody, anywhere, and anytime. These services present enormous potential for positive societal impacts with respect to pollution, energy consumption, congestion, etc. Current mathematical models, however, do not fully address the potential of ride-sharing. Recently, a large-scale study highlighted some of the benefits of car pooling but was limited to static routes with two riders per vehicle (optimally) or three (with heuristics). We present a more general mathematical model for real-time high-capacity ride-sharing that (i) scales to large numbers of passengers and trips and (ii) dynamically generates optimal routes with respect to online demand and vehicle locations. The algorithm starts from a greedy assignment and improves it through a constrained optimization, quickly returning solutions of good quality and converging to the optimal assignment over time. We quantify experimentally the tradeoff between fleet size, capacity, waiting time, travel delay, and operational costs for low- to medium-capacity vehicles, such as taxis and van shuttles. The algorithm is validated with ∼3 million rides extracted from the New York City taxicab public dataset. Our experimental study considers ride-sharing with rider capacity of up to 10 simultaneous passengers per vehicle. The algorithm applies to fleets of autonomous vehicles and also incorporates rebalancing of idling vehicles to areas of high demand. This framework is general and can be used for many real-time multivehicle, multitask assignment problems.

There are plenty of criticisms of this type of study. The major one is that if you make a particular transportation option faster and/or cheaper, economics dictates that people will automatically switch to it from other options over time, eventually making it less fast and/or less cheap until the various modes are balanced again. The study above (based on my quick skim of the abstract) probably took data from one or a few Manhattan rush hours and asked how it could be rerouted in the most efficient possible way. I don’t fault them for doing the study, which is really interesting. The economics and human behavioral feedback loops that happen over longer periods of time just need to be studied too before policy decisions are made based on results like these.

I don’t necessarily want UberPool to be the answer to all our infrastructure problems. I love the idea of subway and above-ground rail and bus rapid transit as much as the next person. But as the opening of the most recent segment of New York subway recently showed us, these projects are taking decades to build in the U.S. and costing enormous amounts of money. Europe and Asia are doing much better than us, so maybe we could learn some lessons from them, but our recent political challenges shed some doubt on the idea that we can improve any time soon. (Europe generally manages to do somewhat better with high-wage union labor, while some Asian countries build extremely cost-effectively by issuing temporary work visas to low-wage labor from developing countries. There are political and moral issues on both ends of this spectrum, obviously, but the point is the U.S. doesn’t do either approach well. Much like our health care system, we spend 2 or 3 or 5 times more than everyone else and get worse results.)

If the criticism of the study I mentioned above is that demand projections made before the new infrastructure options or technologies are in place are not going to be accurate, that criticism certainly applies to a subway system that takes decades to build. The entire population, land use, and employment pattern of the area served could change in that time, not to mention that whatever technology is chosen is almost guaranteed to be obsolete the day operation begins. With the ride-sharing algorithms, even if the projections are wrong at first at least you have a system that should be easy to adapt and tweak over time. I don’t see why public bus systems and bus rapid transit can’t be integrated into a system like this. And if people want a vehicle to themselves for some trips sometimes, the algorithms and pricing schemes should be able to accommodate that. You could even imagine an algorithm managing passenger vehicles, freight and delivery vehicles in urban areas so they are less in conflict with other at various times of day and night. The algorithms could be run by government or non-profit entities if we are really afraid of private control, or private algorithms and entities could be forced to communicate and coordinate with one another.

supersonic jets coming back soon

Virgin has a prototype commercial supersonic jet that it plans to test soon. One thing on my bucket list has always been to take a trans-Atlantic cruise to Europe and then a supersonic jet back.

The manufacturing team for Branson’s Virgin Galactic company is working with Boom Supersonic to test a prototype next year of a passenger plane that can fly at Mach 2.2, more than twice the speed of a typical commercial jet…

Instead of spending seven hours and paying up to $5,500 for a flight from New York to London on a Boeing 747, travelers can spend about $2,500 for a three-hour flight to cross the Atlantic on a supersonic jet, according to Boom.

election hacking

Looking for the declassified report on Russian election hacking. Look no further. Here are a couple juicy phrases from the whopping 25 page report:

We assess Russian President Vladimir Putin ordered an influence campaign in 2016 aimed at the US presidential election. Russia’s goals were to undermine public faith in the US democratic process, denigrate Secretary Clinton, and harm her electability and potential presidency. We further assess Putin and the Russian Government developed a clear preference for President-elect Trump. We have high confidence in these judgments.

We also assess Putin and the Russian Government aspired to help President-elect Trump’s election chances when possible by discrediting Secretary Clinton and publicly contrasting her unfavorably to him. All three agencies agree with this judgment. CIA and FBI have high confidence in this judgment; NSA has moderate confidence…

Russian intelligence obtained and maintained access to elements of multiple US state or local electoral boards. DHS assesses that the types of systems Russian actors targeted or compromised were not involved in vote tallying.

I agree with Trump on virtually nothing, but I agree with him on one thing. These are the same people who brought us weapons of mass destruction. Which will always undermine their credibility in my eyes, along with the President, the State Department, Congress and the New York Times. I was a naive, trusting, patriotic young adult when I figured out that I had been lied to by basically all the branches of government and the media I trusted to keep an eye on them. And that was long before I read Legacy of Ashes and realized just how pathetic the CIA is and just how good the KGB is and always has been. And of course, that is who we are dealing with here.

Meddling in another sovereign country’s elections is one the worst things a country could do, right? Certainly the greatest democracy in the world, let alone the greatest democracy in the history of the world, would never do that, right? Well, the CIA isn’t good at spying, which is why the U.S. lost the Korean War, the Vietnam War, the Afghanistan War, and the Iraq War. They never really understood the motivations of the Soviet Union because they had no real intelligence on it whatsoever, whereas the KGB infiltrated the U.S. government at the highest levels all along. But the CIA was always actually pretty good at influencing elections and they have done it often, sometimes with and sometimes without the knowledge of the President and Congress.

Here’s an article about the U.S. and Russia meddling in elections around the world. So I don’t like the fact that the Russians meddled in our election, and I hate the outcome of the election, but there is some element of hypocrisy in our government expressing such moral outrage about it.

Partisan electoral interventions by the great powers: Introducing the PEIG Dataset

Six decades of rigorous scholarship have greatly increased our knowledge about the causes and effects of various military and non-military forms of foreign interventions.

One blind spot in the international relations (IR) literature on interventions has been interventions designed to affect election results in foreign countries; i.e. as most famously occurred in Italy’s 1948 parliamentary election and more recently in the 2009 Afghan presidential elections. Despite a few, very recent exceptions (Corstange and Marinov, 2012; Levin, 2016; Shulman and Bloom, 2012), such interventions have not been studied by quantitative IR scholars who have preferred to focus on more violent or usually more overt types of interventions.2

However by not studying partisan electoral interventions, quantitative IR scholars miss an important, common form of intervention. Between 1946 and 2000, the US and the Soviet Union/Russia have intervened in about one of every nine competitive national-level executive elections. Partisan electoral interventions have been found to have had significant effects on election results, frequently determining the identity of the winner (Levin, 2016). Overt interventions of this kind have also been found to have significant effects on the views of the target public toward the intervener (Corstange and Marinov, 2012). Some qualitative scholars who have studied particular cases of electoral interventions at times credit, or blame, them with playing an important role in the subsequent nature of the regime in the target country and influencing the direction of its domestic and foreign policies (Rabe, 2006: chap. 5; Trachtenberg, 1999: 128–132). With the growing realization among IR scholars of the importance of regime type (Huth and Allee, 2002; Park, 2013 Ray, 1995; Reiter and Stam, 1998; Russett, 1993) and, more recently, the nature of the leader in power (Chiozza and Choi, 2003; Colgan, 2013; Horowitz, 2014; Keller and Foster, 2010; Potter, 2007) for their countries’ foreign and domestic policies, electoral interventions are a factor that cannot be ignored.

EIA Annual Energy Outlook 2017

The U.S. Energy Information Administration has released its annual energy outlook 2017. In their economic modeling exercises, some of the interesting things that happen are that oil demand stays relatively flat, natural gas demand continues to grow, coal continues to fall, and renewables continue to grow through 2040 although they don’t reach a higher share of the total supply than natural gas or oil. Carbon emissions fall or stay relatively flat in most scenarios, which is interesting but remember that flat emissions that are still too high will cause atmospheric greenhouse gases to continue growing at a steady rate. Some of the most interesting graphs are emissions intensity per dollar of economic output and emissions per unit of energy used, which both fall over time but again this does not guarantee that the atmosphere is healing itself, only becoming sicker at a slower rate.

Thomas More’s utopia

Here’s an interesting article on Thomas More’s utopia from the 1500s. He envisioned a series of economically specialized medium-scale cities (a couple hundred thousand people, keeping in mind a million-person city was enormous at the time and there were only a few in the world) separated by farm and natural lands and connected by transportation links.

2016 in Review

Each month this year, I picked three scary, three hopeful, and three interesting posts or groups of post from the month. Now I’m going to pick one of those three to represent each of the months. The choices are fairly arbitrary and the main point is just to review what the media was saying and what I was thinking about over the course of the year. Then I’ll see if I can identify any trends or come up with any insights.

Most Frightening Stories of the Year

  • JANUARY: Paul Ehrlich is still worried about population. 82% of scientists agree.
  • FEBRUARY: 77% of jobs in China may be threatened by automation.
  • MARCH: An IMF official uttered the words “economic derailment“. That sounds like it could be a real train wreck. Meanwhile Robert Gordon has expanded his pessimistic article on future growth into a book.
  • APRIL: Robert Paxton says Trump is pretty much a fascist. Although conditions are different and he doesn’t believe everything the fascists believed. Umberto Eco once said that fascists don’t believe anything, they will say anything and then what they do once in office has nothing to do with what they said.
  • MAY: The situation in Venezuela may be a preview of what the collapse of a modern country looks like.
  • JUNE: Trump may very well have organized crime links. And Moody’s says that if he gets elected and manages to do the things he says, it could crash the economy.
  • JULY: The CIA is just not that good at spying.
  • AUGUST: A former U.S. secretary of defense thinks the risk of nuclear war is higher now than during the cold war. The Republic Party platform appears to be outright in favor of nuclear weapons, while the Democratic Party platform includes a tepid commitment to maybe “reducing reliance” and spending on nuclear weapons. Jeffrey Sachs says the Syria War has become essentially a U.S.-Russia proxy war.
  • SEPTEMBER: The ecological footprint situation is not looking too promising: “from 1993 to 2009…while the human population has increased by 23% and the world economy has grown 153%, the human footprint has increased by just 9%. Still, 75% the planet’s land surface is experiencing measurable human pressures. Moreover, pressures are perversely intense, widespread and rapidly intensifying in places with high biodiversity.” Meanwhile, as of 2002 “we appropriate over 40% of the net primary productivity (the green material) produced on Earth each year (Vitousek et al. 1986, Rojstaczer et al. 2001). We consume 35% of the productivity of the oceanic shelf (Pauly and Christensen 1995), and we use 60% of freshwater run-off (Postel et al. 1996). The unprecedented escalation in both human population and consumption in the 20th century has resulted in environmental crises never before encountered in the history of humankind and the world (McNeill 2000). E. O. Wilson (2002) claims it would now take four Earths to meet the consumption demands of the current human population, if every human consumed at the level of the average US inhabitant.” And finally, 30% of African elephants have been lost in the last 7 years.
  • OCTOBER: According to James Hansen, the world needs “negative” greenhouse gas emissions right away, meaning an end to fossil fuel burning and improvements to agriculture, forestry, and soil conservation practices to absorb carbon. Part of the current problem is unexpected and unexplained increases in methane concentrations in the atmosphere.
  • NOVEMBER: Is there really any doubt what the most frightening story of November 2016 was? The United Nations Environment Program says we are on a track for 3 degrees C over pre-industrial temperatures, not the “less than 2” almost all serious people (a category that excludes 46% of U.S. voters, apparently) agree is needed. This story was released before the U.S. elected an immoral science denier as its leader. One theory is that our culture has lost all ability to separate fact from fiction. Perhaps states could take on more of a leadership role if the federal government is going to be immoral? Washington State voters considered a carbon tax that could have been a model for other states, and voted it down, in part because environmental groups didn’t like that it was revenue neutral. Adding insult to injury, WWF released its 2016 Living Planet Report, which along with more fun climate change info includes fun facts like 58% of all wild animals have disappeared. There is a 70-99% chance of a U.S. Southwest “mega-drought” lasting 35 years or longer this century. But don’t worry, this is only “if emissions of greenhouse gases remain unchecked”. Oh, and climate change is going to begin to strain the food supply worldwide, which is already strained by population, demand growth, and water resources depletion even without it.
  • DECEMBER: The geopolitical situation is not good. If Russia did hack the U.S. election, it wouldn’t be the first election they have hacked. The wars in Afghanistan and Iraq are not over, and the rest of the greater Middle East is increasingly a mess.

Most Hopeful Stories of the Year

Most Interesting Stories of the Year

  • JANUARY: The World Economic Forum focused on technology: “The possibilities of billions of people connected by mobile devices, with unprecedented processing power, storage capacity, and access to knowledge, are unlimited. And these possibilities will be multiplied by emerging technology breakthroughs in fields such as artificial intelligence, robotics, the Internet of Things, autonomous vehicles, 3-D printing, nanotechnology, biotechnology, materials science, energy storage, and quantum computing.”
  • FEBRUARY: Titanium dioxide is the reason Oreo filling is so white.
  • MARCH: Michael Pollan urged us to eat food. not too much. mostly psychedelic mushrooms.
  • APRIL: Genes can now be programmed just like circuits.
  • MAY: The world has about a billion dogs.
  • JUNE: Switzerland finished an enormous tunnel through the Alps that took 20 years to build.
  • JULY: I was a little side-tracked by U.S. Presidential politics. Nate Silver launched his general election site, putting the odds about 80-20 in favor of Hillary at the beginning of the month. The odds swung toward Trump over the course of the month as the two major party conventions took place (one in my backyard), but by the end of the month they were back to about 70-30 in favor of Hillary. During the month I mused about NAFTA, the fall of the Republic, the banana republic, The Art of the Deal, how to debate Trump, and Jon Stewart.
  • AUGUST: Here is a short video explaining the Fermi Paradox, which asks why there are no aliens. Meanwhile Russian astronomers are saying there might be aliens.
  • SEPTEMBER: Monsanto is trying to help honeybees (which seems good) by monkeying with RNA (which seems a little frightening). Yes, biotech is coming.
  • OCTOBER: Neil deGrasse Tyson says “we might expect to find as many as 100 alien civilizations in our galaxy communicating with radio waves right now.”
  • NOVEMBER: New technology can survey and create a 3D model of a room in seconds.
  • DECEMBER: According to Bill Gates, “new genome technologies are at the cusp of affecting us all in profound ways”. But an article in Nature says we should not be too hopeful about living much past 100.

And now for trends and insights…

Serious long-term threats related to population, food, water resources, natural capital depletion, biodiversity loss, and climate change. These are all inter-related. In past years I probably would have suggested that these threats are so likely and so consequential that we should focus nearly all our efforts on them. But things have changed a bit over the past year. Now it appears that we face dire short term threats as well in the form of serious geopolitical instability, risk of war and global economic stagnation. If you don’t deal with short term threats you might not be around to deal with the long term ones. And voters have chosen leaders in the past year who have no intention of dealing with the long term threats. They make no serious attempt to understand their nature or root causes. In fact, they don’t even acknowledge that the threats exist in many cases.

War. The possibility of war is certainly the biggest short-term threat we face. If we get through the next 4-8 years without a war between major powers or any sort of nuclear detonation, we will have to consider that a win. The greater Middle East from North Africa to Afghanistan is dangerously unstable, and the U.S. has already been drawn into a proxy war with Saudi Arabia and its allies on one side and Iran and Russia on the other side. And it appears that Russia may have played a direct role in influencing the U.S. election. An accidental clash between U.S. and Russian forces in Syria, Eastern Europe, or over the world’s oceans could be enough to set off a series of escalations and miscalculations that leads to a war nobody wants or stands to gain anything from. A naval confrontation between the U.S. and China could be a similar risk.

The Great Recession. Although the U.S. economy has picked up, the overall global growth and employment situation is deeply concerning. Rather than just a cyclical downturn, it may be a long term trend driven by demographics, debt, and underemployment caused by automation. The automation trend is going to be relentless. The 2007-8 financial crisis caused by excessive risk taking in the U.S. finance industry may just have been the straw that broke the camel’s back and made the long-term trends obvious, and another financial crisis that severe at a time of weakness might be the one the world doesn’t recover from. Our new U.S. leaders are already working with big business to roll back the necessary but still inadequate protections put in place after the ’07-8 crisis. Costs and risks imposed by climate change are not going to make the economy any better.

Technology. Technology brings us grave concern over the employment situation, but also great hope that we could see a long-term pickup in productivity, and therefore our overall wealth and quality of life. Of course, an increase in overall wealth and quality of life may help only a small slice of society if that society is structured to concentrate rather than share the wealth, and the leaders we have chosen in the U.S. for the next few years are clearly committed to the former. Extreme concentration of wealth could lead us eventually to a situation of such instability that the only outcomes are armed revolution in the streets or else absolute authoritarian control.

But let’s optimistically assume that our political system eventually comes up with a consensus on sharing the wealth. Now a higher rate of productivity growth (within ecological limits) would be good for everyone. In this world, people whose jobs are displaced by automation would be quickly retrained for new jobs, and they would be educated in the first place so that they are very flexible and adaptable to changing conditions. Over time, we could become so rich that we simply don’t have to work so much, and we could devote more of our time to leisure activities, learning for the sake of learning, the arts, civic and social activities, etc.

This might seem like a utopian vision, but it has happened in the past. People used to work incredibly long, hard hours to grow just enough food to survive, and they didn’t live all that long at that. Later people used to work long, hard hours in factories and sweat shops. Technology, cheap energy, and the wealth they have brought have made huge changes in working hours and life expectancy for most of us. With technology seemingly advancing all around us, the puzzle is why we aren’t seeing similarly spectacular advances today as we have seen in the past.

Advances like the tractor and electricity were enormous changes at the time of course. Maybe today’s technological advances, even though they seem impressive to us, simply aren’t as dramatic as these advances were in their time. That is the basic thesis of Robert Gordon, who I mention above. The World Economic Forum and Nouriel Roubini articles I mention above have good summaries of the advances we are seeing. Roubini categorizes them as:

  • ET (energy technologies, including new forms of fossil fuels such as shale gas and oil and alternative energy sources such as solar and wind, storage technologies, clean tech, and smart electric grids).
  • BT (biotechnologies, including genetic therapy, stem cell research, and the use of big data to reduce health-care costs radically and allow individuals to live much longer and healthier lives).
  • IT (information technologies, such as Web 2.0/3.0, social media, new apps, the Internet of Things, big data, cloud computing, artificial intelligence, and virtual reality devices).
  • MT (manufacturing technologies, such as robotics, automation, 3D printing, and personalized manufacturing).
  • FT (financial technologies that promise to revolutionize everything from payment systems to lending, insurance services and asset allocation).
  • DT (defense technologies, including the development of drones and other advanced weapon systems).

Roubini acknowledges the argument that these advances are not the equivalent of past advances, but also suggests that we may be in the lag phase between when technological advances happen and when they begin to have obvious effects on productivity. I think I said it pretty well in my post so I’ll repeat what I said:

Although the plow, the printing press, the steam engine, electricity, etc. were game changing, the game didn’t change as soon as they were invented. They had to catch on, infrastructure had to be built, resistance to change had to be overcome, and it took awhile. Each successive revolution happened faster though, which is why I am skeptical that this time is different… I think there is a lag, and it just hasn’t hit yet. If and when there is a sharp technology-driven surge in productivity, it doesn’t mean everything is going to instantly be great for everybody. As we produce more with less effort, there will be winners and losers, haves and have nots. And there will be a lag between when that starts and when it gets resolved. And just to beat a dead horse, we can’t just keep producing and consuming more forever unless we figure out a way to do that without growing our ecological footprint. And, we need to watch out for those defense technologies.

The information technology is all around us now, and the biotechnology is just starting to take off. 2017 could be the year when we have the same excitement in the popular imagination about biotech as we saw with the internet in the mid-1990s. Or maybe it will take a few years.

It is possible that our technology could advance so fast that ecological limits will cease to be relevant before they begin to exert a major drag force on our global economy and society. I don’t think it is safe to put all our eggs in that basket though. I am also saddened by the extreme and seemingly accelerating destruction of our planet’s ecosystems as we have known them throughout human history. We can try to preserve some of what is left, but even if we are successful it will be more like a museum or zoo recording what we used to have than a real, large-scale functioning planetary ecosystem.

There, I ended on a pretty pessimistic note. That’s how I feel at the moment. Not all stories have to have a happy ending. (This is exactly why King Lear is my favorite Shakespeare play, because the bad guys do bad things and get away with it, and sometimes real life is like that.) I just don’t want to get my hopes up about 2017. Come on 2017, maybe you will pleasantly surprise me.

Dodd-Frank

After the risk of war, and the existential but somewhat abstract long-term catastrophe of climate change, the scariest risk we might face in the next 4-8 years is a roll-back of the limited protections put in place against a repeat of the 2008 financial crisis, or something worse. Trump is appointing people who are likely to make that happen. If the world is not in Great Depression 2.0 already, this could usher it in. I think it is entirely possible the world has entered a long-term economic downward spiral masked by the usual noise of ups and downs. This is from the blog Baseline Scenario:

The Wall Street Journal has a profile up on Mike Crapo and Jeb Hensarling, the key committee chairs (likely in Crapo’s case) who will repeal or rewrite the Dodd-Frank Wall Street Reform and Consumer Protection Act. It’s clear that both are planning to roll back or dilute many of the provisions of Dodd-Frank, particularly those that protect consumers from toxic financial products and those that impose restrictions on banks (which, together, make up most of the act)…

Introductory economics, and particularly the competitive market model, can be seductive that way. The models are so simple, logical, and compelling that they seem to unlock a whole new way of seeing the world. And, arguably, they do: there are real insights you can gain from a working understanding of supply and demand curves.

The problem, however, is that the people who are most captivated by the first theorem of welfare economics (the one that says that competitive markets produce optimal outcomes) are often the least good at remembering the assumptions that don’t apply and the caveats that do apply in the real world. They forget that the power of a theory in the abstract bears no relationship to its accuracy in practice.