Our Automotive Dystopia and the Hope of the Self-Driving Car

About eighty years ago a classic science fiction short story painted a dystopian picture of a nightmare world where cars made possible vastly bigger cities, after which, as the ratio of cars-to-humans approached one-to-two those cities "choked" on those cars, with "[s]eventy million steel juggernauts, operated by imperfect human beings at high speed" proving "more destructive than war" of property and human life, obscene insurance premiums, and of course, the squandering of a finite oil supply.

The solution the story envisioned was a colossal solar-powered public transport system launched as a public works program.

I can imagine that a good many readers are sneering at this story as some "socialist," "hippie" vision. But it was actually the furthest thing from that. The story is "The Roads Must Roll," by Robert Heinlein, published in the science fiction magazine Astounding when John Campbell was running the show--and in its depiction of a power grab by "Functionalists" a (very) thinly veiled right-wing attack on organized labor and Marxism.

The result is that its looking like a leftie vision is a matter of how times have changed, with our attitudes toward cars, oil, solar energy and public works sucked into the "culture wars" rather than treated as objects of rational appraisal--and it has to be acknowledged also, our having come to take what the story presented as a dystopia utterly for granted--so much so that it seems worth discussing the costs of that "way of life." Back in 2010 a study found that car crashes cost the U.S. economy some $1 trillion a year. (Putting it another way, if the cost of those crashes were a whole national economy by itself it would likely be in the top twenty globally--and one could guess that the figure has only gone up in the past decade.) That same year the country saw nearly 4 million injured in such accidents, 33,000 fatally. (More destructive than war, indeed!) Lest it need saying, all this has given us a $300 billion a year car insurance industry whose premiums weigh heavily on the budgets of the motorists that very few can escape becoming, while the problem cars pose from a natural resources standpoint should need no elaboration these days.

Yet anyone who questions that this is the best of all possible worlds is apt to get a hostile reaction, even when no one mentions anything anywhere near so radical as solar-powered moving roadways--as we see in the wildly exaggerated sneering at the prospect of self-driving cars, or the turn to Transportation-as-a-Service that this might make possible, or even the electrification of the automotive fleet (with, par for the course, the media generally treating the weakest arguments on these scores with great respect and their opponents with none). However, I for one am prepared to declare that a world where we move beyond tens--hundreds--of millions of gas-powered steel juggernauts driven at high speed by imperfect humans as our default way of getting about is likely to be a better one. Indeed, I look forward to a day when people look back at our era and shudder at the insanity of a society that actually relied on the alertness, reflexes and judgment of human beings who were so often sick, tired, distracted, irascible, angry or worse to control such juggernauts crowded together on superhighways as a default mode of transport.

Revisiting George Friedman's The Next Decade

After publishing his geopolitical forecast for the twenty-first century in The Next 100 Years (2009) George Friedman endeavored to provide a more detailed, explanatory and prescriptive discussion of his expectations for the next years, The Next Decade (2011).

This being 2022 we can look back and consider how he did. My thought is that while he made some good points in the book he did not do very well, particularly where his larger and more radical predictions were concerned. Consider the following:

* Friedman predicted that in the wake of the Great Recession the balance of power in economic life would shift back from the private sector to the public, with coming years looking something more like the post-war period. Of course, no such thing happened. The neoliberal model may stand in lower credit with the general public than ever, but it remains the conventional wisdom of business, government, academia, the media--and the few compromises required by policymakers hewing to the line have been slight indeed. (Britain, for example, may have left the EU--but the neoliberal standards of privatization, deregulation, profligacy with corporate welfare and stinginess with the general public, remain the order of the day, as does the foundation of economies on globalization and financialization.)

* Friedman envisioned the U.S. facing a rapprochement between Russia and Germany producing a Paris-Berlin-Moscow axis. Of course, the reality has been quite different.

* Friedman, who has never let go of his once headline-grabbing and since much derided vision of the U.S. and Japan as geopolitical rivals (The Coming War With Japan), or hewing to a pessimistic appraisal of China's prospects, once again predicted China's proving an also-ran in the 2010s, and the U.S. becoming more concerned with checking Japan's power instead. Again, this is not exactly how things have gone.

As readers of this blog know I think it simple-minded to sneer at prediction, and even forecasting, as so many do (with outrageous smugness). After all, as Nicholas Rescher made clear, we have no choice but to constantly make choices based on expectations of future conditions and the future outcomes of our choices, and most of the time we are correct. (For example, when we go to work in the morning we expect that our workplace will be there and be operative, and we are usually right about that.) In fact we take our capacity for correct prediction so much for granted that we are only aware of making predictions when we face the relatively small number of matters where prediction proves trickier. Still, the difficulty does not in itself give us an "out," and we still find ourselves forced to choose, with our only choice making as accurate a prediction as we can, not least by learning from our past mistakes in such situations. And for me that, and not the denigration of prediction, is the reason to revisit Friedman's work and consider where he went wrong--which, it seems to me, was in his simply reasoning from the wrong premises and indulging biases that had proved unhelpful in the past (his superficial grasp of political economy, his attitude toward Germany and China, for example, his endless attempts to rehabilitate his prediction about Japan). Alas, incorrect premises and problematic biases are not at all rare in the business--and unfortunately the media has been more inclined to simple-mindedly make such "experts" into authorities rather than appraise what they have to offer.

Carbon Nanotube-Based Microchips: A (Very Short) Primer

As Moore's Law runs its course those looking forward to continued improvements in computing power necessarily turn their attention in other directions--not least, a turn away from silicon to other materials as the material from which we make our integrated circuits. For decades one of the more promising possibilities has been the use of carbon nanotubes.

Carbon nanotubes are one of many materials formed from an arrangement of carbon atoms in hexagonal (six-sided) structures, themselves arranged in a lattice, with every one of the six atoms connected to and forming part of the adjacent structures of the same type. Left as a flat sheet, the resulting material is called graphene. With a nanotube what happens is that the "sheet" is bent, and its opposite, horizontal ends joined, to form a hollow cylinder.

These nanotubes' ultrathin bodies and smooth walls enable charges to flow through them more rapidly, and at a lower supply voltage, than is the case with silicon, making them potentially faster and more energy-efficient. Their smoother, more energy-efficient structures may also make them a more suitable material than silicon for denser "3-D" chip designs--which would not just put more transistors on a single 2-D surface the way conventional chips do, but layer those 2-D surfaces on top of one another to cram more computing power into a given space. And altogether the combination of attributes has led to speculation about their permitting a thousandfold gain in computing speed over silicon, equivalent to about ten more doublings and an additional couple of decades of Moore's Law-like progress, which as a practical matter that would convert today's personal computers into machines comparable to today's supercomputers.

Of course, in considering all this one has to note that there has been a long record of great expectations and great disappointments in regard to the mass-production of carbon nanotubes, not least because of the old "works well enough in the lab but not ready for real life" problem of consistently getting the required quality at a competitive price when producing at the relevant scale. (Back in 2014 IBM said they would have them in 2020. Well, 2020 has come and gone, with the arrival of the technology, like that of so many others, deferred indefinitely into the future.) Still, it is one thing to acknowledge that the technology has been slower to emerge than hoped, another to write it off--and it may well be that the belated arrival of carbon nanotube-based chips, and the boost they deliver to the continued progress of computing power, will be what opens the way to the next great round of advance in the development of an artificial intelligence sector that it may turn out has been held back from realizing its promises only by the limits of the hardware.

Understanding Moore's Law

Those of us attentive to computing are generally familiar with the existence of something called "Moore's Law." However, really satisfying explanation of what Moore's Law actually is would seem a rarer thing--with one result a great deal of confusion about what it means.

Simply put, Moore's Law has to do with "integrated circuits," or, in more everyday usage, microchips--small wafers ("chips") of semiconducting material, usually silicon, containing an electronic circuit. Within these chips transistors amplify, regulate and switch the electric signals passing through them, enabling them to store and move electronic data. Placing more transistors inside a chip means that more such activity can go on inside it at once, which gives the chip, and the device incorporating it, enabling more "parallelism"--the ability to do more at once, and therefore to work faster. All other things being equal one can only put more transistors on the same-sized chip if the transistors are themselves smaller--which means that the electrons passing through them travel shorter distances, which increases the speed at which the system executes its operations yet again.

Since their invention in the late 1950s microchip manufacturers have steadily increased the number of transistors in their chips, by shrinking transistor size--a process that also caused the cost of each transistor to fall. In 1965 electronics engineer Gordon Moore published a short paper titled "Cramming More Components Into Integrated Circuits" in which he noted that the "density at minimum cost per transistor" doubled every year. He extrapolated from that trend that in the next five years they would have chips with twenty times as many transistors on them, each costing just a tenth of their 1965 price, and that this pattern would continue for "at least ten years."

Moore's prediction (which, it is worth recalling, he never called a "law") was inexactly borne out during those years. He proved somewhat overoptimistic, transistor density not quite doubling annually, and today, in fact, different versions of this "law" get quoted with varying claims about doubling times. (Some say one year, some say eighteen months, some say two years, while claims about the implications for processing power and price also vary.) However, the swift doubling in the number of transistors per chip, and the fall in the price of computing power that went with it, continued for a lot longer than the ten years he suggested, instead going on for a half century past that point. The result is that where an efficiently made chip had fifty transistors on it in 1965, they now contain billions of transistors—all as the low price of these densely transistorized chips means that hundreds of billions of them are manufactured annually, permitting them to be stuffed into just about everything we use.

Nonetheless, Moore's Law has certain in-built limitations. The most significant of these is the physical limit to transistor miniaturization. One cannot make a silicon transistor smaller than a single nanometer (a billionth of a meter, equivalent to the width of a single atom) after all, while even before one gets to that point shrinking size makes transistors so small that the electrons whose movements they are supposed to control actually pass (or "tunnel") through their walls.

Of course, when Moore presented his "Law" the prospects of single atom-wide transistors, or even tunneling, seemed remote in the extreme. Transistors in 1971 were drawn on a ten micrometer (millionth of a meter) scale—ten thousand nanometers in the terms more commonly discussed today. However, by 2017 the transistors in commercially made chips were just a thousandth their earlier size, a mere ten nanometers across. The following year major chipmakers began the mass-production of mere seven nanometer transistors got underway, leaving very little space for further size reductions.

This has led a good many observers to declare that "Moore's Law is dead," or will be before too much longer. The claim is controversial--perhaps more than it ought to be. After all, no one disputes that chip speeds cannot continue to increase on the basis of reducing the size of the transistors on silicon wafers--and that is exactly what Moore's Law was concerned with, not the possibility or impossibility of continued progress in computing power. The result is that those who are convinced that the tendency to the exponential increase of computing power is virtually bound to continue as before might do better to set aside claims for Moore's Law continuing, and instead speak of Ray Kurzweil's "Law of Accelerating Returns."

How Powerful Would a Genuinely Thinking Computer Have to Be?

Discussing the prospect of a computer matching or exceeding human intelligence we find ourselves forced to consider just how it is that we measure human intelligence. That in itself is an old and difficult problem, reflecting the reality that there remains considerable disagreement about just what precisely human intelligence even is. However, one approach that has been suggested is to consider the human brain as a piece of computer hardware, and attempt to measure its apparent capacity by the yardsticks we commonly apply to computers. Based on that we then identify the minimum hardware performance a computer would have to have in order to display human-like performance.

How do we go about this as a practical matter? By and large it has been standard to measure computing power in terms of the number of calculations a computer can perform per second. Of course, there are a variety of kinds of calculation, but in recent years it has been common to think specifically in terms of "floating-point operations," in contrast with simpler "fixed point" operations. (Adding 1.0 to 2.0 to get 3.0 is a fixed point operation--the decimal in the same place in all three numbers. However, the addition of 1.2570 to 25.4620 to get 26.719 is a floating point operation, in that the decimal point appeared in a different place in each of the two numbers.) Indeed, anyone delving very deeply into the literature on high-end computers quickly encounters the acronym "FLOPS" (short for FLOating-point operations Per Second) and derivatives thereof, such as "teraflop" (a trillion flops per second), a "petaflop" (a quadrillion flops--a thousand trillion flops)" and "exaflop" (a quintillion flops--a thousand petaflops, or a million teraflops).

With computers' performance measured in terms of floating-point operations per second, those speculating about artificial intelligence attempt to equate the human brain's performance with a given number of flops. Among others, Ray Kurzweil published an estimate in his 1999 book The Age of Spiritual Machines, since revised in his 2005 The Singularity is Near. The principle he followed was his taking part of the nervous system, estimating its performance in FLOPS, and then extrapolating from that to the human brain. Working from the estimate that individual synapses are in performance equivalent to a two hundred flop computer, and the human brain contained some hundred trillion synapses, he conservatively estimated a figure of some twenty quadrillion (thousand trillion) floating-point operations per second--twenty petaflops--then suggested that the brain may actually run at about half that speed, ten petaflops sufficing.

In considering this one should note that other analysts have used quite different approaches, from which they produced vastly higher estimates of the brain's performance. This is especially the case when they assume the brain does not produce consciousness at the level of nerves, but rather at the level of quantum phenomena inside the nerves. (Jack Tuszynski and his colleagues suggested that not tens of quadrillions, but tens of trillions of quadrillions, would be required.) Of course such "quantum mind" theories (the best known exponent of whom is probably The Emperor's New Mind author Roger Penrose) are extremely controversial--as yet remaining broadly philosophical rather than scientific in the sense, with as yet no empirical evidence in their favor, and indeed, critics regarding such notions as mystical in a way all too common when people delve into quantum mechanics. Still, the idea that Kurzweil's estimate of just how much computing power a human brain possesses may be too low a couple of orders of magnitude is fairly widespread, popular science articles commonly citing the figure as an exaflop (a thousand petaflops).

Still, it can be said that the most powerful supercomputers have repeatedly attained and increasingly surpassed the level suggested by Kurzweil over the past decade. The Fujitsu "K" supercomputer achieved ten "petaflops" (ten quadrillion "floating-point calculations") per second back in November 2011. It also had a 1.4 petabyte memory, about ten times Kurzweil's estimate of the human brain's memory. Moreover, the Fujitsu K has been exceeded in its turn--by dozens of other supercomputers according to the latest (November 2021) edition of the TOP500 list of the world's fastest systems, in cases by orders of magnitude. At the time of this writing the fastest appears to be yet another Fujitsu machine, the Fujitsu Fukagu, with a performance of 442 petaflops per second--some forty times Kurzweil's estimate of human brain performance. And of course, present computer scientists have set their sights higher than that. Among them is a joint effort by the Department of Energy, Intel and Cray to build the Aurora, which is intended to be an exaflop-level machine--as a matter of course, running a hundred times as many calculations per second as Kurzweil's estimate of the human brain's performance--while even that seems modest next to a report this very day that the I4DI consortium is shooting for a 64 exaflop machine by the end of this very year (equivalent to sixty times those higher estimates of the brain's performance, and six thousand times Kurzweil's estimate).

Reading this one may wonder why Kurzweil's hypothesis about such a computer matching or exceeding the brain's capacity has not already been tested with results pointing one way or the other. The reality is that in practice supercomputers like these, which are as few as they are because they are so hugely expensive to build (the Fukagu's a billion dollar machine) and to run (their voracious energy consumption a constant theme of discussion of such equipment), are normally used by only the biggest-budgeted researchers for the most computationally intense tasks, like simulations of complex physical phenomena, such as the Earth's climate or the cosmos--or code-breaking by intelligence services. They have only rarely been available to artificial intelligence researchers. However, the recent enthusiasm for artificial intelligence research has reportedly meant that artificial intelligence researchers has been cited as a factor in the development of the next round of supercomputers (not least because of the utility of AI in facilitating their work).

Especially with this being the case it seems far from impossible that this will enable it to yield new insights into the subject--just as this past decade it was already the case that our having faster computers available permitted the striking advances in areas like machine learning that we saw this past decade. Indeed, even as the recent excitement over artificial intelligence turns into disappointment with the realization that the most-hyped applications (like Level 5 self-driving) are more remote than certain loud-mouthed hucksters promised, the continued expansion of computing power offers considerable grounds to not write those prospects off just yet.

What The Magnificent Ambersons Can Teach Us About Technological Change

I remember reading Booth Tarkington's The Magnificent Ambersons years ago and finding it a rather slight, tepid tale--so much so that I found it hard to understand why Orson Welles, after giving us his ferocious epic Citizen Kane, picked it for a follow-up (and suspected that it was because slight and tepid was what he wanted after the sheer hell he went through making his first movie).

Still, some bits of the novel have stuck in my mind, not least those which had to do with the emergence of the automobile. As men like Eugene Morgan toiled on the vehicles the broader public tended to look at them ironically--an attitude epitomized by the way idiot vulgarians would yell "Git a hoss!" at anybody with a car, and delighting especially in the sight of some motorist stuck repairing a malfunctioning vehicle. However, the technology progressed, and the world changed greatly, leaving the "Git a hoss!"-yelling oafs looking foolish.

Tarkington depicted the shift with some nuance, with this striking me as especially the case in the scenes regarding Aunt Fanny's investment in the headlight manufacturer. She was impressed by a demonstration of the technology, but Morgan, who at this point was growing wealthy from having got into the automotive revolution "on the ground floor" explained that while the headlight in question worked "well enough in the shop" on the road it could only stay lit if a car was going at high speed (twenty-five miles an hour minimum, fifty miles an hour for full illumination)--which meant that the light failed if the motorist drove at all more slowly, and greatly limited the practical usefulness and salability of the technology. Morgan acknowledged that work to improve it continued, but that for the time being she had best eschew putting her money into the company. However, Fanny went ahead and put her money into the company anyway, and ended up broke.

It is as striking a dramatic illustration as I can remember in a major novel of how amid a time of technological flux people go from dismissing a technology altogether to being utterly credulous as a great deal suddenly seems possible--and how at such a moment the word "startup" can seem synonymous with "gold mine." It is a striking illustration, too, of how what works "in the shop" may not be ready for the street just yet, or any time soon, or even ever--with the innovation in question perhaps likely to come out of a different shop, a different startup, than the one that initially caught the eye, because even if it came along later it ended up being the one that made the thing work, or at least cut the deals that got it to market when it became workable.

The more sophisticated technology-watchers, of course, understand this, and indeed NASA developed an excellent system for judging these matters with which I think everyone who cares about these issues should acquaint themselves. Of course, to go by what passes for "science" journalism," which consistently, overwhelmingly, shows and promotes to its audience Fanny's unsophistication rather than Morgan's astuteness, few bother to do so--or in any other way come to understand what Tarkington was able not just to explain but to dramatize in his novel a century ago.

Putting the Reports About the Thwaites Glacier Into Perspective

Last month reports that the Thwaites glacier in Antarctica is likely to collapse within a number of years (as few as three in some of the reports) made the rounds of the news, along with projections that the event could by itself raise sea levels by two feet, and lead to further collapses producing a ten foot sea level rise, inundating all the world's coastlines.

The tone in which all this was reported, of course, made "could" seem like "will," and does not disabuse anyone not reading closely of the impression that the maximum sea level rise anticipated here will happen instantaneously.

Even worse than most in this regard is the title of the piece in Rolling Stone--"'The Fuse Has Been Blown,' and the Doomsday Glacier Is Coming for Us All."

This flatly tells us not that something potentially very bad may be happening not very far from now, or even that something actually very bad is inevitably happening, but that the worst has already happened.

That is, of course, not actually the case--as the article itself makes clear if one reads it rather than just Retweeting the headline. In spite of Rolling Stone's propensity for "collapse porn" (it was through their pages that I became acquainted with the writing of James Howard Kunstler, whom Leigh Phillips has described as "hav[ing] a veritable hard-on for the end of the world, imagining with relish . . . collapse . . . retreat from modernity and an embrace of the Medieval"), Jeff Goodell's article is considerably better-informed, more factually grounded and intellectually nuanced than the great majority of the other items on the subject I have seen thus far. Goodell (who, by the way, writes that collapse may come inside a decade--rather than the five and even three year periods so many others are talking about) acknowledges that the report's findings are not the surprise much of the media seems to think it is (Goodell himself wrote a noted piece on Thwaites back in 2017), and that there are enormous uncertainties not only regarding when and even if Thwaites will crack up, but what would happen afterward. He notes that this does not completely exclude scenarios where it may not make the (already pretty terrible) picture too much worse. And even the really bad ones (ten feet of sea rise) would likely be a matter of a century.

The result is that the title is a real shame--but all too revealing of how the media has tended to report on this subject (as it does on a great many others), prioritizing shock and fear over comprehension, and getting away with it because of what passes for "reading" these days. Still, even this piece lacked something that I think we should be seeing more of, hearing more of, when discussing matters like the Thwaites glacier and climate change generally--solutions. Obviously reducing the accumulation of greenhouse gases in the atmosphere (decarbonizing our energy-transport system, planting more trees, etc.) is central and indispensable to the ultimate, bottom-line, long-term solution to the larger problem of global warming, and no one serious about the matter suggests not doing so. Yet there has also long been discussing the use of other ameliorative strategies that can help us cope with particular effects of such warming as we seem unlikely to be able to avoid, like saving glaciers through engineering efforts (and indeed, the idea of rescuing Thwaites specifically in this manner specifically is not unprecedented). There is no doubt that the schemes are ambitious, relying on unproven technologies--but it would certainly seem that given the stakes we should be hearing A LOT of calls for programs to develop and deploy anything that will help. However, the championing of such ideas is exactly what we do not see when we look at coverage of the issue.

Of course, it is the media's job to be skeptical--but it goes about that job in awfully "selective" fashion. Consider, for example, the New York Times Magazine's 2019 piece on hypersonic missiles. Hypersonic missiles, certainly, are a radical, far from proven technology--but that does not stop the NYT Magazine piece from being hawkish in the extreme about the claims of such missiles' development being a national priority for the United States. I cannot think of a single occasion when I saw an article in the Times and its associated publications, or any other media outlet of comparable standing, try so hard to sell its readers on the importance of a specific technological program that could help with our environmental problems, or show so much respect for the proponents of such a program, or so uncritically embrace their optimism about the feasibility and value of that technology, as they do in the case of those missiles. Instead they strain for any excuse to dismiss such a project, and close on a note of "Don't get your hopes up." And that says everything about the media's prejudices, not least that preference for fear-mongering and defeatism on the subject--to the very great cost of the dialogue on these matters, and our chances of actually dealing with the problem.

I Don't Want to Hear Another Word About Climate Change (Unless You're Going to Tell Us What We're Going To Do About It)

I am not and have never been a climate change denier. I do not dispute that there is an ongoing, anthropogenic and rapidly progressing process of climate change, driven mainly by emissions of GreenHouse Gases (GHGs) like carbon dioxide and methane, taking a large rising toll on the natural environment, and in human life and property (already in 2009 one report estimated 300,000 lives a year--and, given the likelihood of the figure rising rather than falling, implies deaths in the many millions to date). Indeed, I would go further than most in saying that the damage we are seeing indicates that the process has already advanced to an unacceptable degree--that the world is already too hot--and that even were we go to carbon-neutral today the GHGs already in the atmosphere will mean decades more heating, which would very likely have such second-order effects as thawing permafrost likely to intensify the heating that much further, so that even if we did far, far more than we have done to date the survival of human civilization, and perhaps even the human species itself as vast portions of the planet become literally uninhabitable, may be in doubt . . .

Of course, if one recognizes that all this is real then no reasonable person can expect the media to stop talking about it, can they?

No, of course not. But it is also undeniable that what the mainstream media has done is inflict an incessant hard rain of bad news on an already terrified public, while being relentlessly negative about any and every possible way of seriously redressing the problem. It has treated renewable energy (like solar) with disdain, and even as those technologies win victory after victory in the marketplace it still never misses a chance to badmouth them (to the delight of the pro-nuclear trolls, whose activity seems to be way, way up these days--just in case you thought that you'd heard the last of them). It sneers at any talk of a Green New Deal. It falls all over itself trying to criticize even the idea of cellular agriculture, and "Transportation-as-a-Service." It scarcely acknowledges the existence of ideas to save the world's glaciers. And of course, its hostility to geoengineering of any type has been relentless.

In short, after a long period of drawing a false equivalence between acknowledgment of climate change and climate denial it can seem to have shifted (intentionally or unintentionally) to a narrative of climate defeatism, utterly determined to beat down any hope of useful action whatsoever--which leaves us in the same place in the end as that denial to which it was so much an accessory (while, one might add, saddling the powerless with enormous guilt, because somehow not the politicians, not the CEOs, but they, are responsible for it all, especially if they ever ate a burger in their life).

In response I offer a modest proposal. Ordinarily I do not think that it is reasonable to demand that someone pointing out a problem also have a detailed solution in hand. In fact I tend to think of this as a way of suppressing the dialogue over an issue, and thus also the efforts to deal with the problem. However, as we already know how bad things are--are already literally becoming sick over the knowledge of how bad things are as the depressingly, cripplingly, overfamiliar news is pounded into our heads over and over and over again; and as it seems to me that there are a multitude of ideas that could help (and I don't mean the "hairshirt," agonize-over-your-personal-carbon footprint stuff, or even just decarbonizing our electric grid, but also ameliorative stuff like glacier preservation and kelp farming and direct air capture) that ought to be getting far more discussion, and at least some of which seems to me to be worthy of the genuine, massive backing that alone can speed its development and implementation--it is time for the coverage, any coverage we are to take seriously as anything but a promotion of climate defeatism, to start emphasizing what can be done, at length and in detail and as soon as possible, and show the greatest possible rigor in thinking through and explaining those solutions.

This is, of course, not what the media does. It trafficks in fear. And intelligent explanation of problems, never mind solutions, has never been its forte. Yet it is the climate coverage we need to see because we have already long, long passed the point where merely getting people frightened becomes counterproductive.