We’re putting together a list of big, high profile goals that proved far more challenging than people had anticipated circa 1970

Palko writes:

The postwar era (roughly defined here as 1945 to 1970) was a period of such rapid and ubiquitous technological and scientific advances that people naturally assumed that this rate of progress would continue or even accelerate. This led not just futurists like Arthur C Clarke but also researchers in the fields to underestimate the difficulty of certain problems, often optimistically applying the within-a-decade deadline to their predictions.

I [Palko] am trying to come up with a list of big, high profile goals that proved far more challenging than people had anticipated circa 1970.

He continues with some examples:

The war on cancer. I suspect that the celebrated victory over polio significantly contributed to an unrealistic expectation for other major diseases.

Fusion reactors. It took about a decade to go from atomic bomb to nuclear power compact and reliable enough to deploy in submarines.

Artificial intelligence. We’ve already mentioned the famously overoptimistic predictions that came out of the field at the time.

Artificial hearts.
From Wikipedia:

“In 1964, the National Institutes of Health started the Artificial Heart Program, with the goal of putting a man-made heart into a human by the end of the decade.”

Not sure whether they meant 1970 or 1974, but either way, they missed their target.

Does anyone out there have additional items I should add to the list?

Yes, I have some examples! Before getting to them, let me first point out that some obvious candidates don’t really work. Rockets to Mars and flying cars . . . people were talking about both of these, but there was also lots of skepticism. It’s my impression that the flying-car thing was always a bit of a joke, as the energy consumption and air traffic control problems were always pretty obvious.

Weather modification, maybe? I don’t know enough about the history (see book #4 in this list) to know for sure; was this an area in which wild optimism was the norm?

Most of my examples are intellectual rather than physical products:

– Game theory. If you read Luce and Raiffa’s classic 1957 text, you’ll see lots of fun stuff and also a triumphalist attitude that just about all the important problems of game theory had been solved, and we were just in a mopping-up phase.

– Classical statistics. As X and I wrote, “Many leading mathematicians and statisticians had worked on military problems during the World War II, using available statistical tools to solve real problems in real time. Serious applied work motivates the development of new methods and also builds a sense of confidence in the existing methods that have led to such success. After some formalization and mathematical development of the immediate postwar period, it was natural to feel that, with a bit more research, the hypothesis testing framework could be adapted to solve any statistical problem.” As the recent replication crisis illustrates, we’re still living with the consequences of this war-inspired confidence.

– Psychotherapy. Between Freudian analysis from one direction, and Thorazine etc. from the other, it must have seemed to many that we were gradually solving the major problems of mental health.

– Keynesian economics. Just a matter of fine tuning, right?

– Various specific social engineering problems, such as traffic congestion, not enough houses or apartments where people want to live, paying for everyone’s health care, etc.: these were low-level concerns which I imagine that many people assumed would solve themselves in due course as we gradually got richer.

As Palko notes, a common feature of all these examples is that a period of sustained success (in the case of Freudian analysis, success in the social realm even if not in the outcomes that matter) gave people the illusion that they were at the beginning or middle, rather than the end, of a long upward ramp. Also, in none of these cases was the techo-optimism universal; there were always skeptics. But these are all examples where an extreme optimism was, at least, considered an intellectually and socially respectable condition.

What other examples do you have?

P.S. It’s mid-December in blogtime but this topic is so juicy, I’m posting it right away. I’ve bumped today’s scheduled post, “‘My advisor and I disagree on how we should carry out repeated cross-validation. We would love to have a third expert opinion. . .'”, to the end of the queue.

72 thoughts on “We’re putting together a list of big, high profile goals that proved far more challenging than people had anticipated circa 1970

    • A foolproof way to dispose of nuclear waste. Hey, we’ll probably never crack that one, but it sometimes attracts of refrain of “within one more decade.”

  1. Extraterrestrial contact
    Cheap desalination of seawater
    Room temperature superconductivity (and they don’t stop: https://www.sciencealert.com/brand-new-type-of-superconductor-discovered-physics )

    But I think for every one of these that has gone slower, there’s another one that has gone way faster, mostly computer related, but the big one:
    Agricultural productivity increases eviscerating the Population Bomb hysteria

    • While the advances in computer science have certainly been impressive, I’m not sure how much they have exceeded expectations. Moore’s Law dates back to 1965, and while people have been surprised at its longevity, the idea of exponential growth in the field has been baked in for a long time.

      As for agriculture, we also see lots of impressive gains over the past 30 or 40 years, I don’t believe they exceed in relative terms the productivity increases of the postwar green revolution, a term coined 50 years ago.

      • As to whether or not computer developments and agricultural change exceeded expectations of 1970, I think you’re way overstating the mean expectation (as opposed to the Asimovian SF expectation) of 1970, and you’re certainly overstating the expectation of the continued effects of the Green Revolution. No doubt people were impressed in 1970 about the changes that had come in agriculture, but the prevailing paradigm was that of rapidly exhausting all the low-hanging fruit and indeed endangering the fruit tree itself.

        To Martha Smith: population causes problems, sure, but to argue that “demands for equity of opportunity” are on the same level of mass starvation seems uncharitable. And of course the only thing that will solve population problems are people, and we haven’t yet come up with a workable scheme to cause only the people who can solve the problems to be born, thank God. So we take all of them and then let the best of them solve our problems.

        • Just to be clear, I never claimed that people expected to rapidly exceed the advances of the green revolution. I was only making the point that you couldn’t really use agriculture as a counter example since the period that did shock people with its progress was in the postwar era.

          And you are right about the dangers of using science fiction and sensationalistic popular science writing as a proxy for what people actually expected. That’s why (with the exception of Arthur C Clarke whose pretty much unavoidable in this discussion) I limited the examples two cases where we had contemporary evidence in either the form of statements from researchers in the fields (AI, artificial hearts) or major public policy initiatives (such as the war on cancer).

          You can find more details here.

        • Jonathan,

          Perhaps my phrase “demands for equity of opportunity” meant something different to you than it did to me. I was thinking of the gap between the “haves” and the “have nots” — which often means very dire circumstances for the have nots. We may have gotten to the point where there is enough food to feed all, but the distribution of that food (the opportunity to consume it) is not equally distributed. And perhaps some of the people who potentially would be best able to solve some of our problems are among those who are not surviving in the unequal distribution system we now have.

  2. Mass hypersonic transport. It was the natural next step after the horse -> train-> airplane progression, but the environmental and economic problems were harder to solve than foreseen.

    OTOH, feeding the world’s extra billions of people turned out to be not as hard as people had thought.

    The rate of non-AI progress in computer technology doesn’t seem to have been anticipated either – Moore’s law ended up lasting not 5 but 50 years.

    • “Moore’s law ended up lasting not 5 but 50 years.”

      The main culprit there would have to be the invention of the excimer laser in 1970, leading to advances in nanolithography that were exploited by chipmakers in the 80’s to make hitherto inconveivably small computing elements, after the paper of Jain, “Ultrafast deep-UV lithography with excimer lasers”.

  3. Lots of opportunities from the environment …
    – Manage ocean fisheries optimally, or just better
    – Manage water in California optimally, or just better
    – Manage use of pesticides in agriculture better

    From healthcare …
    – Enable Electronic Health Records to interoperate
    – Enable advances in machine learning to work in healthcare
    – Better understand opportunities and challenges with precision medicine (only works on cancer and inherited diseases so far …)
    – Enable caregivers and patients to view evidence is some understandable and practical way

    From education …
    – Better understand role of MOOCs
    – Better understand optimal mix of education modalities

    Globally, biggest challenges are …
    – Climate change
    – Income diversity

  4. I would say gene therapy could certainly belong here.

    We thought by 2000 we will have a cure most of the diseases, but realized that this is very challenging if not impossible.

    • We thought by 2000 we will have a cure most of the diseases, but then adopted NHST which generated a bunch of incorrect and/or conflicting conclusions making it impossible to figure out what is actually going on from the literature while misplaced trust of this same literature by public health policy makers has lead to holy cows blocking the path to progress.

      • Don’t think it has much to do with NHST rather than underestimating the complexity involved in gene manipulation.

        For example, we knew single gene mutation disease like sickle cell anaeamia for more than 60 years and we still don’t have a cure! We also thought that common diseases will be explained by a few DNA variants, but we are now realizing that 1000’s of gene variants are involved in each common disease! We will get there, but this is way too challenging than anybody ever thought, especially after we mapped the human genome project.

        • For example, we knew single gene mutation disease like sickle cell anaeamia for more than 60 years and we still don’t have a cure!

          Why would knowing about a correlation with one nucleotide allow you to easily cure a disease? Also, I know nothing about SCD, but after looking it up I see people with the same gene mutation apparently show an “exceptionally” wide range of symptoms, some may even be asymptomatic:

          Sickle cell anaemia, a monogenic disorder caused by homozygosity for a single beta-globin gene (HBB) mutation (HbS; B6GAG -> GTG; Glu -> Val; glu6val), behaves clinically as a multigenic trait with exceptional phenotypic variability (Table I).
          Some patients may have all of the complications listed in column 1, while other can have few, or even none of these events. Some patients die young from disease complications; other survive into the eighth decade. In common laboratory tests, e.g. leucocyte or reticulocyte counts, broad variation can be found among patients. For example, HbF levels can vary by two orders of magnitude; leucocyte counts can be normal or more than twice normal.

          I agree then the difficulty was “underestimated”, but then the initial “estimate” was just foolish to begin with. This “phenoypic heterogeneity” was already known in the early 1970s: https://jamanetwork.com/journals/jama/article-abstract/347814

          We also thought that common diseases will be explained by a few DNA variants, but we are now realizing that 1000’s of gene variants are involved in each common disease!

          Who thought this? They probably saw a few correlations via NHST and then drew wide ranging incorrect conclusions.

          especially after we mapped the human genome project.

          The human genome was never completed, instead they redefined “complete” to mean “we did the best we could”.

        • “Why would knowing about a correlation with one nucleotide allow you to easily cure a disease?”

          My point is if we cannot find a gene therapy for a single gene imagine the ones where we have problems with 100’s of genes.

          We can all go back and say almost all the ones listed here where the initial estimate was ‘foolish’ to begin with. Probably a hindsight bias.

          “This “phenoypic heterogeneity” was already known in the early 1970s”

          Glad they didn’t do NHST for this. Or did they? :)

        • My point is if we cannot find a gene therapy for a single gene imagine the ones where we have problems with 100’s of genes.

          Afaik, there is no such thing as a problem due to a single gene/mutation. Another classic example is mutation to the retinoblastoma protein, once again not everyone is affected, showing it is not a single gene problem:

          In one of these cases, asymptomatic mother of a URB child had constitutional deletion mosaicism (50% of cells with deletion), whereas mothers of trilateral Rb and other URB child had germline deletion with 100% frequency. Surprisingly, the mothers did not have any visible physical deformities.


          We can all go back and say almost all the ones listed here where the initial estimate was ‘foolish’ to begin with. Probably a hindsight bias.

          There’s many similar issues happening right now. Eg, the current practice of referring to signal transduction pathways which ignore the time dimension is just as foolish. Also, the idea that any drug is selective for a single target rather than acting at a myriad of sites.

          Glad they didn’t do NHST for this. Or did they? :)

          No, they didn’t. They simply described the data. The only place you may be referring to is here:

          The mean score for patients with MSD was 2.0 with a range of 0 to 4. Patients with severe SSA had scores of 4 to 9 with a mean of 5.6. These differences are statistically significant (P<.001).


          This is irrelevant to the overall point and it looks like a sentence added for an ignorant reviewer/editor. They don’t draw any conclusions from the statistical significance, it is just sitting there doing nothing.

        • Afaik, there is no such thing as a problem due to a single gene/mutation. Another classic example is mutation to the retinoblastoma protein, once again not everyone is affected, showing it is not a single gene problem:

          If that’s the truth, then gene therapy is another pipe dream :)

    • from here:

      Afaik, there is no such thing as a problem due to a single gene/mutation. Another classic example is mutation to the retinoblastoma protein, once again not everyone is affected, showing it is not a single gene problem:

      If that’s the truth, then gene therapy is another pipe dream :)

      Why would that be? Its just that a gene therapy needs to be developed based on how it influences the entire system. Trying to understand things piece by piece and ignoring how all the pieces interact over time is a recipe for failure. You seem to keep jumping to wild conclusions.

  5. Protein folding simulations. In 1995, I claimed that it would be resolved within 10 years. But sampling from complex distributions remains a challenge – even when tuned to one very particular problem ☺

  6. The demographically-driven ultimate triumph of the Democratic party.

    Assorted Grand Theories of Everything in physics, dating back to before Einstein.

    Electricity from nuclear fusion.

    Solar power–few would have expected windmills to be more practical than solar.

    A theory of nutrition that produces useful recommendations for the average person.

    But we did solve the Poincare conjecture!

  7. Given that I was born a decade after the target date, I don’t have a great perspective about what was considered eminently solvable. A lot of the comments here don’t seem to fit though.

    1. Keynesian economics: Wasn’t there already big saltwater / freshwater divide in 1970

    2. Batteries: Was this even big on the radar screen of the 1970 scientific establishment? And didn’t we sort of achieve this with respect to what was available in 1970?

    3. Peace: Aren’t we more optimistic now on this now than in 1970 given that we have not had a great war since the second?

    4. Were MOOCs even a twinkle in people’s eyes? Or gene therapy?

    • Don’t know about MOOCs but the structure of the CA public university system was definitely designed around a kind of goal of basically educate everyone to the level of masters degree “for free”

      Of course, if we followed its original intent, it’d work a lot better than it does. Originally Junior/City colleges would educate you for 2 or 3 years out of High School, and then the State Universities would complete your Undergraduate degrees, and you’d go to the UC system for a masters or PhD.

      Of course, that doesn’t satisfy the desire for prestige and signaling and funding, so the UC system became the predators that sucked away the top talent for the undergrads, and the city college and State U system became the second-tier lower prestige system, and basically there’s a huge redundancy that results in none of the economy of scale.

      • I did my masters at a california state school, my PhD at a UCLA, I’ve worked at UCSD, and even did some coursework at a CA community college during high school. I guess it doesn’t function as it was originally intended, but the california public university system has to be considered a resounding success story. We have multiple campuses that are among the worlds top universities, far more than our fair share (e.g. https://www.universityofcalifornia.edu/news/9-uc-campuses-ranked-among-world%E2%80%99s-best-universities).

        • “Has to be considered a resounding success” by your utility function perhaps. I spent a year at CCSF and transferred to UC Davis for a second undergrad, and I agree with you that the education I received was relatively good and many of the students performed at a high level. But the system by far over funds certain areas and under funds others. The system is still doing a mostly 19th century task, lectures in halls, and has ballooned in cost without concomitant improvements in quality. It’s still the case that financially the sheepskin is worth much more than the knowledge, of course that reflects a societal illness, but the CA system isn’t bucking that widespread trend.

          The promise of the Mooc or the original CA University system is to deliver knowledge and skills at low cost. Unfortunately what we deliver is sheepskins at high cost, much of the high cost despite the fact that it really is possible to deliver the knowledge at much lower cost. The problem isn’t how to teach cost effectively, it’s how to make knowledge really matter to society. In a world of rent seeking and signalling, what pays off financially is reputation, prestige, and ever more degree granting. PhDs live in their automobiles and teach for effectively minimum wage.

          International rankings are the wrong metric. Give students follow-up exams 3 years out of their degrees and see if they know anything much, if they have general critical thinking skills, if they know how to write thoughtfully on a topic, or read critically… And then look at what kind of debt they have and compare their skills to someone who is say 3rd year at a city college and what their debt is.

        • > Give students follow-up exams 3 years out of their degrees and see if they know anything much
          Something like that is likely necessary to actually learn about the learning that mattered – but who is going to do it.

          Do student group ever do assessments of say the course they took in first year when they are in third or fourth year and have a better sense the value?

        • Opps – just noticed this https://alumni.utoronto.ca/alumni-impact-survey which does try to get at actual impacts.

          Stuff like “When it comes to employment, alumni active in the labour force enjoy a 97.6 per cent employment rate, with a higher percentage of alumni participating in the knowledge-intensive economy compared to the national average, particularly in the educational, legal, health and government sectors.”

          OK it is a survey [The overall response rate was approximately 8% or just over 21,000 respondents] though it looks like it was adjust for differential response rates and post-stratified to the overall alumni population.

          And there is an obvious conflict of interest (always are, here its just obvious).

          Disclaimer: I have worked with one of the principal investigators in the past and am U of T (as wall as Oxford) alumnus.

        • That survey seems to measure economic impact of the alumni. But as I say, in a world of rent-seeking and signaling, it’s the sheepskin and/or the connections you make that typically gets you those things, not the knowledge. Furthermore, the survey doesn’t compare the Univ. of Toronto alumni to any other alumni. Is UT doing a better job than community colleges? Well, we can’t look at the frequency with which people do better out of UT because the distribution of input students isn’t the same! Can we take case-control matching of students who chose UT and students who chose community colleges, and correct for remaining differences and see a difference in outcomes?

          The survey you link is basically the same as the “international rankings” type survey. What’s relevant to my interests is *how well do these people think, how much scientific and cultural knowledge do they have, and how well are they able to use it and synthesize knowledge together?* And, how much did it cost to get them that knowledge compared to how could they have gotten the knowledge for less?

          Of course, for the individual, the dollars make a big difference. But for society, if we have a plethora of rent-seekers getting the big bucks, and a lot of less well connected, less rich to begin with people with high levels of creativity and knowledge and capacity for real productivity, who aren’t able to be effective at growing the real economy because they can’t afford the debt that the required sheepskin comes with… then our society will crumble. I fully acknowledge that Canada may have a different situation, but here in the US, we have a major predatory industry in student loans, and huge rent seeking by university administrators that has made education costs grow far far faster than the rest of the inflation index:


          What are we “buying” with all these education dollars? is it in any way *education*?

          For example, recently in the news I saw an article about how people who use certain drugs are much more likely to report depression, and then it lists a plethora of drugs, and says that the more you take the more likely you are to report depression. The NYT reported on it for example: https://www.nytimes.com/2018/06/13/well/prescription-drugs-depression-suicide.html

          Of course, there are very obvious questions to ask here: does having chronic health issues cause both drug-taking and depression? How would one control for that effectively?


        • Got distracted and posted before I was done…

          How well do people 3 or 4 years out of their degree do at analyzing the scientific issues related to a study like that one about prescription medicines? Or other similar everyday studies. Can people ask the right questions? Do they know what conclusions are and what aren’t justified by the analysis? Do they have a sense of how to resolve the remaining questions? Can they read articles about historical events and compare them critically to todays events? Do they understand the concept of “real economy” vs “dollars”? I read daily bullshit stuff in the news where people who *write business articles for a living* get *basic* economic concepts wrong, like broken window fallacies and mistaking increases in nominal dollar price of assets for “economic growth”… If professionals are little better then uneducated college freshmen, how well are we doing at educating?

        • Daniel:

          Again its a survey with lots of problems such as response being less likely from those not doing so well.

          Now there is a large percentage of lower income students and kids of recent immigrants (first generation) approaching 50% (can’t remember exactly) so I don’t think its the distribution of input students having mostly privileged backgrounds.

          But at least its something post graduation beyond the usual/ the alumni that showed up an event, all claimed to be doing well.

          Tuition is likely a pittance compared to most US universities – about 5,000 US a year http://utsc.utoronto.ca/admissions/tuition-fees

          By the way, they are actively interested in attracting US students with the hope of lessening the risk of misunderstandings in US Canadian relations of future governments https://www.cnn.com/2018/06/12/politics/peter-navarro-justin-trudeau/index.html

        • Public universities, and private universities alike have become “country club like” as huge amounts of money have poured into attracting students by creating fancy dorms, high end cafeterias, architected lounge spaces, fancy gyms, even *water parks* in the shape of the university initials. All paid for on the back of those students 15 years out (loans) and overhead from government grants, and cheap access to capital (corporate loans).


        • From Daniel’s link:

          Over one-third of Americans take at least one prescription drug…

          I stopped there and thought that is already a serious problem. And that 1/3 is just regarding the subset of drugs that list depression as a side effect. The best side effect of anti-depressants I’ve seen is bedwetting. What a great way to improve your self-worth.

        • I don’t know if they still do this, but Rice University (Houston) used to do student/alumni surveys to rate professors — I think it was something like have seniors list their best professors (resulting in a teaching award) and alumni something like four years out doing the same, resulting in another teaching award. (Or perhaps it was one teaching award based on both surveys?)

        • The George R. Brown teaching prizes are awarded at Commencement each year on the basis of voting alumni who graduated with four-year undergraduate degrees two years and five years previously. They are funded by a generous endowment from the Brown Foundation, which also provides funds in support of innovative teaching projects and the administration of the student teaching evaluations at the end of each semester. The Brown Awards were first made in 1967 and have been given each year since.

  8. After doing that do the 80’s version where everything was going to just go boom! There’s crime, nuclear war, over population, disease, etc. The period was rife with examples of people fortelling the end of, at least some aspect of, the world.

  9. I know weather modification and weaponization was being seriously discussed in 1968.[http://observationalepidemiology.blogspot.com/2018/01/arthur-c-clarke-and-futurists.html]
    That should go on the list.

    Social engineering/behavior modification/economic fine-tuning definitely should as well, particularly because of the way it mirrors similar trends in the other period of interest (late 19th/early 20th century) which gave us ideas like scientific management and (a little bit later) technocracy.

    You’re exactly right about flying cars. The problem there has always been more practicality and lack of demand rather than technology. We’ve been seeing proposals and prototypes for literally a hundred years – – a few have even made it into limited production – – but all have disappeared down the memory hole. Matt Novak of the Gawker remnants Gizmodo published an amusing list of news stories announcing that we were just 2 to 5 years away from the age of the flying car.

    Jet packs, on the other hand, might belong on the list. In the mid-60s, they seemed to be on the verge of viability and their were a number of potential applications, but there were too many problems with safety, reliability, and range.

    As for Martian bases, I flip that around and suggest that it was actually the Apollo program that might be the precursor, the first big postwar project that proved more difficult than anyone had imagined (even its harshest critics were complaining about a cost less than half of the eventual price tag). Coincidentally, that’s the subject of today’s post at the blog.


  10. Killing people who aren’t really “brain dead”: https://jamanetwork.com/journals/jama/fullarticle/2684511

    Practicing “Public Health” when you don’t even know, and use a method that can’t even discover, the correlates (much less the causes) of human diseases: http://www.jstor.org/stable/3702214 – So much for the third epidemiologic transition. Take your eye off the ball and the bacteria, viruses and fungi turn you into a meat pie.

    Both made for nice stories though.

  11. On a more general note, wasn’t there a notion in the past that we could solve most problems within a grand reductivist project? Meaning, as we understand the smaller parts of a system more and more through technological advances, we will be able to predict the behaviour of the larger system. For sure we have made great advances by knowing more of the underlying parts, but it seems there’s still whole hosts of problems that needs to be interpreted and predicted at a higher level of abstraction. Complex things are still complex.

  12. Econometric models.

    Because Keynes gave us the hidden mechanisms of the economy, predicting the economic future should be as easy as predicting the behavior of a machine, right?

    But, simple time-series models do about as well. Unfortunate, but true.

  13. Most new educational theories in the last hundred years or so. (Self-esteem boosting, special learning styles, etc.)

    What a surprise. A powerful lobby of educators constantly comes up with new miracle cures that cost a lot of money but show little or no effectiveness.

    The next one will work for sure! We’ve got Heckman on it! Nobody has REALLY tried before. This time we will succeed spectacularly because our hearts are purer and our zeal burns brighter than the hearts and zeal of every other educator that came before us. How could we possibly fail? Only the most evil of hearts would deny us a few hundred billion more! Think of the children!

    • Terry:

      I think you’re misdiagnosing the problem here. It’s not my impression that the various promotors of educational innovations, whether they be early-childhood interventions, charter schools, mindful learning, mooks, or whatever, are claiming that their success, such as it is, comes from purer hearts and brighter-burning zeal. I think they’d say their success comes from the application of scientific principles and careful experimental tests. And it could well be that these ideas do work, even if not as dramatically as claimed. I think the problems come in the theories, data collection, and assessment of the evidence: these are harder problems than some might hope (I agree with you on that one), miracle cures are not so easy to come by (I agree with you there too), and lots of published (and unpublished) evidence is not as strong as claimed. That’s enough of a problem, without having to bring in pure hearts and zeal. There’s enough zeal to go around on all sides.

    • Anon:

      Those two are biggies, but did people in 1970 really anticipate these problems being solved? I mean, sure, there was hope of progress, but I don’t have the impression that there was a general feeling of confidence, in the same way as in some of the other examples discussed above.

      • Yes, many people in 1970 thought these problems would be largely solved within a few decades.

        Indeed, the logic of the civil rights movement implied a rapid elimination of racial problems. Once structural racism, such as Jim Crow and segregation were dismantled, and minorities were elected to run cities, and funding was equalized across schools, the achievement gaps would rapidly close. Since the social environment was causing the gaps, the gaps had to disappear when the social environment was fixed. And once people saw how we are really all the same, racist thinking would disappear.

        • I remember working in the summer of 1966 in the Upward Bound program that aimed to at least help improve opportunities for minorities to get college degrees. There was also the Job Corps, and other programs with aims to help get people out of poverty and provide equal opportunities for minorities and people from disadvantages backgrounds.

        • Andrew may be too young to remember what people thought during the Civil Rights movement. It would be interesting to see a survey of what people at the time thought. The pro-civil-rights people must have thought there would be substantial changes fairly quickly, or else they would not have thought it worth the effort.

  14. How about a list of problems that turned out to be solved quicker than expected? What comes to mind are the legalization of same-sex marriage and legalization of marijuana (the latter isn’t exactly complete, but we’ve made good progress).

  15. “Automobiles have become startlingly reliable.”

    One way in which they seem to have become quite reliable in recent years is that wing mirrors need repair and/or replacement all too often. ;~)

    • In a prospective, randomised, controlled trial to determine whether comprehensive lifestyle changes affect coronary atherosclerosis after 1 year, 28 patients were assigned to an experimental group (low-fat vegetarian diet, stopping smoking, stress management training, and moderate exercise) and 20 to a usual-care control group. 195 coronary artery lesions were analysed by quantitative coronary angiography. The average percentage diameter stenosis regressed from 40·0 (SD 16·9)% to 37·8 (16·5)% in the experimental group

      I have no doubt that diet and lifestyle can affect atherosclerosis but is reducing how much a vessel is occluded on average from 40% to 37.8% in a year really a “cure”?

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