Morgan Ames is a techie. She majored in computer science at Berkeley and now works at the Center for Science, Technology, Medicine, and Society. She wants to convince you that techies know computer science, but we should not look to them for advice about child-rearing, education, or other social issues. Their range of expertise is narrow. It may make them very rich. But it does not make them wise in every field of endeavor.
in particular, she is critical of the media narrative that techies shield their children from early use of technology.
She writes:
“These articles assume that techies have access to secret wisdom about the harmful effects of technology on children. Based on two decades of living among, working with, and researching Silicon Valley technology employees, I can confidently assert that this secret knowledge does not exist.
”To be sure, techies may know more than most people do about the technical details of the systems they build, but that’s a far cry from having expertise in child development or the broader social implications of technologies. Indeed, most are beholden to the same myths and media narratives about the supposed evils of screen time as the rest of us, just as they can be susceptible to the same myths about, say, vaccines or fad diets. Nothing in their training, in other words, makes them uniquely able to understand arenas of knowledge or practice far from their own.”
Whoa. I disagree with Ames. Monitoring children’s screen time and allowing them time to read and play is one of the most important jobs of parents today.
I think Ames would have been on safer grounds had she criticized techies’ entrance into politics or other realms about which they are clueless, where they think their financial success makes them superior to everyone else and encourages them to scoff at democracy. Or where they think that their financial success gives them the right to “reinvent” education and scoff at democracy. Think Zuckerberg, Gates, and Mrs. Jobs.
Diane Ravitch's blog 
Hubris, the vice of a generation of self-appointed social reformers. Look to the the role of the Technocrats Movement in the French Vichy government. Seduced by power.
exactly
“In short, there is nothing about being a techie — either in terms of training or work — that naturally equips techies to be moral or thought leaders.”
Whatever else she had to say, I agree with this statement from her essay.
I have NEVER thought that techies were the smartest people in the room.
To be fair, in the quoted excerpt she didn’t claim that screen time should be unlimited or unmonitored, nor that activities outside of screen time are unnecessary. The paper is behind a pay wall, so I can’t see if she made such assertions elsewhere.
Morgan works at the Center for Science, Technology, Medicine, and Society….but claims techies have no specialized knowledge about the connection of tech to society? The issue of tech in the life of children and familities and in school is not just about screen time. The big issue is what DATA the techies are collecting, why, and how are they are using it ti capture attention and profits.
Audrey Watters has more knowledge and wisdom about the use and abuse of tech in and beyond school, especially the mid-boggling pursuit of profit from the DATA, DATA, DATA Suggest readers look at this and a few of the links. I also suggest that Morgan get a copy of Audrey’s forthcoming book. http://hackeducation.com/2018/12/18/top-ed-tech-trends-stories
That’s right. Techies don’t worry about screen time; they know about the data. They don’t want their own children’s personally identifiable psychometric data to be sold to the likes of Cambridge Analytica, to private and state actors both foreign and domestic. They know the dark secrets about the $$$ behind the curtain. Data = gold.
Remember Steve Bannon reportedly targeted for political messages, the phones that had recently been in Catholic churches.
From a psychologist’s tweet, “The pull between narcissists and religion- religion is attractive to those who view themselves as grandiose and superior”.
Ames wrote- the educations that tech’s rich “choose for their kids are more about their comfort levels with inequities”.The poster children for what Ames wrote, are Bill and Melinda Gates.
Melinda announced that she loses sleep over gender inequality- while at the same time she spent a billion dollars to de-professionalize the career that gave the most women, financial independence.
Religion is very important to both Melinda and Betsy. Both of their husbands participate in the churches the wives attend.
Remember when the Disrupters were all saying that America had fallen far, far behind other countries on international standardized tests and that, therefore, we needed to “raise standards,” test more, and apply high stakes to those tests–to fire teachers and close schools and turn them over to private management? Well, this was a lie. If you corrected for the socio-economic level of the students taking the tests, American students, even then, were among the highest performing in the world.
Years ago, the literary critic Northrup Frye wrote in his The Educated Imagination that one of the earliest texts ever written that wasn’t simply a record of the amount of grain in some granary was a Sumerian one that lamented that children no longer obey their parents or honor the gods. In other words, there has never been a generation that hasn’t bewailed what’s happening with “these kids these days.” There will always be someone around to complain about the kids moving across the floor to those scandalous Strauss waltzes.
This is not to say that we don’t have real issues. Our kids are really stressed out by the constant testing, they are worried with good reason about their economic futures, and suicide rates are up.
But do we blame this and every other problem on students’ use of tech, on their screentime? Do we say, for example, that because of tech they aren’t reading anymore, a claim that is often made? Well, if we make that claim, we are wrong. They are reading as much as ever before. Here are the facts, from Pew Research: https://21centurytext.wordpress.com/trends-in-reading-habits/
I do think that literacy is changing in the always connected era. My high-school students tended to know a little about a lot from their constant digital gleaning. So, literacy isn’t decreasing, but its quality is changing. And interestingly, my students tended to be extremely tolerant of human differences, something also borne out by national stats. I suspect that this has to do with their spending a lot of time online, where, if someone says something homophobic or sexist or otherwise socially unacceptable, others quickly pile on. In other words, while there are dangerous Galapagos Islands of extremism on the Net, there is also this positive social sanction.
And so it is generally. We read a lot horrific stuff that happens online–about predators and hackers spreading ransomware, but we don’t read much about the online communities of breast cancer survivors sharing their experiences with one another, about the folks going online to learn how to do Greek cooking or how to build a guitar.
Yes, depersonalized education software in schools is a TERRIBLE idea. It’s the old, failed programmed learning dressed up in fancy new graphical formats (“We have Study Buddy avatars!”), but I just don’t see the evidence that screen time IN GENERAL is such a bad thing. I see a mixed bag, some good, some ill. OF COURSE young children should spend a lot of their time socializing face to face and playing outside. Of course. And of course, replacing with depersonalized education software traditional interaction in the classroom with other students and with teachers is a really bad idea. And of course, spending all one’s time in the basement playing Fortnight has huge opportunity costs. But tech has its place. Yes, you can readily go online and find out the relative economic strength of the North and South at the beginning of the Civil War. Yes, you can find that copy, online, of that Langston Hughes poem. Yes, you can readily look up, online, how to format a Works Cited entry for a book with three authors.
In a letter he wrote to the Amherst Student, Robert Frost wrote that people have always thought that they were going down under the greatest forces ever marshaled by God. He was skeptical. So am I.
Techies may be brilliant in their own lane. When they venture into other domains such as education, they are no more informed than other people and, as education “reform” has demonstrated, far less informed than education experts. As we know, they often bring a lot of bias and hubris to the decision making table. Then, they stand on their platform of wealth and try to dictate to everyone else. Their wealth should not give them access to other people’s children to use as guinea pigs.
“Research consistently shows that what really matters is the context of children’s technology use (is this time for the family to be together or a digital babysitter?), the content they consume (is this videochatting with grandparents or violent videos?), and how adults communicate with them about what they are seeing.”
Seems pretty on target to me. I found her criticism on “techies as thought leaders” a more compelling analysis and probably would have led with that as the main idea. She admitted that techies have no special ability to pontificate on education or any other of a variety of social issues, for that matter..
These people are just full of themselves (and something else)
They believe that their wealth makes them untouchable, but I predict that some of them are yet to go down due to their involvement with Epstein.
I think it might be worth noting that ‘computer science’ isn’t a science. It’s engineering.
I find engineers to be certain of almost everything because they are given the rules and then expected to manipulate them. Scientists, however, are expected to investigate the rules and try to come up with better ones, and so they are far less certain about the ‘truth’.
Well, theoretical computer science is science—or, more precisely math. For example, they figure out faster algorithms which make computers work faster. Faster algorithms don’t need to involve any engineering work whatsoever. It just requires a software program that implements the algorithm.
Theoretical computer scientists may show, without a doubt, that certain things are not possible on a computer.
Mate….
When you say computer science is math (theoretical), then I agree. However, math isn’t science. Math is used as a tool in modern science. Science, however, is inductive at it’s core. Math is deduction, starting with and manipulating a set of ‘given’ rules.
Math will always be ‘precise’ and science not as much because mathematicians know the rules and science is trying to discover and predict observed patterns. As you know, precision isn’t the same thing as accuracy.
Sadly, many equate ‘math’ with ‘science’, which leads to the general public being fooled by numbers and such into thinking that if a number is attached, it must be ‘scientifically true’ (an oxymoron if there ever was one).
No doubt, if your basic assumptions are crap or don’t exist, no matter how fancy the math you are using in your analysis, your conclusion will be crap.
“If I am not guilty, I should be let go. Not only that, I should get reimbursed for all my legal fees. Not only that, I should get a salary for the rest of my life for all the treatment I have endured, and I should be provided with a house on the beach and one in the mountain, and I also want a trip tpo Italy and free ticket to every Yenkees game.”
“Well, sure, I agree with all that, except we have a videotape proving that you are guilty. ”
“Oops. But if we assume there is no videotape, you should let me go, right? Not only that, I should get reimbursed for all my legal fees. Not only that …”
“However, math isn’t science. ”
Theoretical math is not, I agree. But applied math, such as much of theoretical computer science, is as much of science as theoretical physics. The results are directly applicable to the real world and their conclusions are verifyable.
Math is a collection of languages to help describe the results and aspirations of the various sciences. Theoretical math develops new languages which may not have immediate applications in the real world, and one never knows when (or ever) such applications will occur. For example, the mathematical language to describe Einstein’s theory of relativity was invented by Riemann about 50 years before Einstein. Einstein acknowledges this fact. Speaking of his General Theory of Relativity, he talks about the influence of the works of three mathematicians, Gauss, Ricci and Riemann.
[In 1912] I suddenly realized that Gauss’s theory of surfaces holds the key for unlocking this mystery. I realized that Gauss’s surface coordinates had a profound significance. However, I did not know at that time that Riemann had studied the foundations of geometry in an even more profound way. I suddenly remembered that Gauss’s theory was contained in the geometry course given by Geiser when I was a student… I realized that the foundations of geometry have physical significance. My dear friend the mathematician Grossmann was there when I returned from Prague to Zürich. From him I learned for the first time about Ricci and later about Riemann. So I asked my friend whether my problem could be solved by Riemann’s theory, namely, whether the invariants of the line element could completely determine the quantities I had been looking for.”
Reply to your 11/4 morning statement (3 paragraphs).
Your last two paragraphs more or less agree with me. The creation of a language is not ‘science’, although some languages are used by science. With one caveat…. a language of mathematics is unlike a natural language in that it is a self-consistent, unchanging, unambiguous construct. So, I would say it is a self-consistent logical system, rather than a ‘language’ (although, once again, ‘computer people’ mutate the word ‘language’ just as they do the word ‘technology’, and thus degrade our ability to communicate. This would be fine if it was understood that their usage was technical jargon, however they, instead, seem to think, or at least want the public to think, that the ONLY meaning of the concept is their technical one).
Earlier, you stated (to someone) that ‘computer science’ was much more precise than other ‘sciences’. So, why, exactly, would you want to be associated with those other messy, uncertain pursuits? Why not simply call it ‘computer programming’? That, after all, is what’s going on. You are simply programming at the level of a ‘compiler’, or perhaps lower. You are manipulating a set of switches, trying to get them to solve problems more quickly and efficiently. You are trying to write a better program. If you are trying to build a better set of switches, that’s engineering.
Science (for me) is Natural Philosophy, an attempt to understand our interaction with the outside just a bit better. ‘Directed’ science usually produces only minor results, for the simple reason that the view is constricted. Is this ‘science’? A ‘natural philosopher’ would refuse to operate in this manner. Most ‘basic’ science produces nothing of immediate use, however every now and then our world view shifts as a result of it looking at the world without blinders.
There were scientists (such as Newton and Gauss) who were also mathematicians.
“Earlier, you stated (to someone) that ‘computer science’ was much more precise than other ‘sciences’. ”
I referd to a good part of theoretical computer science. For example, if they say a sorting algorithm cannot be done faster than blahblah steps, it cannot be, no matter how hard you try, and it won’t be disproved thousand years from now. It’s pure math, I am telling you.
We hold different definitions of ‘science’, you and I. I think of science as ‘natural philosophy; as trying to explain what we see in nature. Math isn’t science.
I think it’s time we give up and agree to disagree.
I doubt I want to give any definition of what science is, and I certainly don’t want to restrict science to what you call natural science.
Note the part, though, where I stated that what theoretical computer scientists come up with can and is used directly to explain natural processes, such as DNA replication or how viruses spread. And there are mathematicians/computer scientists who work in these areas with biologists, chemists, cognitive scientists, and medical professionals and it would be crazy to separate which researcher is doing math and which one is doing natural science. The best of these people are doing both, as did Newton or Archimedes or Gauss or Euler.
This argument reminds of the argument we have here about how to teach: whether we should just fill kids’s long term memory with knowledge or let them be creative and figure things out things out on their own. I have no idea why some people insist to separate the two methods. Both methods are needed.
I agree, Mate, that we need both ‘math’ and ‘science’. They are both modes of thought, just as you indicate different modes of teaching (learning?) are needed. Although you appear to agree that ‘just let kids learn by themselves’ is different from rote memorization, you will not agree that science is different from math. Why?
Science is an inductive process starting from observation. Math is a deductive system starting from assumed truths. The fact that a single person does both doesn’t make them the same any more than a single person eating a fish and an oreo proves that oreos and fish are the same thing. Newton did both, Gauss did both, and so on.
A computer is a machine with known components. Is there a field of ‘bulldozer science’? And, if so, what is the difference between what you call science and engineering? Can you name a science (use of induction starting with observation) that is not ‘natural’? Metaphysical science?
I taught both math and science. I used plenty of math when I worked in physical chemistry. When I was trying to reconcile HCB molecular transport theory with macromolecular transport equations, I was working as a mathematician. It’s nice that I could do so, however, it only confirmed what was already being used, and it started from an accepted ‘truth’ and simply tried to show self-consistency (which it did). This was mathematics, not science.
When, however, I ran molecular diffusion experiments at low temperatures with oddball noble gasses in an attempt to find deviations in HCB theory, that was science.
Science teaches that there are no absolute truths. Mathematics taught you the opposite. But, mathematics is a construct of the human brain, and the human brain is not infinitely wise. The ancient Greeks studied both deduction (take Euclid, for example) and induction, and they understood that induction took precedence if there was a conflict. There’s a common saying that reflects this, “Consistency is the hobgoblin of little minds”. Science hopes for consistency, but understands that in our interaction with the outside world, it is an ideal that will never be realized. Science (like art) revels in the unexpected surprise that jolts our complacency. Math, on the other hand, creates its own consistency that precludes the possibility of unexpected surprises and turns the mind inward.
I think you and I can agree that Euclidean Geometry, Calculus, and Matix Algebra are maths. I think you and I can agree that Physics, Astronomy, and Biochemistry are sciences. Do you care to examine what makes one group different from the other?
“Math is a deductive system starting from assumed truths. ”
If you think all mathematicians do is deduce stuff from assumed truths (axioms), you are badly mistaken.
“‘Math is a deductive system starting from assumed truths. ‘
If you think all mathematicians do is deduce stuff from assumed truths (axioms), you are badly mistaken.”
What Math is and what mathematicians do are two different things. I thought I made that clear in the comment that prompted this reply.
Can you name an accepted (generally thought of as a ‘branch’, like Tensor algebra, or Calculus, or whatever) form of ‘math’ that isn’t deductive and self consistent?. Just one example will prove me wrong.
You love to make ex casthedra statements, and you seem to think, there are clear distinctions between things and people. I don’t believe in either of these, because reality is different.
In math results are not just deduced, but structures are built, often “just because” and often because this is what a real life application dictates.
Your tone and attitude is close to trollish.
And, with that ad-hominem, I think the evidence indicates that nothing of value will come by continuing this discussion.
“You are manipulating a set of switches, trying to get them to solve problems more quickly and efficiently.”
Then you can say the same thing about the functioning of the brain, how short and long term memory works, or how DNA replication works, how viruses spread. There are these algorithms in nature as well, and many results theoretical computer scientists come up with are applicable to those as well.
Imo, these phylosophical definitions of what science is don’t work. What I can say for sure is that the less math a science uses, the less precise and the less reliable it is.
The brain is not a set of switches. Like other parts of the body, it is a spectacularly complex tissue in which thousands of known biochemical interactions take place producing ‘feedback loops’ everywhere. There are probably at least as many undiscovered interactions (with some being uncovered every year). And, most of these actions and reactions are best described as analog, not digital. If you consider a single type of molecule a ‘switch’, notice that there are thousands of different kinds of molecules in the brain interacting with each other. A computer bears almost no resemblance to the brain.
It’s a mistake to assume theoretical computer scientists think only in terms of switches. For example when you analyze algorithms, you don’t have a computer in your mind at all. I personally know world class theoretical computer scientists who barely look at computers (one doesn’t even do emails) and can’t program in any language.
It’s another matter that even Von Neumann’s 61 year old classic The Computer and the Brain never claimed that the brain and computers work the same way.
If the lousy computer programs I have to constantly navigate are any indication, computer scientists don’t even know computers. For people supposedly educated in tech, most computer programs are garbage.
The software aspect of computer “science” is not even engineering.
Practitioners call themsevles “software engineers” but they chose the name to gain credibility, not because they follow engineering practices (just as they also chose the name computer “science”.) In other words, they glommed onto the credibility of scientists and engineers by adopting their names.
I’ve worked with lots of scientists and engineers in R&D and, by and large, they were far more thoughtful than any of the computer “scientists” I worked with. A lot of the latter are just hacks, in my experience. I would hire a real scientist or engineer any day of the week over a computer “scientist”.
A lot of the CS people went into CS because they can’t deal with people and find it far easier to “relate to” computers.
In my opinion, that is the root of the trouble with techies.
The trouble with techies
They’re social impaired
Computers are mommies
When nobody’s there
I wouldn’t call all computer science lousy. Good chunk of theoretical computer science, such as the study of speed of algorithms or encryption theory are very much part of math, so as precise as math, and hence more precise than any of the sciences.
On the other hand, when it comes to AI, that’s where things become looser (but of course, not always).
In general, some economists and AI workers study things which are too complicated for current science to attack. But studying these things shouldn’t be called science, they are ponderings.
I have not worked with theoretical computer people (just run of the mill “software engineers” with CS degrees and quite frankly, I have not been impressed.
And with regard to so called AI, it’s not even clear what that means because its practitioners keep redefining it.
First they just called it AI and now they distinguish between strong AI and week AI and claim that “we have achieved AI, just not strong AI”.
LOL!
Even so called week AI has nothing to do with real intelligence. Much of it is based on neural nets and statistical in nature, completely dependent on the training database and readily fooled. It has little of anything to do with real intelligence.
https://www.quantamagazine.org/machine-learning-confronts-the-elephant-in-the-room-20180920/
Thanks. Interesting article about what AI can presently do and what it cannot. Apparently, our brain can do lots of parallel processing while computers cannot (as we know that computers only simulate multitasking, but they can’t really do it)
Researchers are still trying to understand exactly why computer vision systems get tripped up so easily, but they have a good guess. It has to do with an ability humans have that AI lacks: the ability to understand when a scene is confusing and thus go back for a second glance.
This is good stuff (I certainly use the google photo feature to recognize faces even on childhood photos), but yeah, we have to be aware how much of AI is science, and many of the researchers will not help us draw the line.
And of course, I am not going to buy a Tesla even if I will win on the lottery.
Snafus like those extrapolate in unsettling ways to autonomous driving. A computer can’t drive a car if it might go blind to a pedestrian just because a second earlier it passed a turkey on the side of the road.
It may not be, but IF the (rather credulus) response of some theoretical computer scientists to Google’s claim of having achieved “quantum supremacy” is an accurate reflection of the field, I’d have to say I have some concern.
Real science is ALL about replication AND real scientists REQUIRE replication by independent scientists before making an assessment.
The Google claim had barely been published and some theoretical computer scientists (eg, Scott Aaronson) were acting like it is a done deal.
Yeah, we can read this is cryptography all the time “a fast, unbreakable encryption software was just developed at Miksoft. Price is very affordable: $100 for students, $1000 for profs, $1 million for companies.”
While experts say, it takes at least a decade, but more like two decades, to test and trust a new encryption software.
This article illustrates another reason why real scientists should remain skeptical about claims of quantum supremacy
Major Quantum Computing Advance Made Obsolete by Teenager
It’s actually humorous that Scott Aaronson tasked his student to show the opposite of what the student ended up showing simply because Aaronson believed that no classical algorithm could complete with the so called “quantum speedup” of a quantum algprothm m proposed by two theoretical computer scientists.
”
Kerenidis and Prakash proved that a quantum computer could solve the recommendation problem exponentially faster than any known algorithm, but they didn’t prove that a fast classical algorithm couldn’t exist. So when Aaronson began working with Tang in 2017, that was the question he posed — prove there is no fast classical recommendation algorithm, and thereby confirm Kerenidis and Prakash’s quantum speedup is real.”
https://www.quantamagazine.org/teenager-finds-classical-alternative-to-quantum-recommendation-algorithm-20180731/
Unfortunately, Aaronson was proved wrong.
I don’t mean to pick on Aaronson, but he seems to exemplify the sort of “belief without proof” (eg, that P≠ NP) that infects some theoretical computer science”.
And of course, you can really never actually prove that there is NO possible classical algorithm that can compete with some quantum algorithm that is claimed to be exponentially faster than a classical algorithm (assuming one could make the quantum computer to run the quantum algprothm), so the whole quantum supremacy claim would seem to be a bit of a logical fallacy. Just a bit.
Proof of nonexistence has always been a hard problem, but if anyone can do it, theoretical computer scientists probably can
The problem with self driving cars is the same problem that afflicts many so called AI systems.
They are very good at dealing with what is expected based on previous experience/data, but very poor at dealing with the unexpected (eg, the elephant in the living room)
.
Humans Excel at the latter: dealing with entirely new circumstances.
And humans can also understand what is they are looking at
Most people who saw an elephant in their living room would not only easily identify it but wonder what the hell is this doing in my living room?
Even if the computer identified it, it lacks the understanding to know that there is something seriously amiss.
The computer just goes on its merry way as if everything is fine. Elephant in the living room? Check!
Understanding is actually key to AI — sorry, ” strong AI” gotta get !y terms right here.
“most are beholden to the same myths and media narratives about the supposed evils of screen time as the rest of us, just as they can be susceptible to the same myths about, say, vaccines or fad diets.”
So this is weird, she criticizes techies for pretending to be experts in stuff they know nothing about and then she gives an almost expert opinion about research into the psychological effects of screen time. Is she a psychologist who studied the effects of screen time?
For example, here is an article from her almamater’s magazine
https://greatergood.berkeley.edu/article/item/is_screen_time_toxic_for_teenagers
which references, among others, this study
https://ora.ox.ac.uk/objects/uuid:672ebf78-4b9a-42d3-8e81-8bc2561dce11/download_file?file_format=pdf&safe_filename=Przbylski%2Band%2BWeinstein%252C%2BLarge%2Bscale%2Btest%2Bof%2Bthe%2BGoldilocks%2Bhypothesis%2B-%2BQuantifying%2Bthe%2Brelations%2Bbetween%2Bdigital%2Bscreens.pdf&type_of_work=Journal+article
Thanks for the referenced articles.