from the world's big
Learning From Failure
Robert Sutton is Professor of Management Science and Engineering at Stanford University, where he specializes in organizational behavior. His research includes the links between managerial knowledge and organizational action, organizational creativity and innovation, organizational performance, and evidence-based management. Sutton has written five books including New York Times bestseller "The No A**hole Rule: Building a Civilized Workplace and Surviving One That Isn't," which won the Quill Award for the best business book of 2007. His most recent book is "Good Boss, Bad Boss: How to Be the Best... and Learn from the Worst."
Question: How are the millennials different in the workforce?
Robert Sutton: So this question of whether or not there is generational differences, I think... at the broad brush level I think that all human groups, and the research shows, anthropological research going back to preindustrial times we actually want the same kind of leader, but the nuances are different depending on the generation. What we want, it turns out is we want a boss who is competent and not selfish or benevolent. So in the book I describe this as a boss who is good at performance, getting performance out of people, training them, supporting them in doing their job well and supports dignity and respect. And so the idea of having competence and benevolence or competence and compassion you can see that all through research going way back. Those are the people who tend to rise to the leadership positions in preindustrial tribes and those are the people who we also want as our leaders. So at the most abstract level that is who we want to lead us as human beings.
But at different times the question of what somebody who has got your back or is compassionate I think that gets reinterpreted, so one of the issues that the millennials have, which for example my parents didn’t have and even my generation to a lesser extent is that first of all they want to… both men and women want to be more involved in raising their kids if they have kids, so in that case having a job where you’re working 75 hours a week doesn’t work out too well for everyone. And another thing that has happened with the millennials that’s different than their parents or even to some extent my generation—and I definitely see this at Stanford with my students—is,, boy did I see it the last couple years, is in my family and other families you’d see that somebody would work for a large corporation for years and would be okay, but what has happened to their parents is, well they’ve learned—and they always say the man, it’s funny—they've learned not to trust the man, that the man is going to screw them in the end and in fact, that is the new employment contract, so it always sort of amazes me when I see executives from big corporations and they say, "I don’t know why they don’t trust me." Well you’ve been... layoffs are at an all time high and in fact there is evidence it isn’t just the economic times that layoffs are becoming more an increasingly sort of frequent response to economic troubles. They happen quicker and they happen deeper and then there is fewer organizations with pension plans.
Essentially the employment contract has changed, so my perspective on the millennials is no wonder you act that way. You’ve been taught that the man is going to screw you—or sometimes the woman if you’re working from somebody like Meg Whitman or something. Or Carly Florina who actually laid off lots of people. Meg didn’t layoff very many people. So in some ways the millennials are acting completely rational and therefore I guess the definition of a competent and compassionate boss changes. It’s somebody who is skilled at giving you the skills and abilities and connections you need to continue throughout your career even after they fire you, so I do think that relationship has changed some, and I guess that the definition of a nice boss is nastier than it used to be. You can be known as nice and still do pretty nasty things to people.
Question: Can leadership be taught?
Robert Sutton: Well so the notion is and as a business book author I should probably make the argument you should buy my book and all your problems are solved, but anybody who tells you that by taking this class or reading my book you will magically become a good boss is lying to you.
But the analogy I use is a little bit like medicine, that what you want is a doctor who both has a lot of experience and a doctor who actually knows what the latest research is. Because experience is sort of a dangerous teacher in some ways. It’s good to have the craft knowledge, but you also need to sort of leaven that with the mistakes that many other people have made in more systematic evidence and so I think you sort of need the one-two punch of both of them and one thing that really does strike me is that some of the most effective and impressive bosses an managers to me are people who are hungry to get as much experience as possible, so I think that is true for the millennials or anybody else who takes a job—you want to have as much different sort of management experience as possible—and also hungry to sort of, if you will, consumer information from diverse sources.
So I guess the quote, the Eleanor Roosevelt quote I use in the book is that it’s good to learn from other people’s mistakes because you can’t live long enough to make all those mistakes yourself and although there is an argument for learning from your own mistakes, so to me it’s sort of a balance between the two and very much, especially over the years I’ve sort of developed this notion that management... it’s a craft and I think medicine is an appropriate comparison where you can practice the craft better if you know the best research, but if you haven’t done it there is no way to learn about it. By the way, that is one thing I do like about startup—and teaching at Stanford a lot of the students go into startups—is when you go into a startup you’re thrown in sort of the belly of the beast and you get to do all this management stuff that in a big corporation you’d be protected from. And in fact, I think that some of the best employees of big corporations, I’m thinking of like Facebook, which is actually pretty big, and Google and stuff. Some of the best managers they have are people who have sort of like grown that startup and they’ll chafe against the larger bureaucracy to some extent, but they sort of know what it takes to make things work. So I’m a big believer that sort of first job out of school that starting your own business. Even if you fail, it will have all sorts of rewards the rest of your life in terms of being able to get stuff done because you actually get practice doing management-type stuff.
Question: What can a manager learn from failure?
Robert Sutton: There is no way that people can learn without failing and if you can show me a situation I would love to see the situation where just magically you can parachute in and be instantly lucky and brilliant and you know I think of some of the heroes of our day from Steve Jobs to Mark Zuckerberg and stuff, and right now Zuckerberg is like well a bit of a darling and a bit of an enemy with... he is CEO of Facebook. But like they have made an enormous number of mistakes. And Facebook is a good example because some of us may remember a couple of years back they had this thing come out where automatically if you just went to a restaurant or anything you did would sort of like show up on your... or you bought something it would show up on your Facebook page and God knows, people were probably buying you know pornography or whatever. It would just sort of like show up on their Facebook page unless they stopped it. Well those sort of mistakes actually are part of the process of learning. Zuckerberg is an interesting example because although he is a controversial character he definitely has the guts to try stuff that might offend people, but also sort of push the envelope.
But the argument that I’ve made about failures in bosses, though, in some ways to oversimplify it, when I think about failure there is three general sorts of responses that emerge from both the management literature in practice. The first one is what I call the forgive and forget approach and so just I’m going to see my teenage daughter after this. She is now in college, but an example of the forgive and forget approach is so the first actually day she had her learner’s permit through a series of events I still don’t understand she ran my wife’s brand new Infinity, so it had 300 miles in it, into our house and did $2,000 worth of damage to the car and $500 worth of damage to the house. And her reaction was she wanted us to forgive her and to forget about it and the problem with forgive and forget is there is like no accountability and there is no learning. The second approach is what I call the Silicon Valley standard. This is remember, blame, stigmatize, ostracize and humiliate. And the problem with that is that when you sort of humiliate people or put them down when they fail then they’re afraid to admit mistakes and the whole world turns into a cover-your-ass sort of game, so no learning occurs. And the way that the most effective organizations and in fact, if you look at research on hospitals that learn from medical mistakes—this is sort of the mantra they sometimes use—it’s to forgive and remember. So you forgive to have some psychological safety and you remember so that you can learn from your own mistakes and other people’s mistakes. And the other reason your remember is that if people keep making the same mistakes over and over again then there is some accountability and it’s a sign you’ve kind of got to get rid of them or have them do something else.
But failure is a complicated thing and just as a final point about failure Tom Peters and on down, management theorists I guess including me have celebrated the virtues of failure, but one thing that I’m always very careful to say is I don’t like failure. I think it sucks. It’s a terrible thing. I wish it wasn’t necessary, but I can’t figure out any other way for people to learn how to do most things, but to sort of screw up enough until the point where they get better at it.
Recorded September 13, 2010
Interviewed by John Cookson
Failure is a terrible thing, but there's no other way for people to learn how to do most things except to screw up enough until the point where they get better at it.
If machines develop consciousness, or if we manage to give it to them, the human-robot dynamic will forever be different.
- Does AI—and, more specifically, conscious AI—deserve moral rights? In this thought exploration, evolutionary biologist Richard Dawkins, ethics and tech professor Joanna Bryson, philosopher and cognitive scientist Susan Schneider, physicist Max Tegmark, philosopher Peter Singer, and bioethicist Glenn Cohen all weigh in on the question of AI rights.
- Given the grave tragedy of slavery throughout human history, philosophers and technologists must answer this question ahead of technological development to avoid humanity creating a slave class of conscious beings.
- One potential safeguard against that? Regulation. Once we define the context in which AI requires rights, the simplest solution may be to not build that thing.
Duke University researchers might have solved a half-century old problem.
- Duke University researchers created a hydrogel that appears to be as strong and flexible as human cartilage.
- The blend of three polymers provides enough flexibility and durability to mimic the knee.
- The next step is to test this hydrogel in sheep; human use can take at least three years.
Duke researchers have developed the first gel-based synthetic cartilage with the strength of the real thing. A quarter-sized disc of the material can withstand the weight of a 100-pound kettlebell without tearing or losing its shape.
Photo: Feichen Yang.<p>That's the word from a team in the Department of Chemistry and Department of Mechanical Engineering and Materials Science at Duke University. Their <a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/adfm.202003451" target="_blank">new paper</a>, published in the journal,<em> Advanced Functional Materials</em>, details this exciting evolution of this frustrating joint.<br></p><p>Researchers have sought materials strong and versatile enough to repair a knee since at least the seventies. This new hydrogel, comprised of three polymers, might be it. When two of the polymers are stretched, a third keeps the entire structure intact. When pulled 100,000 times, the cartilage held up as well as materials used in bone implants. The team also rubbed the hydrogel against natural cartilage a million times and found it to be as wear-resistant as the real thing. </p><p>The hydrogel has the appearance of Jell-O and is comprised of 60 percent water. Co-author, Feichen Yang, <a href="https://today.duke.edu/2020/06/lab-first-cartilage-mimicking-gel-strong-enough-knees" target="_blank">says</a> this network of polymers is particularly durable: "Only this combination of all three components is both flexible and stiff and therefore strong." </p><p> As with any new material, a lot of testing must be conducted. They don't foresee this hydrogel being implanted into human bodies for at least three years. The next step is to test it out in sheep. </p><p>Still, this is an exciting step forward in the rehabilitation of one of our trickiest joints. Given the potential reward, the wait is worth it. </p><p><span></span>--</p><p><em>Stay in touch with Derek on <a href="http://www.twitter.com/derekberes" target="_blank">Twitter</a>, <a href="https://www.facebook.com/DerekBeresdotcom" target="_blank">Facebook</a> and <a href="https://derekberes.substack.com/" target="_blank">Substack</a>. His next book is</em> "<em>Hero's Dose: The Case For Psychedelics in Ritual and Therapy."</em></p>
What would it be like to experience the 4th dimension?
Physicists have understood at least theoretically, that there may be higher dimensions, besides our normal three. The first clue came in 1905 when Einstein developed his theory of special relativity. Of course, by dimensions we’re talking about length, width, and height. Generally speaking, when we talk about a fourth dimension, it’s considered space-time. But here, physicists mean a spatial dimension beyond the normal three, not a parallel universe, as such dimensions are mistaken for in popular sci-fi shows.
An algorithm may allow doctors to assess PTSD candidates for early intervention after traumatic ER visits.
- 10-15% of people visiting emergency rooms eventually develop symptoms of long-lasting PTSD.
- Early treatment is available but there's been no way to tell who needs it.
- Using clinical data already being collected, machine learning can identify who's at risk.
The psychological scars a traumatic experience can leave behind may have a more profound effect on a person than the original traumatic experience. Long after an acute emergency is resolved, victims of post-traumatic stress disorder (PTSD) continue to suffer its consequences.
In the U.S. some 30 million patients are annually treated in emergency departments (EDs) for a range of traumatic injuries. Add to that urgent admissions to the ED with the onset of COVID-19 symptoms. Health experts predict that some 10 percent to 15 percent of these people will develop long-lasting PTSD within a year of the initial incident. While there are interventions that can help individuals avoid PTSD, there's been no reliable way to identify those most likely to need it.
That may now have changed. A multi-disciplinary team of researchers has developed a method for predicting who is most likely to develop PTSD after a traumatic emergency-room experience. Their study is published in the journal Nature Medicine.
70 data points and machine learning
Image source: Creators Collective/Unsplash
Study lead author Katharina Schultebraucks of Columbia University's Department Vagelos College of Physicians and Surgeons says:
"For many trauma patients, the ED visit is often their sole contact with the health care system. The time immediately after a traumatic injury is a critical window for identifying people at risk for PTSD and arranging appropriate follow-up treatment. The earlier we can treat those at risk, the better the likely outcomes."
The new PTSD test uses machine learning and 70 clinical data points plus a clinical stress-level assessment to develop a PTSD score for an individual that identifies their risk of acquiring the condition.
Among the 70 data points are stress hormone levels, inflammatory signals, high blood pressure, and an anxiety-level assessment. Says Schultebraucks, "We selected measures that are routinely collected in the ED and logged in the electronic medical record, plus answers to a few short questions about the psychological stress response. The idea was to create a tool that would be universally available and would add little burden to ED personnel."
Researchers used data from adult trauma survivors in Atlanta, Georgia (377 individuals) and New York City (221 individuals) to test their system.
Of this cohort, 90 percent of those predicted to be at high risk developed long-lasting PTSD symptoms within a year of the initial traumatic event — just 5 percent of people who never developed PTSD symptoms had been erroneously identified as being at risk.
On the other side of the coin, 29 percent of individuals were 'false negatives," tagged by the algorithm as not being at risk of PTSD, but then developing symptoms.
Image source: Külli Kittus/Unsplash
Schultebraucks looks forward to more testing as the researchers continue to refine their algorithm and to instill confidence in the approach among ED clinicians: "Because previous models for predicting PTSD risk have not been validated in independent samples like our model, they haven't been adopted in clinical practice." She expects that, "Testing and validation of our model in larger samples will be necessary for the algorithm to be ready-to-use in the general population."
"Currently only 7% of level-1 trauma centers routinely screen for PTSD," notes Schultebraucks. "We hope that the algorithm will provide ED clinicians with a rapid, automatic readout that they could use for discharge planning and the prevention of PTSD." She envisions the algorithm being implemented in the future as a feature of electronic medical records.
The researchers also plan to test their algorithm at predicting PTSD in people whose traumatic experiences come in the form of health events such as heart attacks and strokes, as opposed to visits to the emergency department.