from the world's big
Did HBS Contribute to the Financial Crisis?
Jay Light is the former dean of Harvard Business School and a professor emeritus. He joined the faculty of HBS in December 1969. After a brief leave of absence from 1977 to 1979 to serve as director of investment and financial policies for the Ford Foundation, he returned to HBS as a full professor. He oversaw a range of innovations in the School's MBA program, including the new January term, Immersion Experience Programs (a portfolio of faculty-led seminars in selected regions around the world), and the launch and development of joint degree programs with Harvard's Medical School and Kennedy School.
Question: Did HBS play any role in causing the financial crisis?
Jay Light: Now to be sure it was largely the government’s legislatures, the Fannie Mae, Freddie Mac in this country, the federal agencies and the financial institutions that were most directly involved, but also many of them showed a failure to really think broadly about risk and about how bad things could get and I think that reflects you know for the prior 25 years we hadn’t seen a lot of downside and frankly, all of us got out of the habit of thinking about the downside and at business schools we got out of the habit of teaching about the downside, so in fact, in the 1970s I used to teach a course called "Capital Markets: The Financial System" here, which was in fact, all about these ideas; all about the kinds of risks that could arise from changing financial markets and the mortgage markets and the consumer credit markets and the commercial loan markets. Those kinds of courses both here and at other business schools had largely atrophied. There was relatively little student demand for them. The faculty was more interested in teaching about other things too, so the curriculums got focused on the upside if you will, the how does one increase market share, how do you increase earnings per share, how do you think about how to grow a bigger and better institution.
And that’s great. That is what you should be thinking about except at the same time you have to keep an eye on "How could things go wrong? What kinds of data should I really be putting into my risk management model?" In a world where housing prices were in a bubble and where consumer lending organizations were in fact incenting consumers to borrow at very, very high loan to apparent value ratios the old data that one put into risk models was completely, completely out of touch with the changing reality as became so quickly apparent when the whole down leg started. So I think it was a failure of leadership in the sense that it was a failure to think in a broad and creative and responsive way about risk. There were also some ethical failures I think as there are when any bubble collapses, but the single most important lesson coming out of this crisis in my judgment was more about values and judgment and how you think about analyzing and keeping your eye on the downside in a complex interconnected world.
Question: Is the solution to minimize risk?
Jay Light: Well so I think there is the need for some structural change. A good example is we can’t ever again let true leverage in a financial system get up to the same levels it had gotten to, so we need to insist upon more robust measures of capital, financial capital in a financial institution. We need to insist upon lower leverage ratios. We need to insist upon more stringent liquidity criteria, so there is a regulatory response that I think is much needed and is in the process of being developed. There are also a set of related question about just how interconnected one wants the scope of financial institutions and whether large institutions ought to be forced to divest certain of the activities they’re in and if so just which activities. And that is a more complex question and but I think some real regulatory reform would be appropriate and is quite likely there also.
There is on the other hand, a real danger here because I think what our economy needs more than anything else as a nation is innovation and innovation means we need people to provide funds to different kinds of new companies doing different kinds of new and innovative things and one can go overboard with the vilification of financial institutions. One can go overboard with strenuous and hard to understand regulation that causes firms to become much more risk averse across the board even if the possible things that they could be… might be funding could turn out to be the very innovative kinds of things we need to do as a country, so I think one has to always have a balance here. The pendulum for sure has swung back now towards managing risk, towards thinking about the downside both from a regulatory point of view and from the point of view of those people who manage financial institutions, but there is a danger that the latter could go too far. Indeed there is lots of evidence I think right now that it is going too far, so keeping a balance there between thinking about upon an entrepreneurial perspective on the evolving economy and the evolving financial system while at the same time worrying about risk is where we want to come out and it’s a complex every changing thing that requires enormous amounts of judgment and leadership.
Recorded May 19, 2010
Interviewed by Jessica Liebman
Business schools may not have been focused enough on teaching future leaders how to keep an eye on the downside in an interconnected world.
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.