Manifold Podcast #22 Jamie Metzl on Hacking Darwin: Genetic Engineering and the Future of Humanity

Jamie Metzl joins Corey and Steve to discuss his new book, Hacking Darwin. They discuss detailed predictions for the progress in genomic technology, particularly in human reproduction, over the coming decade: genetic screening of embryos will become commonplace, gene-editing may become practical and more widely accepted, stem cell technology may allow creation of unlimited numbers of eggs and embryos. Metzl is a Technology Futurist, Geopolitics Expert, and Sci-Fi Novelist. He was appointed to the World Health Organization expert advisory committee governance and oversight of human genome editing. Jamie previously served in the U.S. National Security Council, State Department, Senate Foreign Relations Committee and as a Human Rights Officer for the United Nations in Cambodia. He holds a Ph.D. in Southeast Asian history from Oxford University and a J.D. from Harvard Law School.

Transcript

Hacking Darwin: Genetic Engineering and the Future of Humanity

Jamie Metzl (web site)


man·i·fold /ˈmanəˌfōld/ many and various.

In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point.

Steve Hsu and Corey Washington have been friends for almost 30 years, and between them hold PhDs in Neuroscience, Philosophy, and Theoretical Physics. Join them for wide ranging and unfiltered conversations with leading writers, scientists, technologists, academics, entrepreneurs, investors, and more.

Steve Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.

Corey Washington is Director of Analytics in the Office of Research and Innovation at Michigan State University. He was educated at Amherst College and MIT before receiving a PhD in Philosophy from Stanford and a PhD in a Neuroscience from Columbia. He held faculty positions at the University Washington and the University of Maryland. Prior to MSU, Corey worked as a biotech consultant and is founder of a medical diagnostics startup.

Future Investment Initiative (Riyadh)

I'm making my way home from the FUTURE INVESTMENT INITIATIVE 2019 in Riyadh, Saudi Arabia​​​. At the moment I am sitting in a Lufthansa lounge at Frankfurt.

The annual event is sponsored by the Saudi sovereign wealth fund, or PIF (Public Investment Fund), which is one of the largest pools of capital in the world.

The meeting this year had an AI theme, and I spoke in the AI and Health (genomics) session. The mix of people was very interesting -- VC, hedge fund, and private equity investors (among other things, looking for allocations from PIF), tech entrepreneurs, policy and government people, etc. There was a large Chinese contingent at the meeting, and a strong Huawei presence. IIUC the telco infrastructure in the Kingdom uses a lot of Huawei gear.

I got a Star Wars cantina in business suits vibe from the thousands of attendees at the Ritz. The various global tribes were there in almost equal mixture -- Americans (Silicon Valley + NY money), Euro-grifters, money men, technologists, spooks, government suits, Chinese, Arabs, Indians, Russians (even Sputnik News). The Kingdom is really at the global crossroads.

Right away on the first day I "bumped into" someone from the US embassy. Her card says State, but I suspect another agency with three letters.

My hotel was in the DQ or Diplomatic Quarter, not far from the Ritz. The DQ is separated from the rest of the city by serious security checkpoints. The Saudi soldiers like to wear their pistols low on the thigh with cool looking black polymer "gunfighter" holsters.

See also The Geopolitics of US Global Decline: Beijing and Washington Struggle for Dominion over the World Island.

Kaifu Lee and Stephen Schwarzman dialog.

Our panel on AI and Health was held here:

The gala reception in the King Abdullah Financial District. An interesting little drone hovered above the crowd all evening.

My speaker pass. I had a driver and was able to get through the numerous security checkpoints quickly using this. MBS has his own elite Royal Guard, and they were in evidence at the event.

Over the summer I also spoke at the Tallinn Digital Summit and the World Congress of Information Technology in Yerevan Armenia -- lots of travel! I haven't even had time to blog about these events. There are videos of my talks and panels I will try to post at some point.

TDS 2019: Panel on AI social and political impacts
https://youtu.be/fddG7hQkkW4

TDS 2019 Parallel Breakout Sessions I: AI in Healthcare
https://youtu.be/atOnB1dW0OA

Tallinn Digital Summit YouTube Channel
https://www.youtube.com/channel/UC9ptGynkOPe3vFRW6otoI3g

Genomic Prediction of 16 Complex Disease Risks Including Heart Attack, Diabetes, Breast and Prostate Cancer (Nature Scientific Reports)

Published online today!

Genomic Prediction of 16 Complex Disease Risks Including Heart Attack, Diabetes, Breast and Prostate Cancer

Louis Lello, Timothy G. Raben, Soke Yuen Yong, Laurent C. A. M. Tellier & Stephen D. H. Hsu

Nature Scientific Reports volume 9, Article number: 15286 (2019)

We construct risk predictors using polygenic scores (PGS) computed from common Single Nucleotide Polymorphisms (SNPs) for a number of complex disease conditions, using L1-penalized regression (also known as LASSO) on case-control data from UK Biobank. Among the disease conditions studied are Hypothyroidism, (Resistant) Hypertension, Type 1 and 2 Diabetes, Breast Cancer, Prostate Cancer, Testicular Cancer, Gallstones, Glaucoma, Gout, Atrial Fibrillation, High Cholesterol, Asthma, Basal Cell Carcinoma, Malignant Melanoma, and Heart Attack. We obtain values for the area under the receiver operating characteristic curves (AUC) in the range ~0.58–0.71 using SNP data alone. Substantially higher predictor AUCs are obtained when incorporating additional variables such as age and sex. Some SNP predictors alone are sufficient to identify outliers (e.g., in the 99th percentile of polygenic score, or PGS) with 3–8 times higher risk than typical individuals. We validate predictors out-of-sample using the eMERGE dataset, and also with different ancestry subgroups within the UK Biobank population. Our results indicate that substantial improvements in predictive power are attainable using training sets with larger case populations. We anticipate rapid improvement in genomic prediction as more case-control data become available for analysis.

From the Discussion:

The significant heritability of most common disease conditions implies that at least some of the variance in risk is due to genetic effects. With enough training data, modern machine learning techniques enable us to construct polygenic predictors of risk. A learning algorithm with enough examples to train on can eventually identify individuals, based on genotype alone, who are at unusually high risk for the condition. This has obvious clinical applications: scarce resources for prevention and diagnosis can be more efficiently allocated if high risk individuals can be identified while still negative for the disease condition. This identification can occur early in life, or even before birth.

In this paper we used UK Biobank data to construct predictors for a number of conditions. We conducted out of sample testing using eMERGE data (collected from the US population) and adjacent ancestry (AA) testing using UK ethnic subgroups distinct from the training population. The results suggest that our polygenic scores indeed predict complex disease risk - there is very strong agreement in performance between the training and out of sample testing populations. Furthermore, in both the training and test populations the distribution of PGS is approximately Gaussian, with cases having on average higher scores. We verify that, for all disease conditions studied, a simple model of displaced Gaussian distributions predicts empirically observed odds ratios (i.e., individual risk in test population) as a function of PGS. This is strong evidence that the polygenic score itself, generated for each disease condition using machine learning, is indeed capturing a nontrivial component of genetic risk.

By varying the amount of case data used in training, we estimate the rate of improvement of polygenic predictors with sample size. Plausible extrapolations suggest that sample sizes readily within reach of population genetics studies will result in predictors of significant clinical utility. ...

Manifold Podcast #21: Tyler Cowen on Big Business, Socialism, Free Speech, and Stagnant Productivity Growth

Polymath and economist Tyler Cowen (Holbert L. Harris Professor at GMU) joins Steve and Corey for a wide-ranging discussion. Are books just for advertising? Have blogs peaked? Are podcasts the future or just a bubble? Is technological change slowing? Is there less political correctness in China than the US? Tyler's new book, an apologia for big business, inspires a discussion of CEO pay and changing public attitudes toward socialism. They investigate connections between populism, stagnant wage growth, income inequality and immigration. Finally, they discuss the future global order and trajectories of the US, EU, China, and Russia.

Transcript

Personal Website

Marginal Revolution (Blog)

Conversations with Tyler (Podcast)

Tyler Cowen | Bloomberg Opinion Columnist

Big Business: A Love Letter to an American Anti-Hero (Book)


man·i·fold /ˈmanəˌfōld/ many and various.

In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point.

Steve Hsu and Corey Washington have been friends for almost 30 years, and between them hold PhDs in Neuroscience, Philosophy, and Theoretical Physics. Join them for wide ranging and unfiltered conversations with leading writers, scientists, technologists, academics, entrepreneurs, investors, and more.

Steve Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.

Corey Washington is Director of Analytics in the Office of Research and Innovation at Michigan State University. He was educated at Amherst College and MIT before receiving a PhD in Philosophy from Stanford and a PhD in a Neuroscience from Columbia. He held faculty positions at the University Washington and the University of Maryland. Prior to MSU, Corey worked as a biotech consultant and is founder of a medical diagnostics startup.

Brexit: Down to the Wire

Get ready for the general election!

Over the summer I was at the Tallinn Digital Summit in Estonia. At dinner, sitting across from a UN official, I expressed to his initial incredulity that the victory of Vote Leave three years ago was a triumph of the human spirit: a small team of talented individuals defeated overwhelmingly powerful forces arrayed against them -- the UK government, the media, the elites. After some discussion, he came to understand my perspective.

This time the good guys are in Number 10 and the odds are in their favor in the coming election.

Having some insight into what is happening in UK politics, I can assure you that most of what is reported in the media is junk. Sometimes the story is deliberately distorted, sometimes it's just stupidity at work. But you are foolish if you trust the media, in the UK or US. Just as we know that ~50% of published results in biomedical or social psychology journals fails to replicate, it is easy to do a simple look back to see that information from the media is highly unreliable.

I was struck by this photo today in the NYTimes:

A Brexit meeting of European Union ministers on Tuesday in Luxembourg

Compare to Kubrick's Dr. Strangelove :-)

The Quantum Simulation Hypothesis: Do we live in a quantum multiverse simulation?

The Simulation Hypothesis is the idea that our universe might be part of a simulation: we are not living in base reality. (See, e.g., earlier discussion here.)



There are many versions of the argument supporting this hypothesis, which has become more plausible (or at least more popular) over time as computational power, and our familiarity with computers and virtual worlds within them, has increased.

Modern cosmology suggests that our universe, our galaxy, and our solar system, have billions of years ahead of them, during which our civilization (currently only ~10ky old!), and others, will continue to evolve. It seems reasonable that technology and science will continue to advance, delivering ever more advanced computational platforms. Within these platforms it is likely that quasi-realistic simulations, of our world, or of imagined worlds (e.g., games), will be created, many populated by AI agents or avatars. The number of simulated beings could eventually be much larger than the number of biologically evolved sentient beings. Under these assumptions, it is not implausible that we ourselves are actually simulated beings, and that our world is not base reality.

One could object to using knowledge about our (hypothetically) simulated world to reason about base reality. However, the one universe that we have direct observational contact with seems to permit the construction of virtual worlds with large populations of sentient beings. While our simulation may not be entirely representative of base reality, it nevertheless may offer some clues as to what is going on "outside"!

The simulation idea is very old. It is almost as old as computers themselves. However, general awareness of the argument has increased significantly, particularly in the last decade. It has entered the popular consciousness, transcending its origins in the esoteric musings of a few scientists and science fiction authors.

The concept of a quantum computer is relatively recent -- one can trace the idea back to Richard Feynman's early-1980s Caltech course: Physical Limits to Computation. Although quantum computing has become a buzzy part of the current hype cycle, very few people have any deep understanding of what a quantum computer actually is, and why it is different from a classical computer. A prerequisite for this understanding is a grasp of both the physical and mathematical aspects of quantum mechanics, which very few possess. Individuals who really understand quantum computing tend to have backgrounds in theoretical physics, physics, or perhaps computer science or mathematics.

The possibility of quantum computers requires that we reformulate the Simulation Hypothesis in an important way. If one is willing to posit future computers of gigantic power and complexity, why not quantum computers of arbitrary power? And why not simulations which run on these quantum computers, making use of quantum algorithms? After all, it was Feynman's pioneering observation that certain aspects of the quantum world (our world!) are more efficiently simulated using a quantum computer than a classical (e.g., Turing) machine. (See quantum extension of the Church-Turing thesis.) Hence the original Simulation Hypothesis should be modified to the Quantum Simulation Hypothesis: Do we live in a quantum simulation?

There is an important consequence for those living in a quantum simulation: they exist in a quantum multiverse. That is, in the (simulated) universe, the Many Worlds description of quantum mechanics is realized. (It may also be realized in base reality, but that is another issue...) Within the simulation, macroscopic, semiclassical brains perceive only one branch of the almost infinite number of decoherent branches of the multiverse. But all branches are realized in the execution of the unitary algorithm running on qubits. The power of quantum computing, and the difficulty of its realization, both derive from the requirement that entanglement and superposition be maintained in execution.

Given sufficiently powerful tools, the beings in the simulation could test whether quantum evolution of qubits under their control is unitary, thereby verifying the absence of non-unitary wavefunction collapse, and the existence of other branches (see, e.g., Deutsch 1986).



We can give an anthropic version of the argument as follows.

1. The physical laws and cosmological conditions of our universe seem to permit the construction of large numbers of virtual worlds containing sentient beings.

2. These simulations could run on quantum computers, and in fact if the universe being simulated obeys the laws of quantum physics, the hardware of choice is a quantum computer. (Perhaps the simulation must be run on a quantum computer!)

If one accepts points 1 and 2 as plausible, then: Conditional on the existence of sentient beings who have discovered quantum physics (i.e., us), the world around them is likely to be a simulation running on a quantum computer. Furthermore, these beings exist on a branch of the quantum multiverse realized in the quantum computer, obeying the rules of Many Worlds quantum mechanics. The other branches must be there, realized in the unitary algorithm running on (e.g., base reality) qubits.

See also

Gork revisited 2018

Are You Gork?

Big Ed

AI in the Multiverse: Intellects Vast and Cold

In quantum mechanics the state of the universe evolves deterministically: the state of the entire universe at time zero fully determines its state at any later time. It is difficult to reconcile this observation with our experience as macroscopic, nearly classical, beings. To us it seems that there are random outcomes: the state of an electron (spin-up in the z direction) does not in general determine the outcome of a measurement of its spin (x direction measurement probability 1/2 of either spin up or down). This is because our brains (information processing devices) are macroscopic: one macroscopic state (memory record) is associated with the spin up outcome, which rapidly loses contact (decoheres) from the other macroscopic state with memory record of the spin down outcome. Nevertheless, the universe state, obtained from deterministic Schrodinger evolution of the earlier state, is a superposition:

| brain memory recorded up, spin up >

+

| brain memory recorded down, spin down >.


We are accustomed to thinking about classical information processing machines: brains and computers. However, with the advent of quantum computers a new possibility arises: a device which (necessarily) resides in a superposition state, and uses superposition as an integral part of its information processing.

What can we say about this kind of (quantum) intelligence? Must it be "artificial"? Could there be a place in the multiverse where evolved biological beings use superposition and entanglement as a resource for information processing?

Any machine of the type described above must be vast and cold. Vast, because many qubits are required for self-awareness and consciousness (just as many bits are required for classical AI). Cold, because decoherence destroys connections across superpositions. Too much noise (heat), and it devolves back to isolated brains, residing on decohered branches of the wavefunction.

One could regard human civilization as a single intelligence or information processing machine. This intelligence is rapidly approaching the point where it will start to use entanglement as a significant resource. It is vast, and (in small regions -- in physics labs) cold enough. We can anticipate more and larger quantum computers distributed throughout our civilization, making greater and greater use of nearby patches of the multiverse previously inaccessible.

Perhaps some day a single quantum computer might itself be considered intelligent -- the first of new kind!

What will it think?

Consciousness in a mini multiverse... Thoughts which span superpositions.


See also Gork revisited 2018 and Are You Gork?

Combat Drones

These are inexpensive, slow-moving drones -- but potentially quite effective. The Turkish drone should have "lock in" capability on stationary targets, so that the radio link to the operator is unnecessary near the end of the flight (i.e., the drone is invulnerable to jamming near the target).

A larger drone such as an ASBM (Anti-Ship Ballistic Missile) or UAV would not need the operator to perform the targeting  -- it could have enough AI/ML to recognize an aircraft carrier from ~10km distance (e.g., using some combination of visual, IR, radar imaging). Given a satellite fix on the carrier location, just launch to that coordinate and let the AI/ML do final targeting.

See also

Death from the Sky: Drone Assassination

Assassination by Drone

Strategic Implications of Drone/Missile Strikes on Saudi Arabia

Manifold Podcast #20: Betsy McKay (WSJ) on Heart Disease and Health

Steve and Corey talk to Betsy McKay, senior writer on U.S. and global public health at The Wall Street Journal, about her recent articles on heart disease. Betsy describes how background reporting led to her article linking the recent drop in life expectancy in the United States, often attributed to the opioid crisis or increases in middle age suicides due to economic despair, to the increasing prevalence of heart disease, driven by the rise in obesity. The three also discuss current public health recommendations on how to reduce heart disease risk and on the use of calcium scans to assess arterial plaque buildup. Steve describes boutique medical programs available to the super-rich that include full body scans to search for early signs of disease. Betsy elaborates on how she approached reporting on a new study linking egg consumption to higher cholesterol and increased risk of death, a result at odds with other recent findings and national recommendations that two eggs a day eggs is safe and healthy. Finally, they consider whether people are wasting money on buying fish oil supplements.

[ At about 20m I discuss how I got on the keto diet... ]

Transcript

Death Rates Rising for Young, Middle-Aged U.S. Adults

How to Reduce Your Risk of Heart Disease

New BP guidelines that set elevated BP as above 120mmHG/80 and Stage 1 hypertension is 120-130/80-90, Stage 2 140/90 or above.

New ACC/AHA High Blood Pressure Guidelines Lower Definition of Hypertension

Heart Attack at 49—America’s Biggest Killer Makes a Deadly Comeback

Study Links Eggs to Higher Cholesterol and Risk of Heart Disease

Fish Oil: Hunting for Evidence to Tip the Scales

Don’t Use Bootleg or Street Vaping Products, C.D.C. Warns


man·i·fold /ˈmanəˌfōld/ many and various.

In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point.

Steve Hsu and Corey Washington have been friends for almost 30 years, and between them hold PhDs in Neuroscience, Philosophy, and Theoretical Physics. Join them for wide ranging and unfiltered conversations with leading writers, scientists, technologists, academics, entrepreneurs, investors, and more.

Steve Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.

Corey Washington is Director of Analytics in the Office of Research and Innovation at Michigan State University. He was educated at Amherst College and MIT before receiving a PhD in Philosophy from Stanford and a PhD in a Neuroscience from Columbia. He held faculty positions at the University Washington and the University of Maryland. Prior to MSU, Corey worked as a biotech consultant and is founder of a medical diagnostics startup.

Harvard Discrimination Lawsuit: Judge Burroughs on Racial Balancing and "Unhooked" Applicants

As has been widely reported (WSJ):

U.S. District Judge Allison Burroughs found that Harvard’s practices were “not perfect” and could use improvements, including implicit bias training for admissions officers, but said “the Court will not dismantle a very fine admissions program that passes constitutional muster, solely because it could do better.”

I anticipate that this case will end up before the Supreme Court.

While I have not read the entire decision (PDF), I was curious to see how two important arguments made by the plaintiffs (Students For Fair Admissions, SFFA) were addressed. You can evaluate Burroughs' logic and use of evidence for yourself. In the excerpts below I first quote from the SFFA filing, and then from the decision.

Issue #1: Racial Balancing:

SFFA: ... Harvard is engaging in racial balancing. Over an extended period, Harvard’s admission and enrollment figures for each racial category have shown almost no change. Each year, Harvard admits and enrolls essentially the same percentage of African Americans, Hispanics, whites, and Asian Americans even though the application rates and qualifications for each racial group have undergone significant changes over time. This is not the coincidental byproduct of an admissions system that treats each applicant as an individual; indeed, the statistical evidence shows that Harvard modulates its racial admissions preference whenever there is an unanticipated change in the yield rate of a particular racial group in the prior year. Harvard’s remarkably stable admissions and enrollment figures over time are the deliberate result of systemwide intentional racial discrimination designed to achieve a predetermined racial balance of its student body.

This is a relevant figure from the Economist. It shows the increase in Asian representation at Caltech (mostly race-neutral admissions), tracking the overall population of college age Asian Americans, versus the suspicious Ivy league convergence at 15-20% of each class.

From page 80 of the decision:

Although Harvard tracks and considers various indicators of diversity in the admissions process, including race, the racial composition of Harvard’s admitted classes has varied in a manner inconsistent with the imposition of a racial quota or racial balancing. See [Oct. 31 Tr. 119:10–121:10; DX711]. As Figures 1 and 2 show, there has been considerable year-to-year variation in the portion of Harvard’s class that identifies as Asian American since at least 1980.   [ italics mine ]

Figure 1 seems merely to show that admittance by race tends to fluctuate by 5-10% from year to year. No attempt at analysis of correlations across years -- i.e., to detect racial balancing.

Figure 2 seems to show that Asian American applicants are a smaller fraction of the class relative to their share of the applicant pool, whereas, e.g., this ratio is reversed for African Americans. Racial balancing would be found only in detailed comparisons of these ratios across several years, adjusting for strength of application, etc.

Rather than giving a serious analysis of racial balancing (is it actually happening?), Burroughs seems to explicitly support the practice in her comments on racial diversity:

p.30 To summarize the use of race in the admissions process, Harvard does not have a quota for students from any racial group, but it tracks how each class is shaping up relative to previous years with an eye towards achieving a level of racial diversity that will provide its students with the richest possible experience. It monitors the racial distribution of admitted students in part to ensure that it is admitting a racially diverse class that will not be overenrolled based on historic matriculation rates which vary by racial group. [ Isn't this just a definition of racial balancing? ]

Quota Bad, Soft-Quota Good! Is this now the law of the land in the United States of America? SCOTUS here we come...


Issue #2: Is discrimination against Asian Americans especially obvious when one considers "unhooked" applicants separately?

SFFA: ... The task here is to determine whether “similarly situated” applicants have been treated differently on the basis of race; “apples should be compared to apples.” SBT Holdings, LLC v. Town of Westminster, 547 F.3d 28, 34 (1st Cir. 2008). Because certain applicants are in a special category, it is important to analyze the effect of race without them included. Excluding them allows for the effect of race to be tested on the bulk of the applicant pool (more than 95% of applicants and more than two-thirds of admitted students) that do not fall into one of these categories, i.e., the similarly situated applicants. For special-category applicants, race either does not play a meaningful role in their chances of admission or the discrimination is offset by the “significant advantage” they receive. Either way, they are not apples.

Professor Card’s inclusion of these applicants reflects his position that “there is no penalty against Asian-American applicants unless Harvard imposes a penalty on every Asian-American applicant.” But he is not a lawyer and he is wrong. It is illegal to discriminate against any Asian-American applicant or subset of applicants on the basis of race. Professor Card cannot escape that reality by trying to dilute the dataset. The claim here is not that Harvard, for example, “penalizes recruited athletes who are Asian-American because of their race.” The claim “is that the effects of Harvard’s use of race occur outside these special categories.” Professor Arcidiacono thus correctly excluded special-category applicants to isolate and highlight Harvard’s discrimination against Asian Americans. Professor Card, by contrast, includes “special recruiting categories in his models” to “obscure the extent to which race is affecting admissions decisions for those not fortunate enough to belong to one of these groups.” At bottom, SFFA’s claim is that Harvard penalizes Asian-American applicants who are not legacies or recruited athletes. Professor Card has shown that he is unwilling and unable to contest that claim.

The judge seems to have ignored or rejected the claim that discrimination within the pool of unhooked applicants (95% of the total!) is worth considering on its own. This seems to be an entirely legal (as opposed to statistical) question that may be tested in the appeal. (ALDC = Athletes, Legacies, Deans interest list (donors), and Children of Harvard faculty.)

p.52 Although ALDCs represent only a small portion of applicants and are admitted or rejected through the same admissions process that applies to other applicants, they account for approximately 30% of Harvard’s admitted class. [Oct. 30 Tr. 153:6–154:8, DX706; DD10 at 38, 40]. For reasons discussed more fully infra at Section V.F, the Court agrees with Professor Card that including ALDCs in the statistics and econometric models leads to more probative evidence of the alleged discrimination or lack thereof.

See also Former Yale Law Dean on Harvard anti-Asian discrimination case: The facts are just so embarrassing to Harvard... Quotas and a climate of dishonesty and comments therein.

Ronin

My first visit to Japan was in 1993. Ostensibly, I was there to attend a conference on High Energy Physics at the University of Tokyo, and to give a seminar at KEK, the largest particle accelerator laboratory in Japan.

I spent the first night at the Shinagawa Prince Hotel. I had carefully chosen this hotel -- it is a short walk from Sengakugi Temple, the resting place of the 47 Ronin (see photos above and history below).

It was already late at night when I checked in and deposited my luggage in the room. I was jet-lagged, but still energetic after the long trip. Outside, the neighborhood was deserted and dark except for the harsh glare of neon streetlights. It had rained and the streets were wet and shiny. As I approached the temple I could smell the burning incense that suffused the night air ...

47 Ronin (photo above from the 1941 movie directed by Kenji Mizoguchi)

... At the death of their lord, Asano’s samurai retainers become masterless, or rōnin, and under the planning of Ōishi Kuranosuke Yoshio, Asano’s counsellor, 47 of these rōnin plot to avenge their former master. Because Kira suspects this, and spies on Ōishi, revenge is delayed as the rōnin disperse and assume other occupations, while Ōishi performs the life of a drunkard, visiting taverns and geisha. After a year and a half the rōnin return to Edo to stake out Kira’s house, and two years following Asano’s death they attack. Kira is eventually killed and his head is taken as an offering to Asano’s grave. The rōnin then turn themselves in to the Shogunate authorities. Having defied a Shogunate edict prohibiting them to avenge their master, but having followed the requirements of bushido in doing so, the rōnin are sentenced to death but allowed to die honourably by committing seppuku.

I had all but forgotten about my strange visit to Sengakuji, so long ago. But memory returned when I came across the interview below, with former special forces soldier and tactical instructor Tu Lam.

Interview

When you started out in the world of Special Operations it was pre-9/11. What was that like compared to how it is now?

TL: My understanding from birth was one of war. I was born out of war. I was born in ’74 after the fall of Saigon. In ’76 they dragged us out into the streets of Vietnam because they were trying to impose the Communist ideologies of our government. My uncles were serving in the Navy and were dragged out into the streets like animals and shot. They separated our family and imprisoned my other uncles in what they called “re-education camps.” My grandfather took his life savings and smuggled us out of the country because my mom was like, “There’s no way my two sons will grow up under Communist rule.” We left on an overstuffed wooden boat with hundreds of other refugees. First we had to be navigated past the pirating that was going on. There were a lot of bandits, pirates and everyone who was leaving country had money. These pirates would intercept the refugees, rape the women, rob the boats and kill everyone on board.

We navigated past the pirates first then made it into Indonesia where the Coast Guard stopped us. They told us we couldn’t come into their country. They anchored us down and pulled us back into the ocean on lines, then shot our motor and cut the lines, leaving us out in the middle of the waters to die. Our boat drifted further and further into the ocean. My mother told me that people were stealing from each other, fighting, and eventually dying due to the terrible conditions. We were caught up in a storm and this storm took us out into the middle of Russian waters by the grace of God. A Russian supply boat picked us up as they were crossing the Pacific Ocean into Singapore. They dropped us off at a refugee camp in Indonesia. The irony of this story is the same ideology that took me out of my country (Communism) was the same ideology that brought me to safety.

My family was gunned down like animals by a Communist government and yet the Russians, another Communist government, saved us. That was my first lesson in humanity and that everyone is truly different. The Indonesian monks came and helped us while we were in the camp. My aunt had married a Special Forces Green Beret and he expedited the paperwork to get us out of Indonesia and to the United States. At the age of eight I found myself on Ft. Bragg and my mom re-married a Sergeant who was a Green Beret. At that early age, I was indoctrinated in the ways of a Special Forces soldier. I learned how to speak different languages, learned how to take apart many different types of weapons, and learned how to properly navigate the back woods of North Carolina.

I was taught how to navigate the stars and build my own compasses. The truth is, we were just spending father and son time but he was teaching me a trade craft. Throughout my life he’d leave, come back, leave, come back and I’d equate it with seeing something bad on the news. Panama happened and he immediately went over there. I felt from a very young age, being raised as a part of that warrior class, that I had a much higher purpose. I knew what a sheep, sheep dog, and a wolf were from a very young age. My dad taught me that very early on. I asked my father how I could help protect and my dad said I’d have to pass a test to become a part of the brotherhood. At ten years old I wanted to be a Green Beret.

Like a lot of Asians, I was academically gifted at a very young age. I had scholarships and I turned them down. I made better grades than my brother and he ended up being a doctor. When I got to age 18 I went to MEPS and applied for 11B (Infantry). There was no such thing as 18X or direct entry into Special Operations. You couldn’t just come off the streets and train for Special Operations. You had to become an E5 (Sergeant) first and then do a certain amount of years. Those years could be waived and so I made E5 after a year and a half. When I went in I went into long-range reconnaissance, which took me directly into the Marines’ Amphibious School, Ranger training, and a lot of other leadership courses as well as the Army Sniper School.

See also On Japan and Learning how to fight.

Dom: We're enjoying this. We're going to win. We're going to leave.

Boris Johnson UN speech: AI, robots, genetic engineering chickens

Boris Johnson speech on Brexit, AI robots, and genetically engineered chickens at the UN General Assembly. (Thanks to Cyrus Hodes for the pointer :-)

See Big Chickens!

Strategic Implications of Drone/Missile Strikes on Saudi Arabia

The Iranian / Houthi drone shown above might look like a toy, but it is likely capable of flying hundreds of miles, perhaps using GPS guidance and optical imaging for final targeting. Compare to the hobbyist radio controlled jet aircraft in the video at bottom. These weapons are inexpensive and easy to engineer, yet potentially very effective.

In Machine Intelligence Threatens Overpriced Aircraft Carriers (2017) I noted that

Within ~10y (i.e., well within projected service life of US carriers) I expect missile systems of the type currently only possessed by Russia and PRC to be available to lesser powers. I expect that a road-mobile ASBM weapon with good sensor/ML capability, range ~1500km, will be available for ~$10M. Given a rough (~10km accuracy) fix on a carrier, this missile will be able to arrive in that area and then use ML/sensors for final targeting. There is no easy defense against such weapons. Cruise missiles which pose a similar threat will also be exported. This will force the US to be much more conservative in the use of its carriers, not just against Russia and PRC, but against smaller countries as well.

... Basic missile technology is old, well-understood, and already inexpensive (compared, e.g., to the cost of fighter jets). ML/sensor capability is evolving rapidly and will be enormously better in 10y. ... Despite BS claims over the years (and over $100B spent by the US), anti-missile technology is not effective...

One only has to localize the carrier to within few x 10km for initial launch, letting the smart final targeting do the rest. The initial targeting location can be obtained through many methods, including aircraft/drone probes, targeting overflight by another kind of missile, LEO micro-satellites, or even (surreptitious) cooperation from Russia/PRC (or a commercial vendor!) via their satellite network.

Anthony Cordesman writes for the Center for Strategic and International Studies (CSIS):

The Strategic Implications of the Strikes on Saudi Arabia:

.. UCAV/RPV (drone) and cruise missile attacks offer precision strike options with high levels of accuracy from small, easily dispersible systems that are very hard to locate and target... Iranian systems do have both GPS and imagery capability to home in even more precisely on a target. UCAV/RPVs and cruise missiles are also small air defense targets compared to fighters, can fly evasively, and have flight profiles that are hard to detect. Saudi fighter and SAM intercept capabilities to cover wide areas with any effectiveness are uncertain, and ballistic missile defenses can only cope with a different threat.

This is why the success of the existing strikes will – at a minimum — act as a major incentive to Iran, the Hezbollah, and other such powers to develop such forces as well as precision guided ballistic missiles and cruise missiles.

... Looking further into the future, the strikes on Saudi Arabia provide a clear strategic warning that the US era of air supremacy in the Gulf, and the near U.S. monopoly on precision strike capability, is rapidly fading. UCAV/RPVs, cruise missiles, and precision strike ballistic missiles are all entering Iranian inventory and have begun to spread to the Houthi and Hezbollah. Nations like North Korea are following, and other areas of military confrontation like India and Pakistan will follow. All of these systems can be used at low levels of conflict intensity and in “gray area” wars...

We are entering an era in which an inexpensive, easy to obtain device can fly rapidly (~500mph if jet powered), evasively, and automatically to a designated GPS coordinate. It can even use visual or radar information to adjust final targeting. Terrorists could easily attack any public event: i.e., large stadium (sporting event or concert), public speech by politician, etc. They could also attack key infrastructure such as a power station or oil pipeline/refinery. It's the era of the mobile smart IED...

See also Assassination by Drone.

10 Downing Street

Manifold Podcast #19: Ted Chiang on Free Will, Time Travel, Many Worlds, Genetic Engineering, and Hard Science Fiction

Steve and Corey speak with Ted Chiang about his recent story collection Exhalation and his inaugural essay for the New York Times series, Op-Eds from the Future. Chiang has won Nebula and Hugo awards for his widely influential science fiction writing. His short story Story of Your Life, became the film Arrival (2016). Their discussion explores the scientific and philosophical ideas in Ted's work, including whether free will is possible, and implications of AI, neuroscience, and time travel. Ted explains why his skepticism about whether the US is truly a meritocracy leads him to believe that the government-funded genetic modification he envisages in his Op-Ed would not solve the problem of inequality.

Transcript

Ted Chiang's New York Times Op-Ed From the Future

Exhalation by Ted Chiang

Stories of Your Life and Others by Ted Chiang


man·i·fold /ˈmanəˌfōld/ many and various.

In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point.

Steve Hsu and Corey Washington have been friends for almost 30 years, and between them hold PhDs in Neuroscience, Philosophy, and Theoretical Physics. Join them for wide ranging and unfiltered conversations with leading writers, scientists, technologists, academics, entrepreneurs, investors, and more.

Steve Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.

Corey Washington is Director of Analytics in the Office of Research and Innovation at Michigan State University. He was educated at Amherst College and MIT before receiving a PhD in Philosophy from Stanford and a PhD in a Neuroscience from Columbia. He held faculty positions at the University Washington and the University of Maryland. Prior to MSU, Corey worked as a biotech consultant and is founder of a medical diagnostics startup.

London and Tallinn

I'll be speaking about AI and Health in Tallinn, after a stop in London to help the Tories prepare for the upcoming general election ;-)

Tallinn Digital Summit is where the frontrunners of digital nations drive the global conversation on digitalization.

Over the course of a day political leaders, policy innovators, thought-leaders, entrepreneurs and tech-community spotlight the most topical matters of digital transformation and tackle questions about its implications on economies, societies and governments. TDS is an annual meeting place for enhancing practical sharing of ideas and lessons to chase the opportunities of digital transformation for economy, e-governance development as well as societies. Also, to shape a more coherent approach to challenges brought by digital transformation.

Being one of the most digitally advanced countries, Estonia is an ideal location for the event. It has significant experience in building a digital society and economy, having built its digital core on secure distributed architecture. The country is also an outsized creator and exporter of startups, and possesses considerable cybersecurity expertise. Tallinn also hosts the HQ of NATO Cyber Defence Centre of Excellence and the European Agency for the Operational Management of Large-Scale IT Systems.

Manifold podcast #18: Rebecca Campbell on Identifying Serial Perpetrators, Rape Investigations, and Untested Rape Kits

Dr. Rebecca Campbell is Professor of Psychology at Michigan State University. Her research focuses on violence against women and children with an emphasis on sexual assault. Steve and Corey discuss her recent National Institute of Justice-funded project to study Detroit’s untested rape kits. Dr. Campbell describes the problem of untested kits and her work with police departments around the country to reduce the backlog. She explains how the use of the national CODIS database has led to sharply higher estimates of the proportion of rapes committed by serial perpetrators and how many rapists appear to be criminal “generalists” -- committing a wide range of offenses. She describes the dynamics of sexual assault investigations, the factors that lead police to put more effort into investigating certain cases over others, and how police questioning of women can lead them to disengage from the process. Other topics include the incentives at work in law enforcement, the slow pace at which new research in DNA testing and treatment of victims is incorporated into police training, and Dr. Campbell’s efforts to engage with law enforcement agencies to improve investigative practices.

Transcript

Additional links to research articles and media coverage


man·i·fold /ˈmanəˌfōld/ many and various.

In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point.

Steve Hsu and Corey Washington have been friends for almost 30 years, and between them hold PhDs in Neuroscience, Philosophy, and Theoretical Physics. Join them for wide ranging and unfiltered conversations with leading writers, scientists, technologists, academics, entrepreneurs, investors, and more.

Steve Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.

Corey Washington is Director of Analytics in the Office of Research and Innovation at Michigan State University. He was educated at Amherst College and MIT before receiving a PhD in Philosophy from Stanford and a PhD in a Neuroscience from Columbia. He held faculty positions at the University Washington and the University of Maryland. Prior to MSU, Corey worked as a biotech consultant and is founder of a medical diagnostics startup.

Former Yale Law Dean on Harvard anti-Asian discrimination case: The facts are just so embarrassing to Harvard... Quotas and a climate of dishonesty

The excerpt below is from a recent interview in the Chronicle of Higher Education. Anthony Kronman was Dean of Yale Law School from 1994 to 2004 (Yale JD and PhD in Philosophy). These are elite establishment credentials. Yet the observations he makes rather matter of factly below are not to be found in the national media coverage nor in the public remarks of university administrators.

The focus of the Chronicle interview is Kronman's recent book The Assault on American Excellence, which does not, as far as I know, address Asian American university admissions. In case you are wondering, Kronman is an anti-Trump lifelong democrat.

Chronicle: What are your thoughts about the Harvard anti-Asian discrimination case?

... The facts are just so embarrassing to Harvard that with some modest adjustment in its admissions practices it might be able to absorb a judgment against it and get on with life more or less as usual. The vagueness of the category on which Harvard was relying to make sure that it kept its Asian undergraduates at the level that it wished, the so-called personality score, is such a floppy nothing of an empty basket — that’s not gonna do anymore.

There is something profoundly disturbing about Harvard using these flaccid categories to achieve something like a quota. The court papers show how the system was invented to keep the number of Jews down in the late 1920s and early 1930s. It’s all pretty bad, and part of the badness is that colleges have been both compelled and allowed to do what they’re doing under the rubric of "diversity," which conceals from view the actual operation of the whole system, and what they are in fact aiming to achieve. It’s substituting one vocabulary for another in a way that creates a climate of dishonesty. What goes on in the admissions office is increasingly mysterious, and what happens once students are admitted — that is something to which little attention is paid by educators themselves.

[ Italics mine ]

Kronman is presumably aware that other Ivy schools like Yale are little different from Harvard when it comes to undergraduate admissions.

See also

Harvard Admissions on Trial

Harvard discrimination lawsuit: data show penalization of Asian-Americans on subjective personality evaluation

Harvard Office of Institutional Research on Discrimination Against Asian-American Applicants

"When it comes to the score assigned by the Admissions Office, Asian-American applicants are assigned the lowest scores of any racial group. ... By contrast, alumni interviewers (who actually meet the applicants) rate Asian-Americans, on average, at the top with respect to personal ratings—comparable to white applicants ..."

Genomic Prediction of Complex Traits and Disease Risks (video of talk at IGI and OpenAI)

Seminar at the Innovative Genomics Institute (IGI, Berkeley and UCSF) July 17 2019. I gave a similar talk the following day at OpenAI. Jennifer Doudna, one of the co-discoverers of CRISPR-Cas9 gene editing, is the Executive Director of IGI. You might recognize her voice if you can hear the audience questions.

IGI began in 2014 through the Li Ka Shing Center for Genetic Engineering, which was created thanks to a generous donation from the Li Ka Shing Foundation. The Innovative Genomics Initiative formed as a partnership between the University of California, Berkeley and the University of California, San Francisco. Combining the fundamental research expertise and the biomedical talent at UCB and UCSF, the Innovative Genomics Initiative focused on unraveling the mechanisms underlying CRISPR-based genome editing and applying this technology to improve human health.

Slides -- slightly updated from the ones I used in the talk.

Title: Genomic Prediction of Complex Traits and Disease Risks via AI/ML and Large Genomic Datasets

Abstract: The talk is divided into two parts. The first gives an overview of the rapidly advancing area of genomic prediction of disease risks using polygenic scores. We can now identify risk outliers (e.g., with 5 or 10 times normal risk) for about 20 common disease conditions, ranging from diabetes to heart diseases to breast cancer, using inexpensive SNP genotypes (i.e., as offered by 23andMe). We can also predict some complex quantitative traits (e.g., adult height with accuracy of few cm, using ~20k SNPs). I discuss application of these results in precision medicine as well as embryo selection in IVF, and give some details about genetic architectures. The second part covers the AI/ML used to build these predictors, with an emphasis on "sparse learning" and phase transitions in high dimensional statistics.

College quality measures highly correlated to student SAT scores

Research by Brown, Chabris, and Wai shows that quality of students is strongly correlated to other quality measures of a college. (Thanks to a reader for sending the link!) See also this global analysis of university quality rankings.

Of course, causality is complex: schools with strong reputations, large endowments, etc. can attract top applicants. But how did those schools acquire those reputations and endowments in the first place?

Salon: ... Though there is often public controversy over the value of standardized tests, research shows that these tests are quite robust measures to predict academic performance, career potential, creativity and job performance.

Critics of the SAT say it tests for students’ wealth, not caliber. While it is true that wealthier parents tend to have students with higher test scores, it turns out the research robustly shows that test scores, even when you consider socioeconomic status, are predictive of later outcomes.

We first found high correlations between our test score rankings and U.S. News national university rank – 0.892 – and liberal arts college rank – 0.890 – even though U.S. News weights these scores only about 8% in their formula. ...

See also Universities Ranked By SAT Score (2013):

Schools with the strongest students (e.g., as measured by SAT) produce graduates who make outstanding contributions at per capita rates easily 10x or 100x higher than others: see Where Nobel winners get their start (Nature) and Colleges ranked by Nobel, Fields, Turing and National Academies output.

Dept. of Physicists Can Do Stuff: Brexit!

Dominic Cummings on how Vote Leave won the Brexit campaign. (Video should start at 13m30s.)

Dom hired a team of physicists and data scientists who

1. Studied the literature on elections (i.e., entered a well-established subject, studying it de novo, applying real horsepower), figured out which results/beliefs in that field were likely correct (much found was incorrect)

2. Adapted results to the job at hand (Brexit referendum) and invented new techniques for applying them

3. Built a new platform, wrote new code, executed in real time, and won a huge electoral victory against all odds.

Of course, this is the age old story of physicists invading/creating other fields: early computing, electrical engineering, molecular biology, computational biology, quantitative finance, high frequency trading, etc.

This victory will have historical reverberations that are still playing out.

13m35s: ... we had to take risks and we had to do things in a slightly new way so one of the basic things that I did was I brought in a team of physicists who essentially looked at campaigning from complete first principles and what they did was they went they simply scanned around the world and they said what studies have been done on issues of turnout and persuasion that actually have good maths behind them to support and have been replicated and we can actually have confidence in and they basically filtered all when through filtered them all out and came back to me in the team and said here is a small selection of things actually high quality or reasonable quality work which you can rely upon and here are the principles that you can see in these studies that have been replicated with randomised controlled trials and whatnot in the States

we basically created a checklist of what these things were and we built the communications team around trying to exploit each of these elements which the physicists found they also constructed models to help direct resources on the ground campaigns to wedge where to send your activists and the digital campaign how do you actually do that in a in a scientific way and essentially you had streams of data coming in from all sorts of different ways the website email on the ground canvassing a social media blah blah all of this stuff could be traditional polling all of the stuff coming in and you had the data science people sitting at the heart of the operation and essentially taking our core messages and just running experimentally a whole bunch of different things on Facebook and elsewhere and then figuring out what what things and what things don't work and we started off with relatively small amounts of money just to run this experimental process

another thing which which I'll go into a little bit of detail because it's from perhaps of interest regarding this election is we did a new kind of polling so I'm sure all of you know the polling methodology used throughout the world essentially the same system that was invented in the late 1930s and the idea of it is yo you take roughly speaking a thousand person sample and if it's random a representative then you can rely on the mathematics of the normal distribution and the famous bell curve and you that should give you a pretty accurate picture of what people think for various reasons that is becoming harder and harder to do happy to answer questions about why that is but leaving that aside what the physicists said was this is actually not the way that you would invent polling if you were going to invent polling now the way actually to do it is take massive samples of hundreds of thousands of people ideally actually millions of people but say hundreds thousands people and then use machine learning and you will actually have a system which is faster cheaper more accurate and never has another great advantage which we exploited which is that if you do these very large sample surveys you then have sub sample you can define the demographics that you interrogate yourself and what we did was we basically use the exact same categories infer demographics that Facebook uses for its digital advertising platform so we sucked in data on the precise same basis that Facebook marketing allows and then we had therefore large sub samples of the overall polling samples which you could actually rely on and then you could take that data and plug it straight back into Facebook so you could say for example we will target women between 35 and 45 who live in these particular geographical entities who don't have a degree or who do have a degree or whatever it's after cetera

and because you've got very large samples you can actually get useful information on those kind of relatively small breakdowns so we did all this and we as I said we essentially ran a whole series of experiments based on what we found at the conventional polling in the focus groups out in the digital world and then filtered what worked and then we held back almost all of our budget and then we basically dumped the entire budget or in the last ten days...

See also Dept. of Physicists Can Do Stuff: Gene Sequencing, Harold Brown, Ashton Carter.

More Dom.

How Brexit was won, and the unreasonable effectiveness of physicists:

The scale of ... triumph cannot be exaggerated. He ... had brought about a complete transformation of the European international order. He had told those who would listen what he intended to do, how he intended to do it, and he did it. He achieved this incredible feat without commanding an army, and without the ability to give an order to the humblest common soldier, without control of a large party, without public support, indeed, in the face of almost universal hostility, without a majority in parliament, without control of his cabinet, and without a loyal following in the bureaucracy.

...

On the eve and day of Brexit I happened to be staying at the estate of a billionaire hedge fund manager, which hosted a meeting of elite capital allocators. At breakfast, more than half of these titans of capital were in shock ... Markets were down 8% or more and my host asked for my view. It will play out over years, I said. No one knows where this is going to go. The market is oversold and it's a buying opportunity. So it was.

Manifold #17: Mark Moffett on the Life and Death of Human Societies

Steve and Corey talk with Mark Moffett, Photographer and Research Fellow at the Smithsonian Institute, about his new book The Human Swarm: How our Societies Arise, Thrive and Fall. They discuss Mark’s view that being able walk into a cafe filled with others and not be attacked illustrates what makes human societies distinct and so successful. Mark explains why he is far more interested in questions about when war and other events occur than with traditional issues such as the genetic origins of human behavior. The three discuss Dehumanization and its Chimp equivalent, Dechimpanizeeization, and how they lead to the division of societies, friend turning against friend, and genocide. They discuss the conditions under which foreigners are embraced and whether the US might ever enter into a post-racial society where group differences don’t matter and immigrants are more easily accepted.

Mark Moffett's Bio

Mark Moffett's Photography

The Human Swarm: How Our Societies Arise, Thrive, and Fall

Transcript

man·i·fold /ˈmanəˌfōld/ many and various.

In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point.

Steve Hsu and Corey Washington have been friends for almost 30 years, and between them hold PhDs in Neuroscience, Philosophy, and Theoretical Physics. Join them for wide ranging and unfiltered conversations with leading writers, scientists, technologists, academics, entrepreneurs, investors, and more.

Steve Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.

Corey Washington is Director of Analytics in the Office of Research and Innovation at Michigan State University. He was educated at Amherst College and MIT before receiving a PhD in Philosophy from Stanford and a PhD in a Neuroscience from Columbia. He held faculty positions at the University Washington and the University of Maryland. Prior to MSU, Corey worked as a biotech consultant and is founder of a medical diagnostics startup.

MSU New Faculty Welcome 2019

These are excerpts from remarks I gave yesterday at a reception for new faculty.

Good afternoon and Welcome!

We are so pleased that you are here at Michigan State University. You have joined a great research university, at a very exciting time.

I’m told I only have 10 minutes in which to say something about the deep and varied research enterprise here at MSU. That’s only enough time for a high level overview, so let me start with some big picture numbers. Each year the National Science Foundation publishes its Higher Education Research and Development (or HERD) report on the total research expenditures of all US universities. MSU’s total HERD number has grown from about $500M to $700M in the last seven years. We’ve advanced faster than any other Big Ten university, and now rank 32nd in the US among all universities.

MSU is ahead of Rutgers, UT Austin, Illinois (UIUC), Purdue, Arizona, Maryland, Indiana, Iowa, ASU, Colorado (Boulder), and UVA.

Based on the HERD comparison data, MSU ranks 1st in the nation in combined Department of Energy and National Science Foundation research expenditures.

Almost all of the schools ranked above us (and many below) have major research hospitals. In those cases, the medical research component of the HERD total often exceeds the rest of campus combined. At MSU, about ~$100M of our total comes from NIH. We still have significant room to advance.

There are only a few schools without a major medical complex that rank above us -- let me mention two: UC Berkeley $771M (top public university in the US; home of Lawrence Berkeley National Lab) and MIT $952M (home of Lincoln Laboratory, a major defense research lab).

MSU, UC Berkeley, and MIT are all research powerhouses. But we are similar in another important way: all three are land-grant universities. As land-grant universities, we pride ourselves on making breakthroughs in basic research, and applying those breakthroughs to make life better for the entire world.

... MSU is home to the Facility for Rare Isotope Beams, a scientific user facility for the Office of Nuclear Physics in the Office of Science of the U.S. Department of Energy.

FRIB will be operational in 2021 and will deliver the highest intensity beams of rare isotopes available anywhere in the world. Estimates of the total investment in this project are roughly $1 billion dollars. Operated by MSU, FRIB will enable scientists to make discoveries about the properties of rare isotopes (which are unusual forms of the elements) in order to better understand the physics of nuclei, nuclear astrophysics, and the fundamental interactions of nature. It will also produce practical applications for society, including in medicine, homeland security, and industry.

... Another recent development is a new department called Computational Mathematics, Science, and Engineering or CMSE. This department was planned, authorized, and operational in only three years—quite a feat in academia. I often compare “startup time” (the fast pace at which things are accomplished in Silicon Valley) to “academic time” (i.e., nothing gets done, other than committee meetings, and a no-brainer project takes a decade to complete), but with CMSE this was a case of something on campus getting done in startup time. CMSE is one of very few such departments in the country -- it is focused on data science, machine learning, advanced computation and related applications, but is not a traditional CS department. It supports many of the new efforts on campus that require the analysis of large data sets and development of new tools and algorithms. Researchers in this department utilize datasets drawn from astrophysics, business analytics, mobile data, materials science, human and plant genomics, and many other areas. The department was conceived as fundamentally interdisciplinary -- bringing together experts in computation with subject matter experts in areas of science which are becoming increasingly reliant on data.

I can’t help mentioning a couple of big data examples related to my own research: we’ve created a compute resource with more than 500k human genomes, open to interested investigators on campus. All of the data is stored at our High Performance Computing Center or HPCC. Using this data, our collaboration demonstrated for the first time that machine learning applied to large genomic datasets could produce accurate predictors for complex human traits. We can now predict adult human height from genome alone, with accuracy roughly 1 inch. The predictor uses ~20k genetic variants distributed throughout the genome. Predictors of complex disease risk, for conditions such as heart disease, diabetes, schizophrenia, and breast cancer, have been developed and broadly replicated in out-of-sample tests. I recently participated in a meeting at No 10 Downing Street in the UK, to plan a project which will genotype 5 million individuals through their National Healthcare System. This is only the beginning for genomic Precision Medicine.

... If there is a problem -- tell us about it! -- whether it has to do with grant submissions, or startup incubation, or child care, food options on campus, your functional or dysfunctional department. We’re here to fix things, and to provide the best possible environment for your teaching, research, and creative activity.

Only one in a thousand people in our society have the privilege to engage full time in discovery -- in curiosity driven research -- for the benefit of humankind. You are part of that lucky one in a thousand, and we are here to help you succeed.

The bar has been set very high, but with the resources and new opportunities here at MSU, your potential is limitless.

My very best wishes to you all :-)