The Long Game 40: Mental Health & Robots, Aging Research, Incentives, Secrets of Sand Hill Road
🤖 The Simulation Theory, the New Old World, the Tragedy of Legible Expertise, Illusions of Time, Superpowered, and Much More!
Greetings from Paris 🇫🇷
If you missed the past episodes, you could catch up here.
In this episode, we explore:
A new era for research into aging
Mental health and robots
Getting the incentives right
Secrets of Sand Hill Road
The simulation theory
📣 Before we get to today’s newsletter, I wanted to share a message from a friend at On Deck about their new Health Fellowship:
The On Deck Health Fellowship is a 10-week program for startup and healthcare experts looking to found, join, invest in, and advise health tech companies. The program combines a world-class curriculum with top industry speakers, unique access to investors, and a pre-vetted pool of potential hires to help ambitious builders create the future of the healthcare ecosystem.
During the 10-weeks, you and 120 healthcare innovators will come together to:
Navigate the healthcare ecosystem and identify opportunities for innovation
Build, join, or invest in cutting edge health tech startups
Deepen your expertise through fireside chats and panels with industry experts
Collaborate with a group of talented peers to reshape the healthcare system
ODH is like a rolling industry conference, only better: it’s a space for fellows to deepen their industry expertise, accelerate their careers, and build impactful health tech startups — together.
The inaugural cohort kicks off on April 10, 2021. Access to the program, including lifelong access to the community, is $2,480 or five instalments of $500.
Limited scholarships are available, so apply early! Link.
I share this because I know many of the folks at On Deck, and think it is a great opportunity. If you apply for a scholarship and want a good word put in for you let me know.
Now, let’s dive in!
One of the positive changes that might occur during this pandemic is the mainstream understanding of the connection between aging and disease. Why is this important, you might ask. Right now, there are still many scientists who study individual diseases without recognizing the impact of aging biology.
It is still common, for example, to see research studies in cancer, neuroscience, metabolism and other fields where young animal models (such as 4–6 month old mice) are used to study disease processes that almost exclusively occur in old people. ‘Mice are not people’ is a standard refrain when explaining why so many preclinical therapies fail in human trials. Perhaps the mouse isn’t the problem. Failing to account for the physiological changes that occur during aging, both in mice and in people, may be a much bigger reason why so much preclinical research fails to translate to the clinic.
We are at a pivotal moment in the field of longevity and anti-aging research:
Another important advance in aging research has been the development of a concept called geroscience: researchers in this area seek to understand mechanistically how the hallmarks of aging cause age-related disease and functional decline (Sierra and Kohanski, 2017). The growth of the geroscience concept also reflects a recognition that aging research is much closer to clinical application than it was twenty years ago.
As I repeated so many times here, the future of aging depends on us. It’s inevitable (if we don’t eradicate ourselves before that) that we will eventually live much longer than our current lifespan. Whether it happens in the 21st century or the 25th depends on us.
The future of aging research is brighter than ever before, and the pace of discovery is only increasing. We look forward to major breakthroughs over the next few years that will revolutionize the way we think about aging biology and have the potential to significantly impact human healthspan and longevity.
🧘♀️ Mental Health & Robots
Our mental health has taken a major hit during the COVID-19 pandemic, while social distancing means it's harder to meet in person with therapists. That has opened a space for machines to help us.
In a survey published by Oracle, 68% of people reported they would prefer to talk to a robot over their manager about stress and anxiety at work. ⚠️
80% said they were open to having a robot as a counsellor or therapist.
"Workers said that robots can support their mental health better than humans because they can provide a judgment-free zone."
Many startups are jumping on the opportunity. Maslo is one of them.
Maslo uses signal processing techniques to "read" voice, text and even the body language of a human user to identify a baseline level for mental health.
"We can extract the linguistic aspects of what a person is saying, but we can also look at acoustic elements as well — volume, loudness, intonation," says Ross Ingram, Maslo's CEO.
That data can help Maslo's partners build better executive performance coaches, for example, or even help with online dating.
I don’t know how I feel about this; on the one hand, the mental health crisis requires all of our attention and potentially new tools like this. On the hand, I can’t help but think these solutions further worsen our social skills and ability to feel supported and support other human beings.
What do you think?
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🧠 Better Thinking
🎯 Get the Incentives Right
Good thinking often follows the right incentive structure, just as wrong thinking follows the wrong incentive structure. This problem is particularly visible in science & academia. Here’s a paper that outlines how competition to publish first creates a race to the bottom in science:
This paper investigates how competition to publish first and thereby establish priority impacts the quality of scientific research. We begin by developing a model where scientists decide whether and how long to work on a given project. When deciding how long to let their projects mature, scientists trade off the marginal benefit of higher quality research against the marginal risk of being preempted. The most important (highest potential) projects are the most competitive because they induce the most entry. Therefore, the model predicts these projects are also the most rushed and lowest quality. We test the predictions of this model in the field of structural biology using data from the Protein Data Bank (PDB), a repository for structures of large macromolecules. An important feature of the PDB is that it assigns objective measures of scientific quality to each structure. As suggested by the model, we find that structures with higher ex-ante potential generate more competition, are completed faster, and are lower quality. Consistent with the model, and with a causal interpretation of our empirical results, these relationships are mitigated when we focus on structures deposited by scientists who – by nature of their employment position – are less focused on publication and priority.
I also enjoyed this article from the latest edition of Work in Progress about the speed of science. It’s a call for more data sharing and collaboration between scientist, and it sums up many of the other problems affecting science.
The practice of sharing data is also the norm in the neighbouring field of genomics. The tradition largely stems from the Human Genome Project, which began in 1990 and aimed to determine the entire code of the human genome. During the project, a group of scientists developed protocols called the Bermuda Principles, which recommended that labs working on the project should upload the details of any new genetic sequences that they discovered onto public data repositories on a daily basis.
The common problem of these problems seems to be a psychological one: ego and wanting to be better than the other.
I think this also applies outside of science. In life and business, sharing your ideas and adopting positive-sum thinking is a much better approach than being concerned by the competition.
There is never any competition with the outside world, only with yourself.
⚡️ Startup Stuff
This week I read Secret of Sand Hill Road: Venture Capital and How to Get It by Scott Kupor after a friend in VC recommended it. I’m happy I took the time to read it because of two reasons. First, it’s a great book, straight to the point and enjoyable. Second, I think it’s a must-read for every entrepreneur building a company.
If you’re building something for the long term, want to do things the right way and avoid the many traps along the road, this book is for you. From my experience, building a company is hard because you have so many different things to do. You need to learn fast. One of the dangers I often see is not knowing what you don’t know.
For example, you can’t expect to understand VC as a VC does. However, you can understand the important parts you should pay a lot of attention to, so when they arise, you pause, make sure you understand the extent of your decision thoroughly and then continue.
Speed is great, but when the decision is irreversible, you need to be careful. I took many notes, but all I would say here is that you can’t skip on this book, or just read the summary if you’re building a company.
“Live to fight another day” is another great startup mantra to always keep front and center in your mind.
📚 What I Read
Maybe the best article I read so far this year:
The second reason I'm writing this is because people keep asking me "should we listen to experts"?
As usual, the answer is "it depends who you mean by we".
Here's a story which is very flattering and which I hope is true: Zvi gives better advice than the Director of the CDC. This isn't a very legible fact - it's not obvious from the titles each one has - but due to various personal advantages, like having known Zvi for ten years and thinking in the same idiom he does, I'm able to recognize this. I can take Zvi's advice instead of the Director's advice, and benefit from it.
(if you trust me, you probably also trust Zvi now that you’ve read this. But you only trust me because you’ve read me for years, think in the same idiom I do, etc, etc.)
Even if this flattering story is true, it doesn't scale. My personal tendency will be to always trust Zvi. But someone else will decide to always trust *their* friend, a guy in a MAGA cap who says coronavirus is fake and Dr. Fauci is a Satanist. Compared to the median person who disagrees with the experts, the experts look pretty good.
🗺 The New Old World
I’ve developed an increasing interest in geopolitics lately. I tried to read as much as possible about it in the last months, mostly about China, India, and the role of the US in this century.
This week, I particularly enjoyed this piece from Radigan Carter about the current geopolitics of the world. It’s a long article, so here are some highlights I found worth mentioning:
People who don’t think social unrest can spread to systemic risk in the west don’t have experience with real violence.
They think it is edgy and cool to call for violence on twitter and never think it could actually come to their home.
Anyone who has seen instability and conflict is under no illusions.
Is this years away? Yeah probably, but we’re already seeing signs of the changes and the best time to be thinking about things is when most others aren’t.
However this game of global risk plays out, no way most people are understanding the changes that are taking place around them as the new world becomes old again.
🎙 Podcast Episode of the Week
Here are some episodes I enjoyed lately:
Francis Ngannou (a 3-hour conversation when Francis tell his story from Cameroon to the US, how he crossed the Gibraltar Strait, leaving Morocco on an inflatable boat after having tried 6 times and being deported back each time to the Sahara Desert, how he became an MMA fighter while being homeless in Paris, and how he finally got to where he is today, fighting for the Heavyweight MMA title. One of the most fascinating stories I ever hear, and a lesson on tenacity and perseverance.)
🍭 Brain Food
🤖 The Surprising Appeal of Believing in the Simulation Theory
We’ve talked many times about the Simulation Theory on The Long Game. If you’re not familiar with it, you can read the paper from Nick Bostrom, and here’s the abstract:
This paper argues that at least one of the following propositions is true: (1) the human species is very likely to go extinct before reaching a “posthuman” stage; (2) any posthuman civilization is extremely unlikely to run a significant number of simulations of their evolutionary history (or variations thereof); (3) we are almost certainly living in a computer simulation. It follows that the belief that there is a significant chance that we will one day become posthumans who run ancestor-simulations is false, unless we are currently living in a simulation. A number of other consequences of this result are also discussed.
This week I read this interesting interview of Rodney Ascher, the director of a trippy new documentary about simulation theory.
Did you find that most people who believe they are living in a simulated world are excited by this idea, or are they terrified?
The ones that I've talked to, most find it an endlessly fascinating idea. But it also raises questions of: What's the simulation for, and what's my role in it? When people make goofy jokes on Twitter when something crazy happens in the news again [about how] that must be a sign that the simulation is buggy or glitching or messed up, in a way, that lowers the stakes. This world is falling off the rails, but it's not the real world any way, so it's not worth getting that upset about.
🎥 What I’m Watching
⏳ Illusions of Time
Thanks to my cousin, I just discovered Vsauce. I can only recommend the channel. Illusions of Time explores why time seems to be passing at different speeds throughout our life.
🔧 The tool of the Week
I have always been reluctant to try new calendar apps because the cost of switching habits is very high when it comes to calendars. This week, I came across Superpowered, and the simplicity of it looked compelling. In short, it’s one-click quick access to your Zoom & Meet links in the menu bar of your MacBook. I really like it so far.
🪐 Quote I'm Pondering
"I am the end or the beginning."
— Franz Kafka.
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