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#434772 Traditional Higher Education Is Losing ...
Should you go to graduate school? If so, why? If not, what are your alternatives? Millions of young adults across the globe—and their parents and mentors—find themselves asking these questions every year.
Earlier this month, I explored how exponential technologies are rising to meet the needs of the rapidly changing workforce.
In this blog, I’ll dive into a highly effective way to build the business acumen and skills needed to make the most significant impact in these exponential times.
To start, let’s dive into the value of graduate school versus apprenticeship—especially during this time of extraordinarily rapid growth, and the micro-diversification of careers.
The True Value of an MBA
All graduate schools are not created equal.
For complex technical trades like medicine, engineering, and law, formal graduate-level training provides a critical foundation for safe, ethical practice (until these trades are fully augmented by artificial intelligence and automation…).
For the purposes of today’s blog, let’s focus on the value of a Master in Business Administration (MBA) degree, compared to acquiring your business acumen through various forms of apprenticeship.
The Waning of Business Degrees
Ironically, business schools are facing a tough business problem. The rapid rate of technological change, a booming job market, and the digitization of education are chipping away at the traditional graduate-level business program.
The data speaks for itself.
The Decline of Graduate School Admissions
Enrollment in two-year, full-time MBA programs in the US fell by more than one-third from 2010 to 2016.
While in previous years, top business schools (e.g. Stanford, Harvard, and Wharton) were safe from the decrease in applications, this year, they also felt the waning interest in MBA programs.
Harvard Business School: 4.5 percent decrease in applications, the school’s biggest drop since 2005.
Wharton: 6.7 percent decrease in applications.
Stanford Graduate School: 4.6 percent decrease in applications.
Another signal of change began unfolding over the past week. You may have read news headlines about an emerging college admissions scam, which implicates highly selective US universities, sports coaches, parents, and students in a conspiracy to game the undergraduate admissions process.
Already, students are filing multibillion-dollar civil lawsuits arguing that the scheme has devalued their degrees or denied them a fair admissions opportunity.
MBA Graduates in the Workforce
To meet today’s business needs, startups and massive companies alike are increasingly hiring technologists, developers, and engineers in place of the MBA graduates they may have preferentially hired in the past.
While 85 percent of US employers expect to hire MBA graduates this year (a decrease from 91 percent in 2017), 52 percent of employers worldwide expect to hire graduates with a master’s in data analytics (an increase from 35 percent last year).
We’re also seeing the waning of MBA degree holders at the CEO level.
For decades, an MBA was the hallmark of upward mobility towards the C-suite of top companies.
But as exponential technologies permeate not only products but every part of the supply chain—from manufacturing and shipping to sales, marketing and customer service—that trend is changing by necessity.
Looking at the Harvard Business Review’s Top 100 CEOs in 2018 list, more CEOs on the list held engineering degrees than MBAs (34 held engineering degrees, while 32 held MBAs).
There’s much more to leading innovative companies than an advanced business degree.
How Are Schools Responding?
With disruption to the advanced business education system already here, some business schools are applying notes from their own innovation classes to brace for change.
Over the past half-decade, we’ve seen schools with smaller MBA programs shut their doors in favor of advanced degrees with more specialization. This directly responds to market demand for skills in data science, supply chain, and manufacturing.
Some degrees resemble the precise skills training of technical trades. Others are very much in line with the apprenticeship models we’ll explore next.
Regardless, this new specialization strategy is working and attracting more new students. Over the past decade (2006 to 2016), enrollment in specialized graduate business programs doubled.
Higher education is also seeing a preference shift toward for-profit trade schools, like coding boot camps. This shift is one of several forces pushing universities to adopt skill-specific advanced degrees.
But some schools are slow to adapt, raising the question: how and when will these legacy programs be disrupted? A survey of over 170 business school deans around the world showed that many programs are operating at a loss.
But if these schools are world-class business institutions, as advertised, why do they keep the doors open even while they lose money? The surveyed deans revealed an important insight: they keep the degree program open because of the program’s prestige.
Why Go to Business School?
Shorthand Credibility, Cognitive Biases, and Prestige
Regardless of what knowledge a person takes away from graduate school, attending one of the world’s most rigorous and elite programs gives grads external validation.
With over 55 percent of MBA applicants applying to just 6 percent of graduate business schools, we have a clear cognitive bias toward the perceived elite status of certain universities.
To the outside world, thanks to the power of cognitive biases, an advanced degree is credibility shorthand for your capabilities.
Simply passing through a top school’s filtration system means that you had some level of abilities and merits.
And startup success statistics tend to back up that perceived enhanced capability. Let’s take, for example, universities with the most startup unicorn founders (see the figure below).
When you consider the 320+ unicorn startups around the world today, these numbers become even more impressive. Stanford’s 18 unicorn companies account for over 5 percent of global unicorns, and Harvard is responsible for producing just under 5 percent.
Combined, just these two universities (out of over 5,000 in the US, and thousands more around the world) account for 1 in 10 of the billion-dollar private companies in the world.
By the numbers, the prestigious reputation of these elite business programs has a firm basis in current innovation success.
While prestige may be inherent to the degree earned by graduates from these business programs, the credibility boost from holding one of these degrees is not a guaranteed path to success in the business world.
For example, you might expect that the Harvard School of Business or Stanford Graduate School of Business would come out on top when tallying up the alma maters of Fortune 500 CEOs.
It turns out that the University of Wisconsin-Madison leads the business school pack with 14 CEOs to Harvard’s 12. Beyond prestige, the success these elite business programs see translates directly into cultivating unmatched networks and relationships.
Relationships
Graduate schools—particularly at the upper echelon—are excellent at attracting sharp students.
At an elite business school, if you meet just five to ten people with extraordinary skill sets, personalities, ideas, or networks, then you have returned your $200,000 education investment.
It’s no coincidence that some 40 percent of Silicon Valley venture capitalists are alumni of either Harvard or Stanford.
From future investors to advisors, friends, and potential business partners, relationships are critical to an entrepreneur’s success.
Apprenticeships
As we saw above, graduate business degree programs are melting away in the current wave of exponential change.
With an increasing $1.5 trillion in student debt, there must be a more impactful alternative to attending graduate school for those starting their careers.
When I think about the most important skills I use today as an entrepreneur, writer, and strategic thinker, they didn’t come from my decade of graduate school at Harvard or MIT… they came from my experiences building real technologies and companies, and working with mentors.
Apprenticeship comes in a variety of forms; here, I’ll cover three top-of-mind approaches:
Real-world business acumen via startup accelerators
A direct apprenticeship model
The 6 D’s of mentorship
Startup Accelerators and Business Practicum
Let’s contrast the shrinking interest in MBA programs with applications to a relatively new model of business education: startup accelerators.
Startup accelerators are short-term (typically three to six months), cohort-based programs focusing on providing startup founders with the resources (capital, mentorship, relationships, and education) needed to refine their entrepreneurial acumen.
While graduate business programs have been condensing, startup accelerators are alive, well, and expanding rapidly.
In the 10 years from 2005 (when Paul Graham founded Y Combinator) through 2015, the number of startup accelerators in the US increased by more than tenfold.
The increase in startup accelerator activity hints at a larger trend: our best and brightest business minds are opting to invest their time and efforts in obtaining hands-on experience, creating tangible value for themselves and others, rather than diving into the theory often taught in business school classrooms.
The “Strike Force” Model
The Strike Force is my elite team of young entrepreneurs who work directly with me across all of my companies, travel by my side, sit in on every meeting with me, and help build businesses that change the world.
Previous Strike Force members have gone on to launch successful companies, including Bold Capital Partners, my $250 million venture capital firm.
Strike Force is an apprenticeship for the next generation of exponential entrepreneurs.
To paraphrase my good friend Tony Robbins: If you want to short-circuit the video game, find someone who’s been there and done that and is now doing something you want to one day do.
Every year, over 500,000 apprentices in the US follow this precise template. These apprentices are learning a craft they wish to master, under the mentorship of experts (skilled metal workers, bricklayers, medical technicians, electricians, and more) who have already achieved the desired result.
What if we more readily applied this model to young adults with aspirations of creating massive value through the vehicles of entrepreneurship and innovation?
For the established entrepreneur: How can you bring young entrepreneurs into your organization to create more value for your company, while also passing on your ethos and lessons learned to the next generation?
For the young, driven millennial: How can you find your mentor and convince him or her to take you on as an apprentice? What value can you create for this person in exchange for their guidance and investment in your professional development?
The 6 D’s of Mentorship
In my last blog on education, I shared how mobile device and internet penetration will transform adult literacy and basic education. Mobile phones and connectivity already create extraordinary value for entrepreneurs and young professionals looking to take their business acumen and skill set to the next level.
For all of human history up until the last decade or so, if you wanted to learn from the best and brightest in business, leadership, or strategy, you either needed to search for a dated book that they wrote at the local library or bookstore, or you had to be lucky enough to meet that person for a live conversation.
Now you can access the mentorship of just about any thought leader on the planet, at any time, for free.
Thanks to the power of the internet, mentorship has digitized, demonetized, dematerialized, and democratized.
What do you want to learn about?
Investing? Leadership? Technology? Marketing? Project management?
You can access a near-infinite stream of cutting-edge tools, tactics, and lessons from thousands of top performers from nearly every field—instantaneously, and for free.
For example, every one of Warren Buffett’s letters to his Berkshire Hathaway investors over the past 40 years is available for free on a device that fits in your pocket.
The rise of audio—particularly podcasts and audiobooks—is another underestimated driving force away from traditional graduate business programs and toward apprenticeships.
Over 28 million podcast episodes are available for free. Once you identify the strong signals in the noise, you’re still left with thousands of hours of long-form podcast conversation from which to learn valuable lessons.
Whenever and wherever you want, you can learn from the world’s best. In the future, mentorship and apprenticeship will only become more personalized. Imagine accessing a high-fidelity, AI-powered avatar of Bill Gates, Richard Branson, or Arthur C. Clarke (one of my early mentors) to help guide you through your career.
Virtual mentorship and coaching are powerful education forces that are here to stay.
Bringing It All Together
The education system is rapidly changing. Traditional master’s programs for business are ebbing away in the tides of exponential technologies. Apprenticeship models are reemerging as an effective way to train tomorrow’s leaders.
In a future blog, I’ll revisit the concept of apprenticeships and other effective business school alternatives.
If you are a young, ambitious entrepreneur (or the parent of one), remember that you live in the most abundant time ever in human history to refine your craft.
Right now, you have access to world-class mentorship and cutting-edge best-practices—literally in the palm of your hand. What will you do with this extraordinary power?
Join Me
Abundance-Digital Online Community: I’ve created a Digital/Online community of bold, abundance-minded entrepreneurs called Abundance-Digital. Abundance-Digital is my ‘onramp’ for exponential entrepreneurs – those who want to get involved and play at a higher level. Click here to learn more.
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Posted in Human Robots
#434637 AI Is Rapidly Augmenting Healthcare and ...
When it comes to the future of healthcare, perhaps the only technology more powerful than CRISPR is artificial intelligence.
Over the past five years, healthcare AI startups around the globe raised over $4.3 billion across 576 deals, topping all other industries in AI deal activity.
During this same period, the FDA has given 70 AI healthcare tools and devices ‘fast-tracked approval’ because of their ability to save both lives and money.
The pace of AI-augmented healthcare innovation is only accelerating.
In Part 3 of this blog series on longevity and vitality, I cover the different ways in which AI is augmenting our healthcare system, enabling us to live longer and healthier lives.
In this blog, I’ll expand on:
Machine learning and drug design
Artificial intelligence and big data in medicine
Healthcare, AI & China
Let’s dive in.
Machine Learning in Drug Design
What if AI systems, specifically neural networks, could predict the design of novel molecules (i.e. medicines) capable of targeting and curing any disease?
Imagine leveraging cutting-edge artificial intelligence to accomplish with 50 people what the pharmaceutical industry can barely do with an army of 5,000.
And what if these molecules, accurately engineered by AIs, always worked? Such a feat would revolutionize our $1.3 trillion global pharmaceutical industry, which currently holds a dismal record of 1 in 10 target drugs ever reaching human trials.
It’s no wonder that drug development is massively expensive and slow. It takes over 10 years to bring a new drug to market, with costs ranging from $2.5 billion to $12 billion.
This inefficient, slow-to-innovate, and risk-averse industry is a sitting duck for disruption in the years ahead.
One of the hottest startups in digital drug discovery today is Insilico Medicine. Leveraging AI in its end-to-end drug discovery pipeline, Insilico Medicine aims to extend healthy longevity through drug discovery and aging research.
Their comprehensive drug discovery engine uses millions of samples and multiple data types to discover signatures of disease, identify the most promising protein targets, and generate perfect molecules for these targets. These molecules either already exist or can be generated de novo with the desired set of parameters.
In late 2018, Insilico’s CEO Dr. Alex Zhavoronkov announced the groundbreaking result of generating novel molecules for a challenging protein target with an unprecedented hit rate in under 46 days. This included both synthesis of the molecules and experimental validation in a biological test system—an impressive feat made possible by converging exponential technologies.
Underpinning Insilico’s drug discovery pipeline is a novel machine learning technique called Generative Adversarial Networks (GANs), used in combination with deep reinforcement learning.
Generating novel molecular structures for diseases both with and without known targets, Insilico is now pursuing drug discovery in aging, cancer, fibrosis, Parkinson’s disease, Alzheimer’s disease, ALS, diabetes, and many others. Once rolled out, the implications will be profound.
Dr. Zhavoronkov’s ultimate goal is to develop a fully-automated Health-as-a-Service (HaaS) and Longevity-as-a-Service (LaaS) engine.
Once plugged into the services of companies from Alibaba to Alphabet, such an engine would enable personalized solutions for online users, helping them prevent diseases and maintain optimal health.
Insilico, alongside other companies tackling AI-powered drug discovery, truly represents the application of the 6 D’s. What was once a prohibitively expensive and human-intensive process is now rapidly becoming digitized, dematerialized, demonetized and, perhaps most importantly, democratized.
Companies like Insilico can now do with a fraction of the cost and personnel what the pharmaceutical industry can barely accomplish with thousands of employees and a hefty bill to foot.
As I discussed in my blog on ‘The Next Hundred-Billion-Dollar Opportunity,’ Google’s DeepMind has now turned its neural networks to healthcare, entering the digitized drug discovery arena.
In 2017, DeepMind achieved a phenomenal feat by matching the fidelity of medical experts in correctly diagnosing over 50 eye disorders.
And just a year later, DeepMind announced a new deep learning tool called AlphaFold. By predicting the elusive ways in which various proteins fold on the basis of their amino acid sequences, AlphaFold may soon have a tremendous impact in aiding drug discovery and fighting some of today’s most intractable diseases.
Artificial Intelligence and Data Crunching
AI is especially powerful in analyzing massive quantities of data to uncover patterns and insights that can save lives. Take WAVE, for instance. Every year, over 400,000 patients die prematurely in US hospitals as a result of heart attack or respiratory failure.
Yet these patients don’t die without leaving plenty of clues. Given information overload, however, human physicians and nurses alone have no way of processing and analyzing all necessary data in time to save these patients’ lives.
Enter WAVE, an algorithm that can process enough data to offer a six-hour early warning of patient deterioration.
Just last year, the FDA approved WAVE as an AI-based predictive patient surveillance system to predict and thereby prevent sudden death.
Another highly valuable yet difficult-to-parse mountain of medical data comprises the 2.5 million medical papers published each year.
For some time, it has become physically impossible for a human physician to read—let alone remember—all of the relevant published data.
To counter this compounding conundrum, Johnson & Johnson is teaching IBM Watson to read and understand scientific papers that detail clinical trial outcomes.
Enriching Watson’s data sources, Apple is also partnering with IBM to provide access to health data from mobile apps.
One such Watson system contains 40 million documents, ingesting an average of 27,000 new documents per day, and providing insights for thousands of users.
After only one year, Watson’s successful diagnosis rate of lung cancer has reached 90 percent, compared to the 50 percent success rate of human doctors.
But what about the vast amount of unstructured medical patient data that populates today’s ancient medical system? This includes medical notes, prescriptions, audio interview transcripts, and pathology and radiology reports.
In late 2018, Amazon announced a new HIPAA-eligible machine learning service that digests and parses unstructured data into categories, such as patient diagnoses, treatments, dosages, symptoms and signs.
Taha Kass-Hout, Amazon’s senior leader in health care and artificial intelligence, told the Wall Street Journal that internal tests demonstrated that the software even performs as well as or better than other published efforts.
On the heels of this announcement, Amazon confirmed it was teaming up with the Fred Hutchinson Cancer Research Center to evaluate “millions of clinical notes to extract and index medical conditions.”
Having already driven extraordinary algorithmic success rates in other fields, data is the healthcare industry’s goldmine for future innovation.
Healthcare, AI & China
In 2017, the Chinese government published its ambitious national plan to become a global leader in AI research by 2030, with healthcare listed as one of four core research areas during the first wave of the plan.
Just a year earlier, China began centralizing healthcare data, tackling a major roadblock to developing longevity and healthcare technologies (particularly AI systems): scattered, dispersed, and unlabeled patient data.
Backed by the Chinese government, China’s largest tech companies—particularly Tencent—have now made strong entrances into healthcare.
Just recently, Tencent participated in a $154 million megaround for China-based healthcare AI unicorn iCarbonX.
Hoping to develop a complete digital representation of your biological self, iCarbonX has acquired numerous US personalized medicine startups.
Considering Tencent’s own Miying healthcare AI platform—aimed at assisting healthcare institutions in AI-driven cancer diagnostics—Tencent is quickly expanding into the drug discovery space, participating in two multimillion-dollar, US-based AI drug discovery deals just this year.
China’s biggest, second-order move into the healthtech space comes through Tencent’s WeChat. In the course of a mere few years, already 60 percent of the 38,000 medical institutions registered on WeChat allow patients to digitally book appointments through Tencent’s mobile platform. At the same time, 2,000 Chinese hospitals accept WeChat payments.
Tencent has additionally partnered with the U.K.’s Babylon Health, a virtual healthcare assistant startup whose app now allows Chinese WeChat users to message their symptoms and receive immediate medical feedback.
Similarly, Alibaba’s healthtech focus started in 2016 when it released its cloud-based AI medical platform, ET Medical Brain, to augment healthcare processes through everything from diagnostics to intelligent scheduling.
Conclusion
As Nvidia CEO Jensen Huang has stated, “Software ate the world, but AI is going to eat software.” Extrapolating this statement to a more immediate implication, AI will first eat healthcare, resulting in dramatic acceleration of longevity research and an amplification of the human healthspan.
Next week, I’ll continue to explore this concept of AI systems in healthcare.
Particularly, I’ll expand on how we’re acquiring and using the data for these doctor-augmenting AI systems: from ubiquitous biosensors, to the mobile healthcare revolution, and finally, to the transformative power of the health nucleus.
As AI and other exponential technologies increase our healthspan by 30 to 40 years, how will you leverage these same exponential technologies to take on your moonshots and live out your massively transformative purpose?
Join Me
Abundance-Digital Online Community: I’ve created a Digital/Online community of bold, abundance-minded entrepreneurs called Abundance-Digital. Abundance-Digital is my ‘onramp’ for exponential entrepreneurs – those who want to get involved and play at a higher level. Click here to learn more.
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Posted in Human Robots