Tag Archives: Artificial intelligence

Will artificial intelligence “destroy humanity?” Probably not.
But I am concerned that AI and robotics will massively impact the future of work.
McKinsey & Co. predicts that 45 percent of jobs today will be automated out of existence in only 20 years.
This weighs on me.
While the magnitude of the coming change doesn’t bother me, it's the speed of the change I’m worried about.
(Note: We’ve seen such change before. America went from a society of 84 percent farmers in 1810 to only 2 percent farmers today).
This is a post about one mechanism to buffer the impact of rapid technological unemployment.
In this post, I’ll make the case for universal basic income (UBI) and unpack some of the common misconceptions of giving money away for free.
Eradicating poverty
Today, there are 700 million people around the world living in extreme poverty (defined by the World Bank as $1.25/day (in 2005 prices)).
According to the Brookings Institute, just $80 billion would lift all of them out of extreme poverty.
We spend twice this amount in global aid every year. If only we could give the funds directly to the people who need it most.
In a recent Abundance 360 webinar, I interviewed Michael Faye, the co-founder of GiveDirectly, who presented some compelling data about the disruption of philanthropy through peer-to-peer aid.
Let’s dive in.
What is GiveDirectly?
GiveDirectly is the largest UBI experiment to date.
Over the next 12 years, GiveDirectly is running a controlled trial across 4 villages in Kenya, with more than 26,000 participants.
In addition to a control group, one village will receive a regular basic income for 12 years, another for 2 years, and yet another will receive a single lump sum equivalent to 2 years' worth of income.
Within each village, everyone (man, woman and child) receives the same equal payment of roughly 75 cents per day regardless of their current wealth.
Incredibly, since launching the experiment in 2012, GiveDirectly has distributed more than $100 million in total donations for people in extreme poverty.
The data they are accumulating on the efficacy of UBI is incredible.
Here are the top three takeaways from our conversation.
1. Philanthropy is ripe for disruption
Most of today’s billion-dollar non-profits and NGOs are incredibly inefficient and bureaucratic.
Michael estimates only about “15–20 percent of donations” actually get to recipients, adding that in many cases “the current system is so complex that many of the agencies themselves don’t know the actual number.”
Many programs and donations are in-kind items, such as foods, which are often resold at a discount because the recipients simply don't want them.
By giving cash instead of goods, combined with its mobile-enabled technology stack, GiveDirectly flips that ratio.
For every dollar, 90 cents end up in the hand of the recipient.
2. Directly giving cash has counter-intuitive positive byproducts
As a society, we underestimate the ability of the poor to make decisions in their best interest.
We want to prescribe who gets what, how much, and under what conditions.
For example, Michael asks, “If you ask a child whether they’d prefer to give a poor person a cow, or give them money?” They typically respond that it's better to give a cow. It feels better.
We are also hesitant to give cash for fear that it will lead to increased substance abuse, or lead to laziness.
However, well-documented studies consistently show that cash transfers tend to:
Cause a decline in the purchase of alcohol or tobacco.
Lead to an increase in the hours worked.
For example, in Sri Lanka, a study of one-time transfers found that men’s annual income had increased by 64–96 percent of the grant amount after five years.
In Uganda, 4 years after a small one-time donation, recipients were earning 41 percent more than those who had not received the donation.
3. Cash transfers lead to better health and social outcomes
Looking at over 160 studies across 30 countries and 56 cash transfer programs, the Overseas Development Institute recently performed a meta analysis, finding positive results across areas such as education, health and nutrition, savings and investment, and employment.
Specific to health, studies have found:
Large increases in children’s height and weight in South Africa
Reductions in HIV infections and psychological distress in Malawi
Reductions in low birth weight in Uruguay
Reductions in child labor as well as increases in childhood schooling
Decreases in domestic violence
My closing thoughts
Technological unemployment is coming fast, and it has the potential to lead to significant social unrest.
We need to be proposing and running experiments to validate solutions that work across geographies and cultures at scale.
UBI is one idea. I salute the passionate entrepreneurs who are launching experiments to uncover their solutions.
What will you do to make an impact?
We have the raw materials to create a world of abundance. Let’s get to work.
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To create a new drug, researchers have to test tens of thousands of compounds to determine how they interact. And that’s the easy part; after a substance is found to be effective against a disease, it has to perform well in three different phases of clinical trials and be approved by regulatory bodies.
It’s estimated that, on average, one new drug coming to market can take 1,000 people, 12-15 years, and up to $1.6 billion.

There has to be a better way—and now it seems there is.
Last week, researchers published a paper detailing an artificial intelligence system made to help discover new drugs, and significantly shorten the amount of time and money it takes to do so.
The system is called AtomNet, and it comes from San Francisco-based startup AtomWise. The technology aims to streamline the initial phase of drug discovery, which involves analyzing how different molecules interact with one another—specifically, scientists need to determine which molecules will bind together and how strongly. They use trial and error and process of elimination to analyze tens of thousands of compounds, both natural and synthetic.
AtomNet takes the legwork out of this process, using deep learning to predict how molecules will behave and how likely they are to bind together. The software teaches itself about molecular interaction by identifying patterns, similar to how AI learns to recognize images.
Remember the 3D models of atoms you made in high school, where you used pipe cleaners and foam balls to represent the connections between protons, neutrons and electrons? AtomNet uses similar digital 3D models of molecules, incorporating data about their structure to predict their bioactivity.

As AtomWise COO Alexander Levy put it, “You can take an interaction between a drug and huge biological system and you can decompose that to smaller and smaller interactive groups. If you study enough historical examples of molecules…you can then make predictions that are extremely accurate yet also extremely fast.”
“Fast” may even be an understatement; AtomNet can reportedly screen one million compounds in a day, a volume that would take months via traditional methods.
AtomNet can’t actually invent a new drug, or even say for sure whether a combination of two molecules will yield an effective drug. What it can do is predict how likely a compound is to work against a certain illness. Researchers then use those predictions to narrow thousands of options down to dozens (or less), focusing their testing where there’s more likely to be positive results.
The software has already proven itself by helping create new drugs for two diseases, Ebola and multiple sclerosis. The MS drug has been licensed to a British pharmaceutical company, and the Ebola drug is being submitted to a peer-reviewed journal for additional analysis.
While AtomNet is a promising technology that will make discovering new drugs faster and easier, it’s worth noting that the future of medicine is also moving towards a proactive rather than reactive approach; rather than solely inventing drugs to cure sick people, focus will shift to carefully monitoring our health and taking necessary steps to keep us from getting sick in the first place.
Last year, the Chan Zuckerberg Initiative donated $3 billion in a pledge to “cure all diseases.” It’s an ambitious and somewhat quixotic goal, but admirable nonetheless. In another example of the movement towards proactive healthcare, the XPRIZE foundation recently awarded $2.5 million for a device meant to facilitate home-based diagnostics and personal health monitoring. Proactive healthcare technology is likely to keep advancing and growing in popularity.
That doesn’t mean reactive healthcare shouldn’t advance alongside it; fifty or one hundred years from now, people will still be getting sick and will still need medicine to help cure them. AtomNet is the first software of its kind, and it may soon see others following in its footsteps in the effort to apply AI to large-scale challenges.
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AUTOMATION
Veo Robotics Gives Industrial Robots a Sixth Sense for Safely Working Around PeopleDevin Coldewey | TechCrunch"Veo’s system uses a set of four depth-sensing cameras placed around the work space so as to give complete visual coverage. Once you’ve established that, you designate various things as work pieces, forbidden areas and so on…If any robot, no matter how big and powerful, can work alongside a human, in many cases that’s a better option for a manufacturing workflow."
3D PRINTING
This MIT Robot Could Build Your Next House Completely Out Of Local MaterialsMark Wilson | Fast Company"Keating’s Digital Construction Platform (DCP) looks nothing like a tree. It’s a four-ton solar powered robot arm on tank tracks. And yet, it’s a working proof-of-concept that a machine can build a lot like a tree does, sourcing local energy and adapting to local conditions to construct a building out of local materials…Put more simply, DCP is like a Wall-E that builds things, rather than cleaning up trash."

TRANSPORTATION
Don’t Look Now, but Even Buses Are Going AutonomousAarian Marshall | WIRED"On Tuesday, the University of Nevada, Reno announced the start of a three-phase project to get a real, live autonomous bus on the road by as early as 2019…experiments like this show that robo-buses are coming, and that it’s time to grapple with what that means for public transit."
ROBOTICS
An Ostrich-Like Robot Pushes the Limits of Legged LocomotionWill Knight | MIT Technology Review"The Planar Elliptical Runner has a single motor that drives the legs, and the elliptical motion of its legs together with its body shape provide inherent stability. The robot runs at 10 miles per hour, but if it were the size of a human it would travel at 20 to 30 miles an hour, the researchers say. There is a small but growing interest in finding commercial uses for legged robots."
AVIATION
A Look Inside Airbus’s Epic Assembly LineBinyamin Applebaum | The New York Times"Airbus executives realized years ago that the company could benefit from capturing a larger share of America’s immense military budget. And so it embarked on a strategy of investing in the South, a part of the United States that, historically, hosted only the military half of the military-industrial complex."
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In a few hundred years, doctors will scan their patient with a handheld device called a Tricorder to diagnose virtually any ailment. That’s according to Star Trek. Way back here in the 21st century, we’re not supposed to be anywhere near that utopian technology. But we may not be as far off as you’d think. That’s according to an XPRIZE competition inspired by the iconic show.
Searching for the real-life medical tricorder, in 2012 the XPRIZE Foundation partnered with San Diego-based Qualcomm to launch the Tricorder XPRIZE. And recently, XPRIZE announced the winner.
The contest challenged participants to create a Tricorder device that could diagnose 12 different diseases and capture real-time vital signs with a user-friendly handheld device. Such a device would be a major stepping stone to democratizing healthcare, essentially making reliable, home-based diagnostics available to anyone, anywhere in the world.
The nature of healthcare is currently sporadic and reactive; we go to the doctor once we’re already sick or injured. What if instead, healthcare was continuous and proactive, focusing more on preventing illness in the first place rather than on treating it once it’s already manifested?
It’s hoped that Tricorder-like devices can keep patients healthier while also easing the burden on healthcare professionals. The shortage of doctors that currently exists—especially in remote and rural areas—is likely to worsen in the future.
The contest’s three basic rules were the following:
1. Each team could take its own approach to its Tricorder’s design, but the finished product had to weigh five pounds or less.
2. The Tricorders must be able to diagnose 10 core health conditions, including anemia, diabetes, and pneumonia; a choice of three elective health conditions in a list that includes hypertension, melanoma, and shingles; and all five of the required vital signs.
3. Each Tricorder system must include a way for consumers to input basic health information, be accessible remotely via the internet, and be compatible with any smartphone or tablet.
Sounds like a tall order, but 312 teams from 38 countries stepped up to the challenge. After whittling down the competition and honing their tech over five years, a winner and runner-up were chosen last week and awarded $2.5 million and $1 million for their work, respectively.

Pennsylvania-based Final Frontier Medical Devices took first place for their machine called DxtER. DxtER uses a set of non-invasive sensors to check vital signs, body chemistry and biological functions, and pulls data from clinical emergency medicine. This data is synthesized by an artificial intelligence engine, and DxtER comes up with a diagnosis it claims is both quick and accurate.
The team was a family affair, consisting primarily of brothers George and Basil Harris, an engineer and a physician, respectively. They had help from their sister who’s a health policy expert, and their brother who’s a practicing urologist. Though everyone who worked on the project had a full-time job elsewhere, they put in unpaid hours on nights and weekends to make their vision of the Tricorder a reality.
Taiwan-based Dynamical Biomarkers Group, a research team from the country’s National Central University, took second place with its prototype for a smartphone-based device that pairs diagnostic algorithms with analytical methodology. The three-module system includes a Smart Vital-Sense Monitor, Smart Blood-Urine Test Kit, and a Smart Scope Module, each of which is wirelessly connected to a smartphone equipped with an app that guides the user through diagnostic tests.
In the contest’s final round, the two teams had to put together 45 kits for testing, making sure the kits could be used by non-medical professionals. The kits were subjected to diagnostic experience evaluations and consumer testing, and were rated for disease diagnostics, vital signs, and consumer experience.
Both teams' devices ended up surpassing the competition’s benchmarks for disease diagnosis and the user experience requirements.
Speaking about the Tricorder XPRIZE, Qualcomm Chairman Paul Jacobs said, “The competition is an opportunity to spread the availability of health care to anyone anywhere, even those in developing countries with few skilled health care professionals…mobile health care will allow us to be measured all the time, so we’ll immediately see if we’re better, if the treatment is working, and if the medication needs to be changed. It will no longer be ‘Take this pill and call me in the morning.’”
Though the Tricorder contest has been won, we don’t quite have Star Trek’s Tricorder yet—it was a single all-in-one device, while DxtERs are more like kits. They include sensors that require physical contact with the skin or bodily fluids to do their work. The Tricorder scanned patients at a distance, and it provided universal diagnosis instead of covering a select handful of conditions.
That said, both Final Frontier and Dynamical Biomarkers showed the quick progress being made in miniaturized sensors and computing. The diagnostic portions of their devices aren’t expensive, specialized computer/software combinations; they’re powered by everyday smartphones and the apps that run on them.
Going forward, the sensors used in Tricorder-like devices will get progressively smaller and more capable, expanding their list of diagnosable diseases. The technology developed in the competition may also seed future devices—Final Frontier’s founders have reportedly applied for seven patents involved in their invention.
XPRIZE and Qualcomm have committed $3.8 million to continued testing and development of the Tricorders and will support FDA testing of them too. The companies are even planning to create a documentary and a museum exhibit about the device and its potential.
We may not have a full-fledged Tricorder yet, but judging by this investment and enthusiasm, it seems like just a matter of time until people all over the world can monitor their health better than Dr. McCoy himself.
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