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Technology’s role in modern healthcare is growing. Artificial intelligence is being used for mental health, and smartphones can use add-ons to do things we never would have imagined ten years ago, like diagnose STDs and image our eyes.
Now, mobile health is venturing into new and similarly amazing territory: a smartphone app that uses artificial intelligence and an add-on device to diagnose cervical cancer.
World Health Organization statistics show that 87 percent of cervical cancer deaths occur in developing nations, and there’s a shocking differential in mortality rates between the developed and developing world—of 100,000 women diagnosed with cervical cancer, the disease will kill only two in Western Europe or Australia, but more than 27 in Eastern Africa. This differential is mostly due to the unequal access women in various parts of the world have to high-quality healthcare.
Philanthropic innovation company Global Good is out to change that. They want to use mobile technology to bring quality care and diagnostics to parts of the world that lack doctors and medical infrastructure.
From old to new
Traditional cervical cancer screening works like this: a gynecologist does a Pap smear to get a sample of cervical cells. The sample is sent to an offsite lab to be analyzed, where it joins the queue of thousands of other samples waiting to be analyzed. Results are sent back to the patient’s clinic, and if there’s a problem, the patient must schedule a follow-up visit for further analysis or treatment. During the follow-up visit, the doctor does a colposcopy, which involves examining the cervix with a microscope and taking a biopsy of the abnormal tissue.
That’s a lot of hassle and expense, even for women who have access to all of the above-mentioned resources. What about women in areas where mail service is irregular, or where gynecologists are few and far between?
With Global Good’s diagnostic tool, health workers will use an attachment called an enhanced visual assessment (EVA) scope. It clips onto a smartphone and turns the phone into a sort of colposcope, using an app to take a picture of a woman’s cervix then analyze and store that picture. Women who are determined to have cancerous or pre-cancerous symptoms can then be treated on site.
Whereas prior mobile health solutions might still rely on a person to review the information gathered by the device, Global Good aims to pair their hardware with cutting-edge software. Using the latest in deep learning, they’re building a program that will teach itself to recognize and diagnose the disease.
How it works
The app’s creators partnered with the US National Cancer Institute to get access to 100,000 high-quality, annotated, anonymized cervical images. The images get tagged as belonging to categories like healthy tissue, benign inflammation, precancerous lesions, or suspected cancer.
They’re then fed into a deep learning system, where the software learns to differentiate between categories, progressively improving its ability to recognize symptoms and make accurate diagnoses.
Researchers are training the software with the Cancer Institute’s images before integrating images taken with the EVA scope, which will be more complex due to variations in focus, lighting, and alignment. They’ll then monitor the app’s progress by comparing the diagnoses it makes to diagnoses made by medical experts and lab tests (the traditional way).
Global Good plans to begin field trials of the EVA scope and its accompanying app in Ethiopia this year.
A better (healthcare) future
Their work is part of a growing effort to pair a widely-available technology—smartphones—with artificial intelligence to make previously expensive, complex healthcare processes simpler, cheaper, and accessible to anyone. Just last month, the XPRIZE Foundation awarded $2.5 million for a smartphone add-on kit that diagnoses twelve different illnesses and measures vital signs.
In an ideal future, two big things (among others) will change in healthcare: it will shift from being reactive to being proactive and the gap in quality of care for rich and poor will significantly narrow. Personal health monitoring and point-of-care diagnostics can help with both of those goals.
Technologies like the EVA scope will continue to be applied and adapted to more and more health conditions, and they’ll become cheaper and better in the process. Our ideal healthcare future isn’t here yet, but we’re clearly taking steps in that direction.
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Have Scientists Discovered the Cure for Potholes?Angela Chen | The Verge"Self-healing asphalt has been tested on 12 different roads in the Netherlands, and one of these has been functioning and open to the public since 2010. All are still in perfect condition, but Schlangen notes that even normal asphalt roads are fine for about seven to 10 years and that it’s in upcoming years that we’ll really start to see the difference. He estimates that the overall cost of the material would be 25 percent more expensive than normal asphalt, but it could double the life of the road."
The Little Robot That Taught the Big Robot a Thing or TwoMatt Simon | WIRED"New research out today from the MIT Computer Science and Artificial Intelligence Laboratory takes a big step toward making such seamless transfers of knowledge a reality. It all begins with a little robot named Optimus and its friend, the famous 6-foot-tall humanoid Atlas."
A Cheap, Simple Way to Make Anything a Touch PadRachel Metz | MIT Technology Review"Researchers at Carnegie Mellon University say they’ve come up with a way to make many kinds of devices responsive to touch just by spraying them with conductive paint, adding electrodes, and computing where you press on them…Called Electrick, it can be used with materials like plastic, Jell-O, and silicone, and it could make touch tracking a lot cheaper, too, since it relies on already available paint and parts, Zhang says."
A New 3D Printing Technology Uses Electricity to Create Stronger Objects for ManufacturingBrian Heater | TechCrunch"FuseBox’s thrust is simultaneously dead simple and entirely complex, but at the most elementary level, it utilizes heat and electricity to increase the temperature of the material before and after each level is deposited. This serves to strengthen the body of the printed product where it’s traditionally weakest during the FDM (fused deposition modeling) print – the same layer-by-layer technology employed by MakerBot and the majority of desktop 3D printers."
What Is America's Secret Space Shuttle For?Marina Koren | The Atlantic"The news that the military had a space shuttle quietly orbiting Earth for more than 700 days came as a surprise to some. Why didn’t we know about this thing, the reaction seemed to go. The reaction illustrated the distinct line between the country’s civilian and military activities in space, and how much the general public knows about each."
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Press Release by: Robotart.org
Robots Have Learned to Paint in Second Year of Robotic Art Contest
Seattle, Wash – April 19, 2017 – It was just announced that Google has developed AI that can sketch images. It should therefore come as no surprise that dozens of robots from around the world are now also painting with a brush, and many of them are quite skilled.
The Robot Art 2017 competition (http://robotart.org) returns for a second year with over 39 painting robots, more than twice the amount participants it had in its inaugural year. In addition to more robots, there is more artwork. More than 200 paintings have been submitted. With regards to the quality of the artwork, the event’s sponsor and organizer, Andrew Conru, sums it up best,
“The quality of the paintings for many of the teams have reached levels that are comparable with human artists. Many of this year’s entries are expressive, layered, and complex.”
The creativity of the teams and robots was evident not only in the artwork they produced, but also in how they went about making the art. Of the 39 painting robots, no two teams took the exact same approach. The Manibus Team captured the movements of a ballerina and painted it to canvas. HEARTalion built a robot that paints based on emotional interactions with humans. share your inner unicorn used brainwaves to control a mark making mobile robot. Other teams built custom robots that capitalized on their innate lack of precision to make abstract work such as Anguis, a soft snake robot that slithers around its canvas. Other robots were built to collaborate with their artistic creators such as Sander Idzerda’s and Christian H. Seidler’s entries.
Robot Painter. Photo Credit: Robotart.orgTwo returning entries that were notable for their skilled approach to representational paintings in last year’s contest, have gone abstract. e-David submitted multiple abstract self-portraits, not of a human, but of the robot itself. Each of its works was a collaboration between an artist and the machine where most of the decisions were actually made by e-David as it continually watched and optimized its own progress on the canvas with multiple external cameras. CloudPainter also submitted multiple abstract portraits. It’s subjects were taken from photoshoots performed by the robot itself. For several of CloudPainter’s paintings, the only artistic decision made by an artist was to schedule the photoshoot. The robot then used artificial intelligence and deep learning to make all other “artistic” decisions including taking the photos, making an original abstract composition from its favorite, and then executing each brushstroke until it had calculated it had done the best it could to render its original abstract composition.
Robot Painter. Photo Credit: Robotart.orgThe Robot Art 2017 competition will be running between now and May 15th when more than $100,000 in awards will be given to the top painting robots. Winners will be determined based on a combination of public voting, professional judges consisting of working artists, critics, and technologists, and by how well the team met the spirit of the competition – that is to create something beautiful using a physical brush and robotics. The public can see the artwork vote on their favorite robotic paintings at https://robotart.org/artworks/.
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Twenty years ago, IBM computer Deep Blue beat the world's greatest chess player in a first for machines. How far has artificial intelligence come since then? Continue reading
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.
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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