I get out of bed for two reasons.
One, small-scale family farmers need more food.
It's crazy that in 2019 farmers that feed us are hungry.
And two, science needs to be more diverse and inclusive.
If we're going to solve the toughest challenges on the planet, like food insecurity for the millions living in extreme poverty, it's going to take all of us.
I want to use the latest technology with the most diverse and inclusive teams on the planet to help farmers have more food.
I'm a computational biologist.
I know -- what is that and how is it going to help end hunger?
Basically, I like computers and biology and somehow, putting that together is a job.
(Laughter) I don't have a story of wanting to be a biologist from a young age.
The truth is, I played basketball in college.
And part of my financial aid package was I needed a work-study job.
So one random day, I wandered to the nearest building to my dorm room.
And it just so happens it was the biology building.
I went inside and looked at the job board.
Yes, this is pre-the-internet.
And I saw a three-by-five card advertising a job to work in the herbarium.
I quickly took down the number, because it said "flexible hours," and I needed that to work around my basketball schedule.
I ran to the library to figure out what an herbarium was.
(Laughter) And it turns out an herbarium is where they store dead, dried plants.
I was lucky to land the job.
So my first scientific job was gluing dead plants onto paper for hours on end.
(Laughter) It's so glamorous.
This is how I became a computational biologist.
During that time, genomics and computing were coming of age.
And I went on to do my masters combining biology and computers.
During that time, I worked at Los Alamos National Lab in the theoretical biology and biophysics group.
And it was there I had my first encounter with the supercomputer, and my mind was blown.
With the power of supercomputing, which is basically thousands of connected PCs on steroids, we were able to uncover the complexities of influenza and hepatitis C.
And it was during this time that I saw the power of using computers and biology combined, for humanity.
And I wanted this to be my career path.
So, since 1999, I've spent the majority of my scientific career in very high-tech labs, surrounded by really expensive equipment.
So many ask me how and why do I work for farmers in Africa.
Well, because of my computing skills, in 2013, a team of East African scientists asked me to join the team in the plight to save cassava.
Cassava is a plant whose leaves and roots feed 800 million people globally.
And 500 million in East Africa.
So that's nearly a billion people relying on this plant for their daily calories.
If a small-scale family farmer has enough cassava, she can feed her family and she can sell it at the market for important things like school fees, medical expenses and savings.
But cassava is under attack in Africa.
Whiteflies and viruses are devastating cassava.
Whiteflies are tiny insects that feed on the leaves of over 600 plants.
They are bad news.
There are many species; they become pesticide resistant; and they transmit hundreds of plant viruses that cause cassava brown streak disease and cassava mosaic disease.
This completely kills the plant.
And if there's no cassava, there's no food or income for millions of people.
It took me one trip to Tanzania to realize that these women need some help.
These amazing, strong, small-scale family farmers, the majority women, are doing it rough.
They don't have enough food to feed their families, and it's a real crisis.
What happens is they go out and plant fields of cassava when the rains come.
Nine months later, there's nothing, because of these pests and pathogens.
And I thought to myself, how in the world can farmers be hungry?
So I decided to spend some time on the ground with the farmers and the scientists to see if I had any skills that could be helpful.
The situation on the ground is shocking.
The whiteflies have destroyed the leaves that are eaten for protein, and the viruses have destroyed the roots that are eaten for starch.
An entire growing season will pass, and the farmer will lose an entire year of income and food, and the family will suffer a long hunger season.
This is completely preventable.
If the farmer knew what variety of cassava to plant in her field, that was resistant to those viruses and pathogens, they would have more food.
We have all the technology we need, but the knowledge and the resources are not equally distributed around the globe.
So what I mean specifically is, the older genomic technologies that have been required to uncover the complexities in these pests and pathogens -- these technologies were not made for sub-Saharan Africa.
They cost upwards of a million dollars; they require constant power and specialized human capacity.
These machines are few and far between on the continent, which is leaving many scientists battling on the front lines no choice but to send the samples overseas.
And when you send the samples overseas, samples degrade, it costs a lot of money, and trying to get the data back over weak internet is nearly impossible.
So sometimes it can take six months to get the results back to the farmer.
And by then, it's too late.
The crop is already gone, which results in further poverty and more hunger.
We knew we could fix this.
In 2017, we had heard of this handheld, portable DNA sequencer called an Oxford Nanopore MinION.
This was being used in West Africa to fight Ebola.
So we thought: Why can't we use this in East Africa to help farmers?
So, what we did was we set out to do that.
At the time, the technology was very new, and many doubted we could replicate this on the farm.
When we set out to do this, one of our "collaborators" in the UK told us that we would never get that to work in East Africa, let alone on the farm.
So we accepted the challenge.
This person even went so far as to bet us two of the best bottles of champagne that we would never get that to work.
Two words: pay up.
(Laughter) (Applause) Pay up, because we did it.
We took the entire high-tech molecular lab to the farmers of Tanzania, Kenya and Uganda, and we called it Tree Lab.
So what did we do?
Well, first of all, we gave ourselves a team name -- it's called the Cassava Virus Action Project.
We made a website, we gathered support from the genomics and computing communities, and away we went to the farmers.
Everything that we need for our Tree Lab is being carried by the team here.
All of the molecular and computational requirements needed to diagnose sick plants is there.
And it's actually all on this stage here as well.
We figured if we could get the data closer to the problem, and closer to the farmer, the quicker we could tell her what was wrong with her plant.
And not only tell her what was wrong -- give her the solution.
And the solution is, burn the field and plant varieties that are resistant to the pests and pathogens she has in her field.
So the first thing that we did was we had to do a DNA extraction.
And we used this machine here.
It's called a PDQeX, which stands for "Pretty Damn Quick Extraction."
(Laughter) I know.
My friend Joe is really cool.
One of the biggest challenges in doing a DNA extraction is it usually requires very expensive equipment, and takes hours.
But with this machine, we've been able to do it in 20 minutes, at a fraction of the cost.
And this runs off of a motorcycle battery.
From there, we take the DNA extraction and prepare it into a library, getting it ready to load on to this portable, handheld genomic sequencer, which is here, and then we plug this into a mini supercomputer, which is called a MinIT.
And both of these things are plugged into a portable battery pack.
So we were able to eliminate the requirements of main power and internet, which are two very limiting factors on a small-scale family farm.
Analyzing the data quickly can also be a problem.
But this is where me being a computational biologist came in handy.
All that gluing of dead plants, and all that measuring, and all that computing finally came in handy in a real-world, real-time way.
I was able to make customized databases and we were able to give the farmers results in three hours versus six months.
(Applause) The farmers were overjoyed.
So how do we know that we're having impact?
Nine moths after our Tree Lab, Asha went from having zero tons per hectare to 40 tons per hectare.
She had enough to feed her family and she was selling it at the market, and she's now building a house for her family.
Yeah, so cool.
(Applause) So how do we scale Tree Lab?
The thing is, farmers are scaled already in Africa.
These women work in farmer groups, so helping Asha actually helped 3,000 people in her village, because she shared the results and also the solution.
I remember every single farmer I've ever met.
Their pain and their joy is engraved in my memories.
Our science is for them.
Tree Lab is our best attempt to help them become more food secure.
I never dreamt that the best science I would ever do in my life would be on that blanket in East Africa, with the highest-tech genomic gadgets.
But our team did dream that we could give farmers answers in three hours versus six months, and then we did it.
Because that's the power of diversity and inclusion in science.
Thank you.
(Applause) (Cheers)
A girl I've never met before changed my life and the life of thousands of other people.
I'm the CEO of DoSomething.org.
It's one of the largest organizations in the world for young people.
In fact it's bigger than the Boy Scouts in the United States.
And we're not homophobic.
(Laughter) And it's true -- the way we communicate with young people is by text, because that's how young people communicate.
So we'll run over 200 campaigns this year, things like collecting peanut butter for food pantries, or making Valentine's Day cards for senior citizens who are homebound.
And we'll text them.
And we'll have a 97 percent open rate.
It'll over-index Hispanic and urban.
We collected 200,000 jars of peanut butter and over 365,000 Valentine's Day cards.
This is big scale.
OK -- (Applause) But there's one weird side effect.
Every time we send out a text message, we get back a few dozen text messages having nothing to do with peanut butter or hunger or senior citizens -- but text messages about being bullied, text messages about being addicted to pot.
And the worst message we ever got said exactly this: "He won't stop raping me.
It's my dad.
He told me not to tell anyone.
Are you there?"
We couldn't believe this was happening.
We couldn't believe that something so horrific could happen to a human being, and that she would share it with us -- something so intimate, so personal.
And we realized we had to stop triaging this and we had to build a crisis text line for these people in pain.
So we launched Crisis Text Line, very quietly, in Chicago and El Paso -- just a few thousand people in each market.
And in four months, we were in all 295 area codes in America.
Just to put that into perspective, that's zero marketing and faster growth than when Facebook first launched.
(Applause) Text is unbelievably private.
No one hears you talking.
So we spike everyday at lunch time -- kids are sitting at the lunch table and you think that she's texting the cute boy across the hall, but she's actually texting us about her bulimia.
And we don't get the word "like" or "um" or hyperventilating or crying.
We just get facts.
We get things like, "I want to die.
I have a bottle of pills on the desk in front of me."
And so the crisis counselor says, "How about you put those pills in the drawer while we text?"
And they go back and forth for a while.
And the crisis counselor gets the girl to give her her address, because if you're texting a text line, you want help.
So she gets the address and the counselor triggers an active rescue while they're texting back and forth.
And then it goes quiet -- 23 minutes with no response from this girl.
And the next message that comes in says -- it's the mom -- "I had no idea, and I was in the house, we're in an ambulance on our way to the hospital."
As a mom that one just -- The next message comes a month later.
"I just got out of the hospital.
I was diagnosed as bipolar, and I think I'm going to be OK."
(Applause) I would love to tell you that that's an unusual exchange, but we're doing on average 2.41 active rescues a day.
Thirty percent of our text messages are about suicide and depression -- huge.
The beautiful thing about Crisis Text Line is that these are strangers counseling other strangers on the most intimate issues, and getting them from hot moments to cold moments.
It's exciting, and I will tell you that we have done a total of more than 6.5 million text messages in less than two years.
(Applause) But the thing that really gets me hot and sweaty about this, the thing that really gets me psyched is the data: 6.5 million messages -- that's the volume, velocity and variety to provide a really juicy corpus.
We can do things like predictive work.
We can do all kinds of conclusions and learnings from that data set.
So we can be better, and the world can be better.
So how do we use the data to make us better?
Alright, chances are someone here, someone watching this has seen a therapist or a shrink at some point in time in your life -- you do not have to raise your hand.
(Laughter) How do you know that person's any good?
Oh, they have a degree from Harvard on the wall?
Are you sure he didn't graduate in the bottom 10 percent?
(Laughter) When my husband and I saw a marriage counselor, I thought she was a genius when she said, "I'll see you guys in two weeks -- but I need to see you next week, sir."
(Laughter) We have the data to know what makes a great counselor.
We know that if you text the words "numbs" and "sleeve," there's a 99 percent match for cutting.
We know that if you text in the words "mg" and "rubber band," there's a 99 percent match for substance abuse.
And we know that if you text in "sex," "oral" and "Mormon," you're questioning if you're gay.
Now that's interesting information that a counselor could figure out but that algorithm in our hands means that an automatic pop-up says, "99 percent match for cutting -- try asking one of these questions" to prompt the counselor.
Or "99 percent match for substance abuse, here are three drug clinics near the texter."
It makes us more accurate.
On the day that Robin Williams committed suicide, people flooded hotlines all over this country.
It was sad to see an icon, a funnyman, commit suicide, and there were three hour wait times on every phone hotline in the country.
We had a spike in volume also.
The difference was if you text us, "I want to die," or "I want to kill myself," the algorithm reads that, you're code orange, and you become number one in the queue.
So we can handle severity, not chronological.
(Applause) This data is also making the world better because I'm sitting on the world's first map of real-time crises.
Think about it: those 6.5 million messages, auto-tagging through natural language processes, all of these data points -- I can tell you that the worst day of the week for eating disorders: Monday.
The worst time of day for substance abuse: 5am.
And that Montana is a beautiful place to visit but you do not want to live there, because it is the number one state for suicidal ideation.
And we've made this data public and free and open.
We've pulled all the personally identifiable information.
And it's in a place called CrisisTrends.org.
Because I want schools to be able to see that Monday is the worst day for eating disorders, so that they can plan meals and guidance counselors to be there on Mondays.
And I want families to see that substance abuse questions gwhite@example.com.
I want somebody to take care of those Native American reservations in Montana.
(Applause) Data, evidence makes policy, research, journalism, policing, school boards -- everything better.
I don't think of myself as a mental health activist.
I think of myself as a national health activist.
I get really excited about this data, I'm a little nerdy.
Yeah, that sounded too girly.
I'm nerdy.
(Laughter) I love data.
And the only difference really between me and those people in hoodies down the road with their fat-funded companies, is that I'm not inspired by helping you find Chinese food at 2am in Dallas, or helping you touch your wrist and get a car immediately, or swipe right and get laid.
I'm inspired -- (Laughter, applause) I want to use tech and data to make the world a better place.
I want to use it to help that girl, who texted in about being raped by her father.
Because the truth is we never heard from her again.
And I hope that she is somewhere safe and healthy, and I hope that she sees this talk and she knows that her desperation and her courage inspired the creation of Crisis Text Line and inspires me every freaking day.
(Applause)