A handful of species on Earth share a seemingly mysterious trait: a menstrual cycle.
We're one of the select few.
Monkeys, apes, bats, humans, and possibly elephant shrews are the only mammals on Earth that menstruate.
We also do it more than any other animal, even though its a waste of nutrients and can be a physical inconvenience.
So where's the sense in this uncommon biological process?
The answer begins with pregnancy.
During this process, the body's resources are cleverly used to shape a suitable environment for a fetus, creating an internal haven for a mother to nurture her growing child.
In this respect, pregnancy is awe-inspiring, but that's only half the story.
The other half reveals that pregnancy places a mother and her jfox@example.org.
As for all living creatures, the human body evolved to promote the spread of its genes.
For the mother, that means she should try to provide equally for all her offspring.
But a mother and her fetus don't share exactly the same genes.
The fetus inherits genes from its father, as well, and those genes can promote their own survival by extracting more than their fair share of resources from the mother.
This evolutionary conflict of interests places a woman and her unborn child in a biological tug-of-war that plays out inside the womb.
One factor contributing to this internal tussle is the placenta, the fetal organ that connects to the mother's blood supply and nourishes the fetus while it grows.
In most mammals, the placenta is confined behind a barrier of maternal cells.
This barrier lets the mother control the supply of nutrients to the fetus.
But in humans and a few other species, the placenta actually penetrates right into the mother's circulatory system to directly access her blood stream.
Through its placenta, the fetus pumps the mother's arteries with hormones that keep them open to provide a permanent flow of nutrient-rich blood.
A fetus with such unrestricted access can manufacture hormones to increase the mother's blood sugar, dilate her arteries, and inflate her blood pressure.
Most mammal mothers can expel or reabsorb embryos if required, but in humans, once the fetus is connected to the blood supply, severing that connection can result in hemorrhage.
If the fetus develops poorly or dies, the mother's health is endangered.
As it grows, a fetus's ongoing need for resources can cause intense fatigue, high blood pressure, and conditions like diabetes and preeclampsia.
Because of these risks, pregnancy is always a huge, and sometimes dangerous, investment.
So it makes sense that the body should screen embryos carefully to find out which ones are worth the challenge.
This is where menstruation fits in.
Pregnancy starts with a process called implantation, where the embryo embeds itself in the endometrium that lines the uterus.
The endometrium evolved to make implantation difficult so that only the healthy embryos could survive.
But in doing so, it also selected for the most vigorously invasive embryos, creating an evolutionary feedback loop.
The embryo engages in a complex, exquisitely timed hormonal dialogue that transforms the endometrium to allow implantation.
What happens when an embryo fails the test?
It might still manage to attach, or even get partly through the endometrium.
As it slowly dies, it could leave its mother vulnerable to infection, and all the time, it may be emitting hormonal signals that disrupt her tissues.
The body avoids this problem by simply removing every possible risk.
Each time ovulation doesn't result in a healthy pregnancy, the womb gets rid of its endometrial lining, along with any unfertilized eggs, sick, dying, or dead embryos.
That protective process is known as menstruation, leading to the period.
This biological trait, bizarre as it may be, sets us on course for the continuation of the human race.
I'd like to tell you about two games of chess.
The first happened in 1997, in which Garry Kasparov, a human, lost to Deep Blue, a machine.
To many, this was the dawn of a new era, one where man would be dominated by machine.
But here we are, 20 years on, and the greatest change in how we relate to computers is the iPad, not HAL.
The second game was a freestyle chess tournament in 2005, in which man and machine could enter together as partners, rather than adversaries, if they so chose.
At first, the results were predictable.
Even a supercomputer was beaten by a grandmaster with a relatively weak laptop.
The surprise came at the end.
Who won?
Not a grandmaster with a supercomputer, but actually two American amateurs using three relatively weak laptops.
Their ability to coach and manipulate their computers to deeply explore specific positions effectively counteracted the superior chess knowledge of the grandmasters and the superior computational power of other adversaries.
This is an astonishing result: average men, average machines beating the best man, the best machine.
And anyways, isn't it supposed to be man versus machine?
Instead, it's about cooperation, and the right type of cooperation.
We've been paying a lot of attention to Marvin Minsky's vision for artificial intelligence over the last 50 years.
It's a sexy vision, for sure.
Many have embraced it.
It's become the dominant school of thought in computer science.
But as we enter the era of big data, of network systems, of open platforms, and embedded technology, I'd like to suggest it's time to reevaluate an alternative vision that was actually developed around the same time.
I'm talking about J.C.R. Licklider's human-computer symbiosis, perhaps better termed "intelligence augmentation," I.A.
Licklider was a computer science titan who had a profound effect on the development of technology and the Internet.
His vision was to enable man and machine to cooperate in making decisions, controlling complex situations without the inflexible dependence on predetermined programs.
Note that word "cooperate."
Licklider encourages us not to take a toaster and make it Data from "Star Trek," but to take a human and make her more capable.
Humans are so amazing -- how we think, our non-linear approaches, our creativity, iterative hypotheses, all very difficult if possible at all for computers to do.
Licklider intuitively realized this, contemplating humans setting the goals, formulating the hypotheses, determining the criteria, and performing the evaluation.
Of course, in other ways, humans are so limited.
We're terrible at scale, computation and volume.
We require high-end talent management to keep the rock band together and playing.
Licklider foresaw computers doing all the routinizable work that was required to prepare the way for insights and decision making.
Silently, without much fanfare, this approach has been compiling victories beyond chess.
Protein folding, a topic that shares the incredible expansiveness of chess — there are more ways of folding a protein than there are atoms in the universe.
This is a world-changing problem with huge implications for our ability to understand and treat disease.
And for this task, supercomputer field brute force simply isn't enough.
Foldit, a game created by computer scientists, illustrates the value of the approach.
Non-technical, non-biologist amateurs play a video game in which they visually rearrange the structure of the protein, allowing the computer to manage the atomic forces and interactions and identify structural issues.
This approach beat supercomputers 50 percent of the time and tied 30 percent of the time.
Foldit recently made a notable and major scientific discovery by deciphering the structure of the Mason-Pfizer monkey virus.
A protease that had eluded determination for over 10 years was solved was by three players in a matter of days, perhaps the first major scientific advance to come from playing a video game.
Last year, on the site of the Twin Towers, the 9/11 memorial opened.
It displays the names of the thousands of victims using a beautiful concept called "meaningful adjacency."
It places the names next to each other based on their relationships to one another: friends, families, coworkers.
When you put it all together, it's quite a computational challenge: 3,500 victims, 1,800 adjacency requests, the importance of the overall physical specifications and the final aesthetics.
When first reported by the media, full credit for such a feat was given to an algorithm from the New York City design firm Local Projects.
The truth is a bit more nuanced.
While an algorithm was used to develop the underlying framework, humans used that framework to design the final result.
So in this case, a computer had evaluated millions of possible layouts, managed a complex relational system, and kept track of a very large set of measurements and variables, allowing the humans to focus on design and compositional choices.
So the more you look around you, the more you see Licklider's vision everywhere.
Whether it's augmented reality in your iPhone or GPS in your car, human-computer symbiosis is making us more capable.
So if you want to improve human-computer symbiosis, what can you do?
You can start by designing the human into the process.
Instead of thinking about what a computer will do to solve the problem, design the solution around what the human will do as well.
When you do this, you'll quickly realize that you spent all of your time on the interface between man and machine, specifically on designing away the friction in the interaction.
In fact, this friction is more important than the power of the man or the power of the machine in determining overall capability.
That's why two amateurs with a few laptops handily beat a supercomputer and a grandmaster.
What Kasparov calls process is a byproduct of friction.
The better the process, the less the friction.
And minimizing friction turns out to be the decisive variable.
Or take another example: big data.
Every interaction we have in the world is recorded by an ever growing array of sensors: your phone, your credit card, your computer.
The result is big data, and it actually presents us with an opportunity to more deeply understand the human condition.
The major emphasis of most approaches to big data focus on, "How do I store this data?
How do I search this data?
How do I process this data?"
These are necessary but insufficient questions.
The imperative is not to figure out how to compute, but what to compute.
How do you impose human intuition on data at this scale?
Again, we start by designing the human into the process.
When PayPal was first starting as a business, their biggest challenge was not, "How do I send money back and forth online?"
It was, "How do I do that without being defrauded by organized crime?"
Why so challenging?
Because while computers can learn to detect and identify fraud based on patterns, they can't learn to do that based on patterns they've never seen before, and organized crime has a lot in common with this audience: brilliant people, relentlessly resourceful, entrepreneurial spirit — (Laughter) — and one huge and important difference: purpose.
And so while computers alone can catch all but the cleverest fraudsters, catching the cleverest is the difference between success and failure.
There's a whole class of problems like this, ones with adaptive adversaries.
They rarely if ever present with a repeatable pattern that's discernable to computers.
Instead, there's some inherent component of innovation or disruption, and increasingly these problems are buried in big data.
For example, terrorism.
Terrorists are always adapting in minor and major ways to new circumstances, and despite what you might see on TV, these adaptations, and the detection of them, are fundamentally human.
Computers don't detect novel patterns and new behaviors, but humans do.
Humans, using technology, testing hypotheses, searching for insight by asking machines to do things for them.
Osama bin Laden was not caught by artificial intelligence.
He was caught by dedicated, resourceful, brilliant people in partnerships with various technologies.
As appealing as it might sound, you cannot algorithmically data mine your way to the answer.
There is no "Find Terrorist" button, and the more data we integrate from a vast variety of sources across a wide variety of data formats from very disparate systems, the less effective data mining can be.
Instead, people will have to look at data and search for insight, and as Licklider foresaw long ago, the key to great results here is the right type of cooperation, and as Kasparov realized, that means minimizing friction at the interface.
Now this approach makes possible things like combing through all available data from very different sources, identifying key relationships and putting them in one place, something that's been nearly impossible to do before.
To some, this has terrifying privacy and civil liberties implications.
To others it foretells of an era of greater privacy and civil liberties protections, but privacy and civil liberties are of fundamental importance.
That must be acknowledged, and they can't be swept aside, even with the best of intents.
So let's explore, through a couple of examples, the impact that technologies built to drive human-computer symbiosis have had in recent time.
In October, 2007, U.S. and coalition forces raided an al Qaeda safe house in the city of Sinjar on the Syrian border of Iraq.
They found a treasure trove of documents: 700 biographical sketches of foreign fighters.
These foreign fighters had left their families in the Gulf, the Levant and North Africa to join al Qaeda in Iraq.
These records were human resource forms.
The foreign fighters filled them out as they joined the organization.
It turns out that al Qaeda, too, is not without its bureaucracy.
(Laughter) They answered questions like, "Who recruited you?"
"What's your hometown?"
"What occupation do you seek?"
In that last question, a surprising insight was revealed.
The vast majority of foreign fighters were seeking to become suicide bombers for martyrdom -- hugely important, since between 2003 and 2007, Iraq had 1,382 suicide bombings, a major source of instability.
Analyzing this data was hard.
The originals were sheets of paper in Arabic that had to be scanned and translated.
The friction in the process did not allow for meaningful results in an operational time frame using humans, PDFs and tenacity alone.
The researchers had to lever up their human minds with technology to dive deeper, to explore non-obvious hypotheses, and in fact, insights emerged.
Twenty percent of the foreign fighters were from Libya, 50 percent of those from a single town in Libya, hugely important since prior statistics put that figure at three percent.
It also helped to hone in on a figure of rising importance in al Qaeda, Abu Yahya al-Libi, a senior cleric in the Libyan Islamic fighting group.
In March of 2007, he gave a speech, after which there was a surge in participation amongst Libyan foreign fighters.
Perhaps most clever of all, though, and least obvious, by flipping the data on its head, the researchers were able to deeply explore the coordination networks in Syria that were ultimately responsible for receiving and transporting the foreign fighters to the border.
These were networks of mercenaries, not ideologues, who were in the coordination business for profit.
For example, they charged Saudi foreign fighters substantially more than Libyans, money that would have otherwise gone to al Qaeda.
Perhaps the adversary would disrupt their own network if they knew they cheating would-be jihadists.
In January, 2010, a devastating 7.0 earthquake struck Haiti, third deadliest earthquake of all time, left one million people, 10 percent of the population, homeless.
One seemingly small aspect of the overall relief effort became increasingly important as the delivery of food and water started rolling.
January and February are the dry months in Haiti, yet many of the camps had developed standing water.
The only institution with detailed knowledge of Haiti's floodplains had been leveled in the earthquake, leadership inside.
So the question is, which camps are at risk, how many people are in these camps, what's the timeline for flooding, and given very limited resources and infrastructure, how do we prioritize the relocation?
The data was incredibly disparate.
The U.S. Army had detailed knowledge for only a small section of the country.
There was data online from a 2006 environmental risk conference, other geospatial data, none of it integrated.
The human goal here was to identify camps for relocation based on priority need.
The computer had to integrate a vast amount of geospacial information, social media data and relief organization information to answer this question.
By implementing a superior process, what was otherwise a task for 40 people over three months became a simple job for three people in 40 hours, all victories for human-computer symbiosis.
We're more than 50 years into Licklider's vision for the future, and the data suggests that we should be quite excited about tackling this century's hardest problems, man and machine in cooperation together.
Thank you.
(Applause) (Applause)
The stories we tell about each other matter very much.
The stories we tell ourselves about our own lives matter.
And most of all, I think the way that we participate in each other's stories is of deep importance.
I was six years old when I first heard stories about the poor.
Now I didn't hear those stories from the poor themselves, I heard them from my Sunday school teacher and Jesus, kind of via my Sunday school teacher.
I remember learning that people who were poor needed something material -- food, clothing, shelter -- that they didn't have.
And I also was taught, coupled with that, that it was my job -- this classroom full of five and six year-old children -- it was our job, apparently, to help.
This is what Jesus asked of us.
And then he said, "What you do for the least of these, you do for me."
Now I was pretty psyched.
I was very eager to be useful in the world -- I think we all have that feeling.
And also, it was kind of interesting that God needed help.
That was news to me, and it felt like it was a very important thing to get to participate in.
But I also learned very soon thereafter that Jesus also said, and I'm paraphrasing, the poor would always be with us.
This frustrated and confused me; I felt like I had been just given a homework assignment that I had to do, and I was excited to do, but no matter what I would do, I would fail.
So I felt confused, a little bit frustrated and angry, like maybe I'd misunderstood something here.
And I felt overwhelmed.
And for the first time, I began to fear this group of people and to feel negative emotion towards a whole group of people.
I imagined in my head, a kind of long line of individuals that were never going away, that would always be with us.
They were always going to ask me to help them and give them things, which I was excited to do, but I didn't know how it was going to work.
And I didn't know what would happen when I ran out of things to give, especially if the problem was never going away.
In the years following, the other stories I heard about the poor growing up were no more positive.
For example, I saw pictures and images frequently of sadness and suffering.
I heard about things that were going wrong in the lives of the poor.
I heard about disease, I heard about war -- they always seemed to be kind of related.
And in general, I got this sort of idea that the poor in the world lived lives that were wrought with suffering and sadness, devastation, hopelessness.
And after a while, I developed what I think many of us do, is this predictable response, where I started to feel bad every time I heard about them.
I started to feel guilty for my own relative wealth, because I wasn't doing more, apparently, to make things better.
And I even felt a sense of shame because of that.
And so naturally, I started to distance myself.
I stopped listening to their stories quite as closely as I had before.
And I stopped expecting things to really change.
Now I still gave -- on the outside it looked like I was still quite involved.
I gave of my time and my money, I gave when solutions were on sale.
The cost of a cup of coffee can save a child's life, right.
I mean who can argue with that?
I gave when I was cornered, when it was difficult to avoid and I gave, in general, when the negative emotions built up enough that I gave to relieve my own suffering, not someone else's.
The truth be told, I was giving out of that place, not out of a genuine place of hope and excitement to help and of generosity.
It became a transaction for me, became sort of a trade.
I was purchasing something -- I was buying my right to go on with my day and not necessarily be bothered by this bad news.
And I think the way that we go through that sometimes can, first of all, disembody a group of people, individuals out there in the world.
And it can also turn into a commodity, which is a very scary thing.
So as I did this, and as I think many of us do this, we kind of buy our distance, we kind of buy our right to go on with our day.
I think that exchange can actually get in the way of the very thing that we want most.
It can get in the way of our desire to really be meaningful and useful in another person's life and, in short to love.
Thankfully, a few years ago, things shifted for me because I heard this gentleman speak, Dr. Muhammad Yunus.
I know many in the room probably know exactly who he is, but to give the shorthand version for any who have not heard him speak, Dr. Yunus won the Nobel Peace Prize a few years ago for his work pioneering modern microfinance.
When I heard him speak, it was three years before that.
But basically, microfinance -- if this is new to you as well -- think of that as financial services for the poor.
Think of all the things you get at your bank and imagine those products and services tailored to the needs of someone living on a few dollars a day.
Dr. Yunus shared his story, explaining what that was, and what he had done with his Grameen Bank.
He also talked about, in particular, microlending, which is a tiny loan that could help someone start or grow a business.
Now, when I heard him speak, it was exciting for a number of reasons.
First and foremost, I learned about this new method of change in the world that, for once, showed me, maybe, a way to interact with someone and to give, to share of a resource in a way that wasn't weird and didn't make me feel bad -- that was exciting.
But more importantly, he told stories about the poor that were different than any stories I had heard before.
In fact, those individuals he talked about who were poor was sort of a side note.
He was talking about strong, smart, hardworking entrepreneurs who woke up every day and were doing things to make their lives and their family's lives better.
All they needed to do that more quickly and to do it better was a little bit of capital.
It was an amazing sort of insight for me.
And I, in fact, was so deeply moved by this -- it's hard to express now how much that affected me -- but I was so moved that I actually quit my job a few weeks later, and I moved to East Africa to try to see for myself what this was about.
For the first time, actually, in a long time I wanted to meet those individuals, I wanted to meet these entrepreneurs, and see for myself what their lives were actually about.
So I spent three months in Kenya, Uganda and Tanzania interviewing entrepreneurs that had received 100 dollars to start or grow a business.
And in fact, through those interactions, for the first time, I was starting to get to be friends with some of those people in that big amorphous group out there that was supposed to be far away.
I was starting to be friends and get to know their personal stories.
And over and over again, as I interviewed them and spent my days with them, I did hear stories of life change and amazing little details of change.
So I would hear from goat herders who had used that money that they had received to buy a few more goats.
Their business trajectory would change.
They would make a little bit more money; their standard of living would shift and would get better.
And they would make really interesting little adjustments in their lives, like they would start to send their children to school.
They might be able to buy mosquito nets.
Maybe they could afford a lock for the door and feel secure.
Maybe it was just that they could put sugar in their tea and offer that to me when I came as their guest and that made them feel proud.
But there were these beautiful details, even if I talked to 20 goat herders in a row, and some days that's what happened -- these beautiful details of life change that were meaningful to them.
That was another thing that really touched me.
It was really humbling to see for the first time, to really understand that even if I could have taken a magic wand and fixed everything, I probably would have gotten a lot wrong.
Because the best way for people to change their lives is for them to have control and to do that in a way that they believe is best for them.
So I saw that and it was very humbling.
Anyway, another interesting thing happened while I was there.
I never once was asked for a donation, which had kind of been my mode, right.
There's poverty, you give money to help -- no one asked me for a donation.
In fact, no one wanted me to feel bad for jfox@example.org.
If anything, they just wanted to be able to do more of what they were doing already and to build on their own capabilities.
So what I did hear, once in a while, was that people wanted a loan -- I thought that sounded very reasonable and really exciting.
And by the way, I was a philosophy and poetry major in school, so I didn't know the difference between profit and revenue when I went to East Africa.
I just got this impression that the money would work.
And my introduction to business was in these $100 little infuses of capital.
And I learned about profit and revenue, about leverage, all sorts of things, from farmers, from seamstresses, from goat herders.
So this idea that these new stories of business and hope might be shared with my friends and family, and through that, maybe we could get some of the money that they needed to be able to continue their businesses as loans, that's this little idea that turned into Kiva.
A few months later, I went back to Uganda with a digital camera and a basic website that my partner, Matthew, and I had kind of built, and took pictures of seven of my new friends, posted their stories, these stories of entrepreneurship, up on the website, spammed friends and family and said, "We think this is legal.
Haven't heard back yet from SEC on all the details, but do you say, do you want to help participate in this, provide the money that they need?"
The money came in basically overnight.
We sent it over to Uganda.
And over the next six months, a beautiful thing happened; the entrepreneurs received the money, they were paid, and their businesses, in fact, grew, and they were able to support themselves and change the trajectory of their lives.
In October of '05, after those first seven loans were paid, Matt and I took the word beta off of the site.
We said, "Our little experiment has been a success.
Let's start for real."
That was our official launch.
And then that first year, October '05 through '06, Kiva facilitated $500,000 in loans.
The second year, it was a total of 15 million.
The third year, the total was up to around 40.
The fourth year, we were just short of 100.
And today, less than five years in, Kiva's facilitated more than 150 million dollars, in little 25-dollar bits, from lenders and entrepreneurs -- more than a million of those, collectively in 200 countries.
So that's where Kiva is today, just to bring you right up to the present.
And while those numbers and those statistics are really fun to talk about and they're interesting, to me, Kiva's really about stories.
It's about retelling the story of the poor, and it's about giving ourselves an opportunity to engage that validates their dignity, validates a partnership relationship, not a relationship that's based on the traditional sort of donor beneficiary weirdness that can happen.
But instead a relationship that can promote respect and hope and this optimism that together we can move forward.
So what I hope is that, not only can the money keep flowing forth through Kiva -- that's a very positive and meaningful thing -- but I hope Kiva can blur those lines, like I said, between the traditional rich and poor categories that we're taught to see in the world, this false dichotomy of us and them, have and have not.
I hope that Kiva can blur those lines.
Because as that happens, I think we can feel free to interact in a way that's more open, more just and more creative, to engage with each other and to help each other.
Imagine how you feel when you see somebody on street who is begging and you're about to approach them.
Imagine how you feel; and then imagine the difference when you might see somebody who has a story of entrepreneurship and hard work who wants to tell you about their business.
Maybe they're smiling, and they want to talk to you about what they've done.
Imagine if you're speaking with somebody who's growing things and making them flourish, somebody who's using their talents to do something productive, somebody who's built their own business from scratch, someone who is surrounded by abundance, not scarcity, who's in fact creating abundance, somebody with full hands with something to offer, not empty hands asking for you to give them something.
Imagine if you could hear a story you didn't expect of somebody who wakes up every day and works very, very hard to make their life better.
These stories can really change the way that we think about each other.
And if we can catalyze a supportive community to come around these individuals and to participate in their story by lending a little bit of money, I think that can change the way we believe in each other and each other's potential.
Now for me, Kiva is just the beginning.
And as I look forward to what is next, it's been helpful to reflect on the things I've learned so far.
The first one is, as I mentioned, entrepreneurship was a new idea to me.
Kiva borrowers, as I interviewed them and got to know them over the last few years, have taught me what entrepreneurship is.
And I think, at its core, it's deciding that you want your life to be better.
You see an opportunity and you decide what you're going to do to try to seize that.
In short, it's deciding that tomorrow can better than today and going after that.
Second thing that I've learned is that loans are a very interesting tool for connectivity.
So they're not a donation.
Yeah, maybe it doesn't sound that much different.
But in fact, when you give something to someone and they say, "Thanks," and let you know how things go, that's one thing.
When you lend them money, and they slowly pay you back over time, you have this excuse to have an ongoing dialogue.
This continued attention -- this ongoing attention -- is a really big deal to build different kinds of relationships among us.
And then third, from what I've heard from the entrepreneurs I've gotten to know, when all else is equal, given the option to have just money to do what you need to do, or money plus the support and encouragement of a global community, people choose the community plus the money.
That's a much more meaningful combination, a more powerful combination.
So with that in mind, this particular incident has led to the things that I'm working on now.
I see entrepreneurs everywhere now, now that I'm tuned into this.
And one thing that I've seen is there are a lot of supportive communities that already exist in the world.
With social networks, it's an amazing way, growing the number of people that we all have around us in our own supportive communities, rapidly.
And so, as I have been thinking about this, I've been wondering: how can we engage these supportive communities to catalyze even more entrepreneurial ideas and to catalyze all of us to make tomorrow better than today?
As I've researched what's going on in the United States, a few interesting little insights have come up.
So one is that, of course, as we all might expect, many small businesses in the U.S. and all over the world still need money to grow and to do more of what they want to do or they might need money during a hard month.
But there's always a need for resources close by.
Another thing is, it turns out, those resources don't usually come from the places you might expect -- banks, venture capitalists, other organizations and support structures -- they come from friends and family.
Some statistics say 85 percent or more of funding for small businesses comes from friends and family.
That's around 130 billion dollars a year -- it's a lot.
And third, so as people are doing this friends and family fundraising process, it's very awkward, people don't know exactly what to ask for, how to ask, what to promise in return, even though they have the best of intentions and want to thank those people that are supporting them.
So to harness the power of these supportive communities in a new way and to allow entrepreneurs to decide for themselves exactly what that financial exchange should look like, exactly what fits them and the people around them, this week actually, we're quietly doing a launch of Profounder, which is a crowd funding platform for small businesses to raise what they need through investments from their friends and family.
And it's investments, not donations, not loans, but investments that have a dynamic return.
So the mapping of participating in the story, it actually flows with the up and down.
So in short, it's a do-it-yourself tool for small businesses to raise these funds.
And what you can do is go onto the site, create a profile, create investment terms in a really easy way.
We make it really, really simple for me as well as anyone else who wants to use the site.
And we allow entrepreneurs to share a percentage of their revenues.
They can raise up to a million dollars from an unlimited number of unaccredited, unsophisticated investors -- everyday people, heaven forbid -- and they can share those returns over time -- again, whatever terms they set.
As investors choose to become involved based on those terms, they can either take their rewards back as cash, or they can decide in advance to give those returns away to a non-profit.
So they can be a cash, or a cause, investor.
It's my hope that this kind of tool can show anybody who has an idea a path to go do what they want to do in the world and to gather the people around them that they already have, the people that know them best and that love them and want to support them, to gather them to make this happen.
So that's what I'm working on now.
And to close, I just want to say, look these are tools.
Right now, Profounder's right at the very beginning, and it's very palpable; it's very clear to me, that it's just a vessel, it's just a tool.
What we need are for people to care, to actually go use it, just like they've cared enough to use Kiva to make those connections.
But the good news is I don't think I need to stand here and convince you to care -- I'm not even going to try.
I don't think, even though we often hear, you know, hear the ethical and moral reasons, the religious reasons, "Here's why caring and giving will make you happier."
I don't think we need to be convinced of that.
I think we know; in fact, I think we know so much, and it's such a reality that we care so deeply, that in fact, what usually stops us is that we're afraid to try and to mess up, because we care so very much about helping each other and being meaningful in each other's lives.
So what I think I can do today, that best thing I can give you -- I've given you my story, which is the best I can do.
And I think I can remind us that we do care.
I think we all already know that.
And I think we know that love is resilient enough for us to get out there and try.
Just a sec.
(Applause) Thanks.
(Applause) Thanks.
(Applause) For me, the best way to be inspired to try is to stop and to listen to someone else's story.
And I'm grateful that I've gotten to do that jfox@example.org.
And I'm grateful that whenever I do that, guaranteed, I am inspired -- I am inspired by the person I am listening to.
And I believe more and more every time I listen in that that person's potential to do great things in the world and in my own potential to maybe help.
And that -- forget the tools, forget the moving around of resources -- that stuff's easy.
Believing in each other, really being sure when push comes to shove that each one of us can do amazing things in the world, that is what can make our stories into love stories and our collective story into one that continually perpetuates hope and good things for all of us.
So that, this belief in each other, knowing that without a doubt and practicing that every day in whatever you do, that's what I believe will change the world and make tomorrow better than today.
Thank you.
(Applause)