Big data, small farms and a tale of two tomatoes
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0:01 - 0:05So data and analytics are dramatically
changing our everyday lives. -
0:06 - 0:07Not just online,
-
0:07 - 0:09not just in some distant future,
-
0:09 - 0:10but in the physical world,
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0:10 - 0:13and in very real and tangible ways.
-
0:14 - 0:18I spent the past 11 years
of my life as a geek at MIT, -
0:18 - 0:20working in big data labs
-
0:20 - 0:23that seek to use data science
to study the physical world -
0:23 - 0:26and try to solve society's great problems.
-
0:27 - 0:31The field of big data seeks to analyze
massive pools of data -
0:31 - 0:35using computational tools
to find patterns and trends. -
0:36 - 0:39Data can be a really
extraordinary storyteller, -
0:39 - 0:42unveiling the hidden narratives
of things in our everyday lives -
0:42 - 0:43that we never would have seen.
-
0:43 - 0:47I find the personal stories of inanimate
things brought to life -
0:47 - 0:49to be extraordinarily compelling.
-
0:50 - 0:53I want to highlight, first,
two projects from my time at MIT -
0:53 - 0:55that I think highlight
this phenomenon really well. -
0:56 - 0:58The first is called Trash Track,
-
0:58 - 1:02and in this project, we sought to better
understand the waste-management system, -
1:02 - 1:04to answer the question
-
1:04 - 1:06"Where does your trash go
when you throw it away?" -
1:06 - 1:09Your old coffee cup or that flip phone
-
1:09 - 1:11that you carried around
in the early 2000s, -
1:11 - 1:15or a bagel or this morning's paper --
-
1:15 - 1:16where do these things go?
-
1:17 - 1:20This data didn't exist,
so we had to create it. -
1:20 - 1:23We answered and then
visualized this question -
1:23 - 1:27by installing small sensors
into pieces of trash -
1:27 - 1:29and then throwing them
into the waste system. -
1:30 - 1:32And what you're seeing here is the data.
-
1:33 - 1:36Every line, every node that you see
-
1:36 - 1:39is a single piece of trash
moving through the city of Seattle, -
1:39 - 1:42and then across the state,
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1:42 - 1:43and then across the country,
-
1:43 - 1:45as weeks and months go by.
-
1:46 - 1:48And it's important to visualize this data,
-
1:48 - 1:50because none of you
are, probably, sitting here thinking, -
1:50 - 1:52"Yeah, that looks right."
-
1:52 - 1:54(Laughter)
-
1:54 - 1:55"That's working like it should, right?"
-
1:55 - 1:57Because, no --
-
1:57 - 1:58(Laughter)
-
1:59 - 2:03What the data shows us
is a highly inefficient system -
2:03 - 2:06whose inherent brokenness
I don't think we really would have seen -
2:07 - 2:09had the sensors not done
the journalism for us. -
2:11 - 2:13A second project
that I'd have to highlight -
2:13 - 2:18has to do with creating robots
that dive into sewers -
2:18 - 2:20and sample wastewater.
-
2:20 - 2:23I know that sewage kind of gets a bad rap,
-
2:23 - 2:25but it's actually kind of awesome,
-
2:25 - 2:27because it can tell us
an incredible amount -
2:27 - 2:29about the health of our communities.
-
2:29 - 2:32This technology was spun out
by a group call Biobot Analytics, -
2:32 - 2:35who's creating a cutting-edge technology
-
2:35 - 2:39to turn our sewers into modern-day
health observatories. -
2:39 - 2:42Their goal is to study opioids
within the sewage -
2:42 - 2:45to better understand
consumption in cities. -
2:45 - 2:47And this data is key,
-
2:47 - 2:50because it really helps cities understand
where people are using, -
2:50 - 2:52how to allocate resources
-
2:52 - 2:55and the effectiveness
of programming over time. -
2:56 - 2:58Once again, the technology
that's built into this machine -
2:58 - 3:00is pulling back the curtain
-
3:00 - 3:04and showing us something about our cities
that we never would have seen without it. -
3:04 - 3:07So it turns out, as we see,
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3:07 - 3:09that big data is really everywhere --
-
3:09 - 3:11even in your toilet.
-
3:11 - 3:15And so now that we've talked
about trash and sewage, -
3:15 - 3:16let's move on ...
-
3:16 - 3:18to food.
-
3:18 - 3:19(Laughter)
-
3:19 - 3:22A year ago, I left MIT
to pursue a passion in food, -
3:22 - 3:24and in 2017,
-
3:24 - 3:27started a company with my husband,
called Family Dinner. -
3:27 - 3:31The goal of our company
is to create community around local food -
3:31 - 3:33and the people who grow it.
-
3:33 - 3:35To make this happen,
we're using data analytics, -
3:35 - 3:38automation and technology
-
3:38 - 3:40to build a distributed
network of local farms -
3:40 - 3:43and to make improvements
on the food system. -
3:43 - 3:45So what we see here
-
3:45 - 3:48is that the broad techniques
and the mission of what we're trying to do -
3:48 - 3:51is really not dissimilar
from the work at the MIT labs. -
3:52 - 3:55Which brings us to a critical question:
-
3:55 - 3:59Why exactly would someone
leave a very promising career -
3:59 - 4:03at one of the top
urban science labs in the world -
4:03 - 4:06to drive carrots around
in her mom's Acura? -
4:06 - 4:08(Laughter)
-
4:08 - 4:09It's a great car.
-
4:10 - 4:13Because I believe
that the story of local food -
4:13 - 4:17needs to be understood, told and elevated,
-
4:17 - 4:18and in many ways,
-
4:18 - 4:22I think that nerds like us
are really uniquely poised to tell it. -
4:22 - 4:24So where are we starting?
-
4:24 - 4:25What's our starting point?
-
4:26 - 4:30The current national food system
is optimized for one thing only, -
4:30 - 4:33and that's corporate profit, right?
-
4:33 - 4:34And think about that.
-
4:34 - 4:37The most compelling reason
for food companies to exist -
4:37 - 4:39is not to feed hungry people,
-
4:39 - 4:41it's not to make delicious-tasting food.
-
4:42 - 4:43It's profit.
-
4:44 - 4:47And that has detrimental effects
at all levels of our food system. -
4:48 - 4:51The antibiotics and pesticides
that are being put into our food -
4:51 - 4:53are detrimental to our health.
-
4:53 - 4:56Price pressure is forcing
small farms out of business. -
4:56 - 4:59In fact, a lot of the things
that you think about farms -
4:59 - 5:00no longer exist.
-
5:00 - 5:03Farms don't look like farms,
they look like factories. -
5:03 - 5:04And at the end of the day,
-
5:04 - 5:07the quality of the food
that we're eating really suffers, too. -
5:08 - 5:12A factory-farm tomato
may kind of look like a regular tomato: -
5:12 - 5:14bright red exterior ...
-
5:14 - 5:15But when you bite into it,
-
5:15 - 5:18the taste and texture
just leave you wanting. -
5:19 - 5:22And we know that perhaps
the greatest tragedy in all of this -
5:22 - 5:26is that between 30 and 40 percent
of this food is just wasted ... -
5:27 - 5:28thrown away.
-
5:28 - 5:31That is 1.6 billion tons.
-
5:31 - 5:33I can't even wrap my head
around that number. -
5:33 - 5:361.6 billion tons.
-
5:36 - 5:39That's 1.2 trillion dollars a year
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5:39 - 5:41in wasted food.
-
5:42 - 5:44That is the cost of on-demand eating
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5:44 - 5:45and convenience
-
5:45 - 5:47and the broken food system.
-
5:47 - 5:49Now, where's this waste happening?
-
5:49 - 5:51Where's all this waste coming from?
-
5:51 - 5:53Well, we know that it happens in the field
-
5:53 - 5:55when you don't pick
the sexiest-looking potatoes. -
5:55 - 5:58We know that it happens in transit,
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5:58 - 5:59at the warehouses,
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5:59 - 6:01in the grocery stores.
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6:01 - 6:03And finally, on our own kitchen counters,
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6:03 - 6:08when we determine that that spotty,
brown banana no longer looks so yummy. -
6:08 - 6:10All that waste, all that effort.
-
6:11 - 6:12Food is planted,
-
6:12 - 6:15grown, harvested, shipped,
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6:15 - 6:17and then just thrown away.
-
6:19 - 6:21We think that there has to be
a better way. -
6:22 - 6:24And so how to we improve upon this?
-
6:24 - 6:26How do we make a better system?
-
6:27 - 6:28In order to do this,
-
6:28 - 6:30we understand that we need
to eliminate waste -
6:30 - 6:32in the food supply chain.
-
6:33 - 6:35We need to get data
in the hands of farmers, -
6:35 - 6:37so that they can make better predictions.
-
6:37 - 6:40So they can, you know,
kind of compete with the big guy. -
6:40 - 6:41And then finally,
-
6:41 - 6:43we need to prize, as a company,
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6:43 - 6:46quality and taste above everything,
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6:46 - 6:49so that people really value
the delicious food on their plates. -
6:50 - 6:53This, we believe, is the better system.
-
6:53 - 6:55This is the better way.
-
6:55 - 6:58And the path to that better way
is paved with data. -
6:59 - 7:03To highlight all of this,
I want to tell the tale of two tomatoes. -
7:04 - 7:06We'll talk about them one by one.
-
7:06 - 7:09A tomato in itself contains
a beautiful snapshot -
7:09 - 7:13of everything you might want to know
about the life cycle of that fruit: -
7:13 - 7:15where it was grown,
what it was treated with, -
7:15 - 7:17nutritional value,
-
7:17 - 7:18miles traveled to get to your plate,
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7:18 - 7:21CO2 emissions along the way.
-
7:21 - 7:22All of that information,
-
7:22 - 7:25all those little chapters
in one small fruit. -
7:25 - 7:26It's very exciting.
-
7:27 - 7:29This is tomato number one.
-
7:29 - 7:33This is the guy that you'll find
in sub shops, supermarkets -
7:33 - 7:35and fast-food joints around the world.
-
7:35 - 7:38It's got a really long
and complicated backstory. -
7:39 - 7:43It's been treated with a cocktail
of, like, a dozen pesticides -
7:43 - 7:48and it has traveled at least
1,600 miles to get to your house. -
7:48 - 7:50And the image here is green,
-
7:50 - 7:54because these tomatoes are picked
when green and hard as a rock, -
7:54 - 7:56and then they are gassed along the way
-
7:56 - 7:58so that when they arrive
at the destination, -
7:58 - 8:01they look bright and shiny
and red and ripe. -
8:02 - 8:04All of that effort,
-
8:04 - 8:08all of that agricultural
innovation and technology -
8:08 - 8:12to create a product
that is entirely without taste. -
8:12 - 8:15And onto the second tomato in our tale.
-
8:15 - 8:17This is the local version of the fruit.
-
8:17 - 8:19Its story is much, much shorter.
-
8:20 - 8:24This guy was grown by Luke Mahoney
and his family at Brookford Farm -
8:24 - 8:25in Canterbury, New Hampshire.
-
8:26 - 8:28It's got a pretty boring backstory.
-
8:29 - 8:30It was planted,
-
8:30 - 8:32sat in the sun
-
8:32 - 8:33and then it was picked.
-
8:33 - 8:34(Laughter)
-
8:34 - 8:36That's it.
-
8:36 - 8:37Like, you wouldn't want to --
-
8:37 - 8:39yeah, there's not much more to that.
-
8:39 - 8:43And it traveled maybe 70 miles
to get your plate. -
8:43 - 8:44But the difference is dramatic.
-
8:45 - 8:48I want you think about the last time
you ate a fresh, summer tomato. -
8:48 - 8:50And I know we're all
covered in our jackets, -
8:50 - 8:51but think about it.
-
8:51 - 8:54The last time you ate
a tomato from the garden. -
8:54 - 8:55It's warm from the sun,
-
8:55 - 8:57it's richly red,
-
8:57 - 8:58maybe it smells like dirt.
-
8:58 - 9:02There's something nostalgic
and almost magical in that experience. -
9:02 - 9:05The taste and the flavor are incomparable.
-
9:06 - 9:09And we really don't have to travel
super far to get it. -
9:11 - 9:13Now this story extends up the food chain,
-
9:13 - 9:16from the fruits and the vegetables
that are on our plate -
9:16 - 9:19to the animals and the animal
products that we consume. -
9:20 - 9:21What goes into raising them,
-
9:21 - 9:25and more importantly,
what doesn't go into raising them, -
9:25 - 9:27is critically important.
-
9:28 - 9:30Luke and his family have 60 cows.
-
9:31 - 9:32They use traditional methods.
-
9:32 - 9:34They do it the old way:
-
9:34 - 9:35pasture-raised,
-
9:35 - 9:38no hormones, no antibiotics,
-
9:38 - 9:39hay for days.
-
9:40 - 9:44And what they're doing here
is just treating cows like they're cows, -
9:44 - 9:46not like they're in a science experiment.
-
9:46 - 9:49He's raising animals the way
that his grandfather -
9:49 - 9:51and his grandfather would have.
-
9:51 - 9:53And at the end, it's just better.
-
9:53 - 9:54It's better for the animals;
-
9:54 - 9:56it's better for the environment.
-
9:56 - 9:58Luke is not optimizing
for profit or price, -
9:58 - 10:00but for taste and for humanity.
-
10:01 - 10:05And what you're thinking is,
"There's already a solution to this. -
10:05 - 10:06It's the farmer's markets."
-
10:06 - 10:08The ones that many of you visit
-
10:08 - 10:10and the ones that I really enjoy.
-
10:10 - 10:14They are a wonderful, but,
in many ways, suboptimal solution. -
10:14 - 10:17For us as the consumers,
it's kind of great, right? -
10:17 - 10:18You go,
-
10:18 - 10:20there's this beautiful bounty of food,
-
10:20 - 10:23you get the warm and fuzzies
for supporting a local farm -
10:23 - 10:28and you get the experience of trying
something new and trying diverse products. -
10:28 - 10:30And inevitably, there's some guy
playing the ukulele -
10:30 - 10:31somewhere in the background.
-
10:31 - 10:32(Laughter)
-
10:34 - 10:37But for the farmers,
this presents a lot of risk, right? -
10:37 - 10:38You wake up at four.
-
10:38 - 10:40You pack your truck, you hire a team,
-
10:40 - 10:42you get to your stall,
-
10:42 - 10:44but you have no guarantees
-
10:44 - 10:46that you're going to move
your product that day. -
10:46 - 10:48There's too many variables in New England.
-
10:48 - 10:50For example, the weather,
-
10:50 - 10:53which is just, like,
a little bit unpredictable here. -
10:54 - 10:56The weather is one of the many X factors
-
10:56 - 11:00that determine whether or not
a market will be worth it for the farmers. -
11:01 - 11:03Every time, they roll the dice.
-
11:04 - 11:06And there's another option.
-
11:06 - 11:08Here, we're talking about CSAs:
-
11:08 - 11:10community-supported agriculture.
-
11:10 - 11:12In this model, customers pay up front,
-
11:13 - 11:15bearing the financial risk for the farms.
-
11:15 - 11:16Farmers grow what they can
-
11:16 - 11:19and the customers enjoy that bounty.
-
11:19 - 11:21This also has a couple issues.
-
11:21 - 11:22It's great for the farmer,
-
11:22 - 11:25because they're ensuring
that they'll sell what they buy, -
11:25 - 11:26but for us,
-
11:26 - 11:28we still have to go
and pick up that share, -
11:28 - 11:32and we know that a lot of farms
can't grow a huge diversity of products, -
11:32 - 11:35so sometimes, you're stuck with a mountain
of any one particular thing. -
11:36 - 11:38Maybe this has happened to some of you.
-
11:38 - 11:42And what do you do with 25 pounds
of rutabaga in the dead of winter? -
11:42 - 11:44I still don't know.
-
11:45 - 11:47So back to the question.
-
11:47 - 11:49How do we fix this?
-
11:49 - 11:51What we're hoping to do
and what we're hoping to build -
11:51 - 11:53is just a better way to CSA.
-
11:54 - 11:59And there are three core innovations
that make this thing hum. -
11:59 - 12:01The first of which
-
12:01 - 12:04is a subscription-based
e-commerce platform, -
12:04 - 12:06which helps us create
a consistent demand for our farmers -
12:06 - 12:08throughout the year.
-
12:08 - 12:10The subscription part here is key.
-
12:10 - 12:12Orders process weekly,
-
12:12 - 12:14customers opt out instead of opt in --
-
12:14 - 12:17that means we've got kind of the same
number of orders week to week. -
12:18 - 12:22Second, this means
that if farmers can sell online, -
12:22 - 12:25they're no longer limited to the geography
directly around their farm -
12:25 - 12:28or to the number of markets
that they can sell. -
12:28 - 12:30We've blown the doors
off of that for them. -
12:31 - 12:33Second: demand forecasting.
-
12:33 - 12:36We're using analytics to allow
ourselves to look into the future -
12:36 - 12:37and forecast demand.
-
12:37 - 12:41This lets farmers know
how much to harvest in the near-term, -
12:41 - 12:43but also what to plant going forward.
-
12:44 - 12:46If 200 orders process on Monday,
-
12:46 - 12:48then we buy to meet that exact demand.
-
12:49 - 12:50200 heads of broccoli,
-
12:50 - 12:52200 pieces of salmon,
et cetera, et cetera. -
12:53 - 12:54This automation in ordering
-
12:54 - 12:59means that here, we are eliminating
the waste in the food system -
12:59 - 13:01that bothers us all so much,
-
13:01 - 13:05because we are ensuring that the supply
meets the exact demand. -
13:06 - 13:08It also allows us to look
into the future with the farmers -
13:08 - 13:10and do crop planning.
-
13:10 - 13:12So if we can say to them,
in June of this year, -
13:12 - 13:14"I'm going to need 400 pounds of asparagus
-
13:15 - 13:17and 500 pounds of berries every week,"
-
13:17 - 13:19they can plant that accordingly,
-
13:19 - 13:21knowing with confidence
that they will sell -
13:21 - 13:23everything that they have grown.
-
13:23 - 13:25And finally, we use
a route-optimization software -
13:25 - 13:28to help us solve the problem
of the traveling salesman. -
13:28 - 13:32We get a fleet of workers to come in
and help us go the last mile, -
13:32 - 13:34bringing all these goodies
directly to your door. -
13:34 - 13:36Without data science
-
13:36 - 13:38and a super-capable, wonderful team,
-
13:38 - 13:40none of this would be possible.
-
13:41 - 13:42So maybe you've seen
-
13:42 - 13:46that we've got some sort of fiery,
passionate core beliefs. -
13:46 - 13:48Yes, we're trying to build
a sustainable business, -
13:49 - 13:51but our eye is not only on profit,
-
13:51 - 13:53it's on building a better,
holistic system of food. -
13:54 - 13:56And here's what we value.
-
13:56 - 13:58People first.
-
13:58 - 14:00We're trying to build
community around food, -
14:00 - 14:02the people who love it
and the people who grow it. -
14:02 - 14:05We built this company
to support small farms. -
14:06 - 14:07Zero waste.
-
14:07 - 14:10We all hate wasting food,
it just feels wrong -- -
14:10 - 14:11even that weirdo banana
-
14:11 - 14:14that's been sitting around
on your coffee table for too long. -
14:14 - 14:16And lastly, taste.
-
14:16 - 14:18If it doesn't taste good,
-
14:18 - 14:21if it's not that, like,
perfect summer tomato, -
14:21 - 14:22why bother?
-
14:23 - 14:25So what we've done
is worked with all these local farms -
14:25 - 14:27to bring their things in
-
14:27 - 14:29and then to drop them
directly at your door, -
14:29 - 14:31so that we're connecting you right to them
-
14:31 - 14:34and making, again, a more holistic system.
-
14:34 - 14:36This is our vision of the future.
-
14:36 - 14:40To extend this model beyond Boston,
beyond New England -
14:40 - 14:42and across the country.
-
14:42 - 14:46To create a nationwide
distributed network of local farms -
14:46 - 14:48and to connect all these farmers
-
14:48 - 14:50with the people like you
who will love their food. -
14:52 - 14:53We believe, at the end of the day,
-
14:53 - 14:58that really insisting on eating local food
is a revolutionary act. -
14:58 - 15:00And we invite you to join us.
-
15:00 - 15:02And who knows?
-
15:02 - 15:05You may even make
some friends along the way. -
15:06 - 15:07Thank you very much.
-
15:07 - 15:08(Applause)
- Title:
- Big data, small farms and a tale of two tomatoes
- Speaker:
- Erin Baumgartner
- Description:
-
The path to better food is paved with data, says entrepreneur Erin Baumgartner. Drawing from her experience running a farm-to-table business, she outlines her plan to help create a healthier, zero-waste food system that values the quality and taste of small, local farm harvests over factory-farmed produce.
- Video Language:
- English
- Team:
- closed TED
- Project:
- TEDTalks
- Duration:
- 15:21
Victor Borges commented on English subtitles for Big data, small farms and a tale of two tomatoes | ||
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Krystian Aparta edited English subtitles for Big data, small farms and a tale of two tomatoes |
Victor Borges
I think she meant (5:53):
when you [only] pick
the sexiest-looking potatoes.
or
when you don't pick
[the least sexy-looking] potatoes.
Victor Borges
I think she meant (5:53):
when you [only] pick
the sexiest-looking potatoes.
or
when you don't pick
[the least sexy-looking] potatoes.