Big data, small farms and a tale of two tomatoes | Erin Baumgartner

94,014 views ・ 2020-09-11

TED


Please double-click on the English subtitles below to play the video.

00:00
Transcriber: Leslie Gauthier Reviewer: Krystian Aparta
0
0
7000
00:12
So data and analytics are dramatically changing our everyday lives.
1
12513
4494
00:17
Not just online,
2
17566
1173
00:18
not just in some distant future,
3
18763
2334
00:21
but in the physical world,
4
21121
1322
00:22
and in very real and tangible ways.
5
22467
2769
00:25
I spent the past 11 years of my life as a geek at MIT,
6
25897
4205
00:30
working in big data labs
7
30126
1406
00:31
that seek to use data science to study the physical world
8
31556
3776
00:35
and try to solve society's great problems.
9
35356
2174
00:38
The field of big data seeks to analyze massive pools of data
10
38985
3936
00:42
using computational tools to find patterns and trends.
11
42945
3920
00:47
Data can be a really extraordinary storyteller,
12
47561
3015
00:50
unveiling the hidden narratives of things in our everyday lives
13
50600
2970
00:53
that we never would have seen.
14
53594
1466
00:55
I find the personal stories of inanimate things brought to life
15
55439
3797
00:59
to be extraordinarily compelling.
16
59260
1672
01:01
I want to highlight, first, two projects from my time at MIT
17
61853
3000
01:04
that I think highlight this phenomenon really well.
18
64877
2553
01:08
The first is called Trash Track,
19
68074
2065
01:10
and in this project, we sought to better understand the waste-management system,
20
70163
3977
01:14
to answer the question
21
74164
1690
01:15
"Where does your trash go when you throw it away?"
22
75878
2439
01:18
Your old coffee cup or that flip phone
23
78341
2510
01:20
that you carried around in the early 2000s,
24
80875
2429
01:23
or a bagel or this morning's paper --
25
83328
3247
01:26
where do these things go?
26
86599
1564
01:28
This data didn't exist, so we had to create it.
27
88652
2881
01:32
We answered and then visualized this question
28
92251
3168
01:35
by installing small sensors into pieces of trash
29
95443
3497
01:38
and then throwing them into the waste system.
30
98964
2096
01:41
And what you're seeing here is the data.
31
101601
2799
01:44
Every line, every node that you see
32
104903
2776
01:47
is a single piece of trash moving through the city of Seattle,
33
107703
3472
01:51
and then across the state,
34
111199
2306
01:53
and then across the country,
35
113529
1651
01:55
as weeks and months go by.
36
115204
1742
01:57
And it's important to visualize this data,
37
117606
2065
01:59
because none of you are, probably, sitting here thinking,
38
119695
2672
02:02
"Yeah, that looks right."
39
122391
1258
02:03
(Laughter)
40
123673
1878
02:05
"That's working like it should, right?"
41
125575
1858
02:07
Because, no --
42
127457
1162
02:08
(Laughter)
43
128643
1470
02:10
What the data shows us is a highly inefficient system
44
130582
4033
02:14
whose inherent brokenness I don't think we really would have seen
45
134639
3845
02:18
had the sensors not done the journalism for us.
46
138508
2881
02:22
A second project that I'd have to highlight
47
142597
2650
02:25
has to do with creating robots that dive into sewers
48
145271
4658
02:29
and sample wastewater.
49
149953
1621
02:32
I know that sewage kind of gets a bad rap,
50
152306
2695
02:35
but it's actually kind of awesome,
51
155025
1845
02:36
because it can tell us an incredible amount
52
156894
2001
02:38
about the health of our communities.
53
158919
1740
02:40
This technology was spun out by a group call Biobot Analytics,
54
160683
3251
02:43
who's creating a cutting-edge technology
55
163958
2572
02:46
to turn our sewers into modern-day health observatories.
56
166554
4163
02:50
Their goal is to study opioids within the sewage
57
170741
3356
02:54
to better understand consumption in cities.
58
174121
2635
02:56
And this data is key,
59
176780
1938
02:58
because it really helps cities understand where people are using,
60
178742
3094
03:01
how to allocate resources
61
181860
1874
03:03
and the effectiveness of programming over time.
62
183758
3041
03:07
Once again, the technology that's built into this machine
63
187502
2917
03:10
is pulling back the curtain
64
190443
1841
03:12
and showing us something about our cities that we never would have seen without it.
65
192308
4060
03:16
So it turns out, as we see,
66
196392
2534
03:18
that big data is really everywhere --
67
198950
2522
03:21
even in your toilet.
68
201496
1243
03:23
And so now that we've talked about trash and sewage,
69
203318
3588
03:26
let's move on ...
70
206930
1371
03:28
to food.
71
208325
1208
03:29
(Laughter)
72
209557
1151
03:30
A year ago, I left MIT to pursue a passion in food,
73
210732
3656
03:34
and in 2017,
74
214412
1241
03:35
started a company with my husband, called Family Dinner.
75
215677
2933
03:38
The goal of our company is to create community around local food
76
218634
4113
03:42
and the people who grow it.
77
222771
1945
03:44
To make this happen, we're using data analytics,
78
224740
2537
03:47
automation and technology
79
227301
2233
03:49
to build a distributed network of local farms
80
229558
2738
03:52
and to make improvements on the food system.
81
232320
2262
03:55
So what we see here
82
235187
1652
03:56
is that the broad techniques and the mission of what we're trying to do
83
236863
3484
04:00
is really not dissimilar from the work at the MIT labs.
84
240371
3102
04:04
Which brings us to a critical question:
85
244309
2676
04:07
Why exactly would someone leave a very promising career
86
247009
4020
04:11
at one of the top urban science labs in the world
87
251053
4193
04:15
to drive carrots around in her mom's Acura?
88
255270
2653
04:17
(Laughter)
89
257947
1740
04:20
It's a great car.
90
260241
1196
04:22
Because I believe that the story of local food
91
262496
2764
04:25
needs to be understood, told and elevated,
92
265284
3492
04:28
and in many ways,
93
268800
1151
04:29
I think that nerds like us are really uniquely poised to tell it.
94
269975
3780
04:34
So where are we starting?
95
274304
1530
04:35
What's our starting point?
96
275858
1503
04:37
The current national food system is optimized for one thing only,
97
277775
4493
04:42
and that's corporate profit, right?
98
282292
2468
04:44
And think about that.
99
284784
1250
04:46
The most compelling reason for food companies to exist
100
286058
3383
04:49
is not to feed hungry people,
101
289465
1954
04:51
it's not to make delicious-tasting food.
102
291443
1916
04:53
It's profit.
103
293922
1150
04:55
And that has detrimental effects at all levels of our food system.
104
295706
3497
04:59
The antibiotics and pesticides that are being put into our food
105
299778
3008
05:02
are detrimental to our health.
106
302810
2014
05:04
Price pressure is forcing small farms out of business.
107
304848
3138
05:08
In fact, a lot of the things that you think about farms
108
308010
2618
05:10
no longer exist.
109
310652
1156
05:11
Farms don't look like farms, they look like factories.
110
311832
3342
05:15
And at the end of the day,
111
315198
1239
05:16
the quality of the food that we're eating really suffers, too.
112
316461
3006
05:19
A factory-farm tomato may kind of look like a regular tomato:
113
319935
3936
05:23
bright red exterior ...
114
323895
1661
05:25
But when you bite into it,
115
325580
1416
05:27
the taste and texture just leave you wanting.
116
327020
2550
05:30
And we know that perhaps the greatest tragedy in all of this
117
330651
3153
05:33
is that between 30 and 40 percent of this food is just wasted ...
118
333828
4032
05:38
thrown away.
119
338727
1382
05:40
That is 1.6 billion tons.
120
340133
2675
05:42
I can't even wrap my head around that number.
121
342832
2428
05:45
1.6 billion tons.
122
345284
2277
05:47
That's 1.2 trillion dollars a year
123
347585
3889
05:51
in wasted food.
124
351498
1273
05:53
That is the cost of on-demand eating
125
353526
2108
05:55
and convenience
126
355658
1151
05:56
and the broken food system.
127
356833
1767
05:59
Now, where's this waste happening?
128
359220
1659
06:00
Where's all this waste coming from?
129
360903
2041
06:02
Well, we know that it happens in the field
130
362968
2000
06:04
when you don't pick the sexiest-looking potatoes.
131
364992
2373
06:07
We know that it happens in transit,
132
367389
2246
06:09
at the warehouses,
133
369659
1364
06:11
in the grocery stores.
134
371047
1652
06:12
And finally, on our own kitchen counters,
135
372723
2432
06:15
when we determine that that spotty, brown banana no longer looks so yummy.
136
375179
4479
06:20
All that waste, all that effort.
137
380238
2095
06:22
Food is planted,
138
382871
1604
06:24
grown, harvested, shipped,
139
384499
2548
06:27
and then just thrown away.
140
387071
2388
06:30
We think that there has to be a better way.
141
390680
2372
06:34
And so how to we improve upon this?
142
394295
1707
06:36
How do we make a better system?
143
396026
2145
06:38
In order to do this,
144
398601
1238
06:39
we understand that we need to eliminate waste
145
399863
2596
06:42
in the food supply chain.
146
402483
1646
06:44
We need to get data in the hands of farmers,
147
404652
2310
06:46
so that they can make better predictions.
148
406986
1954
06:48
So they can, you know, kind of compete with the big guy.
149
408964
3014
06:52
And then finally,
150
412002
1207
06:53
we need to prize, as a company,
151
413233
2149
06:55
quality and taste above everything,
152
415406
2826
06:58
so that people really value the delicious food on their plates.
153
418256
3130
07:02
This, we believe, is the better system.
154
422493
2532
07:05
This is the better way.
155
425049
1463
07:06
And the path to that better way is paved with data.
156
426830
3485
07:11
To highlight all of this, I want to tell the tale of two tomatoes.
157
431292
3650
07:15
We'll talk about them one by one.
158
435791
1900
07:18
A tomato in itself contains a beautiful snapshot
159
438120
3183
07:21
of everything you might want to know about the life cycle of that fruit:
160
441327
3786
07:25
where it was grown, what it was treated with,
161
445137
2151
07:27
nutritional value,
162
447312
1319
07:28
miles traveled to get to your plate,
163
448655
1760
07:30
CO2 emissions along the way.
164
450439
2086
07:32
All of that information,
165
452549
1620
07:34
all those little chapters in one small fruit.
166
454193
2618
07:37
It's very exciting.
167
457215
1161
07:38
This is tomato number one.
168
458814
2465
07:41
This is the guy that you'll find in sub shops, supermarkets
169
461303
3444
07:44
and fast-food joints around the world.
170
464771
1963
07:47
It's got a really long and complicated backstory.
171
467137
3240
07:50
It's been treated with a cocktail of, like, a dozen pesticides
172
470968
4392
07:55
and it has traveled at least 1,600 miles to get to your house.
173
475384
4230
08:00
And the image here is green,
174
480316
1715
08:02
because these tomatoes are picked when green and hard as a rock,
175
482055
3617
08:05
and then they are gassed along the way
176
485696
2361
08:08
so that when they arrive at the destination,
177
488081
2157
08:10
they look bright and shiny and red and ripe.
178
490262
2936
08:14
All of that effort,
179
494284
1929
08:16
all of that agricultural innovation and technology
180
496237
3341
08:19
to create a product that is entirely without taste.
181
499602
4004
08:24
And onto the second tomato in our tale.
182
504388
2195
08:26
This is the local version of the fruit.
183
506607
2316
08:28
Its story is much, much shorter.
184
508947
2108
08:31
This guy was grown by Luke Mahoney and his family at Brookford Farm
185
511794
3950
08:35
in Canterbury, New Hampshire.
186
515768
1684
08:38
It's got a pretty boring backstory.
187
518028
2018
08:40
It was planted,
188
520567
1505
08:42
sat in the sun
189
522096
1452
08:43
and then it was picked.
190
523572
1291
08:44
(Laughter)
191
524887
1221
08:46
That's it.
192
526457
1158
08:47
Like, you wouldn't want to --
193
527639
1460
08:49
yeah, there's not much more to that.
194
529123
1766
08:50
And it traveled maybe 70 miles to get your plate.
195
530913
3616
08:54
But the difference is dramatic.
196
534553
1833
08:56
I want you think about the last time you ate a fresh, summer tomato.
197
536797
3293
09:00
And I know we're all covered in our jackets,
198
540114
2049
09:02
but think about it.
199
542187
1151
09:03
The last time you ate a tomato from the garden.
200
543362
2192
09:05
It's warm from the sun,
201
545578
1729
09:07
it's richly red,
202
547331
1173
09:08
maybe it smells like dirt.
203
548528
1804
09:10
There's something nostalgic and almost magical in that experience.
204
550356
3253
09:14
The taste and the flavor are incomparable.
205
554175
3091
09:17
And we really don't have to travel super far to get it.
206
557991
3448
09:22
Now this story extends up the food chain,
207
562812
2564
09:25
from the fruits and the vegetables that are on our plate
208
565400
2714
09:28
to the animals and the animal products that we consume.
209
568138
2816
09:31
What goes into raising them,
210
571545
1697
09:33
and more importantly, what doesn't go into raising them,
211
573266
3970
09:37
is critically important.
212
577260
1441
09:40
Luke and his family have 60 cows.
213
580006
2065
09:42
They use traditional methods.
214
582744
1382
09:44
They do it the old way:
215
584150
1623
09:45
pasture-raised,
216
585797
1418
09:47
no hormones, no antibiotics,
217
587239
2302
09:49
hay for days.
218
589565
1305
09:51
And what they're doing here is just treating cows like they're cows,
219
591707
4056
09:55
not like they're in a science experiment.
220
595787
2268
09:58
He's raising animals the way that his grandfather
221
598079
2642
10:00
and his grandfather would have.
222
600745
1841
10:02
And at the end, it's just better.
223
602610
2130
10:04
It's better for the animals;
224
604764
1334
10:06
it's better for the environment.
225
606122
1533
10:07
Luke is not optimizing for profit or price,
226
607679
2363
10:10
but for taste and for humanity.
227
610066
2142
10:13
And what you're thinking is, "There's already a solution to this.
228
613257
3267
10:16
It's the farmer's markets."
229
616548
1690
10:18
The ones that many of you visit
230
618262
1485
10:19
and the ones that I really enjoy.
231
619771
1829
10:22
They are a wonderful, but, in many ways, suboptimal solution.
232
622279
3468
10:26
For us as the consumers, it's kind of great, right?
233
626294
2508
10:28
You go,
234
628826
1231
10:30
there's this beautiful bounty of food,
235
630081
1929
10:32
you get the warm and fuzzies for supporting a local farm
236
632034
3249
10:35
and you get the experience of trying something new and trying diverse products.
237
635307
4229
10:39
And inevitably, there's some guy playing the ukulele
238
639560
2482
10:42
somewhere in the background.
239
642066
1349
10:43
(Laughter)
240
643439
1000
10:45
But for the farmers, this presents a lot of risk, right?
241
645518
3620
10:49
You wake up at four.
242
649162
1151
10:50
You pack your truck, you hire a team,
243
650337
2006
10:52
you get to your stall,
244
652367
1168
10:53
but you have no guarantees
245
653559
1968
10:55
that you're going to move your product that day.
246
655551
2346
10:57
There's too many variables in New England.
247
657921
2025
10:59
For example, the weather,
248
659970
2264
11:02
which is just, like, a little bit unpredictable here.
249
662258
2770
11:05
The weather is one of the many X factors
250
665680
1976
11:07
that determine whether or not a market will be worth it for the farmers.
251
667680
4261
11:13
Every time, they roll the dice.
252
673101
2011
11:15
And there's another option.
253
675647
1857
11:17
Here, we're talking about CSAs:
254
677528
2156
11:19
community-supported agriculture.
255
679708
2252
11:21
In this model, customers pay up front,
256
681984
2516
11:24
bearing the financial risk for the farms.
257
684524
2207
11:26
Farmers grow what they can
258
686755
1669
11:28
and the customers enjoy that bounty.
259
688448
2342
11:31
This also has a couple issues.
260
691176
1687
11:32
It's great for the farmer,
261
692887
1343
11:34
because they're ensuring that they'll sell what they buy,
262
694254
2668
11:36
but for us,
263
696946
1250
11:38
we still have to go and pick up that share,
264
698220
2031
11:40
and we know that a lot of farms can't grow a huge diversity of products,
265
700275
3393
11:43
so sometimes, you're stuck with a mountain of any one particular thing.
266
703692
3605
11:47
Maybe this has happened to some of you.
267
707845
1878
11:50
And what do you do with 25 pounds of rutabaga in the dead of winter?
268
710217
4109
11:54
I still don't know.
269
714350
1366
11:57
So back to the question.
270
717346
1809
11:59
How do we fix this?
271
719179
1605
12:00
What we're hoping to do and what we're hoping to build
272
720808
2582
12:03
is just a better way to CSA.
273
723414
1990
12:06
And there are three core innovations that make this thing hum.
274
726274
4624
12:11
The first of which
275
731448
1170
12:12
is a subscription-based e-commerce platform,
276
732642
2906
12:15
which helps us create a consistent demand for our farmers
277
735572
2804
12:18
throughout the year.
278
738400
1497
12:19
The subscription part here is key.
279
739921
2018
12:21
Orders process weekly,
280
741963
1602
12:23
customers opt out instead of opt in --
281
743589
2422
12:26
that means we've got kind of the same number of orders week to week.
282
746035
3267
12:29
Second, this means that if farmers can sell online,
283
749619
3927
12:33
they're no longer limited to the geography directly around their farm
284
753570
3585
12:37
or to the number of markets that they can sell.
285
757179
2346
12:39
We've blown the doors off of that for them.
286
759549
2319
12:42
Second: demand forecasting.
287
762791
1993
12:44
We're using analytics to allow ourselves to look into the future
288
764808
3001
12:47
and forecast demand.
289
767833
1578
12:49
This lets farmers know how much to harvest in the near-term,
290
769435
3238
12:52
but also what to plant going forward.
291
772697
2165
12:55
If 200 orders process on Monday,
292
775537
2639
12:58
then we buy to meet that exact demand.
293
778200
2095
13:00
200 heads of broccoli,
294
780617
1318
13:01
200 pieces of salmon, et cetera, et cetera.
295
781959
2357
13:04
This automation in ordering
296
784980
1477
13:06
means that here, we are eliminating the waste in the food system
297
786481
4134
13:10
that bothers us all so much,
298
790639
1982
13:12
because we are ensuring that the supply meets the exact demand.
299
792645
4128
13:17
It also allows us to look into the future with the farmers
300
797616
2715
13:20
and do crop planning.
301
800355
1309
13:21
So if we can say to them, in June of this year,
302
801688
2246
13:23
"I'm going to need 400 pounds of asparagus
303
803958
2529
13:26
and 500 pounds of berries every week,"
304
806511
2558
13:29
they can plant that accordingly,
305
809093
1865
13:30
knowing with confidence that they will sell
306
810982
2028
13:33
everything that they have grown.
307
813034
1545
13:34
And finally, we use a route-optimization software
308
814603
2643
13:37
to help us solve the problem of the traveling salesman.
309
817270
2803
13:40
We get a fleet of workers to come in and help us go the last mile,
310
820097
3617
13:43
bringing all these goodies directly to your door.
311
823738
2560
13:46
Without data science
312
826322
1378
13:47
and a super-capable, wonderful team,
313
827724
2591
13:50
none of this would be possible.
314
830339
1705
13:52
So maybe you've seen
315
832800
1650
13:54
that we've got some sort of fiery, passionate core beliefs.
316
834474
3353
13:57
Yes, we're trying to build a sustainable business,
317
837851
2647
14:00
but our eye is not only on profit,
318
840522
2095
14:02
it's on building a better, holistic system of food.
319
842641
2809
14:06
And here's what we value.
320
846421
1373
14:08
People first.
321
848290
1400
14:09
We're trying to build community around food,
322
849714
2049
14:11
the people who love it and the people who grow it.
323
851787
2529
14:14
We built this company to support small farms.
324
854340
2634
14:17
Zero waste.
325
857900
1190
14:19
We all hate wasting food, it just feels wrong --
326
859114
2618
14:21
even that weirdo banana
327
861756
1322
14:23
that's been sitting around on your coffee table for too long.
328
863102
2957
14:26
And lastly, taste.
329
866083
1879
14:28
If it doesn't taste good,
330
868451
1381
14:29
if it's not that, like, perfect summer tomato,
331
869856
3017
14:32
why bother?
332
872897
1150
14:34
So what we've done is worked with all these local farms
333
874803
2584
14:37
to bring their things in
334
877411
1382
14:38
and then to drop them directly at your door,
335
878817
2240
14:41
so that we're connecting you right to them
336
881081
2032
14:43
and making, again, a more holistic system.
337
883137
2441
14:46
This is our vision of the future.
338
886252
2113
14:48
To extend this model beyond Boston, beyond New England
339
888389
3468
14:51
and across the country.
340
891881
1739
14:53
To create a nationwide distributed network of local farms
341
893644
4090
14:57
and to connect all these farmers
342
897758
1799
14:59
with the people like you who will love their food.
343
899581
2586
15:03
We believe, at the end of the day,
344
903602
1684
15:05
that really insisting on eating local food is a revolutionary act.
345
905310
4443
15:10
And we invite you to join us.
346
910213
1528
15:12
And who knows?
347
912311
1293
15:13
You may even make some friends along the way.
348
913628
3009
15:17
Thank you very much.
349
917611
1150
15:18
(Applause)
350
918785
1150
About this website

This site will introduce you to YouTube videos that are useful for learning English. You will see English lessons taught by top-notch teachers from around the world. Double-click on the English subtitles displayed on each video page to play the video from there. The subtitles scroll in sync with the video playback. If you have any comments or requests, please contact us using this contact form.

https://forms.gle/WvT1wiN1qDtmnspy7