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♪ (música) ♪

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- [Narradora] Bienvenidos
a Nobel Conversations.

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En este episodio,
Josh Angrist y Guido Imbens

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están con Isaiah Andrews
para discutir y discrepar

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sobre el papel
del aprendizaje automático

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en la econometría aplicada.

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- [Isaiah] Entonces, por supuesto
que hay muchos temas

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en los que ustedes están muy de acuerdo,
pero me gustaría pasar a uno

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en el que tal vez
tengan algunas discrepancias.

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Me gustaría escuchar
algunas de sus opiniones

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sobre el aprendizaje automático

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y el papel que está desempeñando
y va a desempeñar en la economía.

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- [Guido] He consultado algunos datos
como el propietario----------------------.

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Vemos que no hay
ningún documento publicado allí.

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Se hizo un experimento
sobre algún algoritmo de búsqueda

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y la cuestión era...

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se trataba de clasificar cosas
y cambiar la clasificación.

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Y estaba más o menos claro
que iba a haber mucha heterogeneidad.

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Si buscas, digamos, una foto de Britney Spears --

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realmente no importa dónde la clasifiques-----------------------------------
porque vas a encontrar lo que estás buscando,

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ya sea que la pongas en la primera,
segunda o tercera posición del ranking.

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Pero si estás buscando
el mejor libro de econometría,

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si pones tu libro en primer lugar
o en el décimo,

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eso va a suponer una gran diferencia

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en la frecuencia
con la que la gente va a hacer clic en él.

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Así que ahí...

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[Josh] ¿Por qué necesito
el aprendizaje automático para descubrir eso?

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Parece que --porque puedo descubrirlo simplemente.-----------------------

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- [Guido] En general --

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- [Josh] Había un montón de posibles...

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- Quieres pensar en que hay un montón de características de los artículos,

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que quieres entender lo que impulsa la heterogeneidad en el efecto de --

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- Pero solo estás prediciendo.

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En cierto sentido, estás resolviendo
un problema de marketing.

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- No, es un efecto causal,

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- Es causal, pero no tiene contenido científico.

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Piensa en...

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- No, pero hay cosas similares
en el ámbito médico.

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Si haces un experimento,

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puedes estar muy interesado
en si el tratamiento funciona

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para algunos grupos o no.

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Y tienes un montón
de características individuales,

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y quieres buscar sistemáticamente...

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- Sí. Soy escéptico sobre esa...

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esa especie de idea de que hay
un efecto causal personal

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que me debería importar

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y que el aprendizaje automático
puede descubrirlo de alguna manera que sea útil.

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Así que piensa en --

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he hecho
un montón de trabajo en las escuelas,

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ir a, digamos, una escuela charter,-------------------------------------------------

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una escuela privada financiada
con fondos públicos,

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efectivamente, que es libre de estructurar
su propio plan de estudios para el contexto allí.

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Algunos tipos de escuelas chárter
generan espectaculares ganancias de rendimiento

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y en el conjunto de datos
que produce ese resultado,

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tengo un montón de covariables.

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Así que tengo las puntuaciones de referencia

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y tengo los antecedentes familiares,

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la educación de los padres,
el sexo del niño, la raza del niño.

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Y, bueno, en cuanto reúno
media docena de ellas,

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tengo un espacio de muy alta dimensión.

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Definitivamente me interesan
las características del curso

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de ese efecto del tratamiento,

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como por ejemplo si es mejor para las personas
que provienen de familias con menores ingresos.

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Me cuesta creer que haya una aplicación para la versión de muy alta dimensión de eso,

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en la que descubrí
que para los niños no blancos

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que tienen ingresos familiares altos

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pero puntuaciones de referencia en el tercer cuartil

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y que solo fueron a la escuela pública
en el tercer grado pero no en el sexto.

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Así que eso es lo que produce
ese análisis de alta dimensión.

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Es una declaración condicional
muy elaborada.

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Hay dos cosas que están mal,
en mi opinión.

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En primer lugar, no lo veo como...

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no puedo imaginar
por qué es procesable.

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No sé por qué querrías actuar sobre ello.

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Y también sé que hay algún modelo alternativo que encaja casi igual, que lo invierte todo.

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Porque el aprendizaje automático

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no me dice que este es realmente
el predictor que importa --

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sólo me dice que este es un buen predictor.

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336
00:11:57,608 --> 00:11:59,782


337
00:11:59,782 --> 00:12:04,234


338
00:12:04,234 --> 00:12:06,270


339
00:12:06,786 --> 00:12:09,864


340
00:12:09,864 --> 00:12:11,200


341
00:12:12,944 --> 00:12:14,934


342
00:12:14,934 --> 00:12:18,400


343
00:12:20,189 --> 00:12:23,656


344
00:12:24,700 --> 00:12:27,830


345
00:12:27,830 --> 00:12:29,622


346
00:12:29,622 --> 00:12:31,163


347
00:12:31,163 --> 00:12:34,000


348
00:12:34,900 --> 00:12:36,529


349
00:12:36,529 --> 00:12:40,013


350
00:12:40,582 --> 00:12:42,632


351
00:12:42,632 --> 00:12:43,887


352
00:12:43,887 --> 00:12:46,073


353
00:12:46,073 --> 00:12:49,100


354
00:12:49,800 --> 00:12:52,105


355
00:12:52,105 --> 00:12:53,573


356
00:12:53,573 --> 00:12:57,500


357
00:12:58,600 --> 00:13:00,159


358
00:13:00,159 --> 00:13:03,209


359
00:13:03,209 --> 00:13:06,090


360
00:13:06,549 --> 00:13:08,351


361
00:13:08,351 --> 00:13:10,979


362
00:13:11,198 --> 00:13:13,548


363
00:13:13,548 --> 00:13:16,850


364
00:13:16,850 --> 00:13:19,821


365
00:13:19,821 --> 00:13:23,870


366
00:13:24,424 --> 00:13:27,057


367
00:13:27,218 --> 00:13:30,132


368
00:13:30,132 --> 00:13:31,829


369
00:13:31,829 --> 00:13:33,486


370
00:13:33,486 --> 00:13:35,229


371
00:13:35,229 --> 00:13:37,189


372
00:13:37,189 --> 00:13:38,300


373
00:13:38,300 --> 00:13:41,267


374
00:13:41,267 --> 00:13:43,261


375
00:13:43,261 --> 00:13:46,465


376
00:13:48,657 --> 00:13:51,200


377
00:13:51,600 --> 00:13:54,187


378
00:13:54,187 --> 00:13:56,804


379
00:13:56,804 --> 00:13:58,207


380
00:13:58,207 --> 00:13:59,220


381
00:13:59,220 --> 00:14:00,679


382
00:14:00,679 --> 00:14:01,944


383
00:14:02,520 --> 00:14:03,963


384
00:14:03,963 --> 00:14:06,659


385
00:14:06,659 --> 00:14:08,000


386
00:14:08,000 --> 00:14:11,000


387
00:14:11,000 --> 00:14:12,395


388
00:14:12,395 --> 00:14:13,867


389
00:14:13,867 --> 00:14:15,914


390
00:14:15,914 --> 00:14:17,280


391
00:14:17,280 --> 00:14:18,305


392
00:14:18,305 --> 00:14:21,028


393
00:14:21,500 --> 00:14:24,425


394
00:14:24,698 --> 00:14:26,556


395
00:14:26,556 --> 00:14:27,968


396
00:14:27,968 --> 00:14:30,233


397
00:14:30,233 --> 00:14:32,489


398
00:14:32,489 --> 00:14:34,942


399
00:14:34,942 --> 00:14:36,440


400
00:14:36,440 --> 00:14:40,900


401
00:14:40,900 --> 00:14:42,200


402
00:14:42,200 --> 00:14:47,209


403
00:14:47,209 --> 00:14:49,900


404
00:14:51,000 --> 00:14:52,602


405
00:14:52,602 --> 00:14:55,410


406
00:14:55,410 --> 00:14:57,828


407
00:14:57,828 --> 00:14:59,463


408
00:14:59,463 --> 00:15:02,100


409
00:15:02,100 --> 00:15:03,800


410
00:15:03,800 --> 00:15:08,418


411
00:15:08,418 --> 00:15:09,519


412
00:15:09,519 --> 00:15:13,185


413
00:15:13,185 --> 00:15:14,502


414
00:15:15,700 --> 00:15:18,200


415
00:15:19,700 --> 00:15:21,984


416
00:15:21,984 --> 00:15:23,137


417
00:15:23,137 --> 00:15:25,135


418
00:15:25,805 --> 00:15:28,860


419
00:15:29,500 --> 00:15:31,900


420
00:15:32,200 --> 00:15:34,140


421
00:15:34,140 --> 00:15:37,507


422
00:15:38,100 --> 00:15:43,874


423
00:15:44,300 --> 00:15:46,700


424
00:15:47,300 --> 00:15:50,642


425
00:15:50,642 --> 00:15:53,900


426
00:15:53,900 --> 00:15:56,600


427
00:15:56,600 --> 00:15:58,600


428
00:15:59,000 --> 00:16:02,026


429
00:16:02,026 --> 00:16:06,648


430
00:16:06,648 --> 00:16:08,328


431
00:16:08,328 --> 00:16:11,300


432
00:16:11,300 --> 00:16:12,819


433
00:16:12,819 --> 00:16:14,753


434
00:16:14,753 --> 00:16:18,191


435
00:16:18,191 --> 00:16:20,400


436
00:16:20,950 --> 00:16:22,394


437
00:16:22,500 --> 00:16:24,999


438
00:16:24,999 --> 00:16:26,212


439
00:16:26,425 --> 00:16:27,993


440
00:16:27,993 --> 00:16:33,200


441
00:16:34,100 --> 00:16:35,710


442
00:16:35,920 --> 00:16:37,148


443
00:16:37,148 --> 00:16:40,066


444
00:16:40,066 --> 00:16:43,316


445
00:16:43,316 --> 00:16:45,100


446
00:16:45,100 --> 00:16:46,392


447
00:16:46,392 --> 00:16:49,700


448
00:16:50,000 --> 00:16:52,020


449
00:16:52,020 --> 00:16:53,526


450
00:16:53,526 --> 00:16:55,184


451
00:16:55,184 --> 00:16:57,400


452
00:16:57,976 --> 00:17:00,350


453
00:17:00,350 --> 00:17:03,102


454
00:17:03,102 --> 00:17:05,671


455
00:17:05,671 --> 00:17:08,610


456
00:17:08,610 --> 00:17:09,811


457
00:17:09,811 --> 00:17:12,000


458
00:17:12,400 --> 00:17:15,309


459
00:17:15,309 --> 00:17:17,292


460
00:17:17,292 --> 00:17:19,100


461
00:17:19,500 --> 00:17:21,849


462
00:17:21,849 --> 00:17:23,155


463
00:17:23,155 --> 00:17:25,063


464
00:17:25,063 --> 00:17:27,100


465
00:17:27,872 --> 00:17:29,965


466
00:17:29,965 --> 00:17:32,400


467
00:17:32,400 --> 00:17:35,100


468
00:17:35,100 --> 00:17:36,625


469
00:17:36,625 --> 00:17:40,573


470
00:17:40,573 --> 00:17:43,620


471
00:17:43,620 --> 00:17:45,797


472
00:17:45,797 --> 00:17:47,733


473
00:17:47,733 --> 00:17:50,100


474
00:17:50,100 --> 00:17:52,983


475
00:17:52,983 --> 00:17:55,700


476
00:17:55,700 --> 00:17:58,000


477
00:17:58,000 --> 00:18:01,229


478
00:18:01,229 --> 00:18:03,300


479
00:18:03,600 --> 00:18:05,985


480
00:18:05,985 --> 00:18:07,668


481
00:18:07,668 --> 00:18:10,694


482
00:18:10,694 --> 00:18:12,800


483
00:18:13,000 --> 00:18:16,780


484
00:18:16,780 --> 00:18:18,517


485
00:18:18,517 --> 00:18:20,938


486
00:18:20,938 --> 00:18:22,139


487
00:18:22,139 --> 00:18:27,309


488
00:18:27,309 --> 00:18:28,676


489
00:18:28,900 --> 00:18:30,492


490
00:18:30,492 --> 00:18:33,782


491
00:18:33,782 --> 00:18:35,228


492
00:18:35,529 --> 00:18:39,500


493
00:18:39,500 --> 00:18:41,824


494
00:18:41,824 --> 00:18:44,000


495
00:18:44,000 --> 00:18:47,065


496
00:18:47,065 --> 00:18:48,800


497
00:18:49,000 --> 00:18:52,964


498
00:18:53,504 --> 00:18:56,000


499
00:18:56,300 --> 00:18:58,791


500
00:18:58,791 --> 00:19:01,200


501
00:19:01,500 --> 00:19:02,649


502
00:19:02,649 --> 00:19:06,300


503
00:19:06,500 --> 00:19:08,181


504
00:19:08,181 --> 00:19:09,779


505
00:19:09,779 --> 00:19:11,489


506
00:19:11,489 --> 00:19:12,741


507
00:19:12,741 --> 00:19:14,274


508
00:19:14,274 --> 00:19:17,067


509
00:19:17,067 --> 00:19:20,148


510
00:19:20,349 --> 00:19:21,388


511
00:19:21,388 --> 00:19:23,673


512
00:19:23,673 --> 00:19:25,801


513
00:19:25,801 --> 00:19:28,603


514
00:19:29,900 --> 00:19:32,704


515
00:19:32,704 --> 00:19:35,816


516
00:19:35,816 --> 00:19:37,500


517
00:19:37,500 --> 00:19:40,223


518
00:19:40,223 --> 00:19:41,388


519
00:19:41,388 --> 00:19:43,090


520
00:19:43,090 --> 00:19:45,394


521
00:19:45,394 --> 00:19:46,630


522
00:19:47,100 --> 00:19:49,300


523
00:19:49,300 --> 00:19:52,932


524
00:19:52,932 --> 00:19:54,414


525
00:19:54,414 --> 00:19:56,400


526
00:19:57,000 --> 00:20:00,297


527
00:20:00,297 --> 00:20:03,539


528
00:20:03,539 --> 00:20:06,100


529
00:20:06,600 --> 00:20:08,720


530
00:20:08,720 --> 00:20:10,174


531
00:20:10,174 --> 00:20:11,633


532
00:20:12,926 --> 00:20:14,419


533
00:20:14,419 --> 00:20:16,833


534
00:20:16,833 --> 00:20:18,012


535
00:20:18,012 --> 00:20:20,500


536
00:20:20,500 --> 00:20:23,100


537
00:20:23,600 --> 00:20:26,569


538
00:20:26,569 --> 00:20:28,550


539
00:20:28,550 --> 00:20:30,535