CSPAN3 — History of Artificial Intelligence

20260806 01:32 UTC · 01:32:59 · 1684 transcript segments · GDELT Visual Explorer · plain-text transcript · Event Map

Technology Historians Ekaterina Babintseva (Purdue), Sarah Igo (Vanderbilt), Aaron Mendon-Plasek (Purdue), and Rebecca Slayton (Cornell) discussed the history of artificial intelligence. This discussion was part of the American Historical Association's Congressional briefing series.<br /><br />Sponsor: American Historical Association

Film strip

One frame every 4 seconds, 1395 in all. Click a frame to jump the transcript to that moment, or click a line of the transcript to see what was on screen while it was said. Served from apprised.news, so it loads behind proxies that block Google Cloud Storage.

00:00:00
00:00:04
00:00:08
00:00:12
00:00:16
00:00:20
00:00:24
00:00:28
00:00:32
00:00:36
00:00:40
00:00:44
00:00:48
00:00:52
00:00:56
00:01:00
00:01:04
00:01:08
00:01:12
00:01:16
00:01:20
00:01:24
00:01:28
00:01:32
00:01:36
00:01:40
00:01:44
00:01:48
00:01:52
00:01:56
00:02:00
00:02:04
00:02:08
00:02:12
00:02:16
00:02:20
00:02:24
00:02:28
00:02:32
00:02:36
00:02:40
00:02:44
00:02:48
00:02:52
00:02:56
00:03:00
00:03:04
00:03:08
00:03:12
00:03:16
00:03:20
00:03:24
00:03:28
00:03:32
00:03:36
00:03:40
00:03:44
00:03:48
00:03:52
00:03:56
00:04:00
00:04:04
00:04:08
00:04:12
00:04:16
00:04:20
00:04:24
00:04:28
00:04:32
00:04:36
00:04:40
00:04:44
00:04:48
00:04:52
00:04:56
00:05:00
00:05:04
00:05:08
00:05:12
00:05:16
00:05:20
00:05:24
00:05:28
00:05:32
00:05:36
00:05:40
00:05:44
00:05:48
00:05:52
00:05:56
00:06:00
00:06:04
00:06:08
00:06:12
00:06:16
00:06:20
00:06:24
00:06:28
00:06:32
00:06:36
00:06:40
00:06:44
00:06:48
00:06:52
00:06:56
00:07:00
00:07:04
00:07:08
00:07:12
00:07:16
00:07:20
00:07:24
00:07:28
00:07:32
00:07:36
00:07:40
00:07:44
00:07:48
00:07:52
00:07:56
00:08:00
00:08:04
00:08:08
00:08:12
00:08:16
00:08:20
00:08:24
00:08:28
00:08:32
00:08:36
00:08:40
00:08:44
00:08:48
00:08:52
00:08:56
00:09:00
00:09:04
00:09:08
00:09:12
00:09:16
00:09:20
00:09:24
00:09:28
00:09:32
00:09:36
00:09:40
00:09:44
00:09:48
00:09:52
00:09:56
00:10:00
00:10:04
00:10:08
00:10:12
00:10:16
00:10:20
00:10:24
00:10:28
00:10:32
00:10:36
00:10:40
00:10:44
00:10:48
00:10:52
00:10:56
00:11:00
00:11:04
00:11:08
00:11:12
00:11:16
00:11:20
00:11:24
00:11:28
00:11:32
00:11:36
00:11:40
00:11:44
00:11:48
00:11:52
00:11:56
00:12:00
00:12:04
00:12:08
00:12:12
00:12:16
00:12:20
00:12:24
00:12:28
00:12:32
00:12:36
00:12:40
00:12:44
00:12:48
00:12:52
00:12:56
00:13:00
00:13:04
00:13:08
00:13:12
00:13:16
00:13:20
00:13:24
00:13:28
00:13:32
00:13:36
00:13:40
00:13:44
00:13:48
00:13:52
00:13:56
00:14:00
00:14:04
00:14:08
00:14:12
00:14:16
00:14:20
00:14:24
00:14:28
00:14:32
00:14:36
00:14:40
00:14:44
00:14:48
00:14:52
00:14:56
00:15:00
00:15:04
00:15:08
00:15:12
00:15:16
00:15:20
00:15:24
00:15:28
00:15:32
00:15:36
00:15:40
00:15:44
00:15:48
00:15:52
00:15:56
00:16:00
00:16:04
00:16:08
00:16:12
00:16:16
00:16:20
00:16:24
00:16:28
00:16:32
00:16:36
00:16:40
00:16:44
00:16:48
00:16:52
00:16:56
00:17:00
00:17:04
00:17:08
00:17:12
00:17:16
00:17:20
00:17:24
00:17:28
00:17:32
00:17:36
00:17:40
00:17:44
00:17:48
00:17:52
00:17:56
00:18:00
00:18:04
00:18:08
00:18:12
00:18:16
00:18:20
00:18:24
00:18:28
00:18:32
00:18:36
00:18:40
00:18:44
00:18:48
00:18:52
00:18:56
00:19:00
00:19:04
00:19:08
00:19:12
00:19:16
00:19:20
00:19:24
00:19:28
00:19:32
00:19:36
00:19:40
00:19:44
00:19:48
00:19:52
00:19:56
00:20:00
00:20:04
00:20:08
00:20:12
00:20:16
00:20:20
00:20:24
00:20:28
00:20:32
00:20:36
00:20:40
00:20:44
00:20:48
00:20:52
00:20:56
00:21:00
00:21:04
00:21:08
00:21:12
00:21:16
00:21:20
00:21:24
00:21:28
00:21:32
00:21:36
00:21:40
00:21:44
00:21:48
00:21:52
00:21:56
00:22:00
00:22:04
00:22:08
00:22:12
00:22:16
00:22:20
00:22:24
00:22:28
00:22:32
00:22:36
00:22:40
00:22:44
00:22:48
00:22:52
00:22:56
00:23:00
00:23:04
00:23:08
00:23:12
00:23:16
00:23:20
00:23:24
00:23:28
00:23:32
00:23:36
00:23:40
00:23:44
00:23:48
00:23:52
00:23:56
00:24:00
00:24:04
00:24:08
00:24:12
00:24:16
00:24:20
00:24:24
00:24:28
00:24:32
00:24:36
00:24:40
00:24:44
00:24:48
00:24:52
00:24:56
00:25:00
00:25:04
00:25:08
00:25:12
00:25:16
00:25:20
00:25:24
00:25:28
00:25:32
00:25:36
00:25:40
00:25:44
00:25:48
00:25:52
00:25:56
00:26:00
00:26:04
00:26:08
00:26:12
00:26:16
00:26:20
00:26:24
00:26:28
00:26:32
00:26:36
00:26:40
00:26:44
00:26:48
00:26:52
00:26:56
00:27:00
00:27:04
00:27:08
00:27:12
00:27:16
00:27:20
00:27:24
00:27:28
00:27:32
00:27:36
00:27:40
00:27:44
00:27:48
00:27:52
00:27:56
00:28:00
00:28:04
00:28:08
00:28:12
00:28:16
00:28:20
00:28:24
00:28:28
00:28:32
00:28:36
00:28:40
00:28:44
00:28:48
00:28:52
00:28:56
00:29:00
00:29:04
00:29:08
00:29:12
00:29:16
00:29:20
00:29:24
00:29:28
00:29:32
00:29:36
00:29:40
00:29:44
00:29:48
00:29:52
00:29:56
00:30:00
00:30:04
00:30:08
00:30:12
00:30:16
00:30:20
00:30:24
00:30:28
00:30:32
00:30:36
00:30:40
00:30:44
00:30:48
00:30:52
00:30:56
00:31:00
00:31:04
00:31:08
00:31:12
00:31:16
00:31:20
00:31:24
00:31:28
00:31:32
00:31:36
00:31:40
00:31:44
00:31:48
00:31:52
00:31:56
00:32:00
00:32:04
00:32:08
00:32:12
00:32:16
00:32:20
00:32:24
00:32:28
00:32:32
00:32:36
00:32:40
00:32:44
00:32:48
00:32:52
00:32:56
00:33:00
00:33:04
00:33:08
00:33:12
00:33:16
00:33:20
00:33:24
00:33:28
00:33:32
00:33:36
00:33:40
00:33:44
00:33:48
00:33:52
00:33:56
00:34:00
00:34:04
00:34:08
00:34:12
00:34:16
00:34:20
00:34:24
00:34:28
00:34:32
00:34:36
00:34:40
00:34:44
00:34:48
00:34:52
00:34:56
00:35:00
00:35:04
00:35:08
00:35:12
00:35:16
00:35:20
00:35:24
00:35:28
00:35:32
00:35:36
00:35:40
00:35:44
00:35:48
00:35:52
00:35:56
00:36:00
00:36:04
00:36:08
00:36:12
00:36:16
00:36:20
00:36:24
00:36:28
00:36:32
00:36:36
00:36:40
00:36:44
00:36:48
00:36:52
00:36:56
00:37:00
00:37:04
00:37:08
00:37:12
00:37:16
00:37:20
00:37:24
00:37:28
00:37:32
00:37:36
00:37:40
00:37:44
00:37:48
00:37:52
00:37:56
00:38:00
00:38:04
00:38:08
00:38:12
00:38:16
00:38:20
00:38:24
00:38:28
00:38:32
00:38:36
00:38:40
00:38:44
00:38:48
00:38:52
00:38:56
00:39:00
00:39:04
00:39:08
00:39:12
00:39:16
00:39:20
00:39:24
00:39:28
00:39:32
00:39:36
00:39:40
00:39:44
00:39:48
00:39:52
00:39:56
00:40:00
00:40:04
00:40:08
00:40:12
00:40:16
00:40:20
00:40:24
00:40:28
00:40:32
00:40:36
00:40:40
00:40:44
00:40:48
00:40:52
00:40:56
00:41:00
00:41:04
00:41:08
00:41:12
00:41:16
00:41:20
00:41:24
00:41:28
00:41:32
00:41:36
00:41:40
00:41:44
00:41:48
00:41:52
00:41:56
00:42:00
00:42:04
00:42:08
00:42:12
00:42:16
00:42:20
00:42:24
00:42:28
00:42:32
00:42:36
00:42:40
00:42:44
00:42:48
00:42:52
00:42:56
00:43:00
00:43:04
00:43:08
00:43:12
00:43:16
00:43:20
00:43:24
00:43:28
00:43:32
00:43:36
00:43:40
00:43:44
00:43:48
00:43:52
00:43:56
00:44:00
00:44:04
00:44:08
00:44:12
00:44:16
00:44:20
00:44:24
00:44:28
00:44:32
00:44:36
00:44:40
00:44:44
00:44:48
00:44:52
00:44:56
00:45:00
00:45:04
00:45:08
00:45:12
00:45:16
00:45:20
00:45:24
00:45:28
00:45:32
00:45:36
00:45:40
00:45:44
00:45:48
00:45:52
00:45:56
00:46:00
00:46:04
00:46:08
00:46:12
00:46:16
00:46:20
00:46:24
00:46:28
00:46:32
00:46:36
00:46:40
00:46:44
00:46:48
00:46:52
00:46:56
00:47:00
00:47:04
00:47:08
00:47:12
00:47:16
00:47:20
00:47:24
00:47:28
00:47:32
00:47:36
00:47:40
00:47:44
00:47:48
00:47:52
00:47:56
00:48:00
00:48:04
00:48:08
00:48:12
00:48:16
00:48:20
00:48:24
00:48:28
00:48:32
00:48:36
00:48:40
00:48:44
00:48:48
00:48:52
00:48:56
00:49:00
00:49:04
00:49:08
00:49:12
00:49:16
00:49:20
00:49:24
00:49:28
00:49:32
00:49:36
00:49:40
00:49:44
00:49:48
00:49:52
00:49:56
00:50:00
00:50:04
00:50:08
00:50:12
00:50:16
00:50:20
00:50:24
00:50:28
00:50:32
00:50:36
00:50:40
00:50:44
00:50:48
00:50:52
00:50:56
00:51:00
00:51:04
00:51:08
00:51:12
00:51:16
00:51:20
00:51:24
00:51:28
00:51:32
00:51:36
00:51:40
00:51:44
00:51:48
00:51:52
00:51:56
00:52:00
00:52:04
00:52:08
00:52:12
00:52:16
00:52:20
00:52:24
00:52:28
00:52:32
00:52:36
00:52:40
00:52:44
00:52:48
00:52:52
00:52:56
00:53:00
00:53:04
00:53:08
00:53:12
00:53:16
00:53:20
00:53:24
00:53:28
00:53:32
00:53:36
00:53:40
00:53:44
00:53:48
00:53:52
00:53:56
00:54:00
00:54:04
00:54:08
00:54:12
00:54:16
00:54:20
00:54:24
00:54:28
00:54:32
00:54:36
00:54:40
00:54:44
00:54:48
00:54:52
00:54:56
00:55:00
00:55:04
00:55:08
00:55:12
00:55:16
00:55:20
00:55:24
00:55:28
00:55:32
00:55:36
00:55:40
00:55:44
00:55:48
00:55:52
00:55:56
00:56:00
00:56:04
00:56:08
00:56:12
00:56:16
00:56:20
00:56:24
00:56:28
00:56:32
00:56:36
00:56:40
00:56:44
00:56:48
00:56:52
00:56:56
00:57:00
00:57:04
00:57:08
00:57:12
00:57:16
00:57:20
00:57:24
00:57:28
00:57:32
00:57:36
00:57:40
00:57:44
00:57:48
00:57:52
00:57:56
00:58:00
00:58:04
00:58:08
00:58:12
00:58:16
00:58:20
00:58:24
00:58:28
00:58:32
00:58:36
00:58:40
00:58:44
00:58:48
00:58:52
00:58:56
00:59:00
00:59:04
00:59:08
00:59:12
00:59:16
00:59:20
00:59:24
00:59:28
00:59:32
00:59:36
00:59:40
00:59:44
00:59:48
00:59:52
00:59:56
01:00:00
01:00:04
01:00:08
01:00:12
01:00:16
01:00:20
01:00:24
01:00:28
01:00:32
01:00:36
01:00:40
01:00:44
01:00:48
01:00:52
01:00:56
01:01:00
01:01:04
01:01:08
01:01:12
01:01:16
01:01:20
01:01:24
01:01:28
01:01:32
01:01:36
01:01:40
01:01:44
01:01:48
01:01:52
01:01:56
01:02:00
01:02:04
01:02:08
01:02:12
01:02:16
01:02:20
01:02:24
01:02:28
01:02:32
01:02:36
01:02:40
01:02:44
01:02:48
01:02:52
01:02:56
01:03:00
01:03:04
01:03:08
01:03:12
01:03:16
01:03:20
01:03:24
01:03:28
01:03:32
01:03:36
01:03:40
01:03:44
01:03:48
01:03:52
01:03:56
01:04:00
01:04:04
01:04:08
01:04:12
01:04:16
01:04:20
01:04:24
01:04:28
01:04:32
01:04:36
01:04:40
01:04:44
01:04:48
01:04:52
01:04:56
01:05:00
01:05:04
01:05:08
01:05:12
01:05:16
01:05:20
01:05:24
01:05:28
01:05:32
01:05:36
01:05:40
01:05:44
01:05:48
01:05:52
01:05:56
01:06:00
01:06:04
01:06:08
01:06:12
01:06:16
01:06:20
01:06:24
01:06:28
01:06:32
01:06:36
01:06:40
01:06:44
01:06:48
01:06:52
01:06:56
01:07:00
01:07:04
01:07:08
01:07:12
01:07:16
01:07:20
01:07:24
01:07:28
01:07:32
01:07:36
01:07:40
01:07:44
01:07:48
01:07:52
01:07:56
01:08:00
01:08:04
01:08:08
01:08:12
01:08:16
01:08:20
01:08:24
01:08:28
01:08:32
01:08:36
01:08:40
01:08:44
01:08:48
01:08:52
01:08:56
01:09:00
01:09:04
01:09:08
01:09:12
01:09:16
01:09:20
01:09:24
01:09:28
01:09:32
01:09:36
01:09:40
01:09:44
01:09:48
01:09:52
01:09:56
01:10:00
01:10:04
01:10:08
01:10:12
01:10:16
01:10:20
01:10:24
01:10:28
01:10:32
01:10:36
01:10:40
01:10:44
01:10:48
01:10:52
01:10:56
01:11:00
01:11:04
01:11:08
01:11:12
01:11:16
01:11:20
01:11:24
01:11:28
01:11:32
01:11:36
01:11:40
01:11:44
01:11:48
01:11:52
01:11:56
01:12:00
01:12:04
01:12:08
01:12:12
01:12:16
01:12:20
01:12:24
01:12:28
01:12:32
01:12:36
01:12:40
01:12:44
01:12:48
01:12:52
01:12:56
01:13:00
01:13:04
01:13:08
01:13:12
01:13:16
01:13:20
01:13:24
01:13:28
01:13:32
01:13:36
01:13:40
01:13:44
01:13:48
01:13:52
01:13:56
01:14:00
01:14:04
01:14:08
01:14:12
01:14:16
01:14:20
01:14:24
01:14:28
01:14:32
01:14:36
01:14:40
01:14:44
01:14:48
01:14:52
01:14:56
01:15:00
01:15:04
01:15:08
01:15:12
01:15:16
01:15:20
01:15:24
01:15:28
01:15:32
01:15:36
01:15:40
01:15:44
01:15:48
01:15:52
01:15:56
01:16:00
01:16:04
01:16:08
01:16:12
01:16:16
01:16:20
01:16:24
01:16:28
01:16:32
01:16:36
01:16:40
01:16:44
01:16:48
01:16:52
01:16:56
01:17:00
01:17:04
01:17:08
01:17:12
01:17:16
01:17:20
01:17:24
01:17:28
01:17:32
01:17:36
01:17:40
01:17:44
01:17:48
01:17:52
01:17:56
01:18:00
01:18:04
01:18:08
01:18:12
01:18:16
01:18:20
01:18:24
01:18:28
01:18:32
01:18:36
01:18:40
01:18:44
01:18:48
01:18:52
01:18:56
01:19:00
01:19:04
01:19:08
01:19:12
01:19:16
01:19:20
01:19:24
01:19:28
01:19:32
01:19:36
01:19:40
01:19:44
01:19:48
01:19:52
01:19:56
01:20:00
01:20:04
01:20:08
01:20:12
01:20:16
01:20:20
01:20:24
01:20:28
01:20:32
01:20:36
01:20:40
01:20:44
01:20:48
01:20:52
01:20:56
01:21:00
01:21:04
01:21:08
01:21:12
01:21:16
01:21:20
01:21:24
01:21:28
01:21:32
01:21:36
01:21:40
01:21:44
01:21:48
01:21:52
01:21:56
01:22:00
01:22:04
01:22:08
01:22:12
01:22:16
01:22:20
01:22:24
01:22:28
01:22:32
01:22:36
01:22:40
01:22:44
01:22:48
01:22:52
01:22:56
01:23:00
01:23:04
01:23:08
01:23:12
01:23:16
01:23:20
01:23:24
01:23:28
01:23:32
01:23:36
01:23:40
01:23:44
01:23:48
01:23:52
01:23:56
01:24:00
01:24:04
01:24:08
01:24:12
01:24:16
01:24:20
01:24:24
01:24:28
01:24:32
01:24:36
01:24:40
01:24:44
01:24:48
01:24:52
01:24:56
01:25:00
01:25:04
01:25:08
01:25:12
01:25:16
01:25:20
01:25:24
01:25:28
01:25:32
01:25:36
01:25:40
01:25:44
01:25:48
01:25:52
01:25:56
01:26:00
01:26:04
01:26:08
01:26:12
01:26:16
01:26:20
01:26:24
01:26:28
01:26:32
01:26:36
01:26:40
01:26:44
01:26:48
01:26:52
01:26:56
01:27:00
01:27:04
01:27:08
01:27:12
01:27:16
01:27:20
01:27:24
01:27:28
01:27:32
01:27:36
01:27:40
01:27:44
01:27:48
01:27:52
01:27:56
01:28:00
01:28:04
01:28:08
01:28:12
01:28:16
01:28:20
01:28:24
01:28:28
01:28:32
01:28:36
01:28:40
01:28:44
01:28:48
01:28:52
01:28:56
01:29:00
01:29:04
01:29:08
01:29:12
01:29:16
01:29:20
01:29:24
01:29:28
01:29:32
01:29:36
01:29:40
01:29:44
01:29:48
01:29:52
01:29:56
01:30:00
01:30:04
01:30:08
01:30:12
01:30:16
01:30:20
01:30:24
01:30:28
01:30:32
01:30:36
01:30:40
01:30:44
01:30:48
01:30:52
01:30:56
01:31:00
01:31:04
01:31:08
01:31:12
01:31:16
01:31:20
01:31:24
01:31:28
01:31:32
01:31:36
01:31:40
01:31:44
01:31:48
01:31:52
01:31:56
01:32:00
01:32:04
01:32:08
01:32:12
01:32:16
01:32:20
01:32:24
01:32:28
01:32:32
01:32:36
01:32:40
01:32:44
01:32:48
01:32:52
01:32:56

Transcript

Original Broadcaster Captioning (Enhanced). Treat it as a searchable index of what was broadcast, not a quotation record.

00:00:04MEDIA WORLD, ONE PLACE BRINGS AMERICA TOGETHER. ACCORDING TO A NEW M&G AND
00:00:08RESEARCH REPORT, NEARLY 90 MILLION AMERICANS TURN TO
00:00:12C-SPAN. AND THEY'RE ALMOST PERFECTLY BALANCED. 28% CONSERVATIVE, 10% LIBERAL OR
00:00:18PROGRESSIVE? 41%. MODERATE. REPUBLIC FANS WATCHING
00:00:21DEMOCRATS, DEMOCRATS WATCHING
00:00:23REPUBLICANS, MODERATES WATCHING
00:00:25ALL SIDES BECAUSE C-SPAN VIEWERS WANT THE FACTS STRAIGHT FROM THE
00:00:30SOURCE. NO COMMENTARY, NO AGENDA. JUST DEMOCRACY.
00:00:34UNFILTERED. EVERY DAY ON THE C-SPAN NETWORK'S.
00:00:38OUR MODERATOR THIS MORNING WILL BE KATHERINE KRAMER BROWN.
00:00:41SHE IS A PROFESSOR OF HISTORY
00:00:43AND DIRECTOR OF THE CENTER FOR AMERICAN POLITICAL HISTORY MEDIA
00:00:47AND TECHNOLOGY AT PURDUE UNIVERSITY. SHE IS THE AUTHOR OF TWO BOOKS,
00:00:51SHOWBIZ POLITICS, HOLLYWOOD AND AMERICAN POLITICAL LIFE AND 24
00:00:55SEVEN POLITICS, CABLE TELEVISION AND THE FRAGMENTING OF AMERICA
00:00:58FROM WATERGATE TO FOX NEWS. SHE ALSO SERVES AS SENIOR EDITOR
00:01:02FOR THE MADE BY HISTORY.COM AT TIME MAGAZINE.
00:01:04DR. BROWN, OUT OF THE PODIUM IS
00:01:09YOURS. THANK YOU.
00:01:13GOOD MORNING, EVERYBODY.
00:01:16FIRST AND FOREMOST, THANK YOU TO THE AMERICAN HISTORICAL
00:01:20ASSOCIATION FOR ALL OF THEIR WORK TO MAKE HISTORICAL
00:01:23SCHOLARSHIP RELEVANT AND ACCESSIBLE FOR PEOPLE OUTSIDE THE ACADEMY.
00:01:28AND TO ARRANGE EVENTS LIKE THIS.
00:01:30THE A.J., I HAVE THE THING, AS
00:01:32BEN MENTIONED, THAT EVERYTHING
00:01:34HAS A HISTORY AND THAT IS TRUE.
00:01:37BUT THAT HISTORY IS MORE THAN
00:01:39JUST AN INTERESTING STORY FROM THE PAST.
00:01:41IN FACT, IT'S REALLY ESSENTIAL TO UNDERSTANDING THE CURRENT
00:01:45MOMENT AND PERHAPS EVEN TO
00:01:47REIMAGINING FUTURE PATHWAYS THAT WE MAY PURSUE.
00:01:50AND THIS IS A ESPECIALLY TRUE
00:01:52WHEN IT COMES TO PUBLIC POLICY
00:01:54AND IS ON THE MINDS OF
00:01:56EDUCATORS, POLICYMAKERS, BUSINESS LEADERS, WORKERS AS
00:02:01THEY THINK THROUGH HOW IT'S CHANGING THE DYNAMICS OF
00:02:03EDUCATION AND WORK. BUT IT'S ALSO RAISING REALLY
00:02:07IMPORTANT QUESTIONS THAT HAVE TO DO WITH CITIZENSHIP AND HOW TO
00:02:12BALANCE AS A POLICY QUESTION, PRIVATE SEE, AND THE RIGHTS OF
00:02:16INDIVIDUALS WITH THE IMPERATIVE OF NATIONAL SECURITY AND THE
00:02:19OPERATIONS OF A NATIONAL SECURITY STATE.
00:02:22WHAT TENSIONS AND CONTRADICTION
00:02:25EMERGE AND HOW MIGHT A HISTORICAL LENS HELP US
00:02:29UNDERSTAND THE ORIGINS? CONFLICT, ANSWERS AND STAKES OF
00:02:32THESE CONTEMPORARY CONVERSATIONS AROUND NEW TECHNOLOGY AND ITS
00:02:38RELATIONSHIP TO PRIVACY AND NATIONAL SECURITY?
00:02:41THAT'S WHAT WE'RE GOING TO TACKLE HERE TODAY.
00:02:43AND WE HAVE AN AMAZING LINEUP OF SCHOLARS TO HELP US DIG INTO
00:02:47THESE QUESTIONS AND PROVIDE MUCH NEEDED HISTORICAL CONTEXT, BUT
00:02:51ALSO ANALYSIS THAT'S REALLY CRITICALLY IMPORTANT TO REMIND
00:02:54US THAT TECHNOLOGY ITSELF DOES NOT CHART ITS OWN COURSE.
00:02:58PEOPLE MAKE DECISIONS OVER HOW
00:03:00TO USE AND STRUCTURE NEW
00:03:02TECHNOLOGY AND UNDERSTANDING
00:03:05THESE HISTORICAL DYNAMICS AND THE CONTEXT THAT SHAPES THE
00:03:09AVAILABLE CHOICES THAT PEOPLE HAVE. CAN HELP US BETTER UNDERSTAND
00:03:11THE POLICY TERRAIN TODAY. SO WE WILL BEGIN.
00:03:16I WILL BEGIN WITH INTRODUCTIONS. EACH OF THE PANELISTS WILL OFFER
00:03:19SOME REMARKS AND THEN WE'LL
00:03:22WE'LL END WITH A Q&A.
00:03:24AND EACH OF YOU HAVE A A CARD,
00:03:26AN INDEX CARD WHERE YOU CAN WRITE YOUR QUESTIONS, WILL
00:03:29COLLECT IT, AND WE'LL USE THE LAST HALF AN HOUR FOR A Q&A.
00:03:34SO TO BEGIN OUR PANEL, FIRST WE HAVE FOR I GO WHO IS THE ANDREW
00:03:38JACKSON CHAIR? AND AMERICAN HISTORY AT
00:03:42VANDERBILT UNIVERSITY. SHE TEACHES AND WRITES ABOUT
00:03:45MODERN U.S. CULTURAL, INTELLECTUAL, LEGAL AND
00:03:47POLITICAL HISTORY. AND HER BOOKS INCLUDE THE KNOW
00:03:51AND CITIZEN A HISTORY OF PRIVACY IN MODERN AMERICA AND THE
00:03:56AVERAGE AMERICAN SURVEYS CITIZENS AND THE MAKING OF A
00:03:58MASS PUBLIC. EKATERINA BHABHA AND STEPHEN IS
00:04:02AN ASSISTANT PROFESSOR IN THE DEPARTMENT OF HISTORY AT PURDUE
00:04:06UNIVERSITY. SHE IS A HISTORIAN OF SCIENCE AND TECHNOLOGY WORKING ON A BOOK
00:04:10MANUSCRIPT TENTATIVELY TITLED LEARNING WITH MACHINES IN THE
00:04:14COLD WAR, UNITED STATES AND THE SOVIET UNION.
00:04:17I FIRST A COMPARATIVE HISTORY
00:04:19ABOUT PEDAGOGICAL COMPUTING AND
00:04:22ARTIFICIAL INTELLIGENCE RESEARCH IN THE SOVIET UNION AND THE
00:04:26UNITED STATES DURING THE COLD WAR.
00:04:27REBECCA SLAYTON IS ASSOCIATE
00:04:30PROFESSOR IN CORNELL UNIVERSITY CITIES SCIENCE AND TECHNOLOGY
00:04:34STUDIES DEPARTMENT. HER RESEARCH AND TEACHING
00:04:37EXAMINE RELATIONSHIPS AMONG RISK
00:04:39GOVERNANCE AND EXPERTISE WITH A
00:04:41FOCUS ON INTERNATIONAL SECURITY AND COOPERATION.
00:04:44SINCE WORLD WAR TWO. HER FIRST BOOK IS ARGUMENTS THAT
00:04:48COUNT PHYSICS, COMPUTING AND MISSILE DEFENSE.
00:04:541949 TO 2012 AND BRENDAN CLASSIC IS ASSISTANT PROFESSOR IN THE
00:04:56DEPARTMENT OF HISTORY AT PURDUE UNIVERSITY, AND HE IS WORKING ON
00:05:00HIS FIRST BOOK PROJECT THAT IS TENTATIVELY TITLED THE ILL
00:05:02DEFINED WORLD A HISTORY OF
00:05:05MACHINE LEARNING AND NOVEL POLITICAL KNOWLEDGE, WHICH
00:05:09TRACES HOW SCHEMES OF QUANTIFICATION WOULD GO ON TO
00:05:13REMAKE CONTEMPORARY A.I.
00:05:15SO I WILL TURN THE FLOOR OVER
00:05:17NOW TO DR. EDGAR.
00:05:24WELL, THANKS, KATIE AND THE HRA
00:05:26FOR ORGANIZING THIS SESSION. AND THANKS TO YOU ALL FOR BEING HERE.
00:05:30GOOD MORNING. I THINK IT IS SAFE TO SAY THAT
00:05:33WE PROBABLY ALL RECOGNIZE THAT WE'RE IN THE MIDST OF AN
00:05:37IMPORTANT PUBLIC RECKONING WITH
00:05:39A.I., BOTH ITS PROMISE AND ITS PERILS.
00:05:41SO I'M REALLY GLAD TO HAVE THIS CHANCE TO THINK WITH YOU ALL ABOUT THAT AND THE IMPLICATIONS
00:05:45FOR AMERICANS PRIVACY AND SECURITY. THIS MORNING.
00:05:49TO DO SO, HOWEVER, I'M NOT GOING
00:05:52TO TALK ABOUT A.I. AT ALL. IN FACT, I'M GOING TO LEAVE THE
00:05:5521ST CENTURY BEHIND AND TRANSPORT US TO THE LATE 19TH
00:05:59CENTURY, AN ERA THAT MUCH LIKE
00:06:01OURS WAS FILLED WITH DISRUPTIVE
00:06:05TECHNOLOGICAL CHANGE. IT WAS ALSO COMPLETE WITH
00:06:09MASSIVE PRIVATE ENTITIES THAT
00:06:12CONVERTED, BOUGHT AND SOLD
00:06:14INFORMATION IN NEW WAYS. SO, NOT COINCIDENTALLY, THIS IS
00:06:18THE MOMENT OF THE LATE 19TH CENTURY WHEN MODERN DEBATES OVER
00:06:22PRIVACY GET STARTED.
00:06:25NOW, ROUGHLY SPEAKING, BEFORE
00:06:28THE CIVIL WAR, MOST AMERICANS
00:06:30UNDERSTOOD PRIVACY AS CLOSELY LINKED TO THEIR PHYSICAL
00:06:35ENVIRONMENT AND THEIR PROPERTY LINES. AND SO THE MOST OBVIOUS
00:06:37INFRINGEMENTS OF THEIR PRIVACY CAME IN A KIND OF PHYSICAL
00:06:41MANNER. BUT A HOST OF NEW TECHNOLOGIES IN THE LATE 19TH CENTURY WOULD
00:06:45CHANGE THIS UNDERSTANDING.
00:06:47PARTICULARLY IMPORTANT WHERE A
00:06:49SET OF NEW VIRTUAL INVASIONS,
00:06:52TELEGRAPH LINES, TELEPHONE
00:06:54WIRES, RECORDING DEVICES, THE
00:06:56TABLOID PRESS AND WHAT CONTEMPORARIES CALLED
00:07:00INSTANTANEOUS PHOTOGRAPHY.
00:07:02I PICTURED A FEW OF THESE
00:07:04TECHNOLOGIES ON THE HANDOUT. IF YOU WANT TO TAKE A LOOK AT
00:07:08THEM OR WHAT THEY LOOKED LIKE TO PEOPLE AND HOW CONTEMPORARIES
00:07:11REACTED TO THEM. SO I'LL POINT TO THOSE AS I MOVE ALONG.
00:07:15BUT I WANT TO BEGIN WITH THE TELEGRAPH AND THE TELEPHONE ARE
00:07:17TWO OF THE DAZZLING INNOVATIONS
00:07:20OF THE LATE 19TH CENTURY, 1870S, 1880S.
00:07:23THEY BOTH ALLOWED INFORMATION TO
00:07:25TRAVEL MUCH MORE SWIFTLY AND EFFICIENTLY THAN EVER BEFORE,
00:07:29BUT ALSO LESS SECURELY THAN EVER
00:07:33BEFORE. WHICH IS WHY ONE HISTORIAN CALLS THE TELEGRAPH NETWORK THE
00:07:37VICTORIAN INTERNET, WHICH I THINK IS A GREAT COINING THE
00:07:43TELEGRAPH, LIKE THE INTERNET, POSED A FAMILIAR TRADEOFF
00:07:46BETWEEN CONVENIENCE AND PRIVACY.
00:07:48IT REQUIRED THE DISCLOSURE OF THE CONTENTS OF ONE'S MESSAGE TO
00:07:52A THIRD PARTY AND COMPANIES KEPT
00:07:54COPIES, WHICH MIGHT EXIST IN 3 OR 4 SEPARATE LOCATIONS.
00:07:57AND THOSE CONTENTS COULD BE SUBPOENAED BY THE FEDERAL GOVERNMENT.
00:08:01FOR EXAMPLE, JUST A FEW YEARS
00:08:04LATER, AFTER THE TELEGRAPH, THE COMMERCIAL TELEGRAPH REALLY CAME
00:08:06INTO BEING WAS THE INTRODUCTION
00:08:08OF THE COMMERCIAL TELEPHONE, WHICH LAUNCHED, ACCORDING TO ONE
00:08:12OBSERVER, ONCE AND FOR ALL, AN
00:08:15ERA OF ELECTRONIC EXHIBITION ISM AND VOYEURISM.
00:08:18I MEAN, IT SOUNDS KIND OF RIPPED FROM THE 1990S TO ME.
00:08:22YOU SEE THIS ON THE HANDOUT IN
00:08:24THAT IMAGE AS AN AT&T AD OF A AN
00:08:27OPERATOR REACHING RIGHT INTO
00:08:29PEOPLE'S HOMES ON THAT MAP OF THE UNITED STATES.
00:08:34THERE WERE OTHER LISTENERS, NOT JUST THE TWO PARTIES TO THE
00:08:38CONVERSATION. AND THERE WERE NEW PRACTICES THAT CAME WITH THESE
00:08:43TECHNOLOGIES, THE TAPPING OF TELEPHONE WIRES BY CRIMINALS AS
00:08:47WELL AS THE POLICE AND SOMETIMES THE FEDERAL GOVERNMENT ON NATIONAL SECURITY GROUNDS.
00:08:51THIS WILL, IN FACT, BE WELL-KNOWN ENOUGH TO AMERICANS
00:08:54TO SPAWN A WHOLE NEW GENERE OF LITERATURE. THE WIRE THRILLER.
00:09:00AND YOU SEE AN IMAGE OF THAT ON
00:09:02THE TOP LEFT OF THE HANDOUT. A LEGAL DEBATE WOULD SOON BE
00:09:06SPARKED BY THESE PRACTICES OF INTERCEPTION.
00:09:08DID INFORMATION THAT TRAVELED
00:09:11OVER WIRES OR CABLES DESERVE THE
00:09:13SAME KIND OF PROTECTIONS AS WRITTEN CORRESPONDENCE?
00:09:17IN 1928, A DECADE AFTER THIS OR
00:09:20SEVERAL DECADES AFTER THIS TECHNOLOGY HAD COME INTO USE.
00:09:23THE SUPREME COURT SAID NO. WIRETAPPING WAS NOT A PRIVACY
00:09:27INVASION BECAUSE IT MADE NO PHYSICAL INTRUSION ON SOMEONE'S
00:09:31HOME. THE LINES AND CABLES, YOU KNOW,
00:09:33WENT OUTSIDE OF THE HOUSE.
00:09:35SO THIS RULING WOULD STAY IN PLACE FOR DECADES AND NOT BE
00:09:41OVERTURNED UNTIL 1967. AND I JUST WANT TO NOTE THERE,
00:09:43THE CHALLENGE POSED BY NEW TECHNOLOGIES IN TERMS OF THE
00:09:47REGULATION KEEPING UP WITH THE
00:09:49POSSIBLE RISKS.
00:09:51THE ANALOGY FROM MAIL TO
00:09:54TELEPHONE DIDN'T WORK VERY WELL
00:09:56OR SERVE AMERICANS PARTICULARLY WELL.
00:09:58OTHER TECHNOLOGIES OF THE DAY, LATE 19TH CENTURY WERE CHANGING
00:10:02THE TERMS OF PRIVACY AS WELL,
00:10:04INCLUDING THE NOVEL ABILITY TO
00:10:07STORE AND DISSEMINATE DATA THAT
00:10:09HAD ONCE BEEN EPHEMERAL. AND YOU COULD THINK HERE WE
00:10:12DON'T TYPICALLY THINK OF THIS NOW, TODAY AS A KIND OF
00:10:16TECHNOLOGY OF CAPTURE, BUT THE PHONOGRAPH ALSO PICTURED FOR YOU
00:10:20THERE, WHICH COULD FOR THE FIRST TIME RECORD AND PLAYBACK A HUMAN
00:10:23VOICE, FOR EXAMPLE, MORE ALARMING THAN THE PHONOGRAPH TO
00:10:27MANY AMERICANS WAS THE DISSEMINATION OF THE PERSONAL
00:10:30IMAGE AFFORDED BY NEW TECHNOLOGIES OF EXPOSURE TIMES
00:10:34AND INSTANT PHOTOGRAPHY.
00:10:36PHOTOGRAPHY HAD ONCE BEEN SLOW
00:10:38AND CUMBERSOME SUBJECTS HAD TO SIT FOR A PHOTO.
00:10:41THEY COULDN'T BE CAUGHT UNAWARES. BUT THE SHRINKING OF EXPOSURE
00:10:46TIMES IN THE 1880S MEANT THAT PICTURE TAKING NO LONGER
00:10:48REQUIRED A COOPERATIVE SUBJECT.
00:10:50AMATEUR PHOTOGRAPHY WOULD TAKE OFF AND A MARKET FOR IMAGES AS
00:10:54WELL. YOU SEE THIS IN THE BROWNIE CAMERA.
00:10:58ADVERTISEMENT, AS WELL AS NEW DEVICES FOR SURREPTITIOUS PHOTO
00:11:02TAKING. THE APTLY NAMED DETECTIVE
00:11:06CAMERAS WERE OFTEN DISGUISED AS OTHER THINGS THAT PEOPLE DIDN'T
00:11:09KNOW YOU WERE CARRYING A CAMERA AROUND WITH YOU. ALL OF THIS WOULD OPEN THE
00:11:13FLOODGATES FOR THE MASS CIRCULATION OF IMAGES IN THE
00:11:16NEWSPAPER AND ELSEWHERE, AND
00:11:19ACCOMPANYING STORIES OF SEX, CRIME AND CELEBRITY, WHICH YOU
00:11:22SEE IN A CARTOON THERE AS WELL. ALL OF THIS RAISED THE
00:11:27POSSIBILITY, A NEW POSSIBILITY OF UNDESIRABLE EXPOSURE AND
00:11:30PUBLICITY OF PRIVATE AFFAIRS.
00:11:32SO NEW TECHNOLOGY IS THEN, AS
00:11:36TODAY, SEEMED TO MAKE MATTER OF FACT, EXPECTATIONS OF PRIVACY
00:11:41OBSOLETE. BUT THEY ALSO AND I THINK THIS IS REALLY IMPORTANT TO THINK
00:11:44ABOUT TODAY, THEY GENERATE NEW DEFENSES AND SOMETIMES NEW
00:11:48DEFINITIONS OF PRIVACY, INDIVIDUAL PRIVACY.
00:11:52INDEED, THIS MOMENT WOULD SPARK THE FIRST MODERN STATEMENT OF A
00:11:55RIGHT TO PRIVACY. MAKING THE CASE WERE TO BOSTON
00:11:59LAWYERS SAMUEL WARREN AND LOUIS
00:12:01BRANDEIS IN THE HARVARD LAW REVIEW IN 1890.
00:12:05THEY ARGUED THAT NOVEL METHODS OF INTRUSION, ALL OF THOSE
00:12:09TECHNOLOGIES SUGGEST RACE THROUGH RECORDING DEVICES, INSTANTANEOUS PHOTOGRAPHY, AN
00:12:14AGGRESSIVE PRESS HAD, QUOTE UNQUOTE, INVADED THE SACRED
00:12:18PRECINCTS OF PRIVATE AND DOMESTIC LIFE.
00:12:21AND SO THEY CALLED FOR A REMEDY
00:12:23WHICH THEY CALLED A RIGHT TO BE LET ALONE.
00:12:27AND THEY'LL ARGUE, INTERESTINGLY, FOR SOMETHING FAR
00:12:29BEYOND MERE PROPERTY RIGHTS,
00:12:32SOMETHING THAT WAS FAR LESS TANGIBLE. AND THEY CALLED IT ONE'S
00:12:37INVIOLABLE PERSONALITY, ONE'S SELF, AND NEEDED TO BE PROTECTED
00:12:40FROM ALL OF THESE INVASIONS.
00:12:42SO MORE THAN A CENTURY BEFORE
00:12:45THE FRAMING OF A RIGHT TO BE FORGOTTEN FOR DIGITAL AGE
00:12:48CITIZENS OR WORRY ABOUT
00:12:50DEEPFAKES OR REVENGE --, THIS
00:12:53NOTION OF A RIGHT TO ONE'S OWN
00:12:55IMAGE, PERSONALITY AND REPUTATION REALLY RESONATED
00:12:59QUITE BROADLY. ONE EXAMPLE OF THIS WAS A BILL
00:13:03TO PROTECT LADIES THAT WAS INTRODUCED IN THE US HOUSE OF
00:13:07REPRESENTATIVES IN 1888 TO BAR WOMEN'S IMAGES FROM BEING USED
00:13:11IN COMMERCE WITHOUT THEIR CONSENT.
00:13:13AS THIS SUGGESTS, SOME OF THE FIRST RIGHT TO PRIVACY SUITS AND
00:13:19CLAIMS IN THE UNITED STATES WERE BROUGHT BY INDIVIDUAL MILLS
00:13:22WHOSE IMAGES WERE USED WITHOUT AUTHORIZATION TO ADVERTISE
00:13:26PRODUCTS FROM SOAP TO CIGARETS.
00:13:28I HAVE PICTURED A COUPLE OF THEM ON THAT HANDOUT AGAIN.
00:13:32ONE OF THEM ON THE LEFT THERE WAS MARIANNE MIGNOLA.
00:13:35SHE WAS A STAGE ACTRESS. AND SHE WAS PHOTOGRAPHED IN TIGHTS, SHE SAID, WHICH WAS NOT
00:13:39MEANT TO BE CIRCULATED BEYOND THE THEATER. AND SHE BROUGHT SUIT FOR THE
00:13:43UNWANTED CIRCULATION OF HER IMAGE.
00:13:47MORE FAMOUSLY, IN 1902, A YOUNG WOMAN, STILL A TEENAGER AT THIS
00:13:52POINT. ABIGAIL ROBERTSON LODGED A SIMILAR COMPLAINT IN NEW YORK
00:13:57AGAINST FRANKLIN MILLS FLOWER. SO THE FLOWER MAKER HAD USED HER
00:14:01IMAGE. SHE CITED THE MAKING OF 25,000
00:14:04LITHOGRAPHIC PRINTS, PHOTOGRAPHS
00:14:06AND LIKENESSES OF HERSELF. THEY HAD CIRCULATED THOSE WITHOUT HER KNOWLEDGE AND
00:14:10DISPLAYED THEM IN STORES AND
00:14:12SALOONS AND OTHER PUBLIC VENUES.
00:14:14IN FACT, ROBERTS CLAIMED THAT
00:14:17SHE HAD ONLY LEARNED OF THIS ADVERTISING CAMPAIGN WHEN SHE
00:14:21GLIMPSED HER OWN FACE ON A
00:14:22NEIGHBOR'S BAG OF FLOUR.
00:14:26SO THIS SEEMS AMUSING TO US NOW,
00:14:30BUT THIS WAS A REAL OFFENSE TO HER.
00:14:32SHE CLAIMED GREAT DISTRESS AND
00:14:36SUFFERING TO HAVE LOST CONTROL OF HER IMAGE.
00:14:38AND IN FACT, SHE WILL WIN IN A LOWER COURT.
00:14:40A SYMPATHETIC COURT WILL SAY
00:14:43THIS IS A NOVEL CLAIM. BUT THEY RULED IN HER FAVOR.
00:14:47JUDGING THAT HER RIGHT OF PRIVACY HAD INDEED BEEN VIOLATED.
00:14:51HOWEVER, ANOTHER JUDGE WILL COME ALONG AND OVERTURN THIS VICTORY,
00:14:56ARGUING THAT IN A WORLD OF INVISIBLE VIRTUAL CAPTURE BY NEW
00:14:59TECHNOLOGIES, PERHAPS THERE WAS NO FEASIBLE CLAIM TO ONE'S OWN
00:15:02IMAGE OR ONE'S OWN MOVEMENTS.
00:15:04THE SAME CASE, OF COURSE, IS MADE TODAY BY THE MARKETERS OF
00:15:08FACIAL RECOGNITION TOOLS AND SCRAPERS OF PUBLICLY AVAILABLE
00:15:11DATA OR WRITING. THAT IS, THE BUILDING MATERIAL
00:15:15FOR LARGE LANGUAGE MODELS. AND SO WE SEE SIMILAR ARGUMENTS
00:15:19TODAY THAT NEW TECHNOLOGIES AND
00:15:21THE COLLECTING OF VARIOUS KINDS OF INFORMATION CAN'T BE REINED
00:15:25IN EITHER BECAUSE THERE ARE
00:15:25OTHER PUBLIC INTERESTS AT STAKE
00:15:29OR BECAUSE THE TECHNOLOGY FOR CAPTURE IS ALREADY OUT THERE AND
00:15:32BEING DEPLOYED. IT CAN'T BE STOPPED.
00:15:35AND SO THE QUESTIONS THAT ROBERSON'S LAWSUIT RAISED MORE
00:15:38THAN A CENTURY AGO ARE ONES THAT WE'RE STILL ASKING WHO HAS THE
00:15:42RIGHT TO POSSESS OR CONSUME OR CIRCULATE ONES IMAGE? WHAT RIGHT DOES ONE HAVE TO
00:15:46ONE'S OWN REPUTATION OR BIOGRAPHICAL OR FINANCIAL OR
00:15:50COMMERCIAL DATA? NEVERTHELESS, AS BRANDEIS AND
00:15:54WARREN WOULD HAVE HOPED, PUBLIC OUTCRIES OVER NEW TECHNOLOGIES
00:15:58HAVE SPARKED INNOVATIVE REMEDIES. AND IN FACT, IT WAS PUBLIC
00:16:02OUTRAGE OVER ROBERSON'S CASE BEING OVERTURNED THAT LED THE
00:16:05NEW YORK LEGISLATURE TO PASS THE NATION'S VERY FIRST PRIVACY TORT
00:16:09STATUTE, ALLOWING INDIVIDUALS TO SUE FOR INVASION OF PRIVACY.
00:16:12WHETHER NAME, PORTRAIT OR PICTURE WAS USED WITHOUT CONSENT
00:16:15FOR PURPOSES OF TRADE. AND OVER THE COURSE OF THE 20TH
00:16:19CENTURY, WE SAW THE DEFINITION
00:16:20OF PRIVACY EXPAND DRAMATICALLY.
00:16:23AS I NOTED FROM A SHIFT AROUND FROM PROPERTY RIGHTS AND
00:16:28PHYSICAL SPACE TO ENCOMPASS THINGS LIKE ONE'S IMAGE AND
00:16:31PERSONALITY, COMPUTER ZATION AND
00:16:34THE NETWORKED DATABANKS THAT EMERGED IN THE 1960S WOULD
00:16:37TRIGGER YET ANOTHER PRIVACY
00:16:40DEBATE CENTERING ON THE LAWS,
00:16:42NORMS AND REGULATIONS THAT MIGHT SAFEGUARD INDIVIDUAL'S PERSONAL
00:16:46DATA, SOMETHING WE'RE GOING TO HEAR MORE ABOUT FROM OTHER PANELISTS.
00:16:50BUT IF YOU THINK ABOUT THE COURSE OF OUR UNDERSTANDING OF
00:16:54PRIVACY OVER THE LAST CENTURY, ALL KINDS OF NEW THINGS STARTED
00:16:57TO BE PART OF THAT DEFINITION ONCE INNER SELF, WHEN
00:17:01PSYCHOLOGICAL FREEDOM, ONE'S DECISIONAL AUTONOMY, ONE'S
00:17:03OFFICIAL RECORDS AND DIGITAL IDENTITY.
00:17:05SO WHAT I HOPE THIS BRIEF
00:17:09HISTORICAL TOUR REVEALS IS THAT
00:17:12THE PROBLEMS OF EXPOSURE, OF
00:17:14CAPTURE, SURVEILLANCE, INTERCEPT AND TRANSMISSION AND
00:17:18COMMODIFICATION OF PRIVATE MATERIAL IS NOT AT ALL NEW.
00:17:20WE'RE NOW, I THINK, FACING A
00:17:24THIRD PIVOTAL MOMENT FOR PUBLIC
00:17:26DEBATE AROUND GENERATIVE A.I. IN
00:17:29THIS, I THINK WHERE HISTORY IS MAYBE MOST HELPFUL IS NOT
00:17:33NECESSARILY IN THE ANALOGIES FROM OLD TECHNOLOGIES TO NEW
00:17:37ONES, BUT IN HELPING US SEE PATTERNS, HOW THREATS TO PRIVACY.
00:17:40AND THEREFORE, I WOULD ARGUE SECURITY HAVE OFTEN BEEN
00:17:45WRECKING SIZED, BUT JUST AS OFTEN PUSHED ASIDE, LOBBIED
00:17:47AGAINST OVERWRITTEN OR IGNORED.
00:17:51THIS MEANS THAT PUBLIC CONCERNS OVER THE ARRIVAL OF NEW
00:17:54TECHNOLOGIES HAVE TYPICALLY BEEN ONLY INCOMPLETELY OR WEAKLY
00:17:58RESOLVED. IN THE AGE OF AI, AND WITH SO
00:18:01MUCH AT STAKE IN OTHER WORDS, WE
00:18:03MAY NOT WANT TO ALLOW THE PAST TO SHAPE OUR SENSE OF
00:18:07POSSIBILITY AROUND POLICY SOLUTIONS.
00:18:09THANK YOU VERY MUCH.
00:18:18GOOD MORNING, EVERYONE. THANK YOU SO MUCH.
00:18:23TODAY FOR ORGANIZING THIS PANEL
00:18:26AND IT IS SUCH A PLEASURE TO BE A PART OF IT AND TO PRESENT TO
00:18:29THIS AUDIENCE. THE FIRST ARTIFICIAL
00:18:33INTELLIGENCE SYSTEM THAT WAS DEVELOPED IN THE MID 1950S BY
00:18:38POLITICAL SCIENTIST HERBERT SIMON AND MATHEMATIC ITION ALAN
00:18:42NEWELL AT THE RAND CORPORATION, A MILITARY STRATEGY THINK TANK
00:18:46IN SANTA MONICA, CALIFORNIA,
00:18:49NAMED THE LOGIC THEORY MACHINE.
00:18:51SIMON IN YOUR SYSTEM, AUTOMATED MATHEMATICAL CALCULATION.
00:18:56IT PROVED THEOREMS FROM
00:18:58PRINCIPLE MATHEMATICA BY ALFRED WHITEHEAD AND BERTRAND RUSSELL.
00:19:03SIMON EMPHASIZED THAT THE
00:19:05ALGORITHMS OF THE LOGIC THEORY MACHINE MIMICKED THE VERY WAY
00:19:09HUMANS SOLVE PROBLEMS IN
00:19:13ARTIFICIAL INTELLIGENCE HAS DRAMATICALLY CHANGED SINCE THE 1950S.
00:19:18I DEVELOPERS NO LONGER TRY TO EMULATE THE WORKINGS OF THE HUMAN MIND.
00:19:22AND MORE IMPORTANTLY FOR MY PRESENTATION TODAY, AI SYSTEMS
00:19:25ARE NO LONGER EXCLUSIVELY BOUND
00:19:29TO ELITE UNIVERSITIES AND PRESTIGIOUS THINK TANKS.
00:19:33ARTIFICIAL INTELLIGENCE HAS CEASED TO BE A PURELY ACADEMIC
00:19:37PURSUIT. IT HAS EVOLVED IN A VERY TYPE OF
00:19:40UBIQUITOUS COMMERCIALLY AVAILABLE PRODUCTS, AND A.I. HAS
00:19:44BECOME DEEPLY INTERACTIVE, DATA
00:19:48DRIVEN. AI ALGORITHMS USE OUR DATA TO
00:19:51SHAPE WHAT WE SEE WHEN WE OPEN SOCIAL PLATFORMS AND SEARCH
00:19:55ENGINES AND SYSTEMS THAT USE
00:19:57LARGE LANGUAGE MODELS CAN NOW
00:19:59ENGAGED IN FLUID CONVERSATIONS.
00:20:02AND IT IS THESE INTERACTIVE
00:20:04ABILITIES OF PRESENT DAY AI THAT
00:20:06HAS BEEN OF PUBLIC CONCERN RECENTLY.
00:20:10MACHINE LEARNING HAS PROVEN TO BE EFFECTIVE IN MICROTARGETING
00:20:13CAMPAIGNS AND IN MANIPULATING USERS EMOTIONS.
00:20:17AND GENERATIVE AI IS EXCELLENT
00:20:19AT PRODUCING CONVINCING AND BUT
00:20:22ALWAYS BUT NOT ALWAYS ACCURATE TEXTS.
00:20:24MACHINE LEARNING AND GENERATIVE
00:20:26AI ALGORITHMS ARE RAISING
00:20:29CONCERNS ABOUT THE POTENTIAL OF
00:20:31THIS TECHNOLOGY TO SHAPE HUMAN
00:20:33BEHAVIOR AND INFLUENCE PUBLIC OPINION.
00:20:37ARTIFICIAL INTELLIGENCE HAS CHANGED SINCE THE 1950S, BUT THE
00:20:41CAPACITY OF COMPUTER SYSTEMS TO
00:20:43INFLUENCE HOW WE ACT AND REASON
00:20:45HAS A HISTORY AND THE ROOTS OF
00:20:47THIS HISTORY ARE IN THE HISTORY
00:20:50OF COMPUTING. SO WITH MY TIME TODAY, I'D LIKE
00:20:54TO PRESENT A FEW HISTORY ARTICLE
00:20:56EXAMPLES THAT SHOW HOW THE HISTORY OF COMPUTING HAS BEEN
00:21:00ENTANGLED WITH EFFORTS TO INFLUENCE HUMAN BEHAVIOR AND
00:21:04THINKING. DURING THE WORLD WAR TWO, M.I.T.
00:21:09BASED MATHEMATICIAN NORBERT WIENER WORKED WITH ENGINEER
00:21:11JULIAN BIGELOW AT MIT'S
00:21:13RADIATION LABORATORY TO CREATE A
00:21:17DEVICE THAT COULD PREDICT THE PATH OF AN ENEMY AIRCRAFT.
00:21:21WITNESS. AND BIGELOW'S RESEARCH WAS SUPPORTED BY THE NATIONAL
00:21:24DEFENSE RESEARCH COMMITTEE.
00:21:26THE DEVICE THEY CREATED, THE ANTI AIRCRAFT PREDICTOR, WAS AN
00:21:30ELECTROMECHANICAL COMPUTER THAT
00:21:32USED DATA FROM RADAR TRACKERS TO
00:21:35MAKE A STATISTICAL FORECAST ABOUT THE FUTURE FLIGHT
00:21:38TRAJECTORY OF AN ENEMY AIRPLANE. THE PREDICTOR WAS CONNECTED TO
00:21:42AN AUTOMATIC GUN LANE SYSTEM TO
00:21:44AIM AT THE ENEMY TARGETS. OF COURSE, THE TRAJECTORY OF THE
00:21:48ENEMY AIRCRAFT WAS DETERMINED BY THE PILOTS DECISIONS.
00:21:52SO ESSENTIALLY, WIENER'S COMPUTER USED RADAR DATA TO
00:21:56PREDICT THE BEHAVIOR OF THE ENEMY PILOTS.
00:21:59NOR DID WIENER'S ANTI AIRCRAFT PREDICTOR WAS NEVER IMPLEMENTED
00:22:04ON THE BATTLEFIELD. ON A PRACTICAL LEVEL, IT WAS OF
00:22:07LITTLE VALUE, BUT ONLY THEORETICAL LEVEL.
00:22:09IT PRODUCED A MACHINE MAGICAL
00:22:11THEORY OF STATISTICAL PREDICTION
00:22:13AND A NEW INTERDISCIPLINARY
00:22:16APPROACH CALLED CYBERNETICS.
00:22:18CYBERNETICS ORIGINATES FROM A
00:22:20GREEK WORD DENOTING
00:22:22STATESMANSHIP OR GOVERNANCE. CYBERNETICS BECAME AN
00:22:26INTERDISCIPLINARY SCIENCE THAT
00:22:28THEORIZED HUMANS AND MACHINES AS
00:22:30INFORMATION PROCESSING SPECIES
00:22:33WHOSE BEHAVIOR IS SHAPED BY THE
00:22:35INFORMATION THEY RECEIVE FROM THE SURROUNDING WORLD.
00:22:39WIENER EXPLAINED THE MAIN TENETS
00:22:42OF THIS SCIENCE IN HIS 1948
00:22:44MONOGRAPH CYBERNET ETHICS OR
00:22:46CONTROL AND COMMUNICATION IN THE ANIMAL AND THE MACHINE.
00:22:49AND YOU CAN SEE THE COVER OF THIS MONOGRAPH IN THE HANDOUT
00:22:53THAT WAS DISTRIBUTED.
00:22:55WIENER'S WORK PROVED TO BE
00:22:57INFLUENTIAL ACROSS GEOGRAPHICAL
00:22:59AND RESEARCH CONTEXTS, AND IT
00:23:01BECAME ESPECIALLY RELEVANT IN
00:23:04THE FIELD OF COMPUTER NETWORK DEVELOPMENT.
00:23:07ONE COMPUTING PROJECT INSPIRED
00:23:10BY CYBERNETICS WAS THE PEDAGOGY
00:23:12SCHOOL COMPUTER NAMED PROGRAMED LOGIC FOR AUTOMATED TEACHING
00:23:16OPERATE OR PLATO. AND ONCE AGAIN, IF YOU LOOK AT IF YOU TAKE A LOOK AT THE
00:23:20HANDOUT, YOU'LL SEE WHAT THAT COMPUTER LOOKED LIKE.
00:23:23SO THE PURPOSE OF PLATO WAS TO
00:23:25REPLACE HUMAN INSTRUCT US.
00:23:28THE FIRST VERSION OF PLATO WAS
00:23:30DEVELOPED AT THE COORDINATOR SCIENCES LABORATORY AT THE
00:23:33UNIVERSITY OF ILLINOIS IN 1959.
00:23:37DURING THE KOREAN WAR, THE COORDINATED SCIENCE LABORATORY
00:23:40WAS NAMED CONTROL OF SCIENCE
00:23:42LABORATORY, AND IT RECEIVED U.S. GOVERNMENT FUNDING TO CONDUCT
00:23:46RESEARCH THAT SUPPORTED THE U.S. WARTIME EFFORT.
00:23:49FOR INSTANCE, THE LABORATORY
00:23:51WORKED ON RADAR TECHNOLOGY AND COMPUTER CONTROLLED DEFENSE
00:23:55SYSTEMS. THE LABORATORY WAS HOME TO THE
00:23:58POWERFUL ELLIOTT COMPUTER, ONE OF THE FIRST MIDCENTURY DIGITAL
00:24:02COMPUTERS. SIX YEARS AFTER THE END OF THE KOREAN WAR, THE LABORATORY
00:24:07RECEIVED A MANDATE TO INCREASE COOPERATION WITH OTHER UNITS
00:24:10WITHIN THE UNIVERSITY OF ILLINOIS AND DEVELOP RESEARCH
00:24:14PROJECTS RELEVANT TO THE CIVILIAN NEEDS.
00:24:16THE PLATO PROJECT WAS A PART OF
00:24:19CIA CELLS RESEARCH REORIENTATION.
00:24:22PLATO WAS AN INTERACTIVE COMPUTER NETWORK CONSISTING OF
00:24:25COMPUTER TERMINALS CONNECTED TO THE ILIAC.
00:24:29A STUDENT LEARNING WITH THE PLATO COMPUTER SAT AT A TERMINAL
00:24:32WHERE THEY WERE PRESENTED WITH COURSE MATERIAL WHICH WAS FOLLOWED BY PROBLEMS AND
00:24:37QUESTIONS. THE SYSTEM ALLOWED STUDENTS TO
00:24:39CONTROL THE PACE OF THEIR STUDY FROM THE 1960S AND UNTIL THE
00:24:43LATE 1980S, PLATO WAS USED TO TEACH VIRTUALLY ANY SUBJECT.
00:24:47PLATO WAS A PRODUCT OF
00:24:49INTERDISCIPLINARY EXPERTISE, WHICH INCLUDED COMPUTER ENGINEERS AS WELL AS
00:24:55PSYCHOLOGISTS AND EDUCATORS. AT THE START OF THE PROJECT,
00:24:58PSYCHOLOGIST LAWRENCE WROTE,
00:25:00CONTRIBUTED TO THE DESIGN OF THE PLATO COMPUTER.
00:25:04STELLARIUM HELD A LAUNCH AND AN INTEREST IN THE DESIGN OF
00:25:08SPECIAL TEACHING MACHINES THAT COULD REPLACE HUMAN INSTRUCTORS.
00:25:12HIS INTEREST IN THE SUBJECT WAS IGNITED BY THE WORK OF HARVARD
00:25:15BASED PSYCHOLOGY SHIFT. B.F. SKINNER IN THE 1940S.
00:25:19SKINNER PERFORMED A SERIES OF EXPERIMENTS WITH ANIMALS TO
00:25:23ARGUE THAT IT IS POSSIBLE TO ENGINEER THE BEHAVIOR OF LIVING
00:25:27ORGANISMS THROUGH CAREFULLY ARRANGED ENVIRONMENTAL STIMULI.
00:25:31FOR EXAMPLE, HE DEMONSTRATED HOW
00:25:33BY PRESENTING FOOD TO HUNGRY PIGEONS, IT WAS POSSIBLE TO
00:25:37TRAIN THEM, EXHIBIT SPECIFIC RESPONSES SUCH AS TURNING
00:25:40AROUND, STAMPING THE FOOD AND SO
00:25:42ON, AND DRAWING ON THESE EXPERIMENTS.
00:25:45SKINNER ARGUED THAT THE BEHAVIOR OF ALL ORGANISMS, INCLUDING
00:25:49HUMANS, COULD BE ENGINEERED BY
00:25:51CONTROLLED ENVIRONMENT, MENTAL
00:25:54CONDITIONS. AT HARVARD, SKINNER WORKED ON DESIGNING TECHNOLOGY THAT COULD
00:25:58SHAPE HUMAN BEHAVIOR. AND ONE OF SUCH TECHNOLOGIES WAS
00:26:01THE MECHANICAL TEACHING MACHINE. SKINNER, I SHOULD NOTE, VIEWED
00:26:06LEARNING AS A FORM OF HUMAN BEHAVIOR.
00:26:08HIS MACHINES PRESENTED LEARNING
00:26:11MATERIAL IN SMALL, SPECIALLY ARRANGED INCREMENTAL STEPS.
00:26:14EACH OF WHICH WAS FOLLOWED BY A QUESTION OR A PROBLEM THAT
00:26:17REQUIRED A BRIEF ANSWER.
00:26:19SO THESE MACHINES ALLOWED STUDENTS TO PROCEED ONLY AFTER
00:26:24CORRECT RESPONSE. AND THIS ENTIRE PROCESS CONTROLLED STUDENTS LEARNING OF
00:26:28EVERY TINY PIECE OF MATERIAL. SO AT THE UNIVERSITY OF
00:26:31ILLINOIS, LAWRENCE STOLLER WAS A
00:26:33BIG PROPONENT OF SKINNER'S METHOD.
00:26:36BUT STILL, THE ROW ALSO SAW HOW SKINNER'S MACHINE COULD BE IMPROVED.
00:26:40AND HERE HE FOUND CYBERNETICS TO
00:26:43BE USEFUL IN BETWEEN HIS SCHEME
00:26:45PILOTS AND ANTIAIRCRAFT WEAPONS
00:26:48WERE BOTH SYSTEMS THAT MODIFIED THE BEHAVIOR BASED ON THE
00:26:52INFORMATION THEY RECEIVED FROM THE SURROUNDING WORLD.
00:26:56STILL, LAREAU AGREED WITH SKINNER THAT TEACHING TECHNOLOGY
00:26:59SHOULD DELIVER WELL CALIBRATED
00:27:01CUES, RESPONSES AND FEEDBACK
00:27:03LOOPS TO CONTROL STUDENT BEHAVIOR.
00:27:05BUT SIMILAR TO THE AIRCRAFT
00:27:09PREDICTOR, TEACHING TECHNOLOGY SHOULD BE ADAPTABLE. IT SHOULD ADJUST ITSELF BASED ON
00:27:13THE DATA IT RECEIVES ABOUT THE STUDENT AND THE DIGITAL COMPUTER.
00:27:18ACCORDING TO STELLA ROWE, COULD DELIVER SUCH AN ADAPTABLE FORM OF CONTROL.
00:27:22AND THIS IS THE VISION THAT STOLLER BROUGHT TO THE PLATO
00:27:26SYSTEM. STILL, THE ROW SOON LEFT THE
00:27:29PLATO PROJECT TO WORK ON ANOTHER COMPUTER BASED EDUCATIONAL
00:27:33SYSTEM. BUT THE EFFORT TO USE A DATABASE APPROACH TO BETTER CONTROL
00:27:37STUDENTS BEHAVIOR PERSISTED.
00:27:39IN 1964, ANOTHER PSYCHOLOGIST,
00:27:42JOHN EASLEY, JOINED THE PLATO PROJECT.
00:27:44HE LED A TEAM OF 19 RESEARCHERS
00:27:47WHO WERE TASKED WITH CREATING A
00:27:49PROGRAM THAT WOULD ALLOW PLATO
00:27:51TO RECORD AND ANALYZE STUDENT RESPONSE DATA.
00:27:55AND CALIBRATE THE EDUCATIONAL MATERIAL BASED ON THIS DATA
00:27:59ANALYSIS. THEIR WORK WAS SUPPORTED BY THE U.S. DEPARTMENT OF HEALTH
00:28:04EDUCATION AND WELFARE AND THE DEPARTMENT OF DEFENSE'S ADVANCED
00:28:07RESEARCH PROJECT AGENCY. EASLEY AND HIS COLLEAGUES HOPED
00:28:11THAT THE GIGANTIC AMOUNTS OF
00:28:13DATA COLLECTED ABOUT STUDENTS INTERACTIONS WITH THE PLATO
00:28:17SYSTEM, WHICH KEY THEY PRESS HOW MANY MINUTES THEY SPEND ON EACH
00:28:20QUESTION WOULD OFFER INSIGHT INTO STUDENTS STYLES OF THOUGHT
00:28:24AND LEARNING.
00:28:26THE IDEA WAS THAT SUCH A PROGRAM
00:28:28WOULD MAKE PLATO MORE ADAPTABLE TO INDIVIDUAL STUDENTS NEEDS.
00:28:32THE PROJECT LASTED FOR THREE YEARS AND EVENTUALLY EASILY
00:28:37ABANDONED IT IN 1967. BUT LATER HE WOULD CONFESS THAT
00:28:41HE WAS DROWNING IN THE OVERFLOW
00:28:43OF DATA SO EASILY, STEAM DID NOT
00:28:45MANAGE TO CREATE A PROGRAM THAT
00:28:48COULD TURN THE PLATO SYSTEM INTO A DATA DRIVEN TEACHING
00:28:52TECHNOLOGY. WHILE BEING UNSUCCESSFUL IS THIS
00:28:56PROJECT WAS ONE OF THE FIRST ATTEMPTS TO AGGREGATE DATA IN
00:29:00ORDER TO BETTER CONTROL USER
00:29:02BEHAVIOR VIA INTERACTIVE COMPUTER TECHNOLOGY.
00:29:06THIS WAS DONE IN GOOD FAITH. OF COURSE, THE INTENTION WAS TO
00:29:08MAKE EDUCATION MORE ACCESSIBLE.
00:29:12FROM THE VERY EARLY DAYS OF THE
00:29:14HISTORY OF THE DIGITAL COMPUTER AND COMPUTER NETWORKS, THE
00:29:18QUESTIONS OF HUMAN BEHAVIOR AND COGNITION PLAYED AN IMPORTANT
00:29:21ROLE IN THE DEVELOPMENT OF THIS TECHNOLOGY AND THE HISTORY OF
00:29:25THE PLATO COMPUTER IS NOT THE ONLY EXAMPLE OF THAT.
00:29:29PSYCHOLOGIST JOSEPH LECLERC TO
00:29:32SET THE VISION FOR HOW THE OPEN YET A PRECURSOR OF THE
00:29:36CONTEMPORARY INTERNET COULD EXPAND AND ENHANCE THE COGNITIVE
00:29:40CAPACITIES OF ITS USERS. THE OPEN ACT WAS A WIDE AREA
00:29:44COMPUTER NETWORK DEVELOPED BY THE U.S. DEPARTMENT OF DEFENSE'S
00:29:48ADVANCED RESEARCH PROJECTS AGENCY. THE NETWORK CONNECTED U.S.
00:29:53UNIVERSITIES AND RESEARCH INSTITUTES THAT CONDUCTED PIONEERING WORK IN COMPUTER
00:29:58ENGINEER AND COMPUTER SCIENCE AT ARPA.
00:30:00JOSEPH LEE COLLIDER DIRECTED INFORMATION PROCESSING
00:30:03TECHNIQUES OFFICE IN 1969 YEARS
00:30:06BEFORE THE ARPANET BECAME OPERATIONAL.
00:30:09THE CLYDE PUBLISHED AN INFLUENTIAL PAPER TITLED MEN
00:30:13COMPUTERS SYMBIOSIS, WHERE HE
00:30:15DESCRIBED AN INTERACTIVE COMPUTER NETWORK THAT WOULD
00:30:18ALLOW FOR A SYMBIOTIC RELATIONSHIP BETWEEN HUMAN MINDS
00:30:22WITH THEIR ABILITY FOR CREATIVE REASONING AND JUDGMENT.
00:30:25ON THE ONE HAND, AND COMPUTERS WITH THEIR SUPERIOR ABILITY FOR
00:30:29DATA STORAGE AND PROCESSING.
00:30:32IN THE 20TH CENTURY, COMPUTER TECHNOLOGY HAS BEEN A PRODUCT OF
00:30:36INTO DISCIPLINARY EXPERTISE WITH PSYCHOLOGY, SETTING THE TASKS
00:30:40AND GOALS FOR THIS TECHNOLOGIES INTERACTIVE AND INFORMATION
00:30:45PROCESSING CAPABILITIES.
00:30:46IN THE 20TH CENTURY, COMPUTERS THEREFORE WERE CONCEIVED AS
00:30:51BEHAVIORAL AND COGNITIVE TOOLS TO INFLUENCE HUMAN BEHAVIOR AND
00:30:55THINKING IN THE EXAMPLES THEY PROVIDED TODAY.
00:30:58THERE WAS NO NEFARIOUS PLAN AT THE UNIVERSITY OF ILLINOIS,
00:31:02PSYCHOLOGISTS VIEWED BEHAVIORAL CONTROL AS A KEY TO BETTER
00:31:06EDUCATION, AND IT AUTHOR JOSEPH ALEC LEIDER SAW INTERACTIVE
00:31:11COMPUTING AS A TOOL TO ENHANCE HUMAN COGNITIVE CAPACITIES.
00:31:15RESEARCHERS AT THE UNIVERSITY OF ILLINOIS AND ARPA WORK MOTIVATED
00:31:17BY GOOD INTENTIONS. AND WHILE THERE IS A CLEAR
00:31:21HISTORICAL TRAJECTORY IN THE
00:31:23DESIGN OF COMPUTER TECHNOLOGY TO INFLUENCE HUMAN BEHAVIOR AND
00:31:27THINKING, PRESENT DAY AI DRIVEN COMPUTER SYSTEMS ARE POWERED BY
00:31:32MASSIVE COMPUTING INFRASTRUCTURE AND PRIVATE INVESTMENT.
00:31:35GIVEN THEIR TECHNOLOGICAL POWER AND REACH, WE SHOULD PERHAPS BE
00:31:39EXTRA CAUTIOUS ABOUT THEIR CAPACITY TO INFLUENCE HOW WE THINK AND ACT.
00:31:43THANK YOU.
00:31:49GREAT. THANK YOU.
00:31:51SO IF I CAN GET THIS SET UP, I'M
00:31:56GOING TO PICK UP WHERE SARAH AND
00:31:58KUTCHER LEFT OFF BY TALKING ABOUT WHEN DIGITAL ELECTRONIC
00:32:02COMPUTERS STARTED TO PROVOKE ANXIETIES ABOUT PRIVACY AND SECURITY.
00:32:05SO IN THE 1960S, THAT PERIOD THAT KUTCHER SPOKE ABOUT A
00:32:08LITTLE BIT, ONE OF THE PERIOD SHE SPOKE ABOUT COMPUTERS WERE
00:32:12HUGE ROOMS AND THEY FILLED HUGE ROOMS. THEY'RE BIG MACHINES.
00:32:15THEY WERE SYMBOLS OF IMPERSONAL BUREAUCRATIC ORGANIZATIONS.
00:32:19THEY'VE SEEN A VERY DEHUMANIZING. SO WHEN THE UNITED STATES
00:32:23PROPOSED CREATING A CENTRALIZED DATABASE TO ALLOW FEDERAL
00:32:25AGENCIES TO SHARE INFORMATION ABOUT INDIVIDUALS, THERE WAS A
00:32:29MAJOR DEBATE ABOUT THAT. AND THAT WAS ONE OF THE FIRST DEBATES ABOUT THE IMPACTS OF
00:32:34COMPUTERIZED VERSION ON PERSONAL PRIVACY. SO JUST TO GIVE YOU A SENSE OF
00:32:38THE KINDS OF CONCERNS THAT WERE RAISED AT ONE MAJOR COMPUTING
00:32:42CONFERENCE, THAT CONGRESSIONAL REPRESENTATIVE ARGUED THAT, QUOTE, AMERICA HAS ALWAYS
00:32:46REPRESENTED FOR ME A PLACE WHERE AN INDIVIDUAL COULD CHANGE HIS
00:32:49MIND, HIS BELIEFS AND OUTLOOK ON
00:32:51LIFE AND STILL BE ABLE TO LIVE AS A FREE AND VALUABLE COMPONENT
00:32:55OF OUR SOCIETY. THE AMERICA I HAVE DESCRIBED
00:32:58CANNOT BE THE SAME AMERICA,
00:33:00AFTER A CENTRALIZED COMPUTER SYSTEM, A SYSTEM WHICH NEITHER
00:33:04FORGIVES NOR FORGETS IS INTRODUCED END QUOTE.
00:33:06NOW, SOME COMPUTER SCIENTIST SUGGESTED THAT THIS WAS ACTUALLY
00:33:10THE WRONG WAY TO THINK ABOUT THE TECHNOLOGIES THAT WERE DEVELOPING.
00:33:14SO IN 1966, CONGRESSIONAL HEARINGS, THE COMPUTER
00:33:16SCIENTIST, PAUL BARON, TESTIFIED, QUOTE, TODAY WE CAN
00:33:20SEE THE INDEPENDENT PRIVATE AUTOMATE INFORMATION SYSTEMS
00:33:23BEING INTERCONNECTED TO FORM
00:33:25LARGER GROWING SYSTEMS, WHICH ARE IN MANY WAYS MORE DANGEROUS
00:33:29THAN THE SINGLE DATA BANK. NOW BEING CONSIDERED. IN OTHER WORDS, IT WAS THE
00:33:33INTERNET NETWORKING OF MANY DIFFERENT SYSTEMS, MOSTLY
00:33:36CONTROLLED BY THE PRIVATE SECTOR, THAT WERE GOING TO
00:33:38EVENTUALLY POSE THE GREATEST THREAT. AND IF YOU'RE WONDERING WHY WE SHOULD LISTEN TO THIS GUY, PAUL
00:33:42BARON, HE'S THE PERSON WHO CAME UP WITH THE ARCHITECTURE FOR THE INTERNET. AND THE WHOLE ARCHITECTURE FOR
00:33:46PACKET SWITCHING. SO I START WITH THIS HISTORICAL
00:33:50MOMENT BECAUSE IT'S A REMINDER THAT THE INFRASTRUCTURE FEATURES THAT ENABLE A.I. TODAY, THE
00:33:54INTERNET MASSIVELY INTERCONNECTED DATABASES WERE UNDER DEVELOPMENT 60 YEARS AGO
00:33:58AND PEOPLE WERE WORRIED THEN, RIGHT? SO THE QUESTION IS, WHAT
00:34:02HAPPENED? RIGHT. WHY, DESPITE THESE EARLY WARNINGS, HAS ARTIFICIAL
00:34:06INTELLIGENCE BEEN DEVELOPED IN WAYS THAT CURRENTLY THREATEN PRIVACY AND SECURITY?
00:34:09AND I WANT TO ACKNOWLEDGE THAT IT DOESN'T ONLY THREATEN PRIVACY
00:34:13AND SECURITY, THERE ARE WAYS OF USING A.I. THAT ARE NOT NECESSARILY A THREAT, BUT THERE
00:34:17ARE SOME REALLY LEGITIMATE CONCERNS OUT THERE. SO THERE'S NO SIMPLE ANSWER TO THIS QUESTION.
00:34:20BUT I'M GOING TO ATTEMPT A PARTIAL ONE.
00:34:23PART OF THE ANSWER HAS TO DO WITH HOW WE CAME TO DEFINE SECURITY AND PRIVACY.
00:34:27SO IN THE 1970S, INFORMATION SECURITY CAME TO REFER TO THE
00:34:31CONFIDENTIALITY, INTEGRITY AND AVAILABILITY OF INFORMATION.
00:34:34SO CIA IS THE NICE ACRONYM THAT SEEMS FITTING.
00:34:38THAT TRIAD, THIS UNDERSTANDING
00:34:40OF SECURITY CAME FROM THE U.S.
00:34:42MILITARY INTELLIGENCE AGENCIES, AND IT WAS A RELATIVELY NARROW
00:34:46TECHNICAL DEFINITION. PRIVACY ON THE OTHER HAND, CAME TO BE SEEN AS SOMETHING BROADER
00:34:49AND MORE SUBJECTIVE, LARGELY DOMAIN OF CIVIL SOCIETY AND
00:34:53CIVIL GOVERNMENT. AND WE DEVELOPED A TENDENCY TO
00:34:56SEE SECURITY AND PRIVACY AS BEING IN TENSION, BECAUSE THERE
00:34:58ARE TIMES WHEN SOCIETY'S RIGHT TO KNOW OUTWEIGHS AN
00:35:02INDIVIDUAL'S RIGHT TO PRIVACY. OBVIOUSLY, THAT'S A LOT OF WHY PEOPLE HAVE DRIVEN FOR THE
00:35:05RELEASE OF THE EPSTEIN FILES, FOR EXAMPLE. BUT THERE'S A LOT OF OTHER
00:35:08EXAMPLES LIKE THAT. SO PRIVACY HAD SOMETHING TO DO
00:35:12WITH CONFIDENTIALITY, INTEGRITY AND AVAILABILITY, EVEN FORMATION.
00:35:15BUT IT'S ALSO ABOUT THE WAYS THAT INFORMATION, INCLUDING ERRONEOUS OR INACCURATE
00:35:19INFORMATION, CAN BE MISUSED. FOR EXAMPLE, TO DENY PEOPLE
00:35:23ACCESS TO HOMES, JOBS AND LOANS.
00:35:27MORE THINGS LIKE THAT. SO IT CAN HAVE A VERY DESTRUCTIVE EFFECT ON PEOPLE'S LIVES.
00:35:31AND THAT SENSE, WE CAN ACTUALLY UNDERSTAND VIOLATIONS OF PRIVACY
00:35:34AS VIOLATIONS OF HUMAN SECURITY, BE UNDERSTOOD AS FREEDOM FROM
00:35:37FEAR, FREEDOM FROM WANT, AND THE FREEDOM TO PURSUE NEW OPPORTUNITIES.
00:35:40SO THAT'S JUST TO SAY THAT WE SHOULD RECOGNIZE THERE ARE MANY
00:35:43DIFFERENT KINDS OF SECURITY, NATIONAL SECURITY, INDIVIDUAL HUMAN SECURITY.
00:35:47THEY'RE NOT ALWAYS IN CONFLICT. AND PRIVACY ACTUALLY CAN BE
00:35:51UNDERSTOOD AS A KIND OF HUMAN SECURITY. BUT THEY'VE MOSTLY BEEN TREATED
00:35:55FAIRLY SEPARATELY. SO I'M IN IT AND THE REST OF MY COMMENTS ARE GOING TO MOSTLY
00:35:57FOCUS ON PRIVACY, SINCE THAT'S HOW IT HAS BEEN DISCUSSED
00:36:00SEPARATELY FROM SECURITY. A LOT WAS DONE ON THE PRIVACY
00:36:03PROBLEM IN THE EARLY 1970S WITH MULTIPLE PIECES OF LEGISLATION
00:36:06PASSED, INCLUDING THE LANDMARK 1974 PRIVACY ACT. BUT SOME THINGS WERE VERY
00:36:11EXPLICITLY NOT DONE. SO, FOR EXAMPLE, IN 1977, A
00:36:14FEDERAL COMMISSION ON PRIVACY
00:36:16ISSUED A MASSIVE REPORT, 654
00:36:19PAGES, DETAILING, QUOTE, AN OVERWHELMING IMBALANCE IN THE
00:36:22RECORD KEEPING RELATIONSHIP BETWEEN AN INDIVIDUAL AND AN
00:36:25ORGANIZATION, MEANING THAT ORGANIZATIONS HAD ALL THE POWER.
00:36:28THEY MADE MANY RECOMMENDATIONS. THEY INCLUDED THAT THE US CREATE
00:36:32A NEW FEDERAL PRIVACY BOARD TO ISSUE GUIDELINES ON HOW TO
00:36:35PROTECT INDIVIDUAL PRIVACY BECAUSE THEY ANTICIPATED
00:36:39TECHNOLOGIES WERE GOING TO CHANGE AND WE NEEDED TO THINK
00:36:41ABOUT HOW PRIVACY PROTECTIONS SHOULD ADAPT TO NEW
00:36:44TECHNOLOGICAL CHANGES. NOW, THIS PRIVACY BOARD WAS NOT CREATED.
00:36:48IN FACT, MOST OF THE COMMISSION'S RECOMMENDATIONS
00:36:51WERE NOT IMPLEMENTED. AND AS A RESULT, BY THE EARLY
00:36:541980S, PRIVACY LEGISLATION HAD, IN THE WORDS OF ONE HISTORIAN,
00:36:58QUOTE, FUNDAMENTALLY FAILED TO PROTECT THE PRIVACY INTERESTS OF
00:37:01AMERICAN CITIZENS AND, QUOTE. HE ALSO NOTED THAT THE US
00:37:05SITUATION WAS VERY DIFFERENT THAN THAT OF EUROPE, WHERE PRIVACY PROTECTION AGENCIES WERE
00:37:09CREATED. SOME OF THOSE SAME AGENCIES ARE
00:37:11TODAY PUSHING BACK ON ABUSES OF PRIVACY BY AI FIRMS, BUT
00:37:15REPEATED EFFORTS TO DEVELOP BETTER PRIVACY PROTECTIONS ARE
00:37:18PROPOSALS THAT WE SHOULD HAVE SOME KIND OF A BODY THAT WOULD
00:37:22ACTUALLY HAVE A VESTED INTEREST IN PUSHING FOR INDIVIDUAL
00:37:26PRIVACY PROTECTIONS. THOSE WERE NOT ACCEPTED.
00:37:28SO THOSE POLICY CHOICES THAT
00:37:30HAVE SHAPED THE KINDS OF A.I. DEVELOPMENTS THAT BECAME
00:37:33POSSIBLE AND PROFITABLE. SO WE'VE HAD SEVERAL WAVES OF EXCITEMENT ABOUT EYE CATCHING,
00:37:37MENTIONED A FEW SINCE THE 1950S.
00:37:40THE CURRENT WAVE FOCUSES ON NEURAL NETWORKS OR MACHINE
00:37:43LEARNING AND WHAT MOST DISTINGUISHES IT IS ITS DEPENDANCE UPON VAST AMOUNTS OF
00:37:47DATA AND PROCESSING POWER.
00:37:49AND THE BASIC MODELS UNDERLYING MACHINE LEARNING TODAY WERE
00:37:53DEVELOPED DECADES AGO. BUT IT WAS THE GROWTH AND COMMERCIALIZATION OF THE INTERNET.
00:37:56THAT THING THAT WAS GETTING
00:37:57STARTED IN THE 1960S WITHOUT ANY CORRESPONDING PRIVACY
00:38:02PROTECTIONS THAT ALLOWED THESE MODELS TO BE APPLIED IN WAYS THAT SOMETIMES THREATEN PRIVACY
00:38:06AND SECURITY. SO FOR MORE THAN TWO DECADES, COMPANIES LIKE GOOGLE AND NETA
00:38:10WERE DEVELOPING MASSIVE DATABASES ON USER BEHAVIOR, WHICH THEY COULD THEN SELL TO
00:38:14ADVERTISING FIRMS. AND THESE COMPANIES WERE
00:38:17PARTICULARLY WELL POSITIONED TO DEVELOP AI BECAUSE THEY COULD
00:38:20USE THE DATA OF THEIR USERS TO TRAIN THEIR A.I. MODELS.
00:38:24BUT EVEN COMPANIES THAT DIDN'T HAVE THAT COULD JUST SCRAPE THE
00:38:26INTERNET AND USE THAT FOR NEW
00:38:31INNOVATIONS, SOME OF WHICH HAD SOME REAL PRIVACY IMPACTS AND
00:38:35ACTUALLY HAVE DONE HARM TO PEOPLE. AND I GIVE SOME EXAMPLES OF THAT.
00:38:39IF WE HAVE TIME IN THE Q&A, THE COMPANIES HAVE BEEN MORE
00:38:42RESTRAINED IN SOME NATIONS THAN OTHERS. SO, FOR EXAMPLE, LAST YEAR META
00:38:46NOTIFIED FACEBOOK AND INSTAGRAM USERS IN EUROPE THEY'D BE USING
00:38:49THEIR PUBLIC POSTS TO TRAIN BETTERS, MACHINE LEARNING ALGORITHM.
00:38:53LAMA IT GAVE EUROPEAN USERS AN OPT OUT OPTION.
00:38:57ALTHOUGH IT WAS HARD TO USE.
00:38:59BUT BUT IT DIDN'T EVEN WARN U.S.
00:39:03USERS AND IT DID NOT GIVE USERS IN THE UNITED STATES AN OPT OUT
00:39:06BECAUSE IT DIDN'T HAVE TO. OKAY.
00:39:09SO I'M JUST TO CLOSE, I'M GOING TO BRIEFLY TOUCH ON SECURITY AS
00:39:12TRADITIONALLY THAT SORT OF MORE NARROW CONCEPTION OF
00:39:16CONFIDENTIALITY, INTEGRITY, AVAILABILITY OF INFORMATION SYSTEMS.
00:39:18SO HOW AM I, I IMPACT SECURITY,
00:39:22CYBER SECURITY IN THAT MORE CONVENTIONAL, NARROW SENSE? THE FIRST THING TO NOTE IS THAT
00:39:26MACHINE LEARNING CAN BE USED FOR EITHER OFFENSE OR DEFENSE. IT CAN BE USED TO GENERATE NEW VIRUSES.
00:39:30ALSO TO FIND AND EXPLOIT NEW VULNERABILITIES IN SOFTWARE.
00:39:33IT CAN ALSO BE USED TO DEFEND AGAINST THE SAME THINGS.
00:39:37AND WHAT MAKES IT MOST EFFECTIVE IS, OF COURSE, THE WAY THAT IT'S USED.
00:39:40THE ORGANIZATION, THE SKILLS OF THE ATTACKER, THE DEFENDER.
00:39:43BUT IT'S ALSO TRUE THAT MACHINE
00:39:46LEARNING ENABLES NEW KINDS OF CYBER ATTACKS AND IN FACT,
00:39:49DECEPTION SEEMS TO BE ONE OF THE MOST EFFECTIVE USES OF AI.
00:39:54SO, FOR EXAMPLE, DEEPFAKES OF ELON MUSK APPEAR TO BE ONE
00:39:56PARTICULARLY POPULAR WAY FOR CRIMINALS TO SCAM PEOPLE.
00:40:00ONE HEALTH CARE WORKER REPORT REPEATEDLY SAW ADS ON TIK TOK
00:40:04AND FACEBOOK SHOWING ELON MUSK PROMOTING AN INVESTMENT OPPORTUNITY.
00:40:07AND SHE LAUGHED ABOUT $10,000 IN
00:40:10THAT SCAM, WHICH WAS, OF COURSE, A DEEPFAKE OF MUSK.
00:40:14SO DECEPTION CAN BE USED NOT JUST TO SCAM INDIVIDUALS, BUT
00:40:16ENTIRE POLITIES. AND EVERY HIGH PROFILE POLICYMAKER TODAY HAS PROBABLY
00:40:21BEEN THE TARGET OF ONE OR MORE DEEP FAKES THAT ARE MEANT TO DENIGRATE THEM, MAKE THEM LOOK
00:40:25FOOLISH. AND OF COURSE, IT'S EASY TO GENERATE AND DISTRIBUTE THESE VIDEOS.
00:40:28SO ANY NATION THAT WISHES TO INFLUENCE U.S. ELECTIONS CAN USE
00:40:32A.I. TOOLS IN THEIR PROPAGANDA
00:40:34AND DISINFORMATION CAMPAIGNS FOR DEEP FAKES.
00:40:38CELEBRITIES ARE PROBABLY GOING TO BE UNAVOIDABLE BECAUSE THERE'S SO MUCH VIDEO OF THEM IN
00:40:41PUBLIC, BUT IT'S PRETTY EASY FOR MACHINE LEARNING TOOLS TO MIMIC.
00:40:45BUT EVERYDAY CITIZENS COULD BE BETTER PROTECTED FROM THOSE
00:40:48KINDS OF TOOLS THAT SPIN OUT DEEPFAKE -- OR OTHER FORMS OF
00:40:53HARASSMENT. AND MOST OF THOSE PRIVACY PROTECTIONS COULD HAVE BEEN PUT IN PLACE A LONG TIME AGO.
00:40:57BUT AT LEAST IN THE UNITED STATES, POLICYMAKERS HAVE LARGELY CHOSEN NOT TO.
00:41:00SO I JUST WANT TO CONCLUDE BY NOTING THAT WE OFTEN SORT OF
00:41:04THINK ABOUT WHAT'S THE IMPACT OF AI ON PRIVACY AND SECURITY.
00:41:07WE COULD ALSO THINK ABOUT THE
00:41:09WAYS THAT OUR POLICIES ON PRIVACY AND SECURITY HAVE SHAPED
00:41:12THE EVOLUTION OF AI SO THAT IT'S NOT A MATTER OF JUST THE IS
00:41:17INEVITABLY MOVING ALONG. AND THEN WE HAVE TO SOMEHOW FIGURE OUT HOW TO REIN IT IN OR
00:41:21RESPOND. THANK YOU. I'M GOING TO PASS IT OFF.
00:41:32I DID DRINK SOME WATER. YEAH. OTHERWISE I'LL BE UNABLE TO
00:41:36SPEAK MIDWAY THROUGH. OKAY. ALL RIGHT.
00:41:40MIGHT SOME OF THIS GIVE UP THIS
00:41:43FACADE OF WHATEVER THAT'S ABOUT? OKAY. ALL RIGHT. GRACE.
00:41:46THE TALL PERSON. YEAH. LAST YEAR. WE ARE.
00:41:50OKAY, SO LET ME FIRST START OFF
00:41:53BY SAYING HOW GRATEFUL I AM THAT I AM ABLE TO PARTICIPATE AT ALL.
00:41:56I REALLY ADMIRE ALL OF THESE SCHOLARS, AND IT'S A DELIGHT TO BE ALONGSIDE THEM.
00:42:00SPEAKING WITH YOU TODAY, I'M GOING TO ZOOM OUT AND MAYBE TALK
00:42:04AT A HIGHER LEVEL. I'M PARTICULARLY INTERESTED IN
00:42:08HOW THE STORIES WE TELL ABOUT THE HISTORY OF AI SHAPE OUR
00:42:11CONCEPTIONS OF POSSIBLE RIGHT,
00:42:13AND NOT JUST WHAT WE THINK, WHAT
00:42:15OUR OPPORTUNITIES ARE, BUT WHAT
00:42:18OUR THREATS MIGHT BE, WHAT WE NEED TO BE RESPONDING TO. RIGHT?
00:42:23SO YOU'VE SEEN ALREADY LOTS OF
00:42:27EXAMPLES OF WHERE NEW TECHNOLOGIES DON'T JUST
00:42:33CONSTRAIN OR SERVE AS A NEW TECHNOLOGY TO PRODUCE NEW
00:42:35THREATS, NEW THINGS WE NEED TO RESPOND TO. RIGHT?
00:42:38SO IF I CAN FAIRLY TAKE PHOTOGRAPHS AND PUBLISH THOSE PHOTOGRAPHS OF YOU IN A
00:42:42NEWSPAPER, SUDDENLY YOUR NOTION OF PRIVACY CHANGES, RIGHT?
00:42:46IT CEASES TO BE JUST ABOUT PHYSICAL SPACE. IT BECOMES ABOUT SOMETHING ELSE,
00:42:50RIGHT? YOU SEE IT AGAIN IN TELEPHONES, RIGHT? CHALLENGING CONCEPTIONS OF
00:42:54PRIVACY. YOU SEE IT AGAIN IN LARGE DATABASES. YOU SEE IT AGAIN IN ACTUALLY A
00:42:57HISTORY OF EDUCATION THAT OVER AND OVER AGAIN, NEW TECHNOLOGIES
00:43:03POSE NEW KINDS OF THREAT. SO THEY CHANGE WHAT IT MEANS TO
00:43:05HAVE PRIVACY. RIGHT.
00:43:10OKAY. LET ME SAY THIS.
00:43:14I THINK THAT MACHINE LEARNING AS
00:43:15A NEW KIND OF TECHNOLOGY SERVES
00:43:19AS A WAY OF BINDING IDEAS AND
00:43:21NATIONAL SECURITY AND PRIVACY
00:43:23TOGETHER, WHERE BEFORE YOU MIGHT HAVE CONSIDERED THEM IN SEPARATE SPHERES, RIGHT?
00:43:27IT SORT OF AS YOU WERE DISCUSSING NOW SUDDENLY YOU
00:43:30UNDERSTAND THEM AS THINGS THAT
00:43:31ARE IN TRACTABILITY RELATED, RIGHT?
00:43:35AND I'LL TALK A LITTLE BIT ABOUT THAT AT THE END ABOUT EXACTLY WHY THAT IS, WHY I THINK THAT'S
00:43:39THE CASE. BUT IN ORDER TO SORT OF
00:43:44UNDERSTAND HOW THAT HAPPENED HISTORICALLY, LIKE HOW WE CAME TO THINK OF NATIONAL SECURITY
00:43:47AND PRIVACY AS FUNDAMENTALLY INTERWOVEN IN THIS PARTICULAR
00:43:51SORT OF WAY IN THE PRESENT MOMENT, WE NEED TO LOOK AT HOW
00:43:53WE'RE TELLING THESE HISTORIES OF I.
00:43:57SO I WANT TO DO TWO THINGS. I WANT TO TALK ABOUT SORT OF HOW
00:44:01HISTORY, THE WAY I TALKED ABOUT PRIOR TO THE 20 TENS.
00:44:04AND THEN I WANT TO TALK ABOUT
00:44:06HOW THAT CHANGED AFTERWARDS.
00:44:08SO FIRST OF ALL, WHEN I CAME ON
00:44:11THE SCENE, I DON'T KNOW, IN 2013, I WAS USING BOOKS THAT
00:44:14WERE WRITTEN IN THE 1980S AND THE HISTORY OF I HADN'T CHANGED
00:44:18THAT MUCH UP UNTIL THAT POINT IN HISTORY.
00:44:20I WAS SOMETHING LIKE THIS.
00:44:22IF YOU'RE DOING A.I. IN THE SECOND HALF OF THE 20TH CENTURY,
00:44:26BEGINNING OF THE 21ST CENTURY, WHAT YOU'RE DOING IS
00:44:29MATHEMATICAL PROOF PROVING YOU'RE DOING A GAME, PLAYING
00:44:32LIKE CHESS. WHAT THAT MEANS IS YOU'RE
00:44:35PLAYING, YOU'RE DOING PROBLEMS FROM WHICH THERE'S WELL-DEFINED
00:44:39RULES AND WELL-DEFINED ANSWERS.
00:44:42SO THERE'S NO QUESTION WHEN YOU ARRIVE AT A CORRECT ANSWER, YOU
00:44:46KNOW WHAT IT IS. YOU KNOW, FROM THE BEGINNING WHAT THE CORRECT ANSWER IS AND
00:44:49WHAT THE MACHINE HELPS YOU DO IS ARRIVE AT THAT SOLUTION.
00:44:52WHETHER YOU'RE TRYING TO PROVE A MATH PROBLEM OR TRYING TO WIN A GAME OF CHESS.
00:44:56OKAY, THESE SORTS OF STORIES
00:44:58HAVE CENTER MADE, LEARNING AS A
00:45:01KIND OF OPTIMIZING.
00:45:03AND SO HUMANS FIGURE OUT WHAT THE OPTIONS ARE AND YOU GET THE MACHINE JUST TO OPTIMIZE.
00:45:07BUT HUMANS ARE GOOD AT DECIDING WHAT POSSIBILITIES SHOULD BE
00:45:11CONSIDERED. SO LET HUMANS DO THAT JOB. LET MACHINES OPTIMIZE, RIGHT?
00:45:15SO WE KNOW GOOD STRATEGIES WHEN WE PLAY CHESS.
00:45:19BUT HUMANS BUT MACHINES CAN
00:45:22MAYBE FIND NEW STRATEGIES BASED
00:45:24ON THE SORT OF VALUES AND IDEAS THAT WE HAVE. OKAY.
00:45:28THE PROBLEM THAT THIS NARRATIVE
00:45:30OF I HAS LEARNED HAS CREATED IS
00:45:34THAT IT'S REALLY CENTERED ON
00:45:36JUST A FEW GROUPS OF A.I. RESEARCHERS AT LIKE AT MIT, AT
00:45:42STANFORD, AT CARNEGIE MELLON. YOU KNOW, THE FIRST CONFERENCE,
00:45:45YOU KNOW, DARTMOUTH, RIGHT, IN 1956, ALWAYS GETS TALKED ABOUT
00:45:48AD NAUSEUM, EVEN THOUGH IT WASN'T EVEN AN ACTUAL CONFERENCE. PEOPLE SHOWED UP THROUGHOUT THE
00:45:52SUMMER AT DIFFERENT TIMES. NO ONE WAS EVER THERE AT THE SAME TIME, ALL TOGETHER.
00:45:56SO IT'S JUST EVEN BIZARRE THAT WE STILL TALK ABOUT IT THAT WAY.
00:45:59BUT IT'S REALLY TO REINFORCE
00:46:01THIS MODEL OF SCIENCE WHERE IF YOU WANT TO GET SOMETHING DONE,
00:46:05YOU SUPERCHARGE A FEW ELITE
00:46:08GROUPS WITH TONS OF MONEY. YOU DUMP MONEY ON THOSE GROUPS,
00:46:10AND THAT WILL THAT WILL PROGRESS YOUR SCIENCE RIGHT?
00:46:14THIS HAS GIVEN RISE TO A WHOLE BUNCH OF MYTHS.
00:46:16IF YOU BELIEVE THIS IS THE CORRECT STORY OF THE HISTORY OF
00:46:20A.I., THEN YOU REALLY FOCUS ON IN THE 1980S AND 1990S AND A
00:46:23SUDDEN UPHEAVAL. OH MY GOSH, NEURAL NETWORKS ARE
00:46:27SUDDENLY GREAT AT DOING THINGS THEY WEREN'T BEFORE, BUT WITH THE RISE OF GPUS SUDDENLY NOW
00:46:32THEY CAN ACCOMPLISH ALL THESE TASKS THAT THEY CAN NEVER DO BEFORE. AND THE PROBLEM WITH THIS
00:46:35NARRATIVE IN PART IS IT ASSUMES THAT EVERYONE WAS WORKING ON THE
00:46:39SAME PROBLEMS AND EVERYONE AGREED WHAT THOSE PROBLEMS WERE.
00:46:43AND THAT IS JUST HISTORICALLY INACCURATE. RIGHT?
00:46:46IN FACT, THERE WAS A WILD VARIETY OF BELIEFS ABOUT WHAT
00:46:50PROBLEMS WERE VALUABLE AND WHAT WERE THE PAYOFFS OF THOSE
00:46:53PROBLEMS, EVEN HOW TO SOLVE THOSE PROBLEMS.
00:46:56SO A WILD SET OF DIFFERENT IDEAS
00:47:00ABOUT WHAT WAS WORTH WORKING ON, RIGHT. AND THAT GETS COMPLETE LOST IN
00:47:03OUR SORT OF NARRATIVES ABOUT THE
00:47:05RISE OF A.I. AND WHAT'S IMPORTANT AND IT GETS LOST.
00:47:09THEN WHEN WE TALK ABOUT HOW TO
00:47:10FUND OR OR DEVELOP AI NOW,
00:47:15RIGHT? YOU SEE THESE MODELS ABOUT THE
00:47:17HISTORY OF AI BEING THE RESULT
00:47:21OF A FEW ELITE GROUPS REALLY PLAYS INTO A NOTION THAT A
00:47:25PARTICULAR SET OF COMPANIES OR A PARTICULAR SET OF RESEARCH GROUPS ARE THE ONLY PEOPLE THAT
00:47:29CAN MAKE THIS WORK RIGHT?
00:47:31SO CONTRAST THIS THEN TO A MAJOR
00:47:34SHIFT IN THE HISTORIES OF AI AND THE 20 TENS WHERE PEOPLE WERE
00:47:39TRYING TO UNDERSTAND WHERE DID MACHINE LEARNING COME FROM?
00:47:41BECAUSE IN THESE HISTORIES OF AI, MACHINE LEARNING IS ALWAYS
00:47:45DERIDED AND NOT REALLY SEEN AS SOMETHING THAT VALUABLE.
00:47:47AND ALSO IN THESE HISTORIES OF AI, MACHINE LEARNING IS OFTEN
00:47:51NARROW DOWN TO JUST A FEW THINGS. MAYBE JUST NEURAL NETWORKS AND NOTHING ELSE.
00:47:55BUT IN FACT, MACHINE LEARNING IS EXPANSIVE. THERE'S MANY DIFFERENT KINDS OF
00:47:58MACHINE LEARNING. THERE'S DECISION TREES, THERE'S
00:48:01MANY OTHER WAYS OF APPROACHING MACHINE LEARNING THAT HAVE
00:48:04NOTHING TO DO WITH NEURAL NETWORKS AND KNOWING THIS
00:48:08DIVERSITY OF DIFFERENT APPROACHES IS REALLY IMPORTANT. YOU SEE IT IN PATTERN
00:48:12RECOGNITION, FOR INSTANCE. YOU SEE IT IN ELECTRICAL ENGINEERING, YOU SEE IT IN
00:48:16STATISTIC X, YOU SEE IT IN A
00:48:19VERY CITY OF PLACES THAT ARE NOT CALLING THEMSELVES A.I.
00:48:23RESEARCHERS, RIGHT? THESE ARE NOT IDENTIFY AI RESEARCHERS.
00:48:26AND YET THESE TECHNIQUES ARE SORT OF PROVIDING THEY'RE SORT
00:48:30OF THE FOUNDATION OF WHAT WE WOULD CALL A.I. TODAY. RIGHT.
00:48:34AND SO HISTORIANS IN 2010 SAID, WHERE DO THESE TECHNIQUES COME FROM?
00:48:38HOW DID THEY SUDDENLY COME TO BE CALLED A.I. WHEN FOR SO LONG
00:48:42THEY WERE CAST OUT AND SAID, THIS IS AN AI, THIS IS EVEN WORTH WORKING ON.
00:48:46THESE KINDS OF PROBLEMS FOCUSED
00:48:46ON THINGS LIKE GENERATING NEW
00:48:51HYPOTHESES, RIGHT? THEY FOCUSED ON PROBLEMS IN
00:48:53WHICH YOU DID NOT KNOW THE RULES AND YOU DID NOT KNOW THE CORRECT ANSWERS.
00:48:57AND IN FACT, YOU DIDN'T EVEN KNOW THE SYSTEM.
00:49:00YOU WERE RADICALLY DUMB. YOU KNEW THAT YOU'RE YOU'RE SORT OF INFORMATION WAS SUPER
00:49:04LIMITED. YOU KNOW, THAT YOU DIDN'T HAVE ALL THE INFORMATION YOU NEEDED
00:49:08AND YOU STILL HAD TO MAKE A DECISION. SO THESE TECHNOLOGIES OF
00:49:10DECISION MAKING EXPLICITLY, RIGHT.
00:49:12AND SO HOW DO YOU MAKE DECISIONS
00:49:14UNDER RADICAL UNCERTAINTY? THESE WERE THE KINDS OF PROBLEMS
00:49:17THAT MACHINE LEARNING RESEARCHERS AND PATTERN RECOGNITION RESEARCHERS REALLY FOCUSED ON.
00:49:23AND DEVELOPED QUITE INDEPENDENTLY FROM ME.
00:49:25I UP UNTIL, YOU KNOW, THE 1970S,
00:49:281980S, WHEN WHEN I SORT OF REMADE ITSELF. OKAY.
00:49:34SO I WANT TO CONCLUDE HERE THEN JUST BY SAYING HOW DO THESE NEW
00:49:38HISTORIES GIVE US SOME INSIGHT INTO QUESTIONS OF PRIVACY AND
00:49:41QUESTIONS OF NATIONAL SECURITY TODAY?
00:49:44WELL, FIRST OF ALL, WE SHOULD
00:49:47RECOGNIZE THAT MACHINE LEARNING
00:49:49HAS MADE IT SO THAT RELEVANT
00:49:52INFORMATION IS ANY INFORMATION THAT CAN BE CAPTURED ABOUT YOU,
00:49:55THAT CAN BE CORRELATED WITH SOMETHING THAT'S A RADICALLY
00:49:58DIFFERENT UNDERSTANDING OF PRIVACY THAN THAN CONCEPTIONS OF
00:50:02PRIVACY BEFORE. IT DOESN'T MATTER WHAT INFORMATION I HAVE, AS LONG AS I
00:50:06HAVE ENOUGH PEOPLE TOGETHER AND
00:50:09ENOUGH DATA ABOUT THOSE PEOPLE, I CAN START TO MAKE
00:50:13CLASSIFICATION OF THOSE PEOPLE. ARE THOSE THE RIGHT CLASSIFICATIONS? ARE THEY MEANINGFUL? WHO CARES?
00:50:17THEY ALLOW ME TO MAKE PREDICTIONS.
00:50:19ARE THOSE PREDICTIONS RIGHT? WHO KNOWS?
00:50:22OUTSIDE OF THE INFRASTRUCTURE, IT'S VERY THE INFRASTRUCTURE
00:50:25ITSELF MAKES IT POSSIBLE TO SORT OF JUDGE WHETHER THESE PREDICTIONS ARE CORRECT OR NOT.
00:50:30RIGHT. SO THIS IS RADICALLY DIFFERENT.
00:50:32WHO HAS A LOT OF DATA WILL USUALLY LARGE COMPANIES. RIGHT. AND SO THIS IS WHERE ISSUES OF
00:50:36ANTITRUST MIGHT ACTUALLY BEGIN TO PLAY A ROLE IN PRIVACY AND
00:50:40KIND OF A SURPRISING WAY BECAUSE YOU WOULDN'T NECESSARILY REALLY THINK ANTITRUST WOULD PLAY A ROLE IN PRIVACY.
00:50:45WELL, HERE IT DOES. OKAY. OKAY. THE SECOND THING I WANT TO SAY
00:50:48ABOUT NATIONAL SECURITY, THEN, IF WE BELIEVE THIS STORY OF
00:50:52FUNDING A FEW GROUPS WITH BLANK
00:50:54CHECKS IS THE WAY TO GO, THEN WE
00:50:56WILL SORT OF CONSTRUCT OUR SCIENCE AND CONSTRUCT OUR
00:51:00FUNDING MODELS IN A VERY
00:51:02DIFFERENT WAY THAN WHAT SEEMS TO
00:51:05HAVE WORKED FOR MACHINE LEARNING, RIGHT? THE DEVELOPED MACHINE LEARNING
00:51:07ACTUALLY INVOLVED A WHOLE BUNCH OF DIFFERENT GROUPS TRYING A WHOLE BUNCH OF DIFFERENT THINGS THAT DID NOT DISAGREE WITH EACH
00:51:11OTHER. AND IT WAS ACTUALLY THE RANGE OF
00:51:15APPROACHES AND THE LACK OF AGREEMENT ABOUT WHAT THE RIGHT SOLUTION OR THE RIGHT QUESTION
00:51:19EVEN WAS THAT ALLOWED DIFFERENT KINDS OF MACHINE LEARNING
00:51:22APPROACHES TO BE SO SUCCESSFUL AS STRATEGIES FOR TRYING TO MAKE
00:51:27PREDICTIONS, MAKE DECISIONS ABOUT THE WORLD RIGHT? SO IF WE PAY ATTENTION TO THIS
00:51:31NEWER SET OF HISTORIES, TRYING TO UNDERSTAND WHERE MACHINE
00:51:34LEARNING CAME FROM, HOW AND WHY
00:51:37IT CAME TO BE THINKABLE, THEN
00:51:39THAT GIVES US A REALLY DIFFERENT
00:51:41POSITION WITH WHICH TO JUDGE OUR
00:51:43FUNDING MODELS FOR SCIENCE AND I
00:51:47THINK I'LL STOP RIGHT THERE.
00:51:48THANK YOU SO MUCH FOR YOUR TIME.
00:51:58GREAT. THANK YOU SO MUCH. AND SEE THIS IS TOO TALL FOR ME NOW.
00:52:02THANK YOU SO MUCH TO ALL OF OUR
00:52:06PANELISTS. AS A REMINDER, PLEASE WRITE DOWN YOUR QUESTIONS AND NO CARDS.
00:52:09YOU CAN HAND IT TO PENN OR BEN
00:52:13AND I WILL COMPILE THEM AND MAKE SURE THAT WE HAVE A VERY ROBUST
00:52:17Q&A. I WOULD LIKE TO START BY POSING
00:52:20A QUESTION TO OUR PANELISTS THAT IS STRAIGHT FROM THE CURRENT
00:52:24HEADLINES, AND THAT IS ABOUT THE
00:52:28NEGOTIATIONS THAT ARE CURRENTLY HAPPENING BETWEEN ANTHROPIC AND
00:52:31SECRETARY HEGSETH AND THAT THAT
00:52:33HAS RAISED ATTENTION TO THE
00:52:35DEFENSE PRODUCTION ACT, WHICH IS ACTUALLY A PIECE OF COLD WAR
00:52:39LEGISLATION. AND I'M WONDERING IF OUR
00:52:41PANELISTS CAN KIND OF KIND OF THINK MORE BROADLY ABOUT THIS,
00:52:45THE HISTORICAL RELATIONSHIPS BETWEEN THE DEPARTMENT OF
00:52:49DEFENSE, THE NATIONAL SECURITY STATE AND INFORMATION
00:52:52INDUSTRIES, AND HOW THAT CAN
00:52:54ILLUMINATE BOTH TENSIONS BETWEEN THE TWO ENTITIES AND POINTS OF
00:52:59COOPERATION. ANYONE CAN START.
00:53:02I'LL JUST JUMP IN BRIEFLY. SO YEAH, SO THE 1950 NATIONAL,
00:53:06THE PRODUCTION ACT WAS PASSED AT
00:53:09THE TIME OF THE KOREAN WAR,
00:53:11RIGHT WHEN THERE WAS A SENSE OF NATIONAL EMERGENCY AND THERE WAS
00:53:14A NEED TO PROVIDE SPECIAL INCENTIVES FOR THE PRIVATE
00:53:18SECTOR TO HELP THE U.S.
00:53:20GOVERNMENT FIGHT THAT WAR.
00:53:22AND IT'S BEEN INVOKED A LOT OF TIMES SINCE THEN IN DIFFERENT
00:53:26CONTEXTS. THAT WAS INVOKED DURING COVID, FOR EXAMPLE. RIGHT.
00:53:29TO ENCOURAGE COMPANIES TO REALLY
00:53:32HELP STOP A PANDEMIC.
00:53:34I THINK MOST PEOPLE WOULD AGREE THAT THE USE IN THE CURRENT
00:53:38CONTEXT IS SOMEWHAT UNUSUAL. AND THERE'S ALWAYS THE QUESTION
00:53:41OF WHAT THE EMERGENCY IS, BUT ALSO THE KIND OF THING THAT IS
00:53:45BEING ASKED OF ANTHROPIC, IF
00:53:47MAYBE A LITTLE DIFFERENT THAN, SAY, ASKING A COMPANY TO PRODUCE
00:53:50A BUNCH MORE BOMBS. BECAUSE WHAT ANTHROPIC IS SAYING
00:53:53IS WE'RE NOT SURE HOW THIS WORKS.
00:53:55WE ACTUALLY DON'T KNOW THAT YOU
00:53:58CAN TRUST ACTUALLY, WE'RE PRETTY
00:54:00SURE YOU CAN'T ENTIRELY TRUST
00:54:02THE OUTPUTS IN ANY OBVIOUS WAY.
00:54:06WE STILL NEED TO FIGURE THIS OUT
00:54:08AND WE DON'T WANT TO JUST SAY HERE, HAVE AT IT.
00:54:11DO WHAT YOU WANT WITH IT.
00:54:13AND SO I THINK THAT'S ONE OF THE
00:54:15SOURCES OF TENSION HERE, IS THAT IT'S NOT CLEAR THAT WHETHER THE
00:54:19EMERGENCY IS THE SAME AS IT HAS BEEN HISTORICALLY, AND ALSO
00:54:23WHETHER THE PRODUCT THAT IS BEING ASKED FOR IS THE SAME.
00:54:28SO IT'S I THINK THAT'S GOING TO BE ONE OF THE MAJOR ISSUES THAT'S GOING TO HAVE TO GET
00:54:31HASHED OUT.
00:54:33ANY OTHER THAT I COULD SAY, I
00:54:36THINK, YOU KNOW, THE HISTORY OF
00:54:40THE RELATIONSHIP BETWEEN
00:54:42COMMERCIAL AND GOVERNMENT. WELL, PUBLIC AND PRIVATE
00:54:47INFORMATION USE IS GOES BACK A,
00:54:50YOU KNOW, CENTURIES.
00:54:52AND THERE ARE THEY RAISE REALLY
00:54:55INTERESTING QUESTIONS BECAUSE I THINK MOST AMERICAN CITIZENS
00:54:59AREN'T AWARE OF THE POROUSNESS BETWEEN INFORMATION PUBLIC AND
00:55:03PRIVATE INFORMATION AGGREGATION AND USE.
00:55:05I MENTIONED JUST BRIEFLY IN MY
00:55:11COMMENTS, YOU KNOW, THE RISE OF
00:55:13THINGS LIKE THE TELEGRAPH
00:55:15SYSTEM, WHICH ALLOWED SUDDENLY THE GOVERNMENT TO COLLECT
00:55:20INFORMATION OR TO OBTAIN INFORMATION THAT WAS COLLECTED
00:55:22BY PRIVATE OPERATORS. AND THIS PATTERN HAS CONTINUED
00:55:28THROUGHOUT, YOU KNOW, THE DECADES SINCE.
00:55:32I'M AN OFTEN PRIVATE COMPANIES
00:55:36HAVE HAD BETTER ACCESS TO DATA
00:55:38THAN THE USUAL FEAR IN THE UNITED STATES HAS BEEN.
00:55:42THE GOVERNMENT COLLECTING AND HOUSING AND WAREHOUSING INFORMATION ABOUT THEM.
00:55:46BUT IT'S ACTUALLY TYPICALLY COMMERCIAL ENTITIES HAVE BEEN
00:55:50BETTER AT THIS OR AHEAD OF THE FEDERAL GOVERNMENT ON THIS.
00:55:53I'M REMEMBERING THAT IN THE 19TH CENTURY, FOR INSTANCE, THE OR
00:55:56LATE 19TH CENTURY CREDIT AGENCIES HAD MUCH MORE OF A
00:56:00REACH INTO PEOPLE'S PRIVATE LIVES THAN THEY DID THEN.
00:56:04THEY SENT FBI AND SO FORTH.
00:56:08SO BUT I THINK SO I THINK THIS
00:56:10QUESTION OF THE POROUSNESS IS IN THE RELATIONSHIP BETWEEN THE
00:56:15GOVERNMENT, THE FEDERAL GOVERNMENT AND PRIVATE INFORMATION BROKERS.
00:56:19AND SCRAPERS AND AGGREGATORS IS
00:56:23A REALLY IMPORTANT ONE FOR US TO GET STRAIGHT IN TERMS OF JUST
00:56:27HOW WE UNDERSTAND AND CONCEIVE
00:56:29OF THE POSSIBILITIES FOR BOTH
00:56:31OUR SECURITY AND OUR PRIVACY AND
00:56:35WELL, WE'LL CONTINUE TO COME UP AND I THINK THAT THE ANTHROPIC
00:56:37CASE IS A REALLY INTERESTING INSTANCE WHERE WE'RE SEEING THAT
00:56:41PLAY OUT AS A REAL ACTUAL STRUGGLE RATHER THAN A KIND OF
00:56:44BEHIND THE SCENES ONE, WHICH IS TYPICALLY BEEN THE CASE.
00:56:48I DON'T THINK MOST AMERICANS HAVE HAVE BEEN AS AWARE IN THE
00:56:50PAST OF THE KIND OF RELATIONSHIP
00:56:54BETWEEN THESE ENTITIES AS BEHIND THE SCENES TO SOLVE VARIOUS
00:56:57KINDS OF NATIONAL SECURITY PROBLEMS OR SO FORTH AS THEY'RE SEEING RIGHT NOW.
00:57:02EXCELLENT, GREAT. WE HAVE SOME EXCELLENT QUESTIONS.
00:57:06SO MOVING FORWARD, COULD YOU EXPLAIN THE CONDITIONS THAT
00:57:09CONTRIBUTED TO PREVIOUS AIR WINTERS AND WHAT MIGHT LOOK
00:57:13SIMILAR OR DIFFERENT TO THE
00:57:15CURRENT PERIOD OF AIR EXUBERANCE?
00:57:18SO WHAT REALLY GENERATES INVESTMENT IN OR PERHAPS
00:57:22RETRACTION FROM AN INVESTMENT IN
00:57:23NEW TECHNOLOGIES.
00:57:27YEAH, I'M I'M HAPPY I'M HAPPY TO
00:57:29SPEAK ABOUT AT LEAST ONE OF THE
00:57:32AIR WINTERS. SO WHEN I BEGAN MY TALK, I
00:57:35MENTIONED THE LOGIC THEORY MACHINE. THIS, YOU KNOW, THIS COMPUTER
00:57:39PROGRAM THAT MADE MATHEMATICAL PROOFS.
00:57:41SO THIS IS AN EXAMPLE OF THIS
00:57:44SYMBOLIC A I IT'S VERY DIFFERENT
00:57:46FROM THE DATA DRIVEN A.I., WHICH
00:57:48IS UBIQUITOUS THESE DAYS.
00:57:50WHAT SYMBOLIC A.I. DOES IS THAT
00:57:53IT JUST, YOU KNOW, IT'S A A
00:58:00ENCODES A CERTAIN OPERATIONS FOR EXAMPLE, THE SOLUTION OF A
00:58:03MATHEMATICAL PROOF, RIGHT?
00:58:04THE ALGORITHM DOESN'T WORK WITH
00:58:08DATA, DOESN'T FIND REGULARITIES IN DATA.
00:58:10IT JUST IT JUST FOLLOWS THOSE
00:58:14THE STEPS THAT WERE ALREADY INSERTED INTO THE PROGRAM.
00:58:18AND SO, OKAY, SO THE LOGIC THEORY MACHINE ESTABLISHED THIS
00:58:22ENTIRE SYMBOLIC AI APPROACH,
00:58:26WHICH WAS DOMINANT, I THINK UNTIL THE 1990S.
00:58:30ROUGHLY SPEAKING.
00:58:32IT REALLY PEAKED IN THE 1980S WITH THE DEVELOPMENT OF THE
00:58:36EXPERT SYSTEMS. SO EXPERT SYSTEMS WERE DOMAIN
00:58:41SPECIFIC AI SYSTEMS THAT THEY
00:58:41WERE CREATED FOR MEDICAL
00:58:47DIAGNOSIS FOR AIRLINE COMPANIES,
00:58:53YOU KNOW, IN ORDER TO MAKE
00:58:55DECISIONS ABOUT THIS CELLS.
00:58:57AND SO ON.
00:58:59ACTUALLY A VERY GOOD EXAMPLE, I THINK WE, ALL OF YOU, IF YOU
00:59:03FILE TAXES IN THE UNITED STATES, USE AN EXPERT SYSTEM.
00:59:06IF YOU USE TEXT FILE SOFTWARE.
00:59:12SO THIS IS AN EXAMPLE OF AN EXPERT SYSTEM.
00:59:14IT'S IT'S IN ENCODES IN THE FORM OF THE RULES.
00:59:17THE THE EXPERT'S REASONING.
00:59:20SO THE EXPERT SYSTEMS SAW THAT BOOM IN THE 1980S.
00:59:23IT TAKES QUIET A LOT OF TIME AND
00:59:27EFFORT TO DEVELOP AN EXPERT SYSTEM BECAUSE IN ORDER TO
00:59:30DEVELOP IT, YOU HAVE TO ACTUALLY
00:59:32SIT DOWN WITH A GROUP OF EXPERTS
00:59:34AND INTERVIEW THEM AND ASK THEM HOW THEY APPROACH A CERTAIN PROBLEM.
00:59:38HOW DID HOW DO THEY DECIDE IF
00:59:40YOU ARE EXEMPT FROM, YOU KNOW, A
00:59:43CERTAIN TAX CATEGORY, HOW WOULD
00:59:45YOU RECOGNIZE A CERTAIN NUMBER
00:59:47OF SYMBOLS AS A CERTAIN DISEASE AND SO ON?
00:59:51AND SO WHILE THEY WERE
00:59:53COMMERCIAL SUCCESSFUL, THEY THEY REQUIRED A LOT OF TIME AND A LOT
00:59:57OF RESOURCES.
00:59:58AND SO THAT CONTRIBUTED TO THE
01:00:03THE FIRST DAY I WINTER RIGHT THERE.
01:00:05THE DECLINE IN THE DEMAND IN THE
01:00:07EXPERT SYSTEM AND THE RISE IN URGENCY IN FINDING A DIFFERENT
01:00:11APPROACH WHICH IS A DATA DRIVEN APPROACH. YEAH.
01:00:14AND I JUST WANT TO ADD TO THAT. SO I WANT TO SAY, FIRST OF ALL,
01:00:18AIR WINTERS ARE PERSPECTIVE DEPENDENT.
01:00:22AND I CANNOT STRESS THIS ENOUGH AND IT SORT OF SPEAKS TO THE
01:00:24POINT I WAS MAKING EARLIER, THAT
01:00:27IF YOU ONLY LOOK AT A FEW ELITE
01:00:29GROUPS AND A FEW UNIVERSITIES
01:00:33FROM LIKE THE 1950S TO THE 1980S, THEY WERE FUNDED ALMOST
01:00:36ENTIRELY BY RPA AND A FEW OF THE PLACES BLANK CHECKS.
01:00:40AND SO WHEN SUDDENLY THAT MONEY WAS TAKEN AWAY, IT MUST HAVE
01:00:44REALLY FELT LIKE AN EARTHQUAKE AND THOSE THREE LABS. RIGHT.
01:00:47OR THE I'M BEING A LITTLE OVER THE TOP. BUT LIKE, YOU KNOW, IN THAT VERY
01:00:51SMALL GROUP OF RESEARCH RESEARCHERS. RIGHT. BUT IF YOU START TO LOOK AT
01:00:55OTHER PLACES WHERE MACHINE LEARNING TECHNIQUES ARE BEING DEVELOPED, FOR INSTANCE, AND
01:00:57PATTERN RECOGNITION, YOU WILL SEE THAT THERE ARE MANY, MANY
01:01:02COMPANIES, SMALL COMPANIES YOU
01:01:04DON'T HEAR ABOUT GETTING FUNDED BY THE DEPARTMENT OF DEFENSE AND
01:01:07THEIR FUNDING NEVER STOPS. RIGHT? HOW DO YOU GET SPY SATELLITES?
01:01:11RECOGNIZE TANKS OR MISSILES IN SATELLITE IMAGES?
01:01:14THESE COMPANIES JUST CONTINUE TO GET PAID FOREVER.
01:01:17THERE'S NO WINTER, SO IT REALLY
01:01:19DEPENDS ON WHERE YOU'RE LOOKING.
01:01:21YOU CAN I CAN INVENT I WINTER'S LIKE MAGIC.
01:01:24I CAN MAKE THEM DISAPPEAR LIKE MAGIC.
01:01:27IT JUST DEPENDS WHERE I LOOK. SO I THINK THAT CHANGES THE QUESTION TO BE LIKE INSTEAD OF
01:01:31TALKING ABOUT WINTER IS, IS SORT OF LIKE INEVITABLE THING THAT WE
01:01:36HAVE TO BE AFRAID OF. WE CAN RATHER SAY, WHY ARE WE
01:01:40LOOKING AT THESE PARTICULAR GROUPS?
01:01:43WHY THESE RESEARCH COMMUNITIES AND NOT OTHERS?
01:01:45AND LIKE WHAT ARE THE STAKES OF LOOKING AT THOSE GROUPS RATHER
01:01:48THAN OTHER ONES? RIGHT? SO THAT'S THAT. SO I HAVE A LOT TO SAY ABOUT
01:01:52WINTERS AND HOW I THINK THAT'S THE WRONG WAY TO GO. BUT LIKE THAT GIVES YOU SOME
01:01:55INSIGHT INTO WHY WE MIGHT WANT TO QUESTION A WINTERS.
01:01:58IT'S LIKE A FRAMING NARRATIVE. MM HMM. EXCELLENT.
01:02:02WELL, LET'S SHIFT THE FOCUS A
01:02:04LITTLE BIT TO ADDRESS THIS QUESTION ABOUT THE HISTORICAL
01:02:08CONTEXT OF AI AND THE TECHNOLOGICAL IMPACT ON THE
01:02:12WORKFORCE. SO IF WE KIND OF SHIFT TO THESE QUESTIONS A LITTLE BIT MORE
01:02:15TOWARDS LABOR WORK, WHAT ROLE
01:02:18PERHAPS DO NEW TECHNOLOGIES OR THE PRESSURES THAT THEY MIGHT
01:02:23BRING TO QUESTIONS OF LABOR AND
01:02:28WORK. I CAN JUST JUMP IN HERE.
01:02:31SO, I MEAN, WHAT WE USUALLY SEE IN FRONT OF.
01:02:34THIS IS ALSO A VERY OLD CONCERN, RIGHT, THAT TECHNOLOGY IS GOING
01:02:38TO DISPLACE WORKERS.
01:02:40AND WHAT YOU USUALLY SEE IS THAT A FEW JOBS ARE REPLACED BY
01:02:44COMPUTERS, BUT MUCH MORE. WHAT HAPPENS IS WORK CHANGES AND
01:02:48WORK GETS REORGANIZED AND PEOPLE
01:02:50LEARN NEW SKILLS AND AND ARE
01:02:53ASKED TO DO THINGS DIFFERENTLY. AND SO WE'RE SEEING A LOT OF
01:02:56THAT HAPPENING RIGHT NOW. IT'S NOT REALLY CLEAR WHERE IT'S
01:03:00GOING TO SHAKE OUT. I DO THINK THAT SOME COMPANIES ARE VERY EXCITED ABOUT THE
01:03:03POSSIBLE POSSIBILITY OF DOWNSIZING AND THIS IS SOMETHING
01:03:07THAT IS OF GREAT CONCERN. I WILL SAY I'M AN EDUCATOR, RIGHT.
01:03:11AND SO MANY OF MY STUDENTS ARE
01:03:13DEPRESSED AND NOT SURE IF AND
01:03:15UNDERSTANDABLY, LIKE REALLY
01:03:17ANXIOUS ABOUT WHAT THE CAREER
01:03:20WORLD IS GOING TO LOOK LIKE, WHAT THE JOB MARKET'S GOING TO LOOK LIKE.
01:03:24AND AND WONDERING WHETHER
01:03:26THERE'S EVEN ANY POINT IN LEARNING STUFF ANYMORE BECAUSE, HEY, I CAN DO IT.
01:03:30ALL RIGHT. AND THE ANSWER IS NO. IT TOTALLY CANNOT DO IT ALL.
01:03:34YEAH, I THIS GREAT CONVERSATION
01:03:37WITH MY STUDENTS YESTERDAY WHERE I CAME UP WITH ONE PROMPT AND
01:03:39THEN I HAD A I COME OVER THE PROMPT AND I ASKED IF THEY COULD TELL THE DIFFERENCE AND THEY ALL
01:03:43COULD TELL THE DIFFERENCE.
01:03:45I COULD NOT GET ANY MORE CONTEXT, DID NOT HAVE THE
01:03:48BROADER CONTEXT, BUT COULDN'T
01:03:50THINK ABOUT THINGS IN DIFFERENT WAYS.
01:03:53IT DIDN'T HAVE THAT ABILITY TO BRING IN NEW INSIGHTS OR
01:03:58PERSPECTIVES OR CONNECT DIFFERENT PIECES OF INFORMATION THAT HAD NOT BEEN INCLUDED
01:04:03ORIGINALLY. IT JUST AVERAGES OUT WORDS, RIGHT?
01:04:05SO WHICH CAN BE VERY USEFUL SOMETIMES.
01:04:08AND ALSO IT MADE ERRORS, DEMONSTRABLE ERRORS, WHICH
01:04:11NOBODY CAUGHT UNTIL I POINTED IT OUT ANYWAY.
01:04:15SO SO, YOU KNOW, THE ONE THING
01:04:18TO REMEMBER IS DON'T LET
01:04:20YOURSELF BE REPLACED BY EITHER. IF YOU'RE A YOUNG PERSON, DON'T
01:04:23LET YOURSELF BE REPLACED BY A.I. THAT'S WHAT I TELL MY STUDENTS, BY REFUSING TO LEARN HOW TO DO
01:04:27ANYTHING THAT I CAN'T. IN OTHER WORDS, DON'T LET A.I.
01:04:31DO ALL YOUR HOMEWORK FOR YOU BECAUSE YOU'RE ACTUALLY MISSING OUT ON SOMETHING.
01:04:35I'VE RECOMMENDED THAT EVERYBODY HERE IS IN THAT KIND OF
01:04:39SITUATION. BUT SO, YEAH, I WORK IS GOING TO CHANGE.
01:04:42IT'S ALWAYS BEEN CHANGING IN RELATION TO TECHNOLOGY, THE WAY I DO MY JOB NOW IS VERY
01:04:46DIFFERENT THAN I DID IT 20 YEARS AGO.
01:04:49EVEN, AND IT DOESN'T NECESSARILY IT CERTAINLY DOESN'T MEAN THAT
01:04:52ALL THE JOBS ARE GOING AWAY OR THAT I CAN DO THE JOB THAT YOU DO NOW. IT CAN'T.
01:04:55ONLY YOU CAN DO THAT. MM HMM. CAN I JUST JUMP IN?
01:04:59I'LL ECHO A LITTLE BIT OF WHAT REBECCA SAID.
01:05:02AND I THINK ALL OF US WHO ARE CLASSROOM TEACHERS ARE THINKING
01:05:06ABOUT THIS IN A VERY SPECIFIC WAY WITH MANY OF OUR STUDENTS
01:05:08BECAUSE IT IS AN ANXIETY THAT'S THERE IN THE CLASSROOM.
01:05:12AND WHILE I THINK IT IS REALLY
01:05:14USEFUL TO THINK ABOUT HISTORICAL MIS PREDICTIONS ON THIS SCORE.
01:05:18SO THE IDEA THAT AUTOMATION FACTORY AUTOMATION WAS GOING TO
01:05:22GIVE US FOUR DAY WORKWEEKS AND A 20 HOUR WORKWEEKS AND THINGS
01:05:25LIKE THIS AND IMAGINE AND IMAGINE THE LEISURE SOCIETY IN
01:05:29THE EARLY 20TH CENTURY AND SO FORTH.
01:05:31I DO THINK IT WOULD BE I THINK
01:05:35IT BEHOOVES US TO THINK ABOUT WHAT MIGHT BE DIFFERENT ABOUT
01:05:38GENERATIVE AI AND WHAT IT IS ABLE TO DO, DISPLACING DIFFERENT
01:05:43KINDS OF WORKERS. PERHAPS THEN EARLIER
01:05:46TECHNOLOGIES DID AND TO THINK REALLY CAREFULLY ABOUT THE
01:05:50POSSIBILITY THAT THIS MAY BE A DIFFERENT KIND OF TRANSITION
01:05:54THAT WE'RE WE'RE UP FOR AND THAT
01:05:56MAYBE OUR PAST PREDICTIONS ARE NOT GOING TO SERVE US VERY WELL
01:06:00HERE. WE'RE READING IN ONE OF MY CLASSES RIGHT NOW, WE'RE READING
01:06:04CALLED SCIENCE, TECHNOLOGY AND
01:06:06VALUES OR READING THE CHECK PLAY FROM 1921.
01:06:09I THINK IT IS THAT INVENTED THE
01:06:11TERM ROBOT AND YOU KNOW, THE
01:06:15PREDICTIONS MADE THERE, YOU KNOW, SOUND REALLY ZANY IN SOME WAYS TO US.
01:06:19BUT BUT I DO THINK BUT I DO
01:06:23THINK WE'RE POSSIBLY IN FOR MORE
01:06:25TRANSITION THAN WE HAVE.
01:06:29YOU KNOW, THEN WE MAY BE PREPARED FOR AND AND THAT NO
01:06:32MATTER WHETHER WE ARE OR NOT, THAT WE NEED TO TAKE VERY
01:06:36SERIOUSLY THE CONCERNS THAT AND
01:06:41THINK MAYBE PROACTIVELY ABOUT HOW WE'RE PREPARING PEOPLE FOR A
01:06:43POSSIBLE TRANSITION IN THAT THE
01:06:46NATURE OF WORK.
01:06:49YEAH. SO I ALSO WANT YOU TO QUICKLY
01:06:52FOLLOW UP ON THIS BECAUSE SARAH
01:06:56JUST MENTIONED, YOU KNOW, HOW DO WE PREPARE PEOPLE FOR THIS
01:07:00TRANSITION AND FOR THE CHANGES
01:07:01THAT THE A.I. BRINGS TO THE, YOU
01:07:04KNOW, WORK AND LABOR?
01:07:08SO ONE THING THAT I SEE IN MY RESEARCH IS THAT WHENEVER NEW
01:07:14TECHNOLOGY EMERGES, THERE ARE
01:07:16PEOPLE START MAKING AN ARGUMENT
01:07:19THAT, OKAY, SO TO PREPARE PEOPLE
01:07:21TO CREATE THIS TECHNOLOGY AND,
01:07:23YOU KNOW, WORK WITH THIS TECHNOLOGY, WE NEED TO USE THIS
01:07:27TECHNOLOGY IN EDUCATION.
01:07:28SO WE NEED TO WE NEED TO CHANGE
01:07:31HOW WE TRAIN PEOPLE. WE EMPLOY THIS TECHNOLOGY TO
01:07:34TRAIN THEM, HOW TO FURTHER CREATE THIS TECHNOLOGY.
01:07:38LIKE, YOU KNOW, SPEAKING ABOUT
01:07:39EDUCATIONAL COMPUTING, THAT AGE WAS DISCUSSED.
01:07:43ONE OF THE IDEAS WAS THAT IT WOULD JUST TEACH BETTER
01:07:46SCIENTISTS AND ENGINEERS THAT
01:07:48ARE REQUIRED BY THE INFORMATION SOCIETIES, RIGHT?
01:07:52THE SOCIETY. IT IS WHERE COMPUTER TECHNOLOGY
01:07:55IS UBIQUITOUS, BUT, YOU KNOW, A
01:07:57HISTORICAL ANALYSIS DEMONSTRATES
01:08:00THAT THIS IS ACTUALLY PRETTY SHORT SIGHTED. IT'S RIGHT IF WE JUST CHANGE OUR
01:08:06EDUCATION AND ACCORDING TO THIS
01:08:08SHORT TERM FORECASTS ABOUT LABOR
01:08:13AND WORKFORCE, THEN ACTUALLY WE
01:08:15ARE LEADING OUR STUDENTS INTO A
01:08:17TRAP AND WE'RE PREPARING THEM PERHAPS FOR THE NEXT 5 OR 10 YEARS.
01:08:23BUT A LONG TERM WE PUT THEM IN A
01:08:25PRETTY DISADVANTAGED POSITION.
01:08:29WELL, WELL, THAT ACTUALLY LEADS
01:08:31TO A QUESTION FOR THE AUDIENCE
01:08:35THAT ONE OF THE AUDIENCE MEMBER
01:08:37RAISED, AND THAT IS HOW MANY OF
01:08:39YOU USE AI IN YOUR WORK TO WRITE
01:08:41MEMOS OR TO DO KEY PARTS OF YOUR
01:08:46WORK. AND DID YOU LEARN IT ON THE JOB
01:08:49OR IS IT SOMETHING THAT YOU
01:08:52LEARNED ON THE JOB OR SOMETHING THAT YOU LEARNED AT LIKE DURING
01:08:57YOUR STUDIES, DURING YOUR EDUCATION ON THE JOB, LEARNING IT?
01:09:01AND DO YOU THINK THAT WAS
01:09:02IMPLEMENTED INTO CURRICULUM AND
01:09:08I THINK IS I THINK ONE OF THE INTERESTING THINGS YOU CAN'T
01:09:11REALLY AVOID HOW PART OF YOU IF
01:09:16YOU GOOGLE OR AND I THINK THAT
01:09:18SOMETIMES PEOPLE THINK THEY HAVE TO GO OVER TO CHAT T OR CLOUD OR
01:09:23WHATEVER BUT IT'S ALREADY THERE.
01:09:25IT'S IN OUR MICROSOFT THREE. MM HMM.
01:09:30SO HOW AM I? IT'S A THAT'S A REALLY EXCELLENT
01:09:32POINT ABOUT THE UBIQUITOUS OF,
01:09:35OF AI IN EDUCATIONAL TOOLS.
01:09:37AND SO IF WE THINK HISTORIC
01:09:40ACTUALLY ABOUT THIS CONCEPT, HOW
01:09:42HAVE SOME OF THESE NEW TECHNOL OLOGIES THAT WE'VE TALKED ABOUT,
01:09:45HOW HAVE THEY RESHAPED, YOU
01:09:47KNOW, PEDAGOGY AND EDUCATION?
01:09:51AND IS IT AS PERVASIVE AND QUICK
01:09:53IN TERMS OF THE SPREAD OF THAT?
01:09:55AND WHAT DOES THAT DO TO EDUCATIONAL PRACTICES
01:10:00HISTORICALLY.
01:10:04YOU KNOW, I THINK LOTS OF US
01:10:07PROBABLY HAVE SOME THOUGHTS ON THIS, BUT I'LL BEGIN BY SAYING,
01:10:11YOU KNOW, I THINK MANY OF THE
01:10:15AMBITION NEEDS OF EDUCATORS TO USE NEW TECHNOLOGIES HAVE NOT
01:10:19BORNE OUT IN THE WAY THAT WERE
01:10:24PREDICTED. I THINK PLATO IS A GOOD EXAMPLE.
01:10:26BUT, YOU KNOW, FILMSTRIPS,
01:10:29RADIO, TELEVISION, ALL OF THESE THINGS WERE GOING TO BRING, YOU
01:10:33KNOW, NEW DEMOCRATIC ACCESS,
01:10:34REPLACE HUMAN TEACHERS OR AT
01:10:37LEAST FACE TO FACE TEACHING AND INSTRUCTION IN WAYS THAT HAVE
01:10:42NOT, YOU KNOW, HAVE NEVER
01:10:45SATISFACTORILY, I WOULD ARGUE, REPLACE THE KIND OF HUMAN
01:10:48INTERACTION OF THE CLASSROOM AND MORE OF EDUCATION. BUT THERE'S THIS OTHER ISSUE
01:10:51THAT I THINK WE'RE FACING NOW.
01:10:53WHILE SOME OF THESE PEDAGOGICAL
01:10:57OR TECHNOLOGICAL TOOLS IN PEDAGOGY FOR INSTANCE, WERE HAVE
01:11:01BEEN TRIED IN THE PAST, WHAT WE'RE SEEING NOW WITHOUT A LOT
01:11:04OF DEBATE OR A LOT OF PUBLIC
01:11:06KNOWLEDGE, EVEN, IS THE BUYING
01:11:11UP BY WHOLE SCHOOL DISTRICTS AND THINGS LIKE THAT OF COURSEWARE
01:11:15THAT ARE INFRASTRUCTURAL IN A
01:11:18NEW WAY IN OUR SYSTEM.
01:11:21SO IT MEANS THAT STUDENTS ARE,
01:11:24WHETHER THEY WANT TO OR NOT, BOTH BEING KIND OF SOLICITED
01:11:28INTO A WHOLE, YOU KNOW, PRIVATE
01:11:30COMMERCIAL SYSTEM OF COURSEWARE
01:11:34OR OF DATA TRACKING THE IN WAYS
01:11:37THAT ARE NEW AND MORE
01:11:39UBIQUITOUS, WHICH I THINK, YOU KNOW, DOES POSE CERTAIN KINDS OF
01:11:43PROBLEMS. IF YOU THINK ABOUT WHETHER IT'S
01:11:45A DISCIPLINARY OR RECORDKEEPING,
01:11:50ACADEMIC CREDENTIAL KEEPING OR
01:11:52THOSE KINDS OF SYSTEMS THAT ARE.
01:11:57SUSCEPTIBLE TO OTHER USES, I GUESS IS THE EASIEST WAY TO SAY IT.
01:12:01YOU KNOW, ONE OF THE ONGOING PROBLEMS WITH NEW DATABASE
01:12:05TECHNOLOGIES ARE THEY'RE CREATED FOR ONE REASON AND THEN CAN BE
01:12:08USED OR INFILTRATED OR, YOU KNOW, INTERCEPTED FOR OTHER
01:12:11PURPOSES, CONSCRIPTED INTO OTHER PURPOSES. AND I THINK SO I THINK THERE ARE
01:12:15A NUMBER OF DIFFERENT KINDS OF
01:12:16ISSUES RELATED TO TECHNOLOGIES
01:12:19AND PEDAGOGY IN THE CLASSROOM.
01:12:21SO, YEAH, THE FIRST BEING THE
01:12:25FIRST BEING THIS PROBLEM OF
01:12:28TECHNOLOGIES OVERPROMISING, THE SECOND BEING NEW SYSTEMS THAT ARE POSSIBLY PRIVACY,
01:12:34COMPROMISING. AND THEN THERE'S THE NEW ONE, WHICH IS MAYBE CERTAIN KINDS OF
01:12:37TECHNOLOGIES ARE REPLACING THE KIND OF COGNITIVE WORK THAT WE
01:12:41ASSOCIATE WITH, SAY, A LIBERAL
01:12:43ARTS EDUCATION. RIGHT? READING, WRITING, CRITICAL
01:12:47THINKING, BEING OUTSOURCED TO TECHNOLOGIES.
01:12:49AND THAT THAT IS RELATIVELY NEW,
01:12:51I WOULD SAY, IN THIS HISTORY AND IS THE ONE THAT'S GIVING
01:12:55CLASSROOM EDUCATORS ON THE FRONT LINES. YOU KNOW, THE MOST PAUSE BECAUSE
01:12:58IT SEEMS LIKE A LOT OF THE WORK
01:13:01THAT USED TO HAPPEN AND WAS VALUED IN CLASSROOMS MIGHT BE
01:13:06SIMILAR TO OUTSOURCED TO OTHER
01:13:08OTHER COMMERCIAL PRODUCTS.
01:13:10SO I DO THINK THERE'S A LOT OF
01:13:13GOOD WORK GOING ON RIGHT NOW. I THINK THIS TOOK A LOT OF
01:13:16EDUCATORS BY SURPRISE AND WE'RE NOT PREPARED FOR THIS.
01:13:19I WAS WORKING ON A CURRICULUM REFORM PROJECT THE MOMENT THAT
01:13:23CHATBOT ARRIVED, AND IT REALLY UPENDED US FOR A LITTLE WHILE.
01:13:27BUT BUT I DO THINK COLLEGE
01:13:30FACULTY, K-THROUGH-12 EDUCATORS,
01:13:33ARE STARTING TO REALIZE AND THINK THROUGH THE IMPLICATIONS.
01:13:36AND COMING UP WITH ALL KINDS OF NEW EXPERIMENTS, WHICH SUGGESTS
01:13:39THAT, YOU KNOW, CREATIVITY IS ALWAYS SOMETHING THAT CANNOT BE
01:13:41UNDERESTIMATED, WHETHER IT'S IN TERMS OF THINKING ABOUT
01:13:44WORKFORCE IMPLICATIONS OR PEDAGOGY OR TEACHING.
01:13:49SO I'LL STOP THERE. CAN I JUST JUMP IN REALLY QUICK?
01:13:52SO YOU AGREE WITH ALL OF THAT? I JUST WANTED TO ADD TWO MORE COMMENTS.
01:13:56AND ONE IS JUST IT NOT ONLY ARE PEOPLE TRYING TO OUTSOURCE IT,
01:13:59BUT THEY ACTUALLY CAN'T WRITE. AND I THINK THIS IS SOMETHING THAT UNTIL YOU'VE DONE RESEARCH,
01:14:03YOU DON'T ACTUALLY UNDERSTAND, STUDENTS THINK OTHERS JUST FACTS IN THE WORLD.
01:14:06AND THEY NEED TO LEARN THEM, BUT THEY DON'T NEED TO LEARN THEM ANYMORE BECAUSE THEY KNOWS THEM ALL.
01:14:09YEAH, I NEVER PRODUCES ANY NEW KNOWLEDGE. IT CAN'T TELL YOU ANYTHING THAT
01:14:13SOMEBODY HASN'T ALREADY SAID ON THE INTERNET. A LOT OF THAT STUFF WRONG. AND THEN IT KIND OF AVERAGES OUT
01:14:17INTO SOMETHING THAT'S KIND OF GENERIC AND NOT THAT INTERESTING ACTUALLY.
01:14:21BUT THE OTHER JUST COMMENT IN TERMS OF LIKE STRUCTURALLY WHAT'S HAPPENING AND THINKING
01:14:25ABOUT THIS HISTORICALLY,
01:14:27STUDENTS ARE ALSO TARGETS FOR
01:14:29COMPANIES AND HAVE ALWAYS BEEN RIGHT.
01:14:32SO WHY DOES APPLE AND WHY DID
01:14:34APPLE AND MICROSOFT EARLY ON
01:14:36MAKE ALL THESE DONATIONS TO SCHOOLS VERY CHARITABLY, VERY
01:14:40GENEROUSLY. THEY'RE TRYING TO CAPTURE A MARKET.
01:14:42AND THAT'S EXACTLY WHAT I SEE HAPPENING WITH A.I. RIGHT NOW.
01:14:46THEY'RE PUSHING IT OUT INTO UNIVERSITIES BECAUSE THEN THEY THINK THEY'RE GOING TO CAPTURE A
01:14:49BUNCH OF THE NEXT GENERATION OF WORKERS, RIGHT?
01:14:53WE'RE GOING TO BE DEPENDENT ON THEIR TOOLS AND WE'LL DEMAND
01:14:56THEM AND NEED THEM AND RELY ON THEM IN THE SAME WAY THAT PEOPLE
01:15:00LEARN TO CERTAIN OPERATING SYSTEMS.
01:15:01SO THAT'S THE CYNICAL. NOPE, SORRY.
01:15:05IT'S NOT JUST THAT. I MEAN, I'M NOT SAYING THESE THINGS CAN'T ACTUALLY HELP US DO
01:15:08THINGS THAT HAVEN'T BEEN DONE BEFORE. AND YES, I USE A.I. ALL THE TIME TO HELP ME, LIKE SEARCH THROUGH
01:15:12THE INTERNET FASTER. BUT YOU REALLY GOT TO CHECK IT
01:15:16AND IT DOES NOT TELL YOU ANYTHING THAT SOMEBODY HASN'T ALREADY SAID.
01:15:19AND THAT MIGHT BE WRONG ANYWAY. YOU MIGHT JUMP IN HERE IF NOT YOU.
01:15:22SO I AGREE WITH EVERYTHING, BOTH
01:15:25THERE AND IF I COULD JUST SAID ABSOLUTELY 100%.
01:15:28I JUST WANT TO EMPHASIZE AND THIS SORT OF RELATES TO BOTH
01:15:31LABOR AND EDUCATION WITH WITH THESE DIFFERENT FORMS OF MACHINE
01:15:35LEARNING. SUDDENLY YOU'RE ABLE TO BE
01:15:37TRACKED IN DIFFERENT WAYS, IN
01:15:39WAYS THAT ARE NOT CAUSAL.
01:15:42AND WHAT THAT MEANS IS YOU'RE BEING CLASSIFIED IN WAYS THAT
01:15:45YOU PROBABLY DON'T REALIZE, FOR INSTANCE, AND THAT HAS REAL
01:15:48WORLD CONSEQUENCES, DESPITE YOUR NOT REALIZING IT, RIGHT? SO, FOR INSTANCE, I USE
01:15:54MICROSOFT OFFICE, RIGHT? BECAUSE THAT'S I MEAN, I USE OUTLOOK, RIGHT? BECAUSE THAT'S WHAT MY SCHOOL USES.
01:15:58WELL, YOU KNOW, THERE'S RECORDS
01:16:00OF ME SENDING EMAILS TO EVERYONE. HOW PRODUCTIVE AM I BEING?
01:16:04I ONLY SENT LIKE 20 EMAILS THIS WEEK. I DIDN'T I SENT A JILLION.
01:16:08AND IT'S SAD, BUT BUT BUT I ONLY SENT 20 EMAILS THIS WEEK.
01:16:11I MUST BE SUPER UNPRODUCTIVE. WHERE THE NEXT WEEK WHEN I SEND 150 EMAILS.
01:16:15OH MY GOSH, THEN I MUST BE SUPER PRODUCTIVE. RIGHT?
01:16:18IT CREATES THESE WAYS OF TRACKING PEOPLE THAT MAY OR MAY
01:16:21NOT ALIGN WITH REAL WORLD OR
01:16:25REAL WORLD RESULTS. RIGHT? THAT'S THE FIRST THING. AND IT RELATES TO QUESTIONS OF
01:16:29EDUCATION AS A SERVICE, AS MENTIONED EARLIER. RIGHT.
01:16:32IT'S NOW IS NOW THE CASE IN IN A NUMBER OF SCHOOLS WHERE
01:16:36ELEMENTARY STUDENTS WHO USE
01:16:39THEIR LAPTOPS, EVERYTHING THEY TYPE IN THEIR LAPTOP IS BEING
01:16:43TRACKED. AND IF LIKE THE RIGHT COMBINATION OF WORDS, VARIOUS
01:16:45STATISTICAL THINGS COME TO COME TO PASS ACCORDING TO THIRD PARTY COMPANIES.
01:16:49AND YOU GET IDENTIFIED AS A POTENTIAL SUICIDE RISK OR
01:16:53SUICIDAL IDEATION, THEN LIKE
01:16:55PLEASE SHOW UP AT YOUR DOOR. AND THIS IS THIS IS NOT IN THE
01:16:59FUTURE. THIS IS ALREADY HAPPENING RIGHT. THIS IS HAPPENING.
01:17:02ELEMENTARY SCHOOLS RIGHT NOW. THESE ARE NEW WAYS OF OBSERVING
01:17:07STUDENTS THAT WERE NEVER BEFORE POSSIBLE. RIGHT. PEOPLE HAVE DIFFERENT RESPONSES.
01:17:09WHEN PLEASE SHOW UP AT YOUR DOOR. RIGHT. DIFFERENT POPULATIONS RESPOND
01:17:13DIFFERENTLY. RIGHT? TO SAY THE LEAST.
01:17:18SO AND SCHOOL ADMINISTRATORS LOVE THIS BECAUSE THEY'RE LIKE
01:17:21MY ONLY MY ONLY GOAL IS TO KEEP MY STUDENTS SAFE AND NOTHING
01:17:25ELSE MATTERS RIGHT. BUT THERE ARE REAL QUESTIONS
01:17:29ABOUT PRIVACY AND ABOUT
01:17:31EXECUTION HERE RIGHT. THAT WE'RE OFTEN NOT HAVING
01:17:35BECAUSE THEY'RE OFTEN BEING OUTSOURCED TO THIRD PARTIES WITH
01:17:40LITTLE OR NO DISCUSSION. THIS THIRD PARTIES, BY THE WAY,
01:17:43LIKE HAVE ACCESS TO THAT DATA.
01:17:46AND IN MANY CASES, THAT THE CONTRACTS THAT THEY'RE SIGNING
01:17:49ALLOW THEM TO DO WHATEVER THEY WANT WITH THAT DATA.
01:17:52YOU KNOW, TEXT DATA LIKE THE INFORMATION YOU HAVE, THE CHAT
01:17:56BOT ABOUT HOW YOU'RE FEELING IS NOT PROTECTED INFORMATION
01:18:01ACCORDING TO THE LAW. IT IS NOT THE SAME THING AS TALKING TO A THERAPIST NOT
01:18:05PROTECTED AT ALL. SO THESE ARE JUST SOME THINGS THAT ARE SORT OF LIKE COMING OFF
01:18:08OF BOTH OF WHAT YOU WERE SAYING, THAT IT REALLY CHANGES WHAT CAN
01:18:12BE OBSERVED IN THE KINDS OF CLAIMS PEOPLE ARE WILLING TO MAKE.
01:18:16SO WELL, THAT ACTUALLY LEADS TO OUR NEXT QUESTION, WHICH IS TO
01:18:19KIND OF ZOOM OUT AND THINK MORE
01:18:23GLOBALLY AND AND TO THINK ABOUT
01:18:25HOW YOU WOULD DISCUSS EUROPE AND
01:18:29OTHER COUNTRIES APPROACHES TO
01:18:33PRIVACY AND AI, HOW THAT DIFFERS
01:18:36FROM OR PERHAPS SHAPES THE US
01:18:40POLICY AND APPROACH.
01:18:44I'LL JUST SAY SOMETHING REALLY QUICKLY WHICH IS THAT THE U.S.
01:18:46AND EUROPE WERE MUCH MORE SIMILAR LOOKING BACK SOME
01:18:51DECADES IN THEIR APPROACH TO
01:18:54COMPUTERIZATION AND THE
01:18:56POTENTIAL ISSUES THAT COMPUTER
01:18:58NETWORKS AND DATABASES,
01:19:00INFORMATION SHARING POSED. AND THERE WERE A WHOLE SERIES OF
01:19:04INTERNATIONAL CONFERENCES IN THE
01:19:06EARLY 70S WHERE THERE WAS A KIND
01:19:08OF CONCORDANCE, I WOULD SAY,
01:19:11BETWEEN U.S. AND EUROPEAN
01:19:13APPROACHES TO DATA SECURITY THAT
01:19:15EMERGED AND THE U.S. WAS A REAL LEADER HERE IN CREATING FAIR
01:19:19INFORMATION PRACTICES WHICH GOT ADOPTED IN LOTS OF DIFFERENT PLACES.
01:19:22SINCE THEN, THE UNITED STATES AND EUROPE HAVE DIVERGED IN SOME
01:19:25IMPORTANT WAYS, SOME SCHOLARS
01:19:29HAVE TALKED ABOUT THIS AS A DIFFERENCE IN EUROPEAN LAW
01:19:33AROUND PROTECTING THE DIGNITY OF
01:19:36THE INDIVIDUAL VERSUS A U.S. APPROACH, WHICH IS MUCH MORE
01:19:38ABOUT PROTECTING INDIVIDUAL RIGHTS AND HAVE SO PRIVACY LAWS
01:19:42HAVE EMERGED AS A KIND OF PATCHWORK IN DIFFERENT SECTORS
01:19:46OF THE SOCIETY RATHER THAN A KIND OF UNIFIED APPROACH.
01:19:50AND YOU SEE THIS IN THE CONTRAST
01:19:52BETWEEN THINGS LIKE THE GDPR,
01:19:54THE KIND OF PRIVACY PROTECTION KIND OF UMBRELLA IN EUROPE
01:19:58VERSUS THE US APPROACH, WHICH KIND OF REGULATES PRIVACY
01:20:01DIFFERENTLY IN PLACES LIKE VIDEO RENTALS AND HEALTH PRIVACY AND
01:20:05SO FORTH, WITHOUT A KIND OF
01:20:07UNIFIED APPROACH. YEAH, I'LL JUST ADD TO THAT.
01:20:13SO. CERTAINLY, YOU KNOW, BUILDING ON
01:20:16WHAT SARAH SAID, THERE WAS A
01:20:18PERIOD OF DISCUSSIONS LARGELY
01:20:22BECAUSE OF CONCERNS ABOUT WHAT
01:20:26U.S. COMPANIES WERE DOING WITH DATA FROM AROUND THE WORLD. RIGHT.
01:20:30SO THE U.S. EMERGED AS AN EARLY LEADER IN THE TECH SECTOR.
01:20:34AND THESE COMPANIES WERE GATHERING DATA FROM OTHER
01:20:38COUNTRIES, TAKING IT TO U.S.,
01:20:40PROCESSING IT, PROVIDING INFORMATION SERVICES, WHICH IS A
01:20:43VERY LUCRATIVE INDUSTRY. AND IT WAS VERY THAT WHOLE
01:20:46CONVERSATION ABOUT PRIVACY IN THE 1970S WAS VERY TANGLED UP ALSO WITH SORT OF ECONOMIC
01:20:50PROTECTIONISM AND SOME OF THESE COMPANIES SAYING, WELL, WE DON'T
01:20:53LIKE THE FACT THAT YOUR IBM WAS
01:20:57NOT ONE OF THE BIG ONES AT THE TIME.
01:20:58IF BASIC COLONIZING ARE, YOU
01:21:01KNOW, DATA AND WE WANT OUR COMPANIES TO BE ABLE TO COMPETE AS WELL.
01:21:04SO THOSE TENSIONS WERE ALWAYS THERE BETWEEN EUROPE AND THE
01:21:08UNITED STATES, EVEN IN THE 1970S, DISCUSSIONS VERY
01:21:11EXPLICITLY AND THERE WAS ALSO SOME TALK OF THE DIFFERENT
01:21:15HISTORIES THAT THE UNITED STATES AND EUROPE HAD HAD IN THE 1970S,
01:21:18THAT EUROPE WAS NOT THAT FAR FROM WORLD WAR TWO AND FROM THE
01:21:22KINDS OF SURVEILLANCE THAT LED TO THE HOLOCAUST.
01:21:24AND, YOU KNOW, MAJOR HUMAN RIGHTS ISSUES IN EUROPE AT THE
01:21:29TIME. AND SO THAT HISTORY, WHICH IS
01:21:32SOMETHING THAT U.S. CITIZENS THERE'S CERTAINLY A HISTORY OF
01:21:36SURVEILLANCE IN THE UNITED STATES AS WELL. BUT IT DIDN'T GO QUITE THAT
01:21:40DIRECTION. AND SO WHEN A DIFFERENT
01:21:42DIRECTIONS AS AS A RESULT OF THAT, THOUGH THOSE DIFFERENT HISTORIES.
01:21:46RIGHT. AND THOSE DIFFERENT CULTURAL MEMORIES, I THINK ALSO SHAPED
01:21:49THE WAYS THAT THOSE TWO POLITIES HAVE.
01:21:53AND OF COURSE, IN EUROPE IT'S BEEN TWO POLITIES. IT'S MANY POLITIES, RIGHT IN
01:21:56DIFFERENT REGIONS.
01:21:58BUT EUROPE HAS CONSIST CERTAINLY
01:22:01I THINK, BEEN MORE IN FAVOR OF
01:22:03HAVING OVERSIGHT THAN THE U.S.
01:22:06AND SO ONE OF THE ISSUES THAT HAPPENED EARLY ON WHEN THERE WAS
01:22:09AN AGREEMENT ON TRANSPORT OR DATA FLOWS WAS THAT ALL THE
01:22:12COUNTRIES AGREED THAT THEY WOULD HAVE FEDERAL AGENCIES TO OVERSEE
01:22:16PRIVACY. AND MOST EUROPEAN COUNTRIES CREATED ONE.
01:22:18BUT AS I MENTIONED, THE U.S. DID NOT CREATE ONE.
01:22:21THEY SAID, WELL, YOU KNOW, WE'LL HAVE OMB DO A LITTLE BIT OF THAT
01:22:25AND THIS AGENCY DO A LITTLE BIT. AND NONE OF THOSE AGENCIES WERE REALLY INVESTED IN PRIVACY.
01:22:29THEY HAVE ALL THIS OTHER STUFF. AND OH, YEAH, I'D ADD PRIVACY TO
01:22:31THE LIST, BUT THAT'S JUST ONE OF THE THINGS THEY MIGHT THINK
01:22:35ABOUT OR MIGHT NOT. SO IT REALLY WAS A VERY DIFFERENT APPROACH.
01:22:39YEAH, I THINK IT COULD SAY
01:22:42SOMETHING ABOUT MAYBE US AND
01:22:44OTHER COUNTRIES IN TERMS OF
01:22:48SECURITY RATHER THAN PRIVACY.
01:22:50SO THE UNITED STATES IN THE MID
01:22:5320TH CENTURY EMERGED AS A LEADER
01:22:55IN THE MANUFACTURE OF COMPUTER
01:22:58TECHNOLOGY, POWER WHO COMPUTER
01:23:00TECHNOLOGY THAT CAN WORK WITH
01:23:04LARGE AMOUNTS OF DATA PROCESS
01:23:06THAT DATA PARTIALLY SO THE
01:23:10UNITED STATES BECAME THE LEADER
01:23:12BECAUSE BECAUSE OF THAT, A MUCH
01:23:14MORE POROUS BOUNDARY BETWEEN THE
01:23:19MILITARY DEFENSE SECTOR AND THE PRIVATE SECTOR.
01:23:21AND SO NATURALLY FOR OTHER
01:23:24COUNTRIES DURING THE MID 20TH
01:23:25CENTURY WERE KEEN ON ACQUIRING
01:23:28SOME OF THAT POWERFUL TECHNOLOGY IN ONE OF THE COUNTRIES THAT WAS
01:23:31KEEN ON ACQUIRING THAT TECHNOLOGY WAS THE SOVIET UNION.
01:23:34ACTUALLY, AND GENERALLY THE SOVIET BLOC.
01:23:37AND AND YOU SEE TECH COMPANIES
01:23:43SAW THE SOVIET UNION AND THEY
01:23:45GENERALLY THE SOCIALIST BLOC AS
01:23:48A MARKET FOR THAT DATA PROCESSING TECHNOLOGY AND
01:23:54INTEREST ONLY IN THE IN THE 70S
01:23:56THERE WAS THE WHOLE DEBATE IN THE UNITED STATES ABOUT WHETHER
01:23:59THESE COMPANIES NEED TO BE ALLOWED TO SELL THAT DATA
01:24:04PROCESSING COMPUTER TECHNOLOGY TO OTHER COUNTRIES. AND TO WHAT EXTENT AND OF COURSE
01:24:08THE COMPANIES WERE WILLING TO SELL ON THE NOT THE STATE OF THE
01:24:12ART TECHNOLOGY, BUT SOMETHING A LITTLE BIT OUTDATED.
01:24:15BUT NONETHELESS, STILL, YOU KNOW, TO WHAT EXTENT DOES THE
01:24:18THIS TECHNOLOGY TRANSFER POSE A SECURITY RISK TO THE UNITED
01:24:23STATES? GREAT. ALL RIGHT. THE FINAL QUESTION I HAVE BEFORE
01:24:26WE'RE ABOUT OUT OF TIME IS JUST TO THINK ABOUT AGAINST A CURRENT
01:24:30DEBATE THAT'S HAPPENING AROUND INTELLECTUAL AND ARTISTIC
01:24:35PROPERTY RIGHTS BY AND THEIR
01:24:39USAGE BY LATINS. AND HOW DOES THIS FIT INTO THE
01:24:43LARGER HISTORY OF COMPUTING AND
01:24:45PRIVACY RIGHTS AND.
01:24:50ANY THOUGHTS.
01:24:54I MEAN, I HAVE THOUGHTS.
01:24:57I, I DON'T KNOW IF I'M THE BEST HOST ON THIS ONE, ALTHOUGH I
01:25:00HAVE A WHOLE SERIES OF NOTICES,
01:25:04LEGAL NOTICES FROM ANTHROPIC,
01:25:05TELLING ME OR, YOU KNOW, THE
01:25:08COURT RULING AROUND GETTING MY, YOU KNOW, ROYALTIES OR WHAT HAVE
01:25:11YOU FROM THAT THAT I HAVEN'T DEALT WITH YET.
01:25:14SO I THINK, UM, I MEAN, I DO
01:25:18THINK THIS QUESTION ABOUT ARTISTIC PROPERTY, CREATIVE
01:25:22PURSUIT IS GETTING IS HAVING A REALLY INTERESTING THING LEADING
01:25:26TO A VERY INTERESTING DISCUSSION
01:25:27RIGHT NOW ABOUT WHAT HUMANS CAN
01:25:33DO THAT TECHNOLOGIES CANNOT OR
01:25:36AT LEAST CURRENTLY CANNOT. BUT I THINK I'M PROBABLY LIKE A
01:25:40LITTLE BIT LESS SURE THAT WE
01:25:43WON'T GET TO A POINT WHERE GENERATIVE A.I. IS MUCH, MUCH
01:25:48BETTER THAN IT IS NOW AND AND
01:25:50MUCH MORE QUICKLY THAN WE EXPECT. I THINK THAT'S ALREADY WHERE GPT
01:25:54AND ITS VARIOUS SUCCESSORS HAVE
01:25:57HAVE TAUGHT ME ANYWAY.
01:25:59AND WHEN I SEE WHAT MY STUDENTS ARE ABLE TO DO WITH THIS
01:26:03TECHNOLOGY. BUT I, I THINK, YOU KNOW, WE
01:26:05HAVE OLD AGAIN, WE HAVE OLD LAWS
01:26:09AND OLD METAPHORS AND OLD NARRATIVES. TO AARON'S POINT ABOUT HOW WE
01:26:13PROTECT SOMETHING LIKE CREATIVE PROPERTY OR INTELLECTUAL
01:26:17PROPERTY, I'M GOING TO GO BACK
01:26:19TO WARREN AND BRANDEIS FOR A MOMENT. THERE.
01:26:23SOME OF THE RESOURCES THEY HAD FOR THINKING ABOUT REPUTATION AS
01:26:27PROPERTY OR IMAGE AS PROPERTY
01:26:31CAME FROM THE LAW OF COPYRIGHT. INTERESTINGLY, THAT WAS WHERE
01:26:34THEY LOOKED TO TRY TO FIND THIS NEW DEFINITION OF PRIVACY. IT WAS ONE OF THE PLACES THEY
01:26:39LOOKED AND IT'S HARD TO IT'S
01:26:43HARD FOR ME TO BELIEVE THAT THE
01:26:4719TH CENTURY SORT OF ORIGINS OF ART, INTELLECTUAL PROPERTY LAW
01:26:49ARE GOING TO BE ENOUGH TO DEAL
01:26:56WITH THIS NEW KIND OF ABILITY TO
01:27:00SCRAPE UP, GOBBLE UP ALL OF THIS
01:27:04HUMAN CREATIVITY AND CREATE NEW THINGS MUCH MORE QUICKLY THAN A
01:27:07HUMAN EVER COULD. I JUST DON'T THINK OUR EXISTING
01:27:10REGULATIONS, OUR EXISTING DEBATE IS ROBUST ENOUGH TO HANDLE THE
01:27:16COMING DILEMMAS AROUND THIS AND
01:27:19MAYBE OWNERSHIP IS A REALLY IMPOVERISHED WAY TO THINK ABOUT
01:27:22SOME OF THIS TOO. MAYBE OWNERSHIP AND INDIVIDUAL
01:27:25OWNERSHIP OF CREATIVE PROCESS IS NOT GOING TO SERVE US WELL IN
01:27:29WHATEVER IS COMING NEXT. EXCELLENT.
01:27:33WELL, WE ARE OUT OF TIME, SO
01:27:35THANK YOU, EVERYONE, FOR YOUR
01:27:38THOUGHTFUL QUESTIONS. AND UNFORTUNATELY, WE HAVE TO
01:27:41BRING THIS TO A CLOSE. AND I APOLOGIZE IF WE DIDN'T GET
01:27:45TO YOUR QUESTIONS, BUT I'M SURE YOUR PANELISTS WILL BE HAPPY TO
01:27:49SPEAK WITH YOU AFTER WE CLOSE THE SESSION.
01:27:51I WANT TO ENCOURAGE ALL OF YOU TO STOP BY THE TABLES OUTSIDE OF
01:27:55THE ROOM, PICK UP ONE OF THE HANDOUTS FROM TODAY.
01:27:57THERE ARE SOME KEY TAKEAWAYS, SOME EXCELLENT IMAGES THAT WILL
01:28:01HELP YOU KEEP THINKING THROUGH THE LESSONS AND THE
01:28:05RAMIFICATIONS OF THINKING HISTORICALLY ABOUT THIS TOPIC. AND YOU CAN ALSO PICK UP MORE
01:28:10INFORMATION ABOUT THE AMERICAN HISTORICAL ASSOCIATION AND ITS WORK.
01:28:14WE HOPE TO SEE YOU AT FUTURE CONGRESSIONAL BRIEFINGS HOSTED
01:28:17BY THE A-J. AND THANK YOU AGAIN FOR JOINING US HERE TODAY.
01:28:21AND PLEASE JOIN ME IN CONCLUDING
01:28:23BY THANKING OUR PANELISTS.
01:28:37YOU'RE WATCHING C SPAN THREE
01:28:39DEMOCRACY UNFILTERED.
01:28:44C-SPAN BRINGS YOU DEMOCRACY
01:28:47UNFILTERED IN REAL TIME. DEMOCRACY DOESN'T TAKE SIDES.
01:28:51NEITHER DOES C-SPAN. IN A WORLD FULL OF OPINIONS,
01:28:54C-SPAN GIVES YOU DIRECT ACCESS TO THE PEOPLE AND INSTITUTIONS
01:28:57THAT SHAPE OUR NATION. UNFILTERED COVERAGE OF CONGRESS
01:29:01AS LAWS ARE DEBATED AND DECIDED LIVE PROCEEDINGS FROM THE UNITED
01:29:04STATES SUPREME COURT. PRESIDENTIAL SPEECHES, BRIEFINGS
01:29:08IN HISTORIC MOMENTS AS THEY HAPPEN.
01:29:10NO COMMENTARY, NO SPIN, NO AGENDA.
01:29:14JUST THE DEMOCRATIC PROCESS PRESENTED IN FULL WITHOUT
01:29:19INTERRUPTION. SO YOU CAN WATCH THE DEBATES,
01:29:21HEAR EVERY WORD, AND MAKE UP YOUR OWN MIND.
01:29:23C-SPAN IS RESPECTED.
01:29:25NONPROFIT SERVICE HAS OFFERED
01:29:28AMERICANS UNFILTERED GAVEL TO GAVEL COVERAGE OF THEIR
01:29:30GOVERNMENT IN ACTION.
01:29:32C-SPAN BRINGING YOU DEMOCRACY
01:29:36UNFILTERED. C-SPAN IS BROUGHT TO YOU BY THE CABLE, SATELLITE AND STREAMING
01:29:40COMPANIES THAT PROVIDE C-SPAN AS A PUBLIC SERVICE.
01:29:43ON THURSDAY, NASA ASTRONAUTS
01:29:46JESSICA MEIR AND ANEEL MENEN STEP OUTSIDE THE INTERNATIONAL
01:29:50SPACE STATION FOR A CRITICAL SPACEWALK TO PREPARE THE STATION
01:29:54FOR THE INSTALLATION OF ITS SEVENTH ROLL OUT SOLAR ARRAY.
01:29:57THE NEW HARDWARE WILL INCREASE THE STATION'S POWER CAPACITY AND
01:30:02SUPPORT FUTURE SCIENTIFIC MISSIONS AND HELP ENSURE THE
01:30:04SAFE OPERATION OF THE ORBITING LABORATORY FOR YEARS TO COME.
01:30:08WATCH OUR LIVE COVERAGE STARTING AT 8 A.M. EASTERN ON C-SPAN THREE.
01:30:14C-SPAN NOW OUR FREE MOBILE APP
01:30:16AND ONLINE AT C-SPAN DOT ORG.
01:30:23DISCOVER AMERICA'S STORY WITH C-SPAN'S NEW AMERICAN HISTORY
01:30:26TIMELINE POSTER. THIS LARGE 4.5FT WIDE POSTER
01:30:30EXPLORES THE LIVES AND PUBLIC
01:30:32SERVICE CAREERS OF EVERY U.S. PRESIDENT, ALONG WITH KEY
01:30:36HISTORICAL EVENTS, LANDMARK SUPREME COURT CASES,
01:30:39CONSTITUTIONAL AMENDMENTS AND MAJOR TECHNOLOGY MILESTONES
01:30:42THROUGHOUT OUR NATION'S HISTORY. THE POSTER ALSO FEATURES A
01:30:46SPECIAL AMERICA TWO 50TH SECTION HIGHLIGHTING THE COUNTRY'S
01:30:49FOUNDING AND THE 250TH ANNIVERSARY OF THE UNITED STATES.
01:30:53BRINGING AMERICAN HISTORY HOME WITH C-SPAN, AMERICAN HISTORY
01:30:56TIMELINE POSTER SCAN THE CODE OR
01:30:59VISIT C-SPAN SHOPTALK.
01:31:06WATCH AMERICA'S BOOK CLUB, C-SPAN ONE'S BOLD ORIGINAL
01:31:10SERIES SUNDAY WITH OUR GUEST
01:31:12BESTSELLING AUTHOR HEATHER COX RICHARDSON.
01:31:14SHE'S A PROFESSOR OF HISTORY AT BOSTON COLLEGE AND WHOSE BOOKS
01:31:18SPAN SUBJECTS FROM THE CIVIL WAR
01:31:20AND RECONSTRUCTION TO THE GILDED
01:31:22AGE, THE AMERICAN WEST AND THE HISTORY OF THE REPUBLICAN PARTY.
01:31:26HER MOST RECENT BOOK IS THE BEST SELLING DEMOCRACY AWAKENING.
01:31:30HER NEWSLETTER, LETTERS FROM AN AMERICAN REACHES OVER 6 MILLION READERS.
01:31:34SHE JOINS OUR HOST, RENOWNED AUTHOR AND CIVIC LEADER DAVID
01:31:38RUBENSTEIN. SOME PEOPLE WHO HAVE WRITTEN ABOUT THE REVOLUTIONARY WAR SAY
01:31:41THE INDISPENSABLE PERSON WAS GEORGE WASHINGTON. HAD HE NOT BEEN THE GENERAL, WE
01:31:45PROBABLY WOULD HAVE LOST THE WAR AND SO FORTH. YOU AGREE WITH THAT?
01:31:49IN TERMS OF THE IDEOLOGY, THE
01:31:51PERSON HE WAS AND HIS WILLINGNESS TO WALK AWAY FROM
01:31:55POWER, THAT WAS EXTRAORDINARY. I WAS TELL MY STUDENTS, AMERICA
01:31:58HAS LOCKED OUT A NUMBER OF TIMES, AND THE FIRST TIME IT LUCKED OUT WAS WITH GEORGE
01:32:03WASHINGTON IN THAT POSITION OF EXTRAORDINARY POWER, WALKING
01:32:05AWAY FROM THE THE ARMY FIRST.
01:32:08AND THAT'S JUST WHY THAT'S IN THE ROTUNDA OF THE CAPITOL.
01:32:11BUT THEN WALKING AWAY FROM THE PRESIDENCY IS AN EXTRA ORDINARY THING.
01:32:15WATCH AMERICA'S BOOK CLUB WITH
01:32:16HEATHER COX RICHARDSON SUNDAY AT
01:32:196 P.M. AND 9 P.M. EASTERN AND PACIFIC. ONLY ON C-SPAN.
01:32:33ALL RIGHT. GOOD EVENING, EVERYONE.
01:32:36THE PROGRAM IS STARTING, AND I AM AMY BRAND.
01:32:39I'M THE DIRECTOR AND PUBLISHER
01:32:42OF YOU OF THE MIGHTY PRESS.
01:32:46AND I AM TRULY DELIGHTED TO WELCOME ALL OF YOU HERE THIS
01:32:50EVENING. WE ARE SO THRILLED TO BE PUBLISHING PRIORITY TECHNOLOGIES
01:32:53AND WORKING WITH LIZ REYNOLDS AGAIN AND ALL THE WONDERFUL
01:32:57AUTHORS THAT SHE
Data courtesy of The GDELT Project (gdeltproject.org), from the Internet Archive TV News Archive. Film strip and transcript are GDELT's, rehosted here under their terms of use, which permit it with this citation.