With any recommendationalgorithm, you run the risk of individuals who looksimilar to each...
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With any recommendation
algorithm, you run the risk of individuals who look
similar to each other, in terms of their activity,
getting pushed closer and closer and closer together
in terms of content that they're being recommended, and whatever information
is gonna confirm your preexisting beliefs
algorithm, you run the risk of individuals who look
similar to each other, in terms of their activity,
getting pushed closer and closer and closer together
in terms of content that they're being recommended, and whatever information
is gonna confirm your preexisting beliefs
Full Transcript
00:00:01.000 --> 00:00:04.018
With any recommendation
algorithm, you run the risk
00:00:04.281 --> 00:00:08.384
of individuals who look
similar to each other,
00:00:08.485 --> 00:00:11.506
in terms of their activity,
getting pushed closer
00:00:11.607 --> 00:00:13.987
and closer and closer together
in terms of content
00:00:14.999 --> 00:00:15.829
that they're being recommended,
00:00:15.927 --> 00:00:17.951
and whatever information
is gonna confirm
00:00:18.001 --> 00:00:19.831
your preexisting beliefs.
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Movie Summary
With TikTok crowned the world's most downloaded app, these are the personal stories of a cultural phenomenon, told through an ensemble cast of Gen-Z natives, journalists and experts alike.
