What are some examples of feedback loops in AI?
Feedback loops in AI occur when the output of a system influences its future inputs. For example, in recommendation systems, user interactions can refine future suggestions.
Can you give me a specific example of this in action?
Sure! In a streaming service, if a user watches a particular genre, the AI learns from this behavior and starts recommending more content from that genre.
How does this affect the accuracy of the recommendations?
It significantly improves accuracy, as the system adapts to user preferences over time, leading to more personalized and relevant suggestions.
Are there any downsides to feedback loops?
Yes, one downside is that they can create filter bubbles, where users are only exposed to a narrow range of content, limiting diversity.
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