TED: Why AI needs a "nutrition label" | Kasia Chmielinski

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Information Technology (IT), Architecture, Social Studies
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11th Grade - University
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Hard
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10 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What analogy does the speaker use to describe the lack of transparency in AI systems?
A hidden maze
A mysterious sandwich
A sealed envelope
A locked treasure chest
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Why is it challenging to assess the quality of data used in AI systems?
Data is always accurate
Data is too expensive to analyze
There are no global standards for data quality
Data is often encrypted
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the analogy used to describe the current state of data regulation?
A well-organized library
The Wild West
A peaceful garden
A bustling city
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the purpose of the Data Nutrition Project?
To create new AI algorithms
To provide transparency in data sets
To eliminate the use of AI
To fund AI research
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the main benefit of using data nutrition labels?
They make data more expensive
They encrypt the data
They help understand data quality
They reduce the amount of data
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is a significant concern with the growing trend of data collection for generative AI?
Data is controlled by a few private actors
Data is being ignored
Data is being destroyed
Data is becoming too cheap
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is a potential risk of generative AI mentioned in the transcript?
It can generate false information
It can eliminate AI jobs
It can create too much transparency
It can reduce data size
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