WEBVTT

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Music

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Societal challenges of machine learning

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Blus in algorithms

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Biased data used to train machines

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may lead to biased decisions

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impacting the accuracy of systems

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like facial recognition.

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Job displacement

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machines may replace some jobs

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particularly those involving repetitive tasks.

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Privacy concerns

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Analyzing personal data in machine learning

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raises concerns about how the data is used,

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stored, and whether it's kept private.

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Ethical dilemmas

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Decisions made by machines

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like who gets a loan or a job

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can raise ethical questions

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regarding fairness and discrimination.

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Digital divide

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Not everyone has equal access to technology,

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creating a gap in who benefits

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from machine learning advancements.

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Overreliance on machines

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Depending too much on machines

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like heavy reliance on navigation apps

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may impact people's ability

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to navigate without them.