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What is AI ethics?
Guidelines for responsible AI development and use.
Why AI ethics is important?
It prevents harm and misuse.
What is algorithmic bias?
Unfair outcomes caused by biased data.
How does bias enter AI systems?
Through biased training data.
What is fairness in AI?
Equal treatment across groups.
What is transparency in AI?
Understanding how AI makes decisions.
What is explainable AI?
AI systems whose decisions can be explained.
Why explainability matters?
It builds trust and accountability.
What is accountability in AI?
Responsibility for AI outcomes.
Who is responsible for AI decisions?
Developers and organizations.
What is data privacy in AI?
Protecting personal data used by AI.
What is consent in data usage?
User permission for data use.
What is surveillance risk?
Excessive monitoring using AI.
What is facial recognition concern?
Privacy and misidentification risks.
What is AI misuse?
Using AI for harmful purposes.
What is autonomous decision-making?
AI acting without human input.
Why human oversight is needed?
To prevent harmful outcomes.
What is AI governance?
Rules and policies for AI.
What is ethical data collection?
Fair and transparent data gathering.
What is responsible AI?
AI aligned with human values.
What is social impact of AI?
Effects on society and jobs.
What is job displacement?
Jobs replaced by automation.
How to address job displacement?
Reskilling and education.
What is AI safety?
Preventing unintended consequences.
What is value alignment?
Aligning AI goals with humans.
What is ethical AI design?
Embedding ethics in development.
What is AI regulation?
Legal control of AI usage.
Why global cooperation matters?
AI impacts cross borders.
What is long-term AI risk?
Future unintended impacts.
Why study AI ethics?
To guide safe AI adoption.
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