What are data poisoning attacks in AI?
An example of an AI chatbot conversation about data poisoning attacks in AI systems.
What are data poisoning attacks in AI?
Data poisoning attacks involve manipulating the training data of an AI model to produce incorrect outputs.
How do these attacks affect machine learning models?
They can lead to biased predictions, reduced accuracy, and can even cause the model to behave unpredictably.
Can you give an example of a data poisoning attack?
Sure! An example is when an attacker adds misleading data to a dataset, like fake reviews, to skew sentiment analysis.
What measures can be taken to prevent these attacks?
Implementing data validation, anomaly detection, and robust training techniques can help mitigate the risks of data poisoning.
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