Artificial Intelligence(AI) Testing
- lakshmibala179
- Aug 19
- 1 min read
What is AI testing??
AI testing is the process of evaluating and validating AI systems to ensure they work correctly, safely and fairly. Unlike traditional software testing. AI testing focuses not just on whether the system runs without errors, but also on its predictions, decisions or behaviors are reliable, accurate and ethical.
Here are the main aspects of AI testing:
Functional Testing - Checking if the AI system performs the tasks it was designed for ( eg., a chatbot answering the questions correctly).
Chatbot Performance Testing - Measuring how well the AI handles speed, scalability and large amounts of data.
Accuracy & Reliability Testing - Ensuring AI models give consistent and correct outputs. (eg., testing a fraud detection model against real - world data).
Bias & Fairness Testing - Identifying and reducing unfair biases in AI models (eg., making sure a hiring algorithm doesn't discriminate).
Robustness & Security Testing - Evaluating how AI responds to unexpected, noisy or adversarial inputs (eg., testing self-driving car vision against unusual weather conditions).
Explainability Testing - Assessing whether AI's decisions can be understood and explained to humans.
Compliance Testing - Make sure AI meets legal and regulatory requirements such as GDPR(General Data Production regulation), AI Act, or Industry - specific rules.
In short:- AI testing ensuring that AI systems are accurate, fair, safe and trustworthy before being deployed to the real-world.
