Risk Assessment (AI System)
Risk Assessment (AI System)
What is Risk Assessment in an AI system?
Risk assessment in an AI system is the systematic process of identifying, analysing and evaluating the potential consequences of actions or events within AI systems that could bring harm to the people, property, data and/or the environment.
Why is Risk Assessment important for AI systems?
Since AI can make decisions automatically, a single mistake can cause serious problems. Risk assessment helps keep AI safe, fair, and reliable, especially in sensitive areas like finance, healthcare, and workplace safety.
What types of risks are checked in AI systems?
The most important types of risks in AI system include:
● Security risks (hacking or misuse)
● Privacy risks (leaking of personal data)
● Operational risks (AI system failure)
● Bias risks (unfair decisions)
What does an effective AI risk assessment include?
An effective AI risk assessment includes identifying all possible risks, analyzing how serious and likely they are, involving the right experts, using proper tools to monitor the AI, and taking steps to reduce those risks before they cause harm.
How do experts perform risk assessment in AI?
Generally, risk assessment in AI constitutes the following steps:
● Understanding how the AI system works
● Identifying possible risks
● Measuring how likely and harmful each risk is
● Planning actions to reduce or control the risks.
Article by
Barnali Sharma
Content Writer
Barnali Sharma is a dedicated content contributor for viAct. A university gold medalist with an MBA in Marketing, she crafts compelling narratives, enhances brand engagement, and develops data-driven marketing campaigns. When she’s not busy working her content alchemy, Barnali can be found commanding stages with her public speaking or turning data into stories that actually make sense -because who said analytics can’t have a little creativity?