Learn AI / Learning Paths /Understand AI risks without panic
Understand AI risks without panic
The failures that actually happen, in proportion, without either hype or doom.
Hallucination
A generated answer that sounds plausible but includes false, unsupported or invented details.
Algorithmic bias
Systematic unfair patterns in data, rules or model outputs can disadvantage some people or groups, especially when tools are used in important decisions.
Prompt injection
A text-based attack that tries to make an AI assistant follow hidden or malicious instructions instead of the rules and task it was meant to follow.
Deepfake
A deepfake is an AI-generated or heavily altered image, audio clip or video that convincingly imitates an identifiable real person, usually in a recording or event that did not happen as shown.
Automation bias
The tendency to trust a system’s output too much and miss errors that a careful human review might have caught.
Data exfiltration
Unauthorised copying of information out of a system, application or connected tool to a place an attacker or unapproved user can access.
AI safety
AI safety means designing, testing and using AI systems so they are less likely to cause harm, especially in situations where people could be affected.
Red teaming
A structured attempt to make an AI system fail, so people can find risks, harms and weak controls before real users are affected.
Guardrail
A guardrail is a rule, check or control that limits unsafe or unacceptable AI outputs or actions before people rely on them.