DACI Framework
Drivers, Approvers, Contributors, and Informed (DACI) is a responsibility assignment framework that clarifies roles and responsibilities.
Drivers, Approvers, Contributors, and Informed (DACI) is a responsibility assignment framework that clarifies roles and responsibilities.
A cognitive bias where individuals overestimate their own abilities, qualities, or performance relative to others.
A theory that emphasizes the role of emotions in risk perception and decision-making, where feelings about risk often diverge from cognitive assessments.
The tendency to overestimate how much our future preferences and behaviors will align with our current preferences and behaviors.
Explainable AI (XAI) are AI systems that provide clear and understandable explanations for their decisions and actions.
A phenomenon where vivid mental images can interfere with actual perception, causing individuals to mistake imagined experiences for real ones.
Trust, Risk, and Security Management (TRiSM) is a framework for managing the trust, risk, and security of AI systems to ensure they are safe, reliable, and ethical.
Guidelines and principles designed to ensure that AI systems are developed and used in a manner that is ethical and responsible.
The practice of developing artificial intelligence systems that are fair, transparent, and respect user privacy and rights.