Confidence

From The Foundation for Best Practices in Machine Learning


Confidence

Control

Document and assess the degree of over- and under-confidence in the Product output by Product Team, Stakeholder(s) and End Users. Encourage an appropriate level of confidence through education and self-reflection. Note: Underconfidence will lead to users over-ruling the Product in unexpected ways. Overconfidence leads to lower scrutiny and therefore lowers the chance of detection and prevention of attacks.


Aim

To (a) balance the risk of compromising Product effects against reduced vigilance; and (b) highlight associated risks that might occur in the Product Lifecycle.


Additional Information