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Organizational

The Risks of Machine Learning Systems

Tan, Taeihagh & Baxter (2022)

Sub-category

The risk of financial and/or reputational damage to the organization building or using the ML system.(p. 15)

Entity— Who or what caused the harm

Human

Due to a decision or action made by humans

AI system

Due to a decision or action made by an AI system

Other

Due to some other reason or is ambiguous

Intent— Whether the harm was intentional or accidental

Intentional

Due to an expected outcome from pursuing a goal

Unintentional

Due to an unexpected outcome from pursuing a goal

Other

Without clearly specifying the intentionality

Timing— Whether the risk is pre- or post-deployment

Pre-deployment

Occurring before the AI is deployed

Post-deployment

Occurring after the AI model has been trained and deployed

Other

Without a clearly specified time of occurrence

Other risks from Tan, Taeihagh & Baxter (2022) (17)

First-Order Risks

First-Order Risks > Application

First-Order Risks > Misapplication

First-Order Risks > Algorithm

First-Order Risks > Training & validation data

First-Order Risks > Robustness