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The prevalence of automated decision making, influencing important aspects of our lives – e.g., school admission, job market, insurance and banking – has resulted in increasing pressure from society and regulators to make this process more transparent and ensure its explainability, accountability and fairness. We demonstrate a prototype voiceenabled device, called Glass-Box, which users can question to understand automated decisions and identify the underlying model’s biases and errors. Our system explains algorithmic predictions with class-contrastive counterfactual statements (e.g., “Had a number of conditions been different:. . . the prediction would change. . . ”), which show a difference in a particular scenario that causes an algorithm to “change its mind”. Such explanations do not require any prior technical knowledge to understand, hence are suitable for a lay audience, who interact with the system in a natural way – through an interactive dialogue. We demonstrate the capabilities of the device by allowing users to impersonate a loan applicant who can question the system to understand the automated decision that he received.

Glass-Box: Explaining AI Decisions With Counterfactual Statements Through Conversation With a Voice-enabled Virtual Assistant