Chatbot
Pattern 11C: Present properties of system outputs
Problem The user needs an explanation for why the system did what it did. Solution Provide users with a set of relevant system-output characteristics so they can understand what properties influence the system’s behaviors. Use when How Collaborate with an AI/ML practitioner to: Show system outputs and their respective characteristics. Output characteristics may be independent […]
Pattern 11B: Global explanations
Problem The user needs an explanation for why the system did what it did, and it is important for the user to understand how the AI system works in general. Solution Make available an explanation that pertains to how the AI system makes decisions in general. Use when How Get information about how the AI […]
Pattern 11A: Local explanations
Problem The user needs an explanation for why the system did what it did, and it is important for the user to understand a particular system decision. Solution Make an explanation available for one specific action or decision the AI system made. Use when How Get information about how the AI system made the decision. […]
Pattern 10C: Fall back to other strategies
Problem The AI’s uncertainty level is so high that it is unable to take an action. Solution Enable the AI system to fall back to other strategies so the interaction with the user can proceed. Use when How Collaborate with an AI/ML practitioner to: When the system hits the determined threshold, fall back to another […]
Pattern 10B: Avoid cold starts by eliciting user preferences
Problem The AI system has no knowledge of user preferences and cannot personalize the user experience. Solution Elicit user preferences. Use when How Collaborate with an AI/ML practitioner to identify what information the system needs from the user to learn their preferences for personalization. Trigger an elicitation session to solicit user preferences through selection and/or […]
Pattern 1A: Introductory blurb
Problem The user needs to understand what the system can do. Solution Provide a brief introduction to overall system capabilities and/or to a specific feature. Use when How Make the introduction brief: One sentence or less, consumable in less than 10 seconds. Make the introduction clear and descriptive. The introduction may be displayed: Make the […]
Pattern 16D: Convey the consequences of user action in help and documentation
Problem The user needs to know how their actions impact the system. Solution Make available information about how user actions in general impact experience with the system. Use when User actions (explicit or implicit feedback) impact the decisions made by the AI. How Provide documentation that explains in general how user actions impact experience with […]
Pattern 16C: Remind of consequences of a past action and ask for reconfirmation
Problem The user needs to occasionally be reminded of consequential past actions. Solution Inform the user of consequential actions taken in the past and offer the option to undo or keep those actions. Use when How Inform the user of: When to show notifications: Match the communication’s attention-getting characteristics to the severity of the consequences. […]
Pattern 16B: Feedback: Convey the consequences of user actions after the user takes action
Problem The user needs to know how their actions impact the system. Solution Communicate to the user how the action they just took impacts experience with the system and/or implement the consequences of user actions immediately. Use when How The system should respond immediately to the user’s action by: If using a description: Describe consequences […]
Pattern 16A: Feedforward: Convey the consequences of user actions before the user takes action
Problem The user needs to know how their actions impact the system. Solution Communicate to the user how taking a specific action will impact future experience with the system. Use when How Communicate through: Make clear the scope of the impact to: Describe consequences as specifically as possible, ranging from specific immediate changes to generic […]
Pattern 15D: Use existing public rating or interaction data as feedback for the system
Problem User feedback is needed to assess the system and help it improve over time. Solution Leverage existing public rating or interaction data as feedback for the system. Use when The system collects and displays publicly item-specific feedback, such as ratings or reactions (e.g., like, dislike, sad, celebrate). How Use data from existing item-specific public […]
Pattern 10A: Disambiguate before acting
Problem The AI system is uncertain of user intent and what further actions to take. Solution Elicit clarification from the user before taking action to resolve the system’s uncertainty. Use when How Collaborate with an AI/ML practitioner to: To elicit clarification, ask the user a clarifying question or prompt the user to select from one or more probable […]