Prediction
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 […]
Pattern 9E: Batch-editing data
Problem The AI system is wrong and the user needs to correct a batch of related system behaviors. Solution Enable the user to refine the AI system’s output by editing, correcting, or refining a batch of related data from a single interaction. Use when How When the user corrects or refines a behavior, the AI, […]
Pattern 9D: Do G9 through G15
Problem The AI system is wrong and the user needs to edit, correct, refine, or recover the system’s behavior. Solution Enable the user to alter the AI system’s behavior by editing, correcting, or refining its output and making clear that their correction will be used as feedback for its learning over time (see Guideline 15, Encourage granular […]
Pattern 9C: Undo automated actions
Problem The AI system incorrectly altered user input and the user needs to correct the system’s behavior. Solution Enable the user to revert to a previous state or undo the AI system’s actions. Use when How Enable correction by: User benefits Common pitfalls Keep in mind that repeated correction of the AI system can be […]
Pattern 9B: Rich and detailed edits
Problem The AI system produced an incorrect or partially incorrect result/output and the user needs to edit, correct, refine, or recover the system’s behavior. Solution Enable the user to modify the AI system’s output by editing, correcting, or refining it. Enable the user to edit all parts of the AI system’s output. Use when How […]
Pattern 9A: Switch classification decisions
Problem The AI system incorrectly classified an object and the user needs to edit, correct, refine, or recover the system’s behavior. Solution Enable users to correct the AI system by selecting between two different states for each system output. Use when How The AI classifies each item (e.g., important/not important; spam/not spam). Enable the user to correct […]
Pattern 2D: Provide low performance alerts
Problem The user needs to form realistic expectations about how well the system can do what it can do. Solution Alert the user of known or anticipated issues with system performance. Use when How Distill the most important information from G02-C: Report system performance information about the most probable low performance conditions. For example, identify: Collaborate with […]
Pattern 1E: Show a set of system outputs
Problem The user needs to understand what the system can do. Solution Show a set of system outputs for the user to choose from. Use when How Show a preview of the most probable system outputs, based on the current state and input. Select possible system outputs to display based on one or more considerations: […]
Pattern 1D: Demonstrate possible system inputs
Problem The user needs to understand what the system can do. Solution Show possible user inputs to demonstrate to the user what the system can do. Use when How Show possible user inputs in one or more of the following forms: Select possible user inputs to display based one or more considerations: User benefits Common […]
Pattern 2B: Match the level of precision in UI communication with the system performance – Numbers
Problem The user needs to form realistic expectations about how well the system can do what it can do. Solution Communicate that the system is probabilistic and may make mistakes through intentional use of precision in numeric measurements. Use when How For system outputs and/or behaviors that are qualified numerically, match precision of numbers used […]