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Meet Trust Insights
Uncover how Trust Insights can help protect people from social scams and coercion. Explore how this new framework uses privacy-preserving machine learning to detect when someone may be coached into risky actions. Find out how to integrate Trust Insights into your app, interpret its signals, and design thoughtful interventions that safeguard people while respecting their privacy.
Chapters
- 0:00 - Introduction
- 2:35 - Generating insights
- 6:50 - Feedback requirements
- 9:25 - Privacy
- 10:34 - Best practices
- 12:48 - Next steps
Resources
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3:01 - Generating insights
import TrustInsights let request = IsLikelyBeingCoachedInsight.request(schema: .version1, modelVersion: .current) let context = InsightEvaluator.InsightContext(operationCategory: .resourceUse, requestedEvaluations: request) let evaluator = InsightEvaluator() guard try await evaluator.requestAuthorization(for: context) == .authorized else { return } let assessment = try await evaluator.requestEvaluation(context: context) do { try handleAssessment(assessment) } catch { // Handle error } assessment.reportConsumption(.usedIncreasedFriction) -
5:37 - Handling results for IsLikelyBeingCoachedInsight
func handleAssessment(_ assessment: InsightEvaluation<IsLikelyBeingCoachedInsight>) throws { switch try assessment.insight.outcome.get() { case .unknown: case .medium: case .high: @unknown default: } } -
7:05 - Real-time consumption feedback
import TrustInsights let request = IsLikelyBeingCoachedInsight.request(schema: .version1, modelVersion: .current) let context = InsightEvaluator.InsightContext(operationCategory: .resourceUse, requestedEvaluations: request) let evaluator = InsightEvaluator() guard try await evaluator.requestAuthorization(for: context) == .authorized else { return } let assessment = try await evaluator.requestEvaluation(context: context) do { try handleAssessment(assessment) } catch { // Handle error } assessment.reportConsumption(.usedIncreasedFriction)
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- 0:00 - Introduction
Meet Trust Insights, a new iOS 27 framework that helps your app detect coercion and social engineering.
- 2:35 - Generating insights
Integrating Trust Insights with its client-side Swift API — declaring the entitlement, building a parameter pack of requested insights, and using the InsightEvaluator with an operation category that determines which model logic applies.
- 6:50 - Feedback requirements
The two required types of feedback that keep insights accurate — mandatory real-time consumption feedback reporting how your app responded, and offline feedback for transactions that later prove fraudulent.
- 9:25 - Privacy
Understand how Trust Insights minimizes data, keeps signals on device, and gives users full control.
- 10:34 - Best practices
Learn where Trust Insights adds the most value and how to combine it with your existing risk logic.
- 12:48 - Next steps
Adopting Trust Insights — identify moments where it can work alongside your existing logic, follow the documentation and best practices, and register on Apple Business Register to learn about Partner Data Services.