Main Challenge

Ensuring Professionalism with AI-annotated Data for Undereducated Officers


As the system uses AI to automatically collect and analyze data from video input, inaccuracy is inevitable. The design must therefore communicate professionalism and analytical credibility, while acknowledging uncertainty from AI detection and allowing space for user awareness and correction.

Meanwhile, In the traditional casino environment, the detection is happened when groups of people manually checked camera for possible dealer fault. Most of them don’t have any prior experience in dataset cleanup or AI use.





Design Strategy.



(01)Make AI Decisions Explainable
To support officers without AI or data-cleaning experience, the system provides interpretable reasoning rather than raw model output. Each AI-annotated result is accompanied by visual cues and explanations that indicate what was detected and why it was flagged.



(02)Enable Lightweight Human Correction and Feedback
Recognizing that human judgment remains essential, the system provides simple correction and confirmation actions




(03)Communicate Confidence Levels Instead of Absolute Truth
All AI detection needs to be labelled, prompting the officer to manually check and confirm.