Blog / Reading series
Evidence-aware AI · 以證據理解 AI 系統
A reading path through existing essays: why evidence matters, how speech pipelines preserve it, and how disclosure shapes collaboration. 從既有文章理解證據、語音流程與資訊揭露的關係。
The larger question · 拆解路徑
- Evidence and human judgment · 證據與人的判斷
- Speech pipelines and traceability · 語音流程與可追溯性
- Minimal disclosure across nodes · 跨節點的最小揭露
- Connections to recent systems work · 與系統實作的連接
Read in order · 依序閱讀
From Cybercrime Investigation to Trustworthy AI
An essay on how cybercrime investigation shaped the way I think about evidence, adversarial behavior, and trustworthy AI for high-stakes systems.
Designing Speech Evidence Pipelines with ASR and LLMs
A research note on building speech evidence pipelines with ASR, retrieval, and LLMs while keeping outputs grounded in transcript evidence.
Minimal Disclosure for Fraud Intelligence: Cross-Node Pattern Formation in High-Stakes AI
A research-oriented essay on cross-node fraud intelligence, minimal disclosure, and trustworthy AI design for high-stakes pattern formation under fragmented evidence.
Recent Work, April-June 2026: Evidence-Aware AI Systems in Practice
A public-safe synthesis of recent work across speech decision stability, clinical workflow support, AI triage demos, realtime voice systems, runtime governance, and AI systems engineering education.