【從「解決問題」出發，打造智慧城市的未來 💡】
AI 真的能解決所有問題嗎？在與 Alliance University 的對談中，本中心主任熊博安 Pao-Ann Hsiung點出一個很核心的提醒：
「很多時候，大家急著解決問題，卻還沒搞清楚真正的問題是什麼——這才是最大的問題。」
這場訪談不只談技術，更談「為什麼做、要解決誰的困境」。幾個讓人很有感的重點如下：
問題導向的研究：AI（例如監視系統/CCTV）不該只用來「監控」，也能用來保障漁工的人權與安全，讓科技真正站在弱勢的一方。
聯邦學習（Federated Learning）：在隱私與頻寬限制下，透過邊緣端分散式學習，讓智慧城市更有效率、也更務實可行。
系統性思維：打破技術孤島，建立能讓不同 AI 系統彼此溝通、整合資訊、支援決策的城市平台。
跨領域合作與可信任 AI：工程師需要有社會與政策的敏感度，並與法律、政治等領域合作，才能把透明度、責任與信任放進系統設計裡。
科技的演進不該只是追逐熱潮（LLM、大數據……），更重要的是回到初心：
我們真正想解決的，是什麼樣的人類困境？
精彩對談全文與影片：
#AI #智慧城市 #永續發展 #中正大學 #熊博安 #系統思維 #科技倫理 #AllianceUniversity
【Solving Real-World Problems Through Smart Paradigms 
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Can AI solve everything? In a thought-provoking conversation at Alliance University, Director Pao-Ann Hsiung (AI Center, National Chung Cheng University, Taiwan) offers a powerful reminder:
“Many people start solving a problem without knowing what the real problem is—and that’s the biggest problem.”
This interview goes beyond technology and returns to a deeper question: what human challenge are we truly trying to solve? Key takeaways include:
Problem-First Approach: Using AI and CCTV-based systems not merely for surveillance, but to protect fishermen’s labor rights and safety, proving technology can serve the public good.
Federated Learning: Tackling bandwidth and privacy constraints in smart cities through decentralized, edge-based learning.
Systems Thinking: Moving beyond isolated “silos” to build integrated platforms where AI systems can communicate, coordinate, and support better urban decision-making.
Trustworthy AI: Why engineers must work closely with social scientists and policy experts to strengthen privacy, transparency, and accountability.
Technology evolves best when it’s not about chasing the next hype—but about addressing the layered complexities of our world.
Watch the full interview here:
#ArtificialIntelligence #SmartCities #Sustainability #FederatedLearning #SystemsThinking #TechForGood #ResearchInnovation #AllianceUniversity