{
  "id": 19801219,
  "title": "READ AN EXCERPT FROM THE BOOK HERE >",
  "url": "https://urgent.news/2026/11/13/read-an-excerpt-from-the-book-here",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-11-13T12:04:49.000Z",
  "source": {
    "name": "Rest of World",
    "slug": "restofworld",
    "url": "https://elink32b.restofworld.org/ss/c/u001.wqTatvCe1uEimPApFRU3vFduVjiFuG_K8CXAMZILUNv_JmPBzL4yhBRB5O6BOYnS2cyWbtMpZwzvaZ_izDIsvDCvTv0Ow8-t6IpVNagCxgkWQyqYNTyBRbtLGr_40JRfWKMI2BIpqQwXQbe_eo4qJsVsmUAm2kWWpEJcsWsNKTqaOJi1u3f1NkQ0tmOXRcmnK36fbo2K9mG49JlhTGL2DEFaMZoLXr9Dr4lIiBw_0wVapxK1LQiktLNdlZaA0xAgD6aDsumn6mO_8vpnyw2jKSbLasUm50-b81d9s-eSef0/4vp/IJKTNtThRrGZOOoB5wpwcA/h2/h001.YFHovmz9oUAN5mlkxFqUEMWZDlag764VdStobRLu4ro"
  },
  "original_language": "en",
  "account": "In Taoyuan, Taiwan's bustling industrial hub, Mayor San-Cheng Chang is leveraging AI to spearhead a transformative vision for the city. Known for his technical prowess and government experience, Chang previously served as Taiwan's first nonpartisan premier and held pivotal roles at tech giants Google and Acer. With a background at Taiwan's National Center for High-Performance Computing, Chang's expertise in technology and governance shines through in Taoyuan's AI-driven initiatives.\n\nAs the city hosts Taiwan's international airport and 2.2 million residents, it grapples with heavy truck traffic, air pollution, rapid population growth, and ongoing construction. Since March 2023, Taoyuan has implemented an AI-powered lung cancer screening program targeting citizens over 40 with risk factors like occupational exposure and family history. The initiative has screened over 400,000 residents, detecting 233 lung cancer cases, 90% of which were in early stages. By utilizing AI software that can predict cancer risk from a single low-dose CT scan, the city has significantly reduced the burden on local hospitals and saved NT$500 million ($17 million) in diagnostic costs.\n\nAddressing community concerns, Taoyuan developed AI systems to identify illegally modified vehicle exhaust pipes, reducing noise complaints by 20% compared to the previous year. AI-powered cameras now monitor construction sites and factory chimneys for pollutants, automatically triggering water sprays or alerting inspectors when dust levels or emissions rise suspiciously. Traffic-light cycles at busy intersections are optimized by AI, shaving about 10 seconds off each wait. Moreover, AI-equipped electronic fences create green-light corridors for ambulances approaching, cutting average travel times from four minutes to just over two minutes, potentially saving lives.\n\nWhile Taoyuan serves as a model for AI's practical applications in urban settings, Mayor Chang exercises caution in selecting projects. He refuses to endorse generative AI chatbots that could generate false information and distinguishes between using machine learning to detect existing conditions and predicting future outcomes. The city employs AI to pinpoint potholes for faster road maintenance or identify passengers with wheelchairs at train stations, ensuring assistance is ready when doors open. AI's ability to swiftly identify patterns allows for faster response than human eyes could achieve, but it does not replace human decision-making.\n\nHowever, governments and companies are increasingly relying on machine learning algorithms to forecast future occurrences, such as the risk of recidivism, leading to life-altering decisions like sentencing, parole, credit scoring, and employment opportunities. Princeton University's Arvind Narayanan warns of the grave risks associated with using AI like a Magic 8 Ball, emphasizing the potential for oversimplification and misclassification. For instance, AI-driven fraud detection may unfairly flag individuals based on income patterns, particularly struggling single parents with irregular income from gig work.\n\nNarayanan cautions that forecasting job performance, criminal activity, or life expectancy involves numerous variables and unpredictable events beyond historical data's scope. The \"black box\" nature of AI algorithms and their lack of explainability pose significant accountability and redress challenges in critical areas of public life. While modern AI-powered predictive models may possess an air of infallibility, prediction remains limited and fraught with potential errors and biases. To mitigate risks, Narayanan identifies five fundamental ways these predictive systems can falter: inaccurate predictions leading to bad decisions, reliance on models that do not accurately capture real-world complexity, and the danger of automating human judgment without proper oversight.",
  "summary": null,
  "key_points": [
    "Mayor San-Cheng Chang leads AI-driven initiatives in Taoyuan, Taiwan",
    "AI screens for lung cancer, detecting 233 cases with 90% early detection",
    "AI optimizes traffic lights, reducing wait times by about 10 seconds"
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}