AI đô thị tích hợp để mở rộng phạm vi, tiếp cận và công bằng trong dữ liệu đô thị

The European Physical Journal Special Topics - Tập 231 - Trang 1741-1752 - 2022
Bill Howe1, Jackson Maxfield Brown1, Bin Han1, Bernease Herman1, Nic Weber1, An Yan2, Sean Yang1, Yiwei Yang1
1University of Washington SEATTLE USA
2Meta, Seattle, USA

Tóm tắt

Chúng tôi xem xét việc sử dụng các kỹ thuật trí tuệ nhân tạo (AI) để mở rộng phạm vi, khả năng tiếp cận và công bằng của dữ liệu đô thị. Mục tiêu của chúng tôi là tạo điều kiện cho nghiên cứu toàn diện về động lực của thành phố, chuyển hướng sự chú ý của nghiên cứu AI khỏi các ứng dụng hướng tới lợi nhuận, có hại cho xã hội (ví dụ: nhận diện khuôn mặt) và hướng tới các câu hỏi cơ bản về di chuyển, quản trị tham gia và công lý. Bằng cách cung cấp dữ liệu đa biến, chất lượng cao và qua nhiều cấp độ cho nghiên cứu, chúng tôi nhằm liên kết nghiên cứu vĩ mô về thành phố như là các hệ thống phức tạp với quan điểm giảm thiểu về thành phố như là một tập hợp các nhiệm vụ dự đoán độc lập. Chúng tôi xác định bốn lĩnh vực nghiên cứu trong AI cho các thành phố như là những yếu tố chính: nội suy và ngoại suy dữ liệu không gian-thời gian, sử dụng các kỹ thuật Xử lý ngôn ngữ tự nhiên (NLP) để mô hình hóa các hoạt động quản trị có cường độ sử dụng phát biểu và văn bản, khai thác mô hình ngữ nghĩa trong các nhiệm vụ học tập, và hiểu biết về sự tương tác giữa công bằng và khả năng giải thích trong các ngữ cảnh nhạy cảm.

Từ khóa

#AI đô thị #dữ liệu đô thị #quản trị tham gia #công bằng #mô hình hóa ngữ nghĩa #xử lý ngôn ngữ tự nhiên

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