论文标题

发展以人为本的以人为本的智慧城市:对智能城市安全,解释性和道德挑战的批判性分析

Developing Future Human-Centered Smart Cities: Critical Analysis of Smart City Security, Interpretability, and Ethical Challenges

论文作者

Ahmad, Kashif, Maabreh, Majdi, Ghaly, Mohamed, Khan, Khalil, Qadir, Junaid, Al-Fuqaha, Ala

论文摘要

随着全球人口的增加推动了世界各地的快速城市化,因此非常需要考虑值得生活的城市的未来。特别是,随着现代智能城市采用越来越多的数据驱动的人工智能服务,值得记住的是,技术可以促进繁荣,福祉,城市宜居性或社会正义,但只有在它具有正确的类似物(例如经过精心思考的政策,成熟机构,负责任的政府)时,技术才能促进。这些智能城市的最终目标是促进和增强人类的福利和社会繁荣。研究人员表明,各种技术业务模型和特征实际上可以导致社会问题,例如极端主义,两极分化,错误信息和互联网成瘾。鉴于这些观察结果,解决了这样的AI算法的安全性,安全性和解释性所涉及的哲学和道德问题,这些AI算法将构成未来城市的技术基础,认为这是至关重要的。在全球范围内,有人呼吁使技术变得更加人道和以人为本。在本文中,我们分析和探讨了关键挑战,包括安全性,鲁棒性,可解释性和道德(数据和算法)挑战,以成功地在以人为中心的应用中部署AI,并特别强调这些概念/挑战的融合。我们对这些关键挑战的现有文献进行了详细的综述,并分析了其中一个挑战可能导致其他挑战或帮助解决其他挑战。本文还向这些领域中研究的当前局限性,陷阱和未来方向提供建议,以及它如何填补当前空白并带来更好的解决方案。我们认为,这种严格的分析将为未来在域中进行研究提供基准。

As the globally increasing population drives rapid urbanisation in various parts of the world, there is a great need to deliberate on the future of the cities worth living. In particular, as modern smart cities embrace more and more data-driven artificial intelligence services, it is worth remembering that technology can facilitate prosperity, wellbeing, urban livability, or social justice, but only when it has the right analog complements (such as well-thought out policies, mature institutions, responsible governance); and the ultimate objective of these smart cities is to facilitate and enhance human welfare and social flourishing. Researchers have shown that various technological business models and features can in fact contribute to social problems such as extremism, polarization, misinformation, and Internet addiction. In the light of these observations, addressing the philosophical and ethical questions involved in ensuring the security, safety, and interpretability of such AI algorithms that will form the technological bedrock of future cities assumes paramount importance. Globally there are calls for technology to be made more humane and human-centered. In this paper, we analyze and explore key challenges including security, robustness, interpretability, and ethical (data and algorithmic) challenges to a successful deployment of AI in human-centric applications, with a particular emphasis on the convergence of these concepts/challenges. We provide a detailed review of existing literature on these key challenges and analyze how one of these challenges may lead to others or help in solving other challenges. The paper also advises on the current limitations, pitfalls, and future directions of research in these domains, and how it can fill the current gaps and lead to better solutions. We believe such rigorous analysis will provide a baseline for future research in the domain.

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