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

• URL: http://arxiv.org/abs/2012.09110v1
• Date: Mon, 14 Dec 2020 18:54:05 GMT
• Title: Developing Future Human-Centered Smart Cities: Critical Analysis of Smart City Security, Interpretability, and Ethical Challenges
• Authors: Kashif Ahmad, Majdi Maabreh, Mohamed Ghaly, Khalil Khan, Junaid Qadir, Ala Al-Fuqaha
• Abstract summary: Key challenges include security, robustness, interpretability, and ethical challenges to a successful deployment of AI or ML in human-centric applications. Globally there are calls for technology to be made more humane and human-compatible.
• Score: 5.728709119947406
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: As we make tremendous advances in machine learning and artificial intelligence technosciences, there is a renewed understanding in the AI community that we must ensure that humans being are at the center of our deliberations so that we don't end in technology-induced dystopias. As strongly argued by Green in his book Smart Enough City, the incorporation of technology in city environs does not automatically translate into prosperity, wellbeing, urban livability, or social justice. There is a great need to deliberate on the future of the cities worth living and designing. There are philosophical and ethical questions involved along with various challenges that relate to the security, safety, and interpretability of AI algorithms that will form the technological bedrock of future cities. Several research institutes on human centered AI have been established at top international universities. Globally there are calls for technology to be made more humane and human-compatible. For example, Stuart Russell has a book called Human Compatible AI. The Center for Humane Technology advocates for regulators and technology companies to avoid business models and product features that contribute to social problems such as extremism, polarization, misinformation, and Internet addiction. In this paper, we analyze and explore key challenges including security, robustness, interpretability, and ethical challenges to a successful deployment of AI or ML in human-centric applications, with a particular emphasis on the convergence of these 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.

Related papers

• Imagining and building wise machines: The centrality of AI metacognition [78.76893632793497]
  We argue that shortcomings stem from one overarching failure: AI systems lack wisdom. While AI research has focused on task-level strategies, metacognition is underdeveloped in AI systems. We propose that integrating metacognitive capabilities into AI systems is crucial for enhancing their robustness, explainability, cooperation, and safety.
  arXiv  Detail & Related papers  (2024-11-04T18:10:10Z)
• Blockchain-based AI Methods for Managing Industrial IoT: Recent Developments, Integration Challenges and Opportunities [3.3030080038744947]
  Authors present a comprehensive survey on the AI approaches with BC in the smart IIoT. We focus on state-of-the-art overviews regarding AI, BC, and smart IoT applications. We highlight the various issues--security, stability, scalability, and confidentiality.
  arXiv  Detail & Related papers  (2024-05-21T07:34:49Z)
• The Promise and Peril of Artificial Intelligence -- Violet Teaming Offers a Balanced Path Forward [56.16884466478886]
  This paper reviews emerging issues with opaque and uncontrollable AI systems. It proposes an integrative framework called violet teaming to develop reliable and responsible AI. It emerged from AI safety research to manage risks proactively by design.
  arXiv  Detail & Related papers  (2023-08-28T02:10:38Z)
• Artificial Intelligence for Real Sustainability? -- What is Artificial Intelligence and Can it Help with the Sustainability Transformation? [0.0]
  This article briefly explains, classifies, and theorises AI technology. It then politically contextualises that analysis in light of the sustainability discourse. It argues that AI can play a small role in moving towards sustainable societies.
  arXiv  Detail & Related papers  (2023-06-15T15:40:00Z)
• ChatGPT, Large Language Technologies, and the Bumpy Road of Benefiting Humanity [2.28438857884398]
  The promise that AI technologies will benefit all of humanity is empty so long as we lack a nuanced understanding of what humanity is supposed to be in the face of widening global inequality and pressing existential threats. We also need to develop standards in a sustainable and equitable way that differentiate between merely speculative and well-researched questions. Failure to do so could result in a future in which our AI technological advancements outstrip our ability to navigate their ethical and social implications.
  arXiv  Detail & Related papers  (2023-04-21T22:53:45Z)
• Proceedings of the Artificial Intelligence for Cyber Security (AICS) Workshop at AAAI 2022 [55.573187938617636]
  The workshop will focus on the application of AI to problems in cyber security. Cyber systems generate large volumes of data, utilizing this effectively is beyond human capabilities.
  arXiv  Detail & Related papers  (2022-02-28T18:27:41Z)
• Needs and Artificial Intelligence [0.0]
  We reflect on the relationship between needs and AI, and call for the realisation of needs-aware AI systems. We discuss some of the most critical gaps, barriers, enablers, and drivers of co-creating future AI-based socio-technical systems.
  arXiv  Detail & Related papers  (2022-02-18T15:16:22Z)
• Explainable Artificial Intelligence for Smart City Application: A Secure and Trusted Platform [6.1938383008964495]
  It is acknowledged that the loss of control over interpretability of decision-making becomes a critical issue for many data-driven automated applications. This chapter conducts a comprehensive study of machine learning applications in cybersecurity to indicate the need for explainability to address this question. Considering the new technological paradigm, Explainable Artificial Intelligence (XAI), this chapter discusses the transition from black-box to white-box.
  arXiv  Detail & Related papers  (2021-10-31T21:47:12Z)
• Trustworthy AI: A Computational Perspective [54.80482955088197]
  We focus on six of the most crucial dimensions in achieving trustworthy AI: (i) Safety & Robustness, (ii) Non-discrimination & Fairness, (iii) Explainability, (iv) Privacy, (v) Accountability & Auditability, and (vi) Environmental Well-Being. For each dimension, we review the recent related technologies according to a taxonomy and summarize their applications in real-world systems.
  arXiv  Detail & Related papers  (2021-07-12T14:21:46Z)
• Building Bridges: Generative Artworks to Explore AI Ethics [56.058588908294446]
  In recent years, there has been an increased emphasis on understanding and mitigating adverse impacts of artificial intelligence (AI) technologies on society. A significant challenge in the design of ethical AI systems is that there are multiple stakeholders in the AI pipeline, each with their own set of constraints and interests. This position paper outlines some potential ways in which generative artworks can play this role by serving as accessible and powerful educational tools.
  arXiv  Detail & Related papers  (2021-06-25T22:31:55Z)
• The Short Anthropological Guide to the Study of Ethical AI [91.3755431537592]
  Short guide serves as both an introduction to AI ethics and social science and anthropological perspectives on the development of AI. Aims to provide those unfamiliar with the field with an insight into the societal impact of AI systems and how, in turn, these systems can lead us to rethink how our world operates.
  arXiv  Detail & Related papers  (2020-10-07T12:25:03Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.