Collaborative Intelligence in Smart Cities: A Systematic Review

Kwecko, Viviani; Botelho, Sílvia Silva da Costa

doi:10.4236/sn.2018.73015

Cited by 4 publications

(2 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Emphasis also on educated/uneducated publics. Kwecko and Botelho (2018) Described collective intelligence in smart cities using three approaches: technological, human resources, and citizen-related governance.…”

Section: Past Literature Reviews On Publics In Public Engagement In Aimentioning

confidence: 99%

“… Simonofski et al, 2017 ), citizen participation in smart cities since smartness is associated with technologies like AI (e.g. Kwecko and Botelho, 2018 ), distillations of AI ethics ( Jobin et al, 2019 ), implications of AI in governance ( Zuiderwijk et al, 2021 ), and political empowerment through AI ( Savaget et al, 2019 ). Characterization of publics appeared to vary by object of study.…”

Section: Past Literature Reviews On Publics In Public Engagement In Aimentioning

confidence: 99%

See 1 more Smart Citation

Who are the publics engaging in AI?

Sieber,

Brandusescu,

Adu-Daako

et al. 2024

Public Underst Sci

View full text Add to dashboard Cite

Given the importance of public engagement in governments’ adoption of artificial intelligence systems, artificial intelligence researchers and practitioners spend little time reflecting on who those publics are. Classifying publics affects assumptions and affordances attributed to the publics’ ability to contribute to policy or knowledge production. Further complicating definitions are the publics’ role in artificial intelligence production and optimization. Our structured analysis of the corpus used a mixed method, where algorithmic generation of search terms allowed us to examine approximately 2500 articles and provided the foundation to conduct an extensive systematic literature review of approximately 100 documents. Results show the multiplicity of ways publics are framed, by examining and revealing the different semantic nuances, affordances, political and expertise lenses, and, finally, a lack of definitions. We conclude that categorizing publics represents an act of power, politics, and truth-seeking in artificial intelligence.

show abstract

Section: Past Literature Reviews On Publics In Public Engagement In Aimentioning

confidence: 99%

Section: Past Literature Reviews On Publics In Public Engagement In Aimentioning

confidence: 99%

Who are the publics engaging in AI?

Sieber,

Brandusescu,

Adu-Daako

et al. 2024

Public Underst Sci

View full text Add to dashboard Cite

show abstract

What is civic participation in artificial intelligence?

Sieber,

Brandusescu,

Sangiambut

et al. 2024

Environment and Planning B: Urban Analytics and City Science

View full text Add to dashboard Cite

There are increasing calls across disciplines and sectors that the public should participate in decisions about the use of artificial intelligence (AI). Public input in governmental decision-making is particularly crucial to promoting a well-functioning democracy and mitigating harms from AI. However, AI’s opacity, mutability, and resource requirements impede meaningful civic engagement particularly in urban environments. Many prior systematic reviews of civic participation and AI draw on the smart city literature. However, several other disciplines influence civic participation in AI so a siloed disciplinary focus offers only partial guidance for participation’s future role in AI. Our multi-disciplinary analysis blends works in smart cities, and in public policy, communication and, importantly, computer science to reveal distinct and highly variable pathways for civic participation. We use a sequence of manual and automated steps to conduct a structured literature analysis beginning with over 3,000 articles. We categorize authors’ work on participation in AI into five themes: participation as a natural byproduct of automating government, participation facilitated through the medium of AI, participation in AI as quantification, participation as a technocracy of trust, and participation as meaningful. With few exceptions, authors seemed not to challenge the status quo nor diminish the authority of the experts. Authors focused on the processual without the influence and AI aided in that process orientation. We conclude that the future of public participation in AI requires careful attention to become meaningful including recognition of neoliberal intent and power differentials.

show abstract

Smart Cities Data Indicator-Based Cyber Threats Detection Using Bio-Inspired Artificial Algae Algorithm

Chauhan

Chakravorty

Khang³

2023

Advances in Computational Intelligence and Robotics

View full text Add to dashboard Cite

Smart cities have benefited greatly from the quick development of information technology, such as cloud computing, sensors, and the IoT. Smart cities improve living services and analyze massive amounts of data, which increases privacy and security concerns. But managing security and privacy issues is crucial for a smart city that encourages businesses to adopt new computing paradigms. In recent years, there has been a proliferation of literature on security and privacy, covering topics like end-to-end security, reliable data acquisition, transmission, and processing, legal service provisioning, and privacy of personal data, as well as the application of bio inspired computing techniques to system design and operation. Effective computing systems have been developed by utilizing bio-inspired computing approaches for intelligent decision support. The indicator-based threat detection system with BAAA algorithm is the quickest and most efficient way to scope an environment after observation, and its usefulness is greatly influenced by the adversary rate of change.

show abstract

Collaborative Intelligence in Smart Cities: A Systematic Review

Cited by 4 publications

References 22 publications

Who are the publics engaging in AI?

Who are the publics engaging in AI?

What is civic participation in artificial intelligence?

Smart Cities Data Indicator-Based Cyber Threats Detection Using Bio-Inspired Artificial Algae Algorithm

Contact Info

Product

Resources

About