Artificial Intelligence and the Internet of Things: UK Policy Opportunities and Challenges

Bunz, Mercedes; Janciute, Laima

doi:10.16997/book25

Cited by 8 publications

(12 citation statements)

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“…These types of technologies integrate the entire AI process, from data collection, to storage, to transmission and analysis, resulting in rich high value-added data resources (Peter et al 2016). Notably, the Internet of Things (IoT) also integrates basic infrastructures and supported technologies and is emerging as an R&D direction in current AI research (Bunz and Janciute 2017;Tripathy 2017).…”

Section: Case Studymentioning

confidence: 99%

A hybrid approach to detecting technological recombination based on text mining and patent network analysis

et al. 2019

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Detecting promising technology groups for recombination holds the promise of great value for R&D managers and technology policymakers, especially if the technologies in question can be detected before they have been combined. However, predicting the future is always easier said than done. In this regard, Arthur's theory (The nature of technology: what it is and how it evolves, Free Press, New York, 2009) on the nature of technologies and how science evolves, coupled with Kuhn's theory of scientific revolutions (Kuhn in The structure of scientific revolutions, 1st edn, University of Chicago Press, Chicago, p 3, 1962), may serve as the basis of a shrewd methodological framework for forecasting recombinative innovation. These theories help us to set out quantifiable criteria and decomposable steps to identify research patterns at each stage of a scientific revolution. The first step in the framework is to construct a conceptual model of the target technology domain, which helps to refine a reasonable search strategy. With the model built, the landscape of a fieldits communities, its technologies, and their interactions-is fleshed out through community detection and network analysis based on a set of quantifiable criteria. The aim is to map normal patterns of research in the domain under study so as to highlight which technologies might contribute to a structural deepening of technological recombinations. Probability analysis helps to detect and group candidate technologies for possible recombination and further manual analysis by experts. To demonstrate how the framework works in practice, we conducted an empirical study on AI research in China. We explored the development potential of recombinative technologies by zooming in on the top patent assignees in the field and their innovations. In conjunction with expert analysis, the results reveal the cooperative and competitive relationships among these technology holders and opportunities for future innovation through technological recombinations.

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Section: Case Studymentioning

confidence: 99%

A hybrid approach to detecting technological recombination based on text mining and patent network analysis

et al. 2019

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“…Today, many companies developing AI rely on collecting, analyzing, and sharing personal data in both their product development and as part of their business models. Data is often collected without the full knowledge of consumers or concern for individual privacy (Bunz & Janciute, 2018). While individual privacy can be upheld by anonymizing data, doing so would significantly challenge the current business models of many companies, including Facebook and Google.…”

Section: What Are the Risks?mentioning

confidence: 99%

“…As such, finding sufficient, quality, and representative data has proved to be one of the most difficult barriers faced by new companies seeking to develop AI-powered technologies (Element AI, 2018). To reduce barriers for new entrants to the AI industry, Canada should partner with provinces, territories, and private enterprises to create large databases that are accessible to AI developers (Bunz & Janciute, 2018). As the use of individual data raises serious ethical implications, the government must ensure that all data that is provided publicly has first been completely cleared of any personal identifiers.…”

Section: The Government Of Canada Should Create and Facilitate The Cr...mentioning

confidence: 99%

“…To uphold trust when using AI within government, limits should be placed on the use of AI for decisions that have serious impacts on human lives. In these cases, AI should only be used to augment human decision making, rather than replace it (Bunz & Janciute, 2018).…”

Section: The Government Of Canada Should Develop and Implement A Seri...mentioning

confidence: 99%

“…In Canada, ethical questions surround the use of algorithmic decision-making in sensitive areas like health care, insurance, and policing. In particular, the potential for human bias to become embedded within the decision-making of AI-powered technologies raises serious concern (Bunz & Janciute, 2018). Due to the disruptive potential of AI, Canada must also work to evaluate and mitigate the adverse impacts that automation could have upon the Canadian workforce.…”

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confidence: 99%

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Artificial Intelligence and the Internet of Things: UK Policy Opportunities and Challenges

Cited by 8 publications

References 0 publications

A hybrid approach to detecting technological recombination based on text mining and patent network analysis

A hybrid approach to detecting technological recombination based on text mining and patent network analysis

Leading the Way: How the Canadian Government can Continue to Foster the Development of a Robust and Ethical Artificial Intelligence Industry

Digital Childhood?

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