AI & SOCIETY

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Comparative legal study on privacy and personal data protection for robots equipped with artificial intelligence: looking at functional and technological aspects

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Abstract

This paper undertakes a comparative legal study to analyze the challenges of privacy and personal data protection posed by Artificial Intelligence (“AI”) embedded in Robots, and to offer policy suggestions. After identifying the benefits from various AI usages and the risks posed by AI-related technologies, I then analyze legal frameworks and relevant discussions in the EU, USA, Canada, and Japan, and further consider the efforts of Privacy by Design (“PbD”) originating in Ontario, Canada. While various AI usages provide great convenience, many issues, including profiling, discriminatory decisions, lack of transparency, and impeding consent, have emerged. The unpredictability arising from the AI machine learning function poses further difficulties, which have only been partially addressed by legal frameworks in the aforementioned jurisdictions. However, analyzing the relevant discussions yielded several suggestions. The first priority is adopting PbD as the most flexible, soft-legal, and preferable approach toward AI-oriented issues. Implementing PbD will protect individual privacy and personal data without specific efforts, and achieve both the development of AI and the advancement of privacy and personal data protection. Technical measures that can adapt to an individual’s dynamic choices according to the “context” should be further developed. Furthermore, alternative technical measures, including those to solve the “algorithmic black box” or achieve differential privacy, warrant thorough examination. If AI surpasses human intelligence, a terminating function, such as a “kill switch” will be the last resort to preserve individual choice. Despite numerous difficulties, we must prepare for the coming AI-prevalent society by taking a flexible approach.

Keywords

Artificial intelligence Robots Privacy Personal data Comparative study 

Notes

Acknowledgements

This research is supported by the research program “Human-Information Technology Ecosystem” within the Research Institute of Science and Technology for Society, Japan Science and Technology Agency.

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Copyright information

© Springer-Verlag London Ltd. 2017

Authors and Affiliations

  1. 1.Faculty of Library, Information and Media ScienceUniversity of TsukubaTsukubaJapan

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