Building effective practices for managing personal data, collected by unmanned transport

The article addresses the problem of ensuring the privacy of data collected by unmanned transport. It is shown that the amount of data actually collected by an autonomous transport in a day is not comparable to the amount of data needed for its training. It is concluded that the approach to data collection needs to be more selective. It is noted that the data on which unmanned and connected vehicles are trained may be inaccurate or even biased. As a result, artificial intelligence is biased. This study sought to explore the provisions of the concept of a fair artificial intelligence that is intolerant of discrimination, whatever it may be. The author came to the conclusion that in reality it is practically impossible to ensure zero tolerance of discrimination by intelligent systems, as its manifestations may not always be obvious. It is rightly pointed out that artificial intelligence has the potential to undermine autonomous, rational human decision-making. The author expresses confidence that centralised data lifecycle management can be the key to consumer trust.

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