UDC 53.08
DOI: 10.36871/2618-9976.2022.05.001
Authors
Taymanov R.Ye.
Head of Laboratory for Metrological Maintenance of Computerised Sensors and Measuring Systems,
D.I. Mendeleyev Institute for Metrology; Full Member of the Metrological Academy; IMEKO TC 7 Member;
ICMI Member; Editorial Advisory Board Member: International Journal on Advances in Systems
and Measurements, Soft Measurements and Computing; Saint Petersburg, Russia
Sapozhnikova K.V.
Deputy Head of Laboratory for Metrological Maintenance of Computerised Sensors and Measuring
Systems, D.I. Mendeleyev Institute for Metrology; IMEKO TC 7 Member; ICMI Member; Editorial Advisory
Board Member: Sensors & Transducers Journal, Soft Measurements and Computing; Saint Petersburg,
Russia
Abstract
The issues of ensuring measurement trustworthiness of multidimensional quantities by means of measuring systems based on artificial intelligence, both strong and weak, are considered. The issue choice has been stimulated by a discussion at an interdisciplinary conference of the RAS. The effectiveness of comparing the evolution of the nervous system and natural intelligence with the development of artificial intelligence is shown. Based on the analogy with human formation as a personality, an approach to the organisation of learning and selflearning system based on artificial intelligence is proposed and justified. This approach partly resembles a verification procedure, but has significant differences from it. It is noted that the methods for increasing the trustworthiness of measurement results through the use of metrological selfchecking, which have been developed so far in metrology, can serve as an effective analogue for systems based on AI. Due to the novelty and relevance of the arising challenges connected with AI, to prepare highly skilled experts in metrology is necessary. It is planned to realise this task taking into account the achievements of neurophysiology and psychology, within the framework of the educational metrological cluster being developed on the initiative of the State Scientific Centre D.I. Mendeleyev Institute for Metrology.
Keywords
Trustworthiness, Artificial intelligence, Metrological selfcheck, Soft measurements, Industry XNUMX
