Abstract
The semantic substance that gives body to the concept of [Trust], and its slight variation according to the distinct contexts of experience and/or according to the different entities involved, is here briefly addressed in order to identify what is really at stake when we define [Trust] as a core criterion for accepting the development and deployment of artificial intelligent systems (either embodied or non embodied) in different domains of human life.
Highlighting the deep biological roots the concept stems from, the paper posits the existence of a preconceptual primitive common to most living organisms. Human conceptualising capacity incorporates this primitive and through a process that is socially and culturally determined shapes its rich meaning-nuanced character.
Claiming that the concept is primarily inherently associated with an implicit or explicit risk assessment by the potentially affected entity, the paper identifies two fundamental cognitive dimensions involved in that assessment: an intuitive and a rational. The rational risk assessment bases itself on the individual’s direct experience or on the empirical evidence provided by the experience of others. In cases such as those of adopting a scientific or technological innovation, and lacking the competence to ground their judgement, the end-user’s assessment will rely heavily on a certification issued by organisms, publicly acknowledged as competent, that declare the risk free character of a product or procedure.
It is in this context that benchmarking, standardisation and certification assume a fundamental role across the processual pipeline. The permanent and systematic monitoring of how all these new technologies evolve in their different contexts of use, updating predefined sets of standards will guarantee their quality, efficiency, reliability, integrity and safety.
The paper concludes by advocating the urge of making standards in general, and the standardisation of AIS in particular, available as open-source for the sake of a universal harmonious and beneficial technological development.
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Notes
- 1.
- 2.
For a comprehensive view on the different philosophical approaches to the concept cf. https://plato.stanford.edu/entries/trust/.
- 3.
According to Engelman and Herrman (2016) evidence indicates that human friendships have evolved especially robust forms of trust that are relatively immune to the contingencies of a volatile and ever-changing environment.
- 4.
Steven Pinker (2005) refers that there is evidence that trust has a strong evolutionary value.
- 5.
Those that don’t result from actual personal or from reported experiences.
- 6.
Independently of its lec.
- 7.
Game theory has its roots in an article by the Hungarian mathematician John von Neumann, who subsequently published his book on the Theory of Games and Economic Behavior with Oskar Morgenstern in 1944. Game theory models a social situation as a strategic game. Such a game consists formally of three elements: the players who interact with each other; a set of available actions for each player; and a so-called pay-off function for each player. The possible outcomes that an individual player can achieve depend not only on the player's own behaviour but also on the other players with whom he or she interacts.
- 8.
The author played this game when visiting the museum in 2019.
What seems to be a video taken by another visitor when playing the game is presently available in the internet at https://www.youtube.com/watch?v=kzBzi8LNk34.
- 9.
We lack evidence if this behaviour can also be found in organisms as plants.
- 10.
https://vax-trust.eu/. VAX-TRUST examines vaccine hesitancy as a broad societal phenomenon aiming to identify the societal factors that shape beliefs and attitudes towards vaccinations in current societies.
- 11.
- 12.
- 13.
For the sake of conciseness we will not analyse structures as: “X trusts Y with Z” or “X trusts Z to Y”, which we consider as being a specification of the basic (1) X trusts Y.
- 14.
- 15.
The fact that for many consumers white label products, though cheaper, are viewed with suspicion is a proof of that.
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- 17.
- 18.
Ethics, in this sense, (i) reflects on the nature of the changes technological innovation introduces in human reality by modifying behavioural patterns and lifestyles; (ii) identifies the eventual disruption caused on common values, accepted norms and relations and consequently the eventual harm to individuals, to the communities or to the environment; (iii) it defines a human-centred approach where human well-being and dignity as well as the respect for other species and the planet are prioritised.
- 19.
- 20.
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- 22.
Technical Committee: Meysam Basiri, Instituto Superior Técnico, Portugal, Pedro Lima, Instituto Superior Técnico, Portugal, Daniele Nardi, Sapienza University of Rome, Italy, Gianluca Bardaro, The Open University, UK, External Expert: Alessandro Saffiotti, Örebro University, Sweden.
- 23.
- 24.
- 25.
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- 27.
Keynote, at the International Conference on Robot Ethics and Standards 2019, London Southbank University.
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- 30.
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Ferreira, M.I.A. (2022). In Machines We Trust?. In: Ferreira, M.I.A., Tokhi, M.O. (eds) Towards Trustworthy Artificial Intelligent Systems. Intelligent Systems, Control and Automation: Science and Engineering, vol 102. Springer, Cham. https://doi.org/10.1007/978-3-031-09823-9_2
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