Artificial intelligence by any other name: a brief history of the conceptualization of “trustworthy artificial intelligence”

Abstract

Recent years have seen an increase in artificial intelligence (AI) capabilities and incidents. Correspondingly, there has been an influx of government strategies, panels, dialogues and policy papers, including efforts to regulate and standardize AI systems [12,20,37,52]. A first step in most of these efforts is to delineate the scope of the resulting document, typically by either outlining a range of standard technical definitions of AI [76,85] or referencing existing scholarly work [73]. After defining their scope, many policy documents published by governments delve deeper into the 'type' of AI they wish to solicit from industry players and deploy nationally or globally. This largely serves to ensure that the strategies, policy discussions and AI-related milestones sketched within these documents are guided by a 'north star' , or overarching goal. The north star should be comprehensible to all who read and implement the document. Describing the north star allows a non-technical audience to follow and partake in the relevant policy discussions, though it does not replace technical definitions. Although more could be said as to why this is being done and whether it is sensible, such discussion is outside the scope of this paper. Instead, I focus on and contextualize some of these 'north star' definitions themselves. In particular, I explore one of the most prominent recent descriptions: the EU's concept of "trustworthy AI. " I explain its background, its international effects and its drawbacks in more depth. What is in a name? What is in "trustworthy AI?".

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“…As a starting point, a historical perspective of the trustworthy AI concept is given. Accordingly, Stix (2022) discuss its history and find as main related concepts the following ones: 'ethical AI', 'AI for good', 'beneficial AI ', and 'responsible AI'. Moreover, Laux Wachter & Mittelstadt (2023) bring together the notion of TAI (Trustworthy AI) with the one of acceptability arguing that equal attention needs to be provided to both the potential of AI to produce trust to humans and to erode the trustworthiness of humans and public institutions.…”

“…This is directly captured in the two main components of trustworthy AI: "(i) its development, deployment, and use should respect fundamental rights and applicable regulation, as well as core principles and values, ensuring an 'ethical purpose', and (ii) it should be technically robust and reliable" (EU Commission, 2019). Stix (2022) identifies five meanings of trustworthy AI: "(i) trust in the proper functioning and safety of the technology, (ii) the technology being worthy of the trust of the humans making use of it or encountering it otherwise, (iii) humans making use of it or encountering it seeing the technology as trustworthy, (iv) humans making use of it or encountering it experiencing the technology as trustworthy, and (v) the technology that is worthy of trust at all". The human-AI relationship needs to be developed in the paradigm of trust while making sure to (de)construct trustworthiness by embedding corresponding mechanisms that facilitate risks' acceptance that one the one side AI brings (Laux, Wachter & Mittelstadt, 2023) and on the other side humans, the human-AI dynamics considering technical, user, and societal perspectives bring (Laux, Wachter & Mittelstadt, 2023).…”

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“…La IA ha abierto una serie de debates entre los investigadores relacionado con la ética de dicha tecnología. Entre las preocupaciones principales frente a la IA, se encuentra el sesgo algorítmico, la transparencia y la explicabilidad, la seguridad de los vehículos autónomos, la preocupación por la violación de la privacidad a causa de la vigilancia generalizada y los efectos económicos y políticos del desempleo tecnológico (Stix, 2022). Contrariamente, existe otro término denominado IA para el bien.…”

“…Contrariamente, existe otro término denominado IA para el bien. El término se refiere a "los sistemas de IA que ayudan a resolver problemas globales complejos previamente identificados para la sociedad, beneficiando así a la humanidad" (Stix, 2022, p. 2, citando a ONU, 2015. Otro de los términos asociados a la IA, según Stix (2022), es la IA beneficiosa.…”

“…El término se refiere a "los sistemas de IA que ayudan a resolver problemas globales complejos previamente identificados para la sociedad, beneficiando así a la humanidad" (Stix, 2022, p. 2, citando a ONU, 2015. Otro de los términos asociados a la IA, según Stix (2022), es la IA beneficiosa. Esta se refiere a la tecnología de IA que beneficia a la sociedad en general y, por lo tanto, al medio ambiente y que al mismo tiempo evita daños definibles e indefinibles al entorno.…”