Table 1. Overview of literature outside... | Emerald Publishing

Table 1.

Overview of literature outside of marketing on AI certification

								Decision specificity
Authors	Year	Field	Methodology	Type/part of AI	Entity proposed	Geographical focus	Mention of consumer trust	Domain	High-risk/low risk	Summary
Scherer	2015	Law	Prescriptive	Automated machines	Government	USA				Discusses the complexity of governmental regulation of AI and proposes a framework to deal with these challenges
Guihot et al.	2017	Law	Prescriptive	AI	Government and self-declaration	Global		✓	✓	Urges for the government’s involvement in standard setting for AI applications and self-declarations by industry players
Tutt	2017	Law	Prescriptive	AI	Government	USA	✓			Argues for an FDA-like institution to certify AI applications and develop AI standards in partnership with the industry
Erdélyi and Goldsmith	2018	Computer Science	Prescriptive	AI	Government	Global				Urges for a new international governmental body for standard-setting that can inform individual countries’ regulations and legislation
Winfield and Jirotka	2018	Computer Science	Prescriptive	Intelligent Autonomous Systems	Self-declaration	Global	✓			Outlines a roadmap to ethical governance, including a company’s self-declaration of ethical conduct
Floridi et al.	2018	Philosophy and Cognitive Sciences	Prescriptive	AI	Government	European Union	✓			Provides concrete recommendations for AI governance and certification within the European Union
Yanisky and Hallisey	2019	Law	Prescriptive	Data used for the development of AI	Government or (commercial) third-party	USA		✓		Proposes an “AI Data Transparency Model”. The model includes an auditing regime and certification program
Arnold et al.	2019	Industry Paper	Prescriptive	AI services for developers	Self-declaration and (commercial) third-party	Global	✓			Proposes and outlines the characteristics of a supplier certificate called FactSheet
Sharkov et al.	2021	Information and Security+	Descriptive	AI	Independent body	European Union	✓			Provides an overview of European initiatives towards AI regulation/certification and argues for an independent body to certify AI
Winter et al.	2021	Computer Science	Prescriptive	Low-risk machine learning applications	Independent body	Global			✓	Outline existing standardisation methods used in other fields and introduce four levels relating to AI’s impact on people, the environment and organisations to be certified
Falco et al.	2021	Computer Science	Prescriptive	Automated systems	Government	Global	✓			Argue for certification of automated AI systems according to three “AAA” governance principles: Assessment of risk; Audit trails; and system Adherence to jurisdictional requirements
Badran	2021	Computer Science	Descriptive	AI	(Governmental) independent body	Global				Provides an overview of the pitfalls of governmental AI regulation and opportunities for an independent regulatory agency to certify AI
Roski et al.	2021	Medicine	Prescriptive	AI	Self-declaration	USA	✓	✓		Outlines a process for the health-care industry to develop standards for AI certification to promote more trust
Mökander et al.	2022	Philosophy and Cognitive Sciences	Descriptive	High-risk AI	Government and NGO or (commercial) third-party	European Union			✓	Provides an overview of the proposed European Artificial Intelligence Act (AIA) and specifies how the proposed conformity assessments could be applied using existing literature on AI auditing
Raji et al.	2022	Computer Science and Law	Descriptive	AI	(Commercial) third-party	USA				Argues that the current landscape does not allow for effective commercial third-party algorithmic auditing and argues for solutions by drawing a connection to other certification spaces (e.g. finance, health)
Stuurman and Lauchaud	2022	Law	Prescriptive	AI	NGO or (commercial) third-party	European Union	✓		✓	Outlines the requirements for a voluntary label for medium- to low-risk AI applications and the challenges in the implementation

								Decision specificity
Authors	Year	Field	Methodology	Type/part of AI	Entity proposed	Geographical focus	Mention of consumertrust	Domain	High-risk/low risk	Summary
Scherer	2015	Law	Prescriptive	Automated machines	Government	USA				Discusses the complexity of governmental regulation of AI and proposes a framework to deal with these challenges
Guihot et al.	2017	Law	Prescriptive	AI	Government and self-declaration	Global		✓	✓	Urges for the government’s involvement in standard setting for AI applications and self-declarations by industry players
Tutt	2017	Law	Prescriptive	AI	Government	USA	✓			Argues for an FDA-like institution to certify AI applications and develop AI standards in partnership with the industry
Erdélyi and Goldsmith	2018	Computer Science	Prescriptive	AI	Government	Global				Urges for a new international governmental body for standard-setting that can inform individual countries’ regulations and legislation
Winfield and Jirotka	2018	Computer Science	Prescriptive	Intelligent Autonomous Systems	Self-declaration	Global	✓			Outlines a roadmap to ethical governance, including a company’s self-declaration of ethical conduct
Floridi et al.	2018	Philosophy and Cognitive Sciences	Prescriptive	AI	Government	European Union	✓			Provides concrete recommendations for AI governance and certification within the European Union
Yanisky and Hallisey	2019	Law	Prescriptive	Data used for the development of AI	Government or (commercial) third-party	USA		✓		Proposes an “AI Data Transparency Model”. The model includes an auditing regime and certification program
Arnold et al.	2019	Industry Paper	Prescriptive	AI services for developers	Self-declaration and (commercial) third-party	Global	✓			Proposes and outlines the characteristics of a supplier certificate called FactSheet
Sharkov et al.	2021	Information and Security+	Descriptive	AI	Independent body	European Union	✓			Provides an overview of European initiatives towards AI regulation/certification and argues for an independent body to certify AI
Winter et al.	2021	Computer Science	Prescriptive	Low-risk machine learning applications	Independent body	Global			✓	Outline existing standardisation methods used in other fields and introduce four levels relating to AI’s impact on people, the environment and organisations to be certified
Falco et al.	2021	Computer Science	Prescriptive	Automated systems	Government	Global	✓			Argue for certification of automated AI systems according to three “AAA” governance principles: Assessment of risk; Audit trails; and system Adherence to jurisdictional requirements
Badran	2021	Computer Science	Descriptive	AI	(Governmental) independent body	Global				Provides an overview of the pitfalls of governmental AI regulation and opportunities for an independent regulatory agency to certify AI
Roski et al.	2021	Medicine	Prescriptive	AI	Self-declaration	USA	✓	✓		Outlines a process for the health-care industry to develop standards for AI certification to promote more trust
Mökander et al.	2022	Philosophy and Cognitive Sciences	Descriptive	High-risk AI	Government and NGO or (commercial) third-party	European Union			✓	Provides an overview of the proposed European Artificial Intelligence Act (AIA) and specifies how the proposed conformity assessments could be applied using existing literature on AI auditing
Raji et al.	2022	Computer Science and Law	Descriptive	AI	(Commercial) third-party	USA				Argues that the current landscape does not allow for effective commercial third-party algorithmic auditing and argues for solutions by drawing a connection to other certification spaces (e.g. finance, health)
Stuurman and Lauchaud	2022	Law	Prescriptive	AI	NGO or (commercial) third-party	European Union	✓		✓	Outlines the requirements for a voluntary label for medium- to low-risk AI applications and the challenges in the implementation

Source: Authors’ own work