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Governance of Ethical and Trustworthy AI Systems: Research Gaps in the ECCOLA Method [article]

Mamia Agbese, Hanna-Kaisa Alanen, Jani Antikainen, Erika Halme, Hannakaisa Isomäki, Marianna Jantunen, Kai-Kristian Kemell, Rebekah Rousi, Heidi Vainio-Pekka, Ville Vakkuri
2021 arXiv   pre-print
This research analyzes the ECCOLA method for developing ethical and trustworthy AI systems to determine if it enables AI governance in development processes through ethical practices.  ...  As a result, users are calling for better AI governance practices in ethical AI systems. Therefore, AI development methods are encouraged to foster these practices.  ...  According to [7] , ethical principles alone are insufficient for developing and deploying ethical and trustworthy AI.  ... 
arXiv:2111.06207v1 fatcat:jbjez3ydwjhi3a6mxzjj2atigy

Ethical funding for trustworthy AI: proposals to address the responsibilities of funders to ensure that projects adhere to trustworthy AI practice

Allison Gardner, Adam Leon Smith, Adam Steventon, Ellen Coughlan, Marie Oldfield
2021 AI and Ethics  
Such reports beg the question as to why such systems continue to be funded, developed and deployed despite the many published ethical AI principles.  ...  and AI audit frameworks.  ...  This is particularly important to provide explanations of reasons for rejection based on inadequate ethical AI statements.  ... 
doi:10.1007/s43681-021-00069-w pmid:34790951 pmcid:PMC8197676 fatcat:ph7hvy243zdrjolkq2g6siyjqy

The relationship between trust in AI and trustworthy machine learning technologies [article]

Ehsan Toreini, Mhairi Aitken, Kovila Coopamootoo, Karen Elliott, Carlos Gonzalez Zelaya, Aad van Moorsel
2019 arXiv   pre-print
To guide technology developments, this paper provides a systematic approach to relate social science concepts of trust with the technologies used in AI-based services and products.  ...  To build AI-based systems that users and the public can justifiably trust one needs to understand how machine learning technologies impact trust put in these services.  ...  Trustworthy AI is related to normative statements on the qualities of the technology and typically necessitates ethical approaches, while trust is a response to the technologies developed or the processes  ... 
arXiv:1912.00782v2 fatcat:65yuc7yqxjd5bkc3kyul45huma

Z-Inspection®: A Process to Assess Trustworthy AI

Roberto V. Zicari, John Brodersen, James Brusseau, Boris Dudder, Timo Eichhorn, Todor Ivanov, Georgios Kararigas, Pedro Kringen, Melissa McCullough, Florian Moslein, Naveed Mushtaq, Gemma Roig (+5 others)
2021 IEEE Transactions on Technology and Society  
In this article, we outline a novel process based on applied ethics, namely, Z-Inspection , to assess if an AI system is trustworthy.  ...  To the best of our knowledge, Z-Inspection is the first process to assess trustworthy AI in practice.  ...  This work is dedicated to him.  ... 
doi:10.1109/tts.2021.3066209 fatcat:z646hl5oy5hufasowq3tsrmvue

Explainability Auditing for Intelligent Systems: A Rationale for Multi-Disciplinary Perspectives [article]

Markus Langer, Kevin Baum, Kathrin Hartmann, Stefan Hessel, Timo Speith, Jonas Wahl
2021 arXiv   pre-print
National and international guidelines for trustworthy artificial intelligence (AI) consider explainability to be a central facet of trustworthy systems.  ...  Moreover, we emphasize that explainability auditing needs to take a multi-disciplinary perspective, and we provide an overview of four perspectives (technical, psychological, ethical, legal) and their  ...  Thus, ensuring system explainability seems to be a central step towards trustworthy AI.  ... 
arXiv:2108.07711v1 fatcat:xxlwgapqhbc5ldzrzqgavme3ue

Acknowledging Sustainability in the Framework of Ethical Certification for AI

Sergio Genovesi, Julia Maria Mönig
2022 Sustainability  
In the past few years, many stakeholders have begun to develop ethical and trustworthiness certification for AI applications.  ...  This study furnishes the reader with a discussion of the philosophical arguments that impel the need to include sustainability, in its different forms, among the audit areas of ethical AI certification  ...  Sustainability as an Audit Area for an Ethical Certification of AI We argue that sustainability, as an ethical issue, should be considered when certifying ethical and trustworthy AI.  ... 
doi:10.3390/su14074157 fatcat:bmokyjqpz5c2rjnmbxzyv3t7fi

The Sanction of Authority: Promoting Public Trust in AI [article]

Bran Knowles, John T. Richards
2021 arXiv   pre-print
We discuss how existing efforts to develop AI documentation within organizations -- both to inform potential adopters of AI components and support the deliberations of risk and ethics review boards --  ...  We argue that being accountable to the public in ways that earn their trust, through elaborating rules for AI and developing resources for enforcing these rules, is what will ultimately make AI trustworthy  ...  The authors would like to thank Richard Harper for his enormously helpful comments on an early draft of this work.  ... 
arXiv:2102.04221v1 fatcat:copsnyfc5vgn5m6pa6lxctev7q

Trustworthy AI in the Age of Pervasive Computing and Big Data [article]

Abhishek Kumar, Tristan Braud, Sasu Tarkoma, Pan Hui
2020 arXiv   pre-print
Trust in AI systems is thus intrinsically linked to ethics, including the ethics of algorithms, the ethics of data, or the ethics of practice.  ...  In this paper, we formalise the requirements of trustworthy AI systems through an ethics perspective.  ...  Data Auditing: Data auditing for AI systems takes place during both development and deployment.  ... 
arXiv:2002.05657v1 fatcat:zugg3dfdpfg37ctxdy2othtafe

Trustworthy AI in the Age of Pervasive Computing and Big Data

Abhishek Kumar, Tristan Braud, Sasu Tarkoma, Pan Hui
2020 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)  
Trust in AI systems is thus intrinsically linked to ethics, including the ethics of algorithms, the ethics of data, or the ethics of practice.  ...  In this paper, we formalise the requirements of trustworthy AI systems through an ethics perspective.  ...  Data Auditing: Data auditing for AI systems takes place during both development and deployment.  ... 
doi:10.1109/percomworkshops48775.2020.9156127 dblp:conf/percom/KumarBTH20 fatcat:h3ft5ktzznfc7fyqnsdyyohfhm

From AI ethics principles to data science practice: a reflection and a gap analysis based on recent frameworks and practical experience

Ilina Georgieva, Claudio Lazo, Tjerk Timan, Anne Fleur van Veenstra
2022 AI and Ethics  
Operationalisation is required, since ethics frameworks are often not suited to be used by data scientists in the development of AI-based services or products.  ...  Therefore, in this paper, we aim to contribute to this third wave by mapping AI ethical principles onto the lifecycle of an AI-based digital service or product and combining it with an explicit governance  ...  Their process is based on the AI for social good (AI4SG) values [23] , which relate to the ethical principles in the Ethical Guidelines for Trustworthy AI [1] .  ... 
doi:10.1007/s43681-021-00127-3 fatcat:ohlfkanwwnd2pdv55rj45n7yie

Audit and Assurance of AI Algorithms: A framework to ensure ethical algorithmic practices in Artificial Intelligence [article]

Ramya Akula, Ivan Garibay
2021 arXiv   pre-print
A modern market, auditing, and assurance of algorithms developed to professionalize and industrialize AI, machine learning, and related algorithms.  ...  Governments, businesses, and society would have an algorithm audit, which would have systematic verification that algorithms are lawful, ethical, and secure, similar to financial audits.  ...  Based on the audit outcome, measures to reduce the risk interventions may enhance the result of the system across the different phases of the algorithm development.  ... 
arXiv:2107.14046v1 fatcat:ic4bq5f73rcxdg6we4qxdw6mcm

Exploring the Assessment List for Trustworthy AI in the Context of Advanced Driver-Assistance Systems [article]

Markus Borg, Joshua Bronson, Linus Christensson, Fredrik Olsson, Olof Lennartsson, Elias Sonnsjö, Hamid Ebabi, Martin Karsberg
2021 arXiv   pre-print
To help development organizations, AI-HLEG recently published the Assessment List for Trustworthy AI (ALTAI).  ...  AI-HLEG defined Trustworthy AI as 1) lawful, 2) ethical, and 3) robust and specified seven corresponding key requirements.  ...  A year later, AI-HLEG published the Ethics Guidelines for Trustworthy AI [3] that puts ethical AI as a key component of trustworthy AI.  ... 
arXiv:2103.09051v1 fatcat:vgeey7c5b5bkdinhqwxqwxefgi

Towards a Roadmap on Software Engineering for Responsible AI [article]

Qinghua Lu, Liming Zhu, Xiwei Xu, Jon Whittle, Zhenchang Xing
2022 arXiv   pre-print
To close the gap in operationalizing responsible AI, this paper aims to develop a roadmap on software engineering for responsible AI.  ...  Many ethical regulations, principles, and frameworks for responsible AI have been issued recently. However, they are high level and difficult to put into practice.  ...  Ethical audit trail records every step of AI systems from the ethics perspective.  ... 
arXiv:2203.08594v1 fatcat:b47ffuu6pfb2bh4humtgjaujtu

Systematizing Audit in Algorithmic Recruitment

Emre Kazim, Adriano Soares Koshiyama, Airlie Hilliard, Roseline Polle
2021 Journal of Intelligence  
In this article, we apply a systematic algorithm audit framework in the context of the ethically critical industry of algorithmic recruitment systems, exploring how audit assessments on AI-driven systems  ...  Such studies have informed the development of artificial intelligence systems (AI) designed to measure individual differences.  ...  These verticals are derived from a maturing of the engineering literature referred to in terms of 'AI ethics' and 'trustworthy AI' (Kazim and Koshiyama 2020a; Hagendorff 2020; Bartneck et al. 2021; Dignum  ... 
doi:10.3390/jintelligence9030046 pmid:34564294 fatcat:53chpacij5brhp6fxmrsqrqupq

Trustworthy AI: From Principles to Practices [article]

Bo Li, Peng Qi, Bo Liu, Shuai Di, Jingen Liu, Jiquan Pei, Jinfeng Yi, Bowen Zhou
2022 arXiv   pre-print
The rapid development of Artificial Intelligence (AI) technology has enabled the deployment of various systems based on it.  ...  to model development, to system development and deployment, finally to continuous monitoring and governance.  ...  Acknowledgments The authors would like to thank Yanqing Chen, Jing Huang, Shuguang Zhang, and Liping Zhang for their valuable suggestions.  ... 
arXiv:2110.01167v2 fatcat:2u7hqdrfujc5lbcsmwpmxxsd74
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