Comparison and Analysis of 3 Key AI Documents: EU’s Proposed AI Act, Assessment List for Trustworthy AI (ALTAI), and ISO/IEC 42001 AI Management System

Golpayegani, Delaram; Pandit, Harshvardhan J.; Lewis, David

doi:10.1007/978-3-031-26438-2_15

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…The establishment of auditable industry standards is a key step in promulgating the broad base of organizational compliance, which may be relied upon by various regulations. An important recent development in this vein is the launch of ISO 42001 by the ISO on December 2023 57 , which was designed to facilitate compliance with the EU AI Act while being aligned with related AI safety guidelines, such as the AI Risk Management Framework (RMF) by the U.S. National Institute of Standards and Technology (NIST) 55,58,59 .…”

Section: Introduction Of Iso 42001 Aims Certificationmentioning

confidence: 99%

The Emerging Role of ISO 42001 Certification in Fostering the Deployment of Responsible Generative AI Healthcare Solutions

Thiers, MD PhD,

Harned

2024

Preprint

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The growing excitement about the potential positive impact of generative AI (GenAI) solutions in healthcare has been tempered by uncertainty on how to ensure that such solutions are deployed safely and effectively. A core issue is that the current product-centric regulatory oversight model does not apply well to a technology that adapts to the operating environment and becomes enmeshed with medical practice in a non-deterministic manner. This difficulty has led to the development of alternate approaches to foster the responsible deployment of GenAI solutions that are focused on the organizations developing and using the technology, as they are uniquely positioned to prevent and quickly address issues as they occur. One emerging approach is via the certification with the ISO 42001 standard, which defines the structure for auditable AI Management Systems (AIMS) in organizations developing and/or deploying AI solutions. The process of ISO 42001 certification can enable healthcare organizations to build adaptive and auditable AIMS that mitigate risks while supporting the deployment of trustworthy AI. The wide adoption of ISO 42001 certification by healthcare organizations would allow for the utilization of beneficial GenAI solutions while potentially facilitating the performance of oversight functions by regulators and payers. This article introduces the ISO 42001 implementation process in healthcare organizations and describes the next steps in the operationalization of this new GenAI risk mitigation approach.

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Section: Introduction Of Iso 42001 Aims Certificationmentioning

confidence: 99%

The Emerging Role of ISO 42001 Certification in Fostering the Deployment of Responsible Generative AI Healthcare Solutions

Thiers, MD PhD,

Harned

2024

Preprint

View full text Add to dashboard Cite

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Case study on delivery time determination using a machine learning approach in small batch production companies

Rokoss,

Syberg,

Tomidei

et al. 2024

J Intell Manuf

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Delivery times represent a key factor influencing the competitive advantage, as manufacturing companies strive for timely and reliable deliveries. As companies face multiple challenges involved with meeting established delivery dates, research on the accurate estimation of delivery dates has been source of interest for decades. In recent years, the use of machine learning techniques in the field of production planning and control has unlocked new opportunities, in both academia and industry practice. In fact, with the increased availability of data across various levels of manufacturing companies, machine learning techniques offer the opportunity to gain valuable and accurate insights about production processes. However, machine learning-based approaches for the prediction of delivery dates have not received sufficient attention. Thus, this study aims to investigate the ability of machine learning to predict delivery dates early in the ordering process, and what type of information is required to obtain accurate predictions. Based on the data provided by two separate manufacturing companies, this paper presents a machine learning-based approach for predicting delivery times as soon as a request for an offer is received considering the desired customer delivery date as a feature.

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SHAPES Project Pilots' Self-assessment for Trustworthy AI

Rajamäki

Rocha

Perenius

et al. 2022

2022 12th International Conference on Dependable Systems, Services and Technologies (DESSERT)

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Comparison and Analysis of 3 Key AI Documents: EU’s Proposed AI Act, Assessment List for Trustworthy AI (ALTAI), and ISO/IEC 42001 AI Management System

Cited by 3 publications

References 12 publications

The Emerging Role of ISO 42001 Certification in Fostering the Deployment of Responsible Generative AI Healthcare Solutions

The Emerging Role of ISO 42001 Certification in Fostering the Deployment of Responsible Generative AI Healthcare Solutions

Case study on delivery time determination using a machine learning approach in small batch production companies

SHAPES Project Pilots' Self-assessment for Trustworthy AI

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