The ISO/IEC 42001:2023
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Abstract
Artificial Intelligence (AI) and Machine Learning offer extraordinary potential for innovation for society and businesses: from advanced diagnostics to complex data analysis, right through to process automation. However, inappropriate use or a lack of control over these technologies exposes companies to new and complex risks. ISO/IEC 42001:2023 is the first certifiable international standard for the safe and reliable development and implementation of Artificial Intelligence systems.
GLOBAL CONSULTING S.A.S. supports organisations across all sectors on this pioneering journey, providing best practices for the responsible management of risks and operational aspects related to AI, ensuring transparency and absolute adherence to ethical principles.
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Method
- Identification and mitigation of risks associated with AI implementation, ensuring the adoption of appropriate control and security measures.
- Integration of Ethics: We emphasise and apply ethical principles and values in the use of AI systems, ensuring fairness, non-discrimination and respect for privacy.
- Compliance: We assist organisations in strictly adhering to data protection laws and new institutional regulations.
- Human-Centric Approach: We guide companies to prioritise human well-being, safety and user experience in the design and use of algorithms.
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Advantages
- Transparency and Trust: Promotes the use of transparent and responsible AI systems, reassuring customers, business partners and stakeholders.
- Reputational and Legal Protection: It promptly identifies vulnerabilities (such as algorithmic cognitive biases or security flaws), avoiding penalties or damage to the company’s reputation.
- Competitive Advantage: Positions the company as a pioneer and ethical leader in the adoption of new technologies, becoming a crucial differentiating factor in the market and in high-level partnerships.
- Sustainable Innovation: Enables you to harness the full potential of Artificial Intelligence whilst ensuring you retain full control over the machine’s decision-making processes.
