Nowadays, Artificial Intelligence (AI) is becoming more significance in adoption, be it in daily life activities or industrial operational process. From enhancing customer experience, improving operational efficiencies to automating business process, the outcomes of AI are compelling. The growing number of implementation of AI industry and business however is beneficial yet overwhelming both due to its capabilities and the threats it carry. Hence, the world is introduced to a framework that ensures the reliability of adoption of AI called AI governance. This post uncovers the principles of AI governance framework and other aspects of AI risk protection.
AI governance Framework: Objective and Principles
AI Governance aims to remove various issues circulated around an AI model, making the model trustworthy and adoptable without prejudice. It is a framework based on multiple principles including;
1. Explainability – An AI system should be transparent where decision-making algorithm applied by the model are clear and understandable.
2. Fairness – An AI system should not be biased and free from discrimination against individuals or groups based on race, gender, religion, or other personal characteristics.
3. Integrity – An AI system should ensure data validity and algorithm integrity including where the data being collected from, how data is used and the appropriateness in handling data as well as respecting data privacy and security.
4. Resilience – Resiliency and robustness are important as it ensure an AI system is effective and reliable at all time even in challenging and unpredicted events or failures.
5. Regulation Compliance – An AI system should be built and designed to continuously align with regulation legal standards in order to protect the public from AI risk.
The risk of AI – AI Governance and Organisation Responsibility
Ethical issues related to AI have been present since its inception in the 1950s. Today, newly launched AI products such as ChatGPT and Bard, which continuously capture the public’s attention, have expanded the issue to a greater extent. The risks associated with AI are formidable. Recently, we hear country leaders calling for technology leaders to ensure protection from AI risk. Even an AI luminary, Geoffrey Hinton, has decided to step back from the AI development world. Subsequently, AI governance has emerged as a way to remove AI risks by building trust in AI through regulation but it should as well be complemented by organizational responsibility to establish a holistic framework.
AI adoption, AI governance framework and the future
Despite the understandable risks associated with AI, rejecting such powerful technology that can accelerate operational and business growth would be a shortsighted decision. However, it is important to develop AI systems that can perform at the highest standards without compromising public safety and trust in AI adoption. This can be achieved through the effective establishment of an AI governance framework, as failing to do so may lead to critical AI risks in the future.
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