What is AI governance and why is it needed?
AI governance refers to the principles and frameworks that ensure the responsible use of AI — it’s the conductor of your AI orchestra, making sure your use of the technology is note-perfect in terms of managing risks, ensuring ethical deployment, and maintaining transparency.
Without appropriate governance techniques, organizations could run the risk of legal, financial and reputational damage as a result of misuse and biased outcomes from their algorithmic inventory. AI governance is, therefore, necessary to mitigate these threats and — on a grander scale — promote trust in AI technologies.
Defining AI governance frameworks: a multi-layered approach
AI governance consists of several interconnected layers, ranging from organizational structure to regulatory alignment. It involves establishing mechanisms to steer the development and deployment of AI technologies, with clearly defined principles, procedures and metrics crucial to transparent and well-governed AI. Significantly, a robust governance structure – which covers everything from AI adoption and development to risk management – gives organizations a platform to ensure that their AI use corresponds with their strategy, ethical principles and regulatory requirements.
Why should an organisation be responsible for AI governance?
Organisations, as the entities creating and using AI systems, play a crucial role in defining and implementing AI governance.
Sound governance practices fall under the umbrella of responsible AI, the school of thought which champions the ethical use of AI technologies. It involves developing and using AI in a way that respects rights, promotes fairness, and encourages transparency. Responsible AI is a core aspect of AI governance, as it helps ensure that AI technologies are used for the benefit of all, without causing harm or perpetuating biases.
While they are duty-bound to implement responsible structures, there is a strategic incentive for organisations to implement AI governance too. Having oversight and a comprehensive understanding of your AI inventory not only mitigates threats posed by improper governance, but it also makes it easier to monitor and update operational practices in line with evolving risks and regulations.
AI governance measures and metrics
Measuring the effectiveness of AI governance is crucial to ensure that it achieves its goals. Some metrics that can be adopted include the level of transparency and explainability of AI systems, the detection and mitigation of biases, and the impact of AI systems on stakeholders. Regular audits and assessments should be conducted to measure these metrics and identify areas for improvement.
How organisations should approach AI governance
Implementing AI governance in an organisation requires a systematic approach. It begins with familiarising oneself with all relevant ethical principles, legal requirements, and industry guidelines.
Next, organisations should assess – or commission an independent third-party to assess – their existing AI systems, data practices, and policies. This way, they can identify any gaps or areas for improvement.
Lastly, establishing monitoring mechanisms and conducting regular audits is crucial. This facilitates the assessment of the effectiveness of your AI governance practices.
What are the benefits of effective AI governance?
Effective AI governance offers myriad benefits. It helps to prevent AI harm to individuals, society, and the environment, fostering trust and social acceptance of AI systems. Ethical considerations also help enterprises meet legal and regulatory requirements that, if flouted, could result in legal consequences and reputational damage. It also contributes to the efficient and responsible use of AI, promoting scalability and transparency.
The role of everyone in AI governance
Everyone in an organisation plays a part in AI governance. From the executive team defining the AI strategy, the developers building the AI models, to the users interacting with the AI systems, everyone has a responsibility to ensure the ethical and responsible use of AI. Employees need to understand how AI works, be aware of governance issues, and actively participate in governance practices to contribute to a responsible AI environment.
Holistic AI – AI governance done right
Holistic AI helps organisations implement responsible AI governance through a suite of solutions centered around the Holistic AI Platform. This includes conducting independent AI audits to evaluate systems for bias and risks, performing in-depth AI risk assessments, and maintaining a detailed inventory of all AI systems in use.
P.S.
In our organization, we have divided AI Governance into two distinct components to facilitate a more in-depth and professional approach to addressing its complexities. These two components are AI Legal and AI Safety as shown in this picture:
