3 Truths about AI assurance
Updated: Aug 20, 2022
Artificial intelligence (AI) is advancing in many industries, and ensuring that AI is deployed responsibly is becoming a real challenge for many organizations.
Regulations intend to promote AI trustworthiness by defining guidelines to ensure that AI systems meet regulatory requirements.
In August 2022, the WEF promoted certification programs to make AI innovation safer.
What does this mean?
🕵️ Development of new assurance tools by subject matter experts to identify risks and provide independent oversight of the assurance service.
Assessing not only the model, but also the data and contextual deployment of an AI system, and its impact on responsible AI.
Develop recognized and trusted standards to share the same expectations for a product, process or service.
Provided by independent third parties or certified assessors.
Audit trail
Everyone must play their part!
💪Today, the big challenge is to shape the AI assurance ecosystem effectively.
We need to align the different stakeholders (government policies, regulators, researchers, developers, users, concerned citizens, legislators, investors) who have different expectations of responsible AI today.
Is it useful?
🏆 Initially, it will be helpful to be compliant, as the lack of commonly accepted standards is a significant barrier to the wider adoption of AI.
It can also help address the problem of disconnected silos in building and maintaining AI in various organizations.
But we will not achieve a universal standard that is applicable everywhere, given the need to consider the broader context, the variety of aspects and uses of an AI system, and the current alignment of skills and responsibilities.
Across all industries and organizations, AI is not a one-size-fits-all solution, and neither will certification.
So it's time to start getting ready and taking the first steps for certification: risk identification and strategy development.
For more information on how to start it, contact us.
