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How To Control Risk Using Ethical AI

Although AI-driven solutions are rapidly gaining popularity across industries, it is also becoming obvious that implementation calls for careful supervision to avoid unintended harm. AI, like the majority of technologies, has the potential to expose people and businesses to a variety of dangers, risks that could have been avoided via careful consideration of potential effects early in the process.

This is where “responsible AI” enters the picture, i.e., a governance framework outlining how a particular organisation should approach the moral and legal issues raised by AI. Eliminating doubt about who would be held responsible if something goes wrong is a fundamental driver for ethical AI endeavours.

In the most recent Tech Vision survey from Accenture, only 35% of customers worldwide expressed confidence in the use of AI. And 77% said businesses should be held accountable for the improper use of AI.

However, the creation of moral, reliable AI standards is primarily left to the whim of individuals who create and implement an organization’s AI algorithmic models. This implies that the actions necessary to control AI and guarantee transparency differ from business to business.

Furthermore, without clearly defined standards and procedures in place, it is impossible to establish accountability or to come to wise conclusions about how to maintain the legality of AI applications and the profitability of brands.

The large gap in AI competence that exists between policymakers, data scientists, and developers is another significant obstacle for machine learning. Risk management experts may not always have the resources to apply their knowledge to machine learning operations and set up the proper governance and controls.

These issues served as the impetus for the Palo Alto-based Credo AI, which was established in 2020 to close the knowledge gap between data scientists’ ethical understanding and policymakers’ technical understanding in order to assure AI’s sustainable development.

Putting responsible AI into practice

Singh intends to expand the use of responsible AI governance across businesses worldwide after closing a $12.8 million Series A financing round, which was headed by Sands Capital. The money will be used to speed up product development, create a potent go-to-market team to maintain Credo AI’s leadership in the responsible AI industry, and bolster the tech policy department to support new norms and laws.

Singh and her colleagues seek to enable businesses to measure, monitor, and manage AI-introduced risks at scale. They have Fortune 500 customers in the financial services, banking, retail, insurance, and defence sectors.

The future of AI governance

Despite corporate behemoths like Google and Microsoft are lifting the veil to reveal how they’re using AI at work, responsible AI is still a young field that is continually developing.

Though it seems doubtful that legislation will change in the near future regarding AI oversight, one thing is certain: governments and private companies must collaborate to bring all stakeholders on the same page in terms of compliance and accountability.

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