How to Use Human Resources to Managing Risk in a Responsible Admin

How to Use Human Resources to Managing Risk in a Responsible Admin ...

While AI-driven solutions are becoming a mainstream technology across industries, it has also become clear that deployment requires careful monitoring to prevent unintentional damage. AI has the potential to expose individuals and businesses to a variety of threats, risks that might otherwise have been mitigated early on in the process.

This is where responsible AI comes in, essentially, a governance framework that identifies how a specific organization should resolve the ethical and legal challenges posed by AI. A key motivation for responsible AI initiatives is to resolve uncertainty about who is accountable if something goes wrong.

According to Accentures'' latest Tech Vision report, only 35 percent of worldwide customers trust how AI is being implemented. And 78 percent believe companies must be held liable for their misuse of AI.

The development of ethical, trustworthy AI standards is largely done at the discretion of those who create and deploy a company''s AI algorithmic models. This means that the standards required to regulate AI and ensure transparency are vary from business to business.

There is no way to establish accountability and make informed decisions about how to keep AI applications compliant and profitable, even if there are no established policies and processes in place.

Another significant challenge of machine learning is the enormous AI expertise divide between policymakers and data scientists and developers. Credo AI, which was founded in 2020 to bridge the gap between policymakers'' technology and data scientists ethics knowledge, has spawned many challenges.

Putting responsible AI into practice

Singh, who led the $12.8 million Series A financial round, hopes to extend the responsible AI governance to more businesses around the globe. The money will be used to strengthen product development, build a robust go-to-market team to support Credo AI''s lead in AI category development, and strengthen the tech policy function to support emerging standards and regulations.

Singh and her team aim to enable enterprises to measure, monitor, and manage AI-introduced risks at an all-time high.

The future of AI governance

Despite equities like Google and Microsoft slowly putting the curtain on how they are approaching AI in their workplace, responsible AI is a relatively new subject that is still evolving.

Singh claims that she envisions a future in which enterprises prioritize responsible AI as they do cybersecurity. Similar to what we saw on climate change and cyber safety issues, we anticipate more disclosures about data and AI systems.

While legislation modifications to AI oversight may seem unlikely in the near future, one thing is that certain policymakers and private organizations must work together in order to get all stakeholders on the same page in terms of compliance and accountability.

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