AI Safety Depends on More Than Just Tech. It’s About Human Buy-In
Organisations worldwide are struggling to implement data governance strategies that can help them scale AI safely. And the problem isn’t just about the tech – it’s about people.
As AI continues to advance at an unprecedented rate, data governance has become a critical component of ensuring AI systems operate responsibly. However, a recent report highlights that the biggest hurdles in implementing effective data governance are not related to technology, but rather people and processes.
Ditching the IT Silo
Data governance is often seen as an IT issue, with responsibility falling squarely on the shoulders of the technology department. But this approach is no longer sufficient. “Organisations are beginning to understand that data governance is a business imperative, not just an IT function,” says Susan Etlinger, a senior fellow at the Altimeter Group. “Moving data governance out of the IT silo and into the mainstream of business decision-making is essential for ensuring that AI systems are used responsibly.”
Securing Executive Buy-In
To achieve this, organisations must secure executive buy-in and make data governance a top priority. This means getting executives to understand the importance of data governance and to make it a key component of their overall strategy. “Executives need to be involved in the decision-making process around data governance, and they need to be held accountable for ensuring that data governance is implemented effectively,” says Dr. Helen Nissenbaum, a professor of philosophy at New York University.
A Human-Centric Approach to AI Governance
Implementing effective data governance requires a human-centric approach, one that takes into account the needs and perspectives of all stakeholders. This includes not just IT professionals, but also business leaders, data scientists, and even employees who will be impacted by AI decisions. “Data governance is not just about technology; it’s about people and processes,” says Dr. Rachel Plotnick, a professor of computer science at the University of Illinois. “Organisations need to take a holistic approach to data governance, one that takes into account the social and cultural implications of AI.”
What this means:
Organisations that want to scale AI safely and responsibly need to take a human-centric approach to data governance. This means moving data governance out of the IT silo and into the mainstream of business decision-making, securing executive buy-in, and implementing a holistic approach that takes into account the needs and perspectives of all stakeholders. By doing so, organisations can ensure that AI systems are used responsibly and that data governance is a key component of their overall strategy.
