Artificial intelligence has touched almost every use case in nearly every industry. Its benefits are undeniable, but so are the risks. If left ungoverned, AI systems can damage your corporate reputation or worse, according to Navrina Singh, founder and CEO of Credo AI.
During a recent talk at the AI and machine learning (ML) conference Scale TransformX, Singh explained why AI governance is key.
Read on to learn what Singh said AI governance means, how unintended consequences of ungoverned AI can span a spectrum of core areas, and how good AI governance can build trust, mitigate risk, and position enterprises for growth.
AI governance is the discipline used to steer the development of AI by providing and assuring comprehensive oversight and organizational accountability to deliver responsible AI—AI that is auditable, fair, compliant, and explainable—at scale.
Good AI governance is essential to avoid unintended consequences arising from the use of AI. For example, bias in training datasets may propagate down the line and show up in AI systems. ML applications may be unfair, especially across different demographics, and AI systems could be susceptible to adversarial attacks. Unmanaged, these risks can expose companies to regulatory compliance issues and brand damage and could potentially block business growth.
Figure 1. Six common (but not quite accurate) reasons organizations say they’re not addressing AI governance. Image credit: Navrina Singh, Credo AI
Companies that have doubled down on AI and governed their AI technologies from end to end know it’s a game-changer. AI-first organizations—those built on AI—deploy at scale quickly. They build ML applications within their enterprise but also actively purchase ML systems and algorithms from third-party vendors. Among other benefits, governance allows faster procurement cycles and the ability to leverage new markets.
A side benefit is that setting up AI governance requires the participation of many stakeholders, including oversight professionals from compliance, risk, audit, and other functions, as well as technical stakeholders. Consider it a team sport.
Organizations that fail to address AI governance will pay the price by lagging in their ability to scale AI quickly and in a compliant manner, said Singh. The excuses for not addressing AI governance are many: There’s no regulation requiring it, it’s too soon to implement, no one else is doing it (see the figure above). These are myths, she said.
Simply put, good governance is good business. Companies building differentiation by using AI have already started implementing good governance practices and building in tools for good governance. You can’t afford to wait.
For more about how comprehensive AI governance can help organizations successfully build AI that is compliant, trustworthy, explainable and fair, watch Singh’s talk, “The Governance of Artificial Intelligence,” and read the transcript here.