6 Important Reasons Why Governance is Needed for AI Usage

As a powerful tool, AI continues to transform our world, but one essential question still remains: How can we ensure that we use AI for good? Stanford’s AI Index, which analyzes the governance in 127 countries, reveals that interest in AI-related policymaking is increasing.

Fears around misinformation, deepfakes, and the impact of AI on democracy have inspired a range of proposals to regulate AI, but the debate about the best approach continues. Focusing on the ways that humans can help AI tools make fair decisions requires a balanced approach to AI governance, transparent laws, and secure ethical frameworks. This article will explore AI governance and 6 important reasons why it is needed.

What is AI Governance?

AI governance is all about ensuring that the benefits of machine learning (ML) algorithms and other types of AI are accessible to everyone fairly and equitably.

The goal is to promote the ethical application of AI so that it is free of bias and its use is private, accountable, safe, and transparent. But to be effective, AI governance needs to bring together federal agencies, industry organizations, system designers, researchers, and public interest groups to:

• Ensure that artificial intelligence vendors can profit from their technology as well as realize the benefits without societal harms and injustices
• Give developers practical guidelines and ethical codes of conduct
• Create a mechanism to measure the social and economic impact of AI
• Develop regulations that enforce the safe usage of AI

6 Principles of Ethical AI Use

The ethical use of AI depends on six principles, and by having AI principles set in place, governance can help guide how and when AI is used.

• Empathy: AI systems need to understand the social impact of their responses as well as respect human feelings
• Fairness: The systems cannot perpetuate existing societal biases, even unintentionally, so that it doesn’t violate human rights
• Transparency: Decision-making mechanisms in AI must be clear so that accountability and scrutiny are possible
• Unbiased: AI must be trained on data that has been regulated and assessed to remove bias that may perpetuate
• Accountability: It must be necessary to determine who is responsible for an adverse outcome from AI usage
• Safety: Society and individuals must be protected from AI risks, including data quality, decision-making, and system architecture

Risks of Not Having AI Governance

Without effective AI governance, it can perpetuate biases, exacerbate inequalities, and even compromise individual privacy. Algorithms left unchecked could make critical decisions without accountability and possibly endanger lives, especially in healthcare and finance. It would change how AI is used in positive ways and limit its growth.

More than that, without standardized regulations, there is a greater chance that someone can maliciously use AI for deepfakes, disinformation, or cyberattacks. It’s important to address these threats now by developing comprehensive AI governance frameworks.

Whether or not AI is applied for good depends on the people who create, develop, implement, and monitor its usage. The metaphorical cat is out of the bag, so the next step is to ensure businesses govern their usage of AI so that it’s only applied in ways that enhance lives and society.