From generative AI to chatbots, businesses are finding new and innovative ways to use artificial intelligence for increased efficiency and process automation. However, as these tools continue to evolve, it becomes more imperative for organizations to make sure AI is used responsibly.
AI governance is essential to any company using AI tools, helping to keep it safe, ethical, and compliant with legal standards.
AI governance empowers organizations to establish policies and frameworks to mitigate risks, protect privacy, and establish ethical guidelines while leveraging technology to improve business operations.
What is AI governance?
AI governance is the policies, procedures, and frameworks that outline how AI systems are developed, used, and maintained to ensure compliance with ethical standards and legal regulations.
An effective AI governance plan includes input from AI developers, users, and stakeholders to prevent privacy infringement and misuse and protect human rights.
Who is responsible for AI governance?
The team or individual(s) responsible for AI governance varies by organization or industry. In many Fortune 500 companies, it falls under the Chief AI Officer(s) (CAIOs) and the Chief Data Analytics Officer(s) (CDAOs).
Additional team members or committees, such as a board of directors or an AI ethics board, may be involved. However, every organization using AI is responsible for making sure the right governance team and policies are in place to protect employees and users.
What’s the difference between AI governance and AI ethics?
AI governance and AI ethics are similar in that both aim to ensure AI technology does not infringe on privacy, human rights, or ethical standards. The two functions work together but operate at different levels.
AI ethics focuses on the principles that guide AI use. It addresses issues like fairness, accountability, privacy, and security.
AI governance defines how organizations execute these principles through their policies, regulations, and frameworks to ensure responsible AI use and compliance with legal and regulatory standards.
Put simply, AI ethics is the “why” behind the protocols, and AI governance is the “how” or the actual approach to enforcing ethical practices.
The importance of AI governance
AI governance ensures that AI use aligns with ethical principles and regulatory requirements.
Agentic AI operates with more autonomy than traditional AI models and requires less human intervention. AI agents have the ability to make independent decisions based on a specific goal rather than following predefined rules.
Without strict governance measures, agentic AI systems could make autonomous decisions with minimal human oversight, leading to unintended consequences. Organizations can mitigate these risks, establish accountability, and protect privacy by establishing protocols to outline AI use.
Risk mitigation
AI systems can inherit biases from training data and generate false information, called hallucinations.
Implementing a sound governance plan helps to prevent these issues through ongoing testing for fairness and accuracy.
Privacy
AI systems collect and use many different types of data, some of which may include sensitive personal information. Without the right safeguards in place, this data could be misused or exposed.
AI governance ensures data is collected, stored, and used safely to protect individuals and organizations.
Accountability
What happens when an AI system makes an error?
AI governance assigns roles, sets ethical guidelines, and ensures transparency and accountability in AI decision-making.
AI governance examples
Here are three examples of how organizations can implement policies and frameworks to ensure responsible, ethical AI use.
AI governance in healthcare
Doctors use an AI model to help with medical diagnoses and treatment plans. Patient care coordinators also use conversational AI to answer basic questions. To ensure these systems are being used responsibly, the medical institution has developed an AI governance framework that includes:
- Audits to prevent bias: AI workflows are audited to reduce biases in medical diagnoses, ensuring fair treatment for patients.
- Physician review: AI recommendations must be reviewed and approved by a licensed physician before being used in patient care.
- Regulatory compliance: AI applications must meet HIPAA and FDA standards for medical AI tools to protect patient privacy and safety.
AI governance in banking
A financial services organization uses autonomous AI agents for algorithmic trading and traditional AI for fraud detection and credit scoring.
The company has implemented AI governance protocols that include:
- Fair lending policies: Credit decisions must be checked to ensure that biases do not affect loan approvals.
- AI auditing: AI-powered financial models are subject to regular audits for accuracy and fairness.
- Regulatory compliance: AI systems must adhere to financial regulations, such as the Fair Credit Reporting Act (FCRA) to protect consumers.
AI governance in technology
A technology provider specializing in AI solutions for government agencies helps optimize public services from predictive policing to fraud detection in welfare programs.
To ensure responsible AI use, the company follows:
- Ethical standards: AI models must be free from bias, especially in sensitive areas like criminal justice or social services.
- Data privacy protocols: AI tools must comply with privacy laws, including GDPR and the Freedom of Information Act (FOIA).
- Ethics board review: A committee is responsible for reviewing and approving high-risk AI projects to ensure they align with public interest.
Comprehensive AI governance protocols help to ensure that AI tools are used for innovation and operational efficiency while mitigating risks, protecting privacy, and maintaining data accuracy.
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