“Organizations are responsible for ensuring that AI projects they develop, deploy or use do not have negative ethical consequences,” as per Gartner. Yet while 79% of executives say AI ethics is important to their enterprise-wide AI approach, less than 25% have operationalized ethics governance principles. In a new case study featuring IBM, Gartner talks about how to establish a governance framework to streamline the process of detecting and managing technology ethics concerns in AI projects.
Addressing the need for an AI governance framework
The case study observes that, “As AI is more widely adopted in business operations, organizations must ensure this technology is used ethically.” As AI use cases expand, broadly defined and abstract principles are proving to be insufficient by not providing clear processes for legal and ethical review.
IBM’s governance framework is built around four core roles within the company:
- The Policy Advisory Committee: senior global leaders who provide oversight of the AI Ethics Board and help to establish the company’s strategy and risk tolerance.
- The AI Ethics Board: a central, cross-disciplinary body that supports a centralized governance, review and decision-making process for IBM ethics policies, practices, communications, research, products and services. The Board recently published its point of view on foundation models addressing the risks that generative AI poses.
- AI Ethics Focal Points: business unit representatives trained in AI ethics, who act as points of first contact to identify concerns, mitigate related risks for each use case and escalate issues to the AI Ethics Board where required.
- An Advocacy Network: a grassroots-level network of employees across the many board workstreams who share and promote IBM’s technology ethics principles within their teams and scale AI ethics initiatives throughout the organization.
In addition, the CPO AI Ethics Project Office supports all of these initiatives, serving as a liaison between governance roles, supporting implementation of technology ethics priorities, helping establish AI Ethics Board agendas and ensuring the board is kept up to date on industry trends and company strategy.
Building a culture of responsible AI
IBM has publicly defined its multidisciplinary, multidimensional approach to AI ethics, built upon principles for trust and transparency. These fundamentals undergird the work of IBM’s AI Ethics Board, which reviews AI use cases to help ensure alignment with IBM’s principles and the evolving regulatory landscape.
Using the framework described above, IBM advances ethical AI governance through its product offerings. IBM watsonx.governance™, a component of the watsonx™ platform that will be available on December 5th, helps organizations monitor and govern the entire AI lifecycle. It helps accelerate responsible, transparent and explainable AI workflows. Its toolkit automates risk management, monitors models for bias and drift, captures model metadata and facilitates collaborative, organization-wide compliance.
IBM Consulting also provides extensive AI consulting services in adherence with our company-wide approach to AI ethics. Our experts can help organizations implement responsible, trustworthy AI across a wide range of use cases, including customer service, application modernization, talent transformation, marketing and finance operations.
Gartner, Case Study: An AI Governance Framework for Managing Use Case Ethics, Legal and Compliance Research Team, 20 September 2023.
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