AI Governance Playbook
Dr. Jagreet Kaur
Researcher, Author, Intersection of AI and Quantum and helping Enterprises Towards Responsible AI, AI governance and Data Privacy Journey
The world is in the middle of a global experiment, with rapid technological advancements and data algorithms shaping our destinies. Artificial intelligence (AI) is an important player in this experiment, with its rise causing both excitement and uncertainty. This AI Playbook guides executives and board members, providing ethical guidance and strategic decision-making advice regarding using AI responsibly. The Playbook is informed by various business perspectives, offering additional context, texture, and perspective to the conversation surrounding AI ethics, use, and oversight.
Xenonstack AI Governance Playbook
The Xenonstack AI Governance Playbook is a comprehensive guide outlining critical governance and oversight pillars necessary for creating a culture of responsible AI use. The framework offers a balanced approach between safety and innovation, short-term profits, and long-term value creation, with people at its core. It covers foundational AI platforms, machine learning, Gen AI, and large language models and addresses ethical considerations such as bias, human rights, privacy, disinformation, and copyright issues.
The Playbook has been written by women who represent various functions and leadership roles and is helpful for anyone interested in understanding and overseeing the implementation of new technologies. It provides a first step and is designed to be agile and adapt as our understanding of AI impacts unfolds.
The Playbook supports board members and company leaders in ensuring their organizations deploy safe, relevant, compliant, and responsible AI policies and products. It merges ethical, regulatory, and strategic considerations, emphasizing long-term value, responsible stewardship, and comprehensive situational awareness of converging forces. Key takeaways include the necessity of adaptable AI governance frameworks, robust talent strategies, and proactive tech risk intelligence.
It's imperative that all business leaders, regardless of the functional area, strive to align AI advancements with risk oversight, strategic growth, ethical principles, and societal well-being. This Playbook is an indispensable resource for leaders seeking a sustainable, proactive approach to AI governance.
THE FIVE PILLARS OF ORGANIZATIONAL AI GOVERNANCE
The five pillars of Organizational AI Governance apply to various entities, including businesses, societal organizations, and government bodies. These pillars primarily focus on the role of the board, but it is equally essential for management to understand and integrate them into their organizations:
AI Oversight and the Duty of Care
As a member of the board of directors at a technology company, I believe in the essential concept of duty of care. This means that the board must ensure the safety and well-being of others, which includes the level of competence and business judgment expected of a board member.
In addition, the board should make informed decisions in good faith to serve the organization and its stakeholders. Emphasizes that duty of care extends beyond the tech stack and includes regulatory risk, people and culture, brand health, M&A, the geopolitical landscape, stakeholder considerations, and strategic growth.
To effectively oversee AI, the board must be fit for purpose and create an AI governance framework with management. This framework should ensure accountability and risk assessments, cybersecurity, data management, fairness and ethics, human capital oversight, privacy, transparency, and customer and key stakeholders' trust.
I acknowledge that these considerations are critical for every organization to understand, but the capacity to respond may differ based on the organization's size and budget. Thus, the recommendations and questions here serve as a guidepost for all boards, who can determine how to prioritize and resource them based on individual circumstances. By committing to trust-building, transparency, regulatory adherence, and future readiness, the board can reinforce the power of these values as they relate to the company's technology footprint.
The duty of care extends beyond the board to include senior leadership within the organization. This means that CEOs and other executives have a legal responsibility to maintain ongoing discussions with the board regarding AI strategies, emphasizing ethical and legal considerations, collaborations with third parties, and the creation of long-term value. This dialogue should be informed by continuous learning and staying up to date at an oversight level of AI advancements and their broader business and societal impacts.
For example, a CEO could ensure that the company's leadership has a firm grasp on the evolving landscape of technology risks, such as privacy and cyber considerations, AI-related biases, disinformation, and data provenance and quality. They should engage the board as active partners in building a forward-thinking perspective. This way, the leadership team and the board can work together to balance innovation with integrity, foresight with ethics, and growth with sustainability.
To achieve this, the board should ask management thoughtful and relevant questions that get to the heart of core issues related to strategy and risk. For instance, they could ask how the company stays abreast of the latest AI technological advancements and their potential impact on the industry. Also, they could inquire about the company's education program to ensure a baseline of fluency in AI and related tech issues as they relate to the industry and business model.
By engaging in strategic discussions on AI implementation and fostering collective intelligence through "divide and conquer", the board can align AI with ethical and strategic objectives. They should also evaluate the board and succession planning to ensure that the board's skillsets matrix aligns with the technology strategy, including AI.
Ethics, Risk and Responsible Stewardship
As a board member, some questions you could ask to ensure responsible AI use within the company are:
1. How is AI being integrated into different company domains, and how are these applications aligning with ethical norms and business objectives?
2. Are third-party AI tools being used by the company, and if so, how are they being evaluated and monitored for compliance with ethical and legal standards?
3. What protocols are in place for continuously monitoring AI usage, and how are failures and unintended consequences addressed?
4. How does the company ensure that data provenance, model design, training, and implementation align with principles prioritizing fairness, transparency, and privacy?
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5. Are policies in place for human oversight of AI models, and how are corrective actions taken as needed?
6. How does the company communicate and educate stakeholders on policies and procedures, including how data will be used for AI training and adoption?
Oversight of Strategy and Adaptability
The board should closely monitor the effectiveness of the company's AI practices in enabling strategy. They should be adaptable and stay aligned with technological advancements and the competitive landscape to ensure that the company's AI initiatives remain effective and responsible.
For instance, they should differentiate between what AI applications are table stakes or operational versus those that strategically fuel growth. They should also consider what accuracy is acceptable for a product release or use of third-party tools. This impacts competitiveness, brand, and credibility, so it should be discussed and weighed carefully.
Additionally, the board should encourage and facilitate cross-functional collaboration in AI strategy formulation. This is because data silos are antithetical to adequately managing complex, interconnected risks and harnessing potential opportunities. By integrating AI initiatives across business functions, the company ensures a unified and practical approach to AI, aligning technological innovation with the company's overarching goals and values. For example, a board may consider organizing questions to management using a matrix of internal vs. external AI usage overlaid with the organization's various functions.
Furthermore, the board should help management develop strategies to navigate data access challenges in vendor systems, especially in the face of disruptions such as database intrusions or ransom demands. This includes setting appropriate contractual obligations for vendors to protect their data and IP. They should also identify areas of experimentation with AI in a controlled environment, keeping in mind risk mitigation and ensuring safe exploration. For instance, they can start small with a few low-risk use cases, learn from them, and then plan accordingly for the larger, more complex and likely more value-added opportunities.
Lastly, the board should encourage cross-functional collaboration in AI strategy development. This can help ensure that the strategy crafted is more robust and considers opportunities and constraints across business units and products, IT systems, regulation and compliance, data availability, talent bench strength, customer needs and norms, and other vital areas applicable to the organization. They should also refine and adjust as the future unfolds, providing clear and continual oversight of strategy.
Holistic Situational Awareness
Board members are responsible for recognizing the social and environmental implications of the technologies they oversee, particularly AI. For instance, the exponential growth of AI presents challenges related to environmental and social issues. One of the critical considerations that the board should focus on is ensuring that the company's enterprise-wide risk management (ERM) system includes a comprehensive and inclusive approach to identifying all relevant risks and opportunities that impact key stakeholders and longer-term value creation.
To achieve this, the company should deeply understand its core material technology issues and opportunities to assess its universe of technology risks and opportunities adequately. Additionally, the company should understand the intersection of its core tech issues, risks, and opportunities with other aspects of sustainability and social issues. For example, how much say do the subjects of data collection have over how their data is shared and treated? What is the company doing to ensure that the data it uses or generates for its products or services is analyzed for provenance, quality, balance, and lack of bias and discrimination?
The board should ensure that management fully considers and integrates these issues into their ERM system and other risks and opportunities related to sustainability and social issues. Additionally, the board must question management on how it approaches the provenance, equity, integrity, fairness, and safety of the AI it develops and deploys, focusing on overseeing risk, ethics, and impact.
Furthermore, the board, in partnership with management, must ensure that AI applications are developed and utilized in ways that are sustainable and contribute positively to the company's environmental goals. This means considering the energy consumption of data centres, the lifecycle of AI technologies, and the potential for AI to contribute to more efficient operations and reduced waste.
Finally, the board and management should keep people's impacts central to the strategy. They should consider workplace and talent impacts of the deployment of AI for assistance in hiring, promotion, firing, and diversity, equity, and inclusion (DEI) decisions. They should also ensure that the product life cycle from design to implementation is created to mitigate bias and weigh and take precautions to prioritize stakeholders' privacy concerns.
In summary, board members must ensure that they are asking the right questions of management regarding AI and technology, risk, and impact on the environment and society. By doing so, they can ensure that the company is not only mitigating harm but leveraging AI to actively foster environmental stewardship and aligning technological progress with the urgent need for ecological preservation and sustainability.
Talent, Incentives and Culture
The focus on AI has been primarily on technology, but it is essential to remember that people, not machines, ultimately drive its application and impact. Companies need to create a talent strategy with AI and technology systems strategy to ensure they are fit for purpose in rapidly evolving times.
Culture focuses people on the right metrics, behaviours, and outcomes, and thus, ensuring that the organization's talent strategy holistically addresses the implications of AI and exponential technology is crucial. It is recommended that organizations take a multi-stakeholder approach to managing tech risk, ensuring responsible use, application, data validation, and deployment of AI. Compensation should reflect the potential risks and opportunities of AI and related tech, and transparency should be encouraged on how compensation, accountability, and ethics align as they relate to AI and associated technologies.
Boards should evaluate the impact of talent strategy and conduct a talent gap assessment to identify critical gaps in talent and skills that must be filled in the short term. They should also examine training from multiple angles and solicit team member feedback to ensure that AI education programs are inclusive and relevant to everyone. Boards should review the company's code of conduct to expressly address AI ethics and develop a process for how unanticipated AI outcomes will be handled.
Board members should ask management talent various questions about AI risks and opportunities related to talent, DEI strategy, and how company culture and compensation align with the organization's AI strategy. Preparing for the unexpected and developing a process to handle unanticipated AI outcomes is essential.
CONCLUSION
This playbook is a call to action for executives and board members. It emphasizes their essential role in guiding organizations through the AI era with foresight, integrity, and a sense of responsibility. The five pillars of AI governance provide an ethical decision-making framework, talent management strategy, and risk intelligence. As AI continues to shape the business and social landscape, the playbook highlights the crucial role of each decision-maker in achieving the best outcomes for their organizations and society as a whole.
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