Introduction:
Ethical oversight often takes a back seat to growth in the race to harness Generative AI’s (GenAI) transformative potential. However, as leaders in education, healthcare, finance, or business, we know that today’s choices (or lack thereof) will shape how this technology impacts society tomorrow. From ensuring access to preventing unintended consequences like algorithmic bias or misinformation, traceability, reliability, and consistency, GenAI ethics isn’t just a nice to have or a checkbox to click or a public relations stance—it must be a critical point for leaders to building trust within your organization and to ensure the long-term success of the individuals and organizations you are entrusted to lead in this rapidly changing AI Age. Your organization’s survival depends on it.
GenAI is Here to Stay
Generative AI has already begun to disrupt industries such as healthcare, education, finance, and businesses, from creating personalized learning pedagogies in education such as synthetic tutors and automated grading to driving innovation in healthcare diagnostics, ambiance technology to capture patients’ data and allowing health providers to spend more time with their patients versus typing in front of a computer or responding to patients email or in finance help improve economic patterns, reduce fraud or improve administrative tasks. However, these advancements come with risks, some known and others unknown or downstream in the organization and society:
- Algorithmic Inaccuracies and Biases: GenAI models train with large corpora of data, most of which come from uncurated data on the Internet. This data often reflects societal inequalities, leading to biased outcomes that can reinforce discrimination in patient care, education pedagogy, hiring, lending, and resource allocation.
- Trust and Transparency: GenAI foundational models often function as “black boxes,” making decision-making challenging to understand. This lack of transparency erodes trust among users, stakeholders, and regulators.
- Human Governance and Accountability: As we embrace GenAI’s potential to automate and improve organizational processes, human judgment and accountability remain critical to ensuring GenAI serves human values rather than replaces them.
As leaders, we must recognize that GenAI ethics frameworks can strengthen technology innovation, not hinder it. Leaders’ critical thinking centered on ethical principles with appropriate frameworks, including checks and balances, should facilitate and guide the selection, deployment, use, and monitoring of GenAI within your organization. These are not mutually exclusive or binary decisions; leaders can develop their GenAI ethics strategies centered on trust, improving decision-making, and aligning them with organizational and societal needs.
Conclusion and Recommendations:
To responsibly integrate GenAI ethics into your organization, leaders can focus on these critical principles:
- Transparency: Communicate clearly about how your GenAI applications work and what data they use, whether uncurated data from the Internet, only from your legacy system, or a combination of both. This will help your stakeholders, whether health providers, patients, educators, students, or employees and clients, build trust and be on the lookout for some of the potential challenges described earlier, such as algorithmic data biases, traceability, and transparency.
- Accountability: Define clear GenAI outcomes and who is responsible for monitoring them in your organization. Ensure that human oversight and issue escalation remain a priority.
- Inclusivity: Involve multi-functional, multi-departmental, and multi-voiced teams designing, selecting foundational models, deploying, and monitoring to minimize known and unknown risks, including bias, and equitable and consistent outcomes.
- Continuous Improvement Approach: GenAI is evolving rapidly, and GenAI ethics frameworks are also changing. Leverage current organizational processes and teams to monitor and reassess your GenAI platform as technology evolves, new challenges emerge, and regulations change.
Gen AI can offer significant opportunities for your organization and society. However, leaders should be mindful of speed, responsibility, accuracy, and ethics tradeoffs. Hence, leaders must consider GenAI ethics frameworks an integral part of their projects, not an afterthought. GenAI ethics frameworks are critical for leaders’ strategic journey to adapt, survive, and thrive in the era of AI.
Engagement Questions:
- How does your organization currently approach GenAI ethics?
- What steps can you take today to ensure your GenAI strategy aligns with your mission and values?
- Do your teams responsible for GenAI assessment, model selection, deployment, and monitoring have the appropriate tools and ethical frameworks aligned with your organization’s values, goals, and societal impact?
Useful Links
- Harvard Business Review. Eliminating Algorithmic Bias Is Just the Beginning of Equitable AI. Simon Friis and James Riley September 29, 2023, https://hbr.org/2023/09/eliminating-algorithmic-bias-is-just-the-beginning-of-equitable-ai
- McKinsey and Co. As gen AI advances, regulators—and risk functions—rush to keep pace. December 21, 2023, https://www.mckinsey.com/capabilities/risk-and-resilience/our-insights/as-gen-ai-advances-regulators-and-risk-functions-rush-to-keep-pace
Mentions:
University of San Francisco, USF School of Nursing and Health Professions AMIA (American Medical Informatics Association) American Association of Colleges and Universities (AAC&U). #GenAI Ethics, #AI Ethics, #Generative AI, #Higher Education, #Healthcare, #Financial Services, #Silicon Valley Startups, #Responsible AI, #Technology Ethics, #AI Governance, #Leadership
About the Project
This article is part of a continuous exploration – a joint journey to share insights, foster discussions, and empower leaders with the frameworks they need to navigate the complex ethical landscape of Generative AI (GenAI). I want this series to be a space to critically interrogate, question, and leverage GenAI to drive the best possible societal impact together and shape our organizations and ecosystems as a conscious, intentional set of choices – not something we just fall into because we fail to see the new opportunity space. We can all be agents of change in our organizations, communities, homes, and professional networks. Hence, I see this as a joint exploration with fellow travelers.
About the Author
Freddie Seba is a distinguished thought leader and educator specializing in Generative AI ethics. He holds an MBA from Yale and an MA from Stanford and is pursuing a Doctorate in Education at the University of San Francisco (USF), focusing on GenAI Ethics. Since 2017, Freddie has served as the program director for the Masters of Science in Digital Health Informatics at USF’s School of Nursing and Health Professions (SONHP). He teaches and mentors graduate students in this program and collaborates closely with the healthcare ecosystem. He developed and taught a course on Generative AI Ethics in Educational and Healthcare Ecosystems. Freddie is a seasoned Silicon Valley entrepreneur, co-founding and working with innovative startups in financial services, healthcare, and education. As a speaker, faculty, and writer, Freddie inspires others to navigate GenAI ethics complexities with purpose. You can find more information at www.freddieseba.com