GenAI Ethics for Leaders #6: Intellectual Property and Human Centrality in the Age of Generative AI

GenAI Ethics for Leaders #6: Intellectual Property and Human Centrality in the Age of Generative AI

Freddie Seba Freddie Seba

Freddie Seba

MBA | MIPS | EdD Candidate - Org. & Leadership Focusing on GenAI Ethics | AI Ethics Thought Leader | Speaker | Faculty | Serial Entrepreneur | Former Global Corporate Executive | Lifelong Learner

发布日期: 2025年2月6日
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Introduction

Last week, two remarkable developments sent shock waves through the technology and business worlds, encouraging leaders to rethink their GenAI strategies.

  1. DeepSeek, a Chinese GenAI Startup, Shocked Markets: DeepSeek demonstrated that GenAI models can be created using open-source frameworks and cost-effective, less expensive equipment. Their approach challenges the hegemony of BigTechs such as NVIDIA, Meta, Google, OpenAI, and others, whose high-end hardware and proprietary models were considered essential for GenAI development a few days ago. This disruption reportedly wiped out over $1 trillion in market value across these major players (Business Insider, 2025).
  2. U.S. Copyright Office Reaffirms Human Centrality:? The U.S. Copyright Office released new guidelines clarifying that machine-generated content is not copyrightable. In contrast, human-generated content retains copyright protection even using tools like GenAI. This pronouncement reinforces that humans in the loop are critical in the creative process to meet legal and ethical standards (U.S. Copyright Office, 2024).

Together, these developments highlight two critical challenges for leaders in the AI era: a) Intellectual Property (IP) management and the ethical dilemma of human replacement in GenAI-driven workflows. b) GenAI is a nascent technology that continues to evolve rapidly. Its leading players, BigTech disruptors, are not immune to disruptions from new entrants, such as DeepSeek.

This article explores how GenAI Ethics frameworks can help leaders navigate technology and regulation changes, fostering organizational growth and human empowerment.?

Recap of Previous Articles in the GenAI Ethics for Leaders Series

In previous articles, we examined:

  1. Algorithmic Bias and Inaccuracies – How biases in AI models impact decision-making and fairness.
  2. Privacy and Security Concerns – GenAI risks sensitive data, including breaches and misuse.
  3. Intellectual Property and Compliance Risks – GenAI-generated content's legal and ethical challenges.
  4. Traceability and Accountability – The importance of making GenAI decisions explainable and ensuring responsibility in deployment and regulatory compliance.
  5. Upskilling and Deskilling – Develop initiatives to provide stakeholders with GenAI literacy, ensuring they understand GenAI's capabilities and challenges. Encourage critical thinking and creativity that complement GenAI-lead efficiencies versus compete or replace.

These articles underscored the need for strong GenAI ethics frameworks to align technological advancements, growth, and profitability with organizational ethics, mission, and stakeholder trust. Now, in this article, we touch on the issue of deskilling and how leaders can counterbalance it by embracing GenAI ethics frameworks and best practices.

Real-World Use Cases: Healthcare, Higher Education, and Financial Services

Healthcare

  • Supporting Caregivers, Not Replacing them: GenAI-powered tools can help doctors and nurses analyze medical images and patient data faster and more accurately. But if we over-rely on GenAI like we sometimes do with our car navigation apps, we risk losing the crucial human touch in healthcare. The key is using GenAI to support healthcare professionals, not replace them.
  • Intellectual Property in Personal Healthcare: Consider GenAI-powered apps that remind patients to take their medications. Who owns the data—the app developer, the healthcare provider, or the patient? Leaders must create clear frameworks that protect patient privacy and ensure data integrity while leveraging these tools for better health outcomes.

Higher Education

  • Faculty and GenAI-Enhanced Learning: GenAI can generate course content, auto-grade assignments, and offer personalized tutoring. But we can't let technology undermine academic integrity. Universities need clear policies on using GenAI in teaching and learning, ensuring faculty remain central to the educational process.
  • Copyright in AI-Generated Research: As GenAI tools become more common in academic research, institutions must determine how to credit human authorship while preventing plagiarism. Leaders need to ensure that GenAI is a collaborator, not a shortcut.

Financial Services and Banking

  • The Role of Financial Advisors and Bank Tellers: GenAI chatbots are making financial services more efficient. But at what cost? Leaders must balance automation with customer trust and data security, ensuring financial services remain practical, ethical, and human-centered.
  • Regulatory Compliance in GenAI Co-Created Financial Reports: As GenAI takes on more decision-making roles in finance, leaders must ensure compliance with financial disclosure laws and prevent legal risks tied to machine-generated insights.

领英推荐

Building GenAI Enhanced Workforce

  • Empowering Employees, Not Replacing Them: GenAI should be seen as a tool to enhance human capacities, not reducing human dignity. Leaders need to adopt Human-in-the-Loop strategies that keep people in control of decision-making.
  • Investing in Upskilling: Leaders must invest in reskilling and training their employees to thrive in a GenAI-driven world. Upskilling your team isn't just about survival—it's about giving your team the tools to innovate and excel.
  • Creating Ethical GenAI and Copyright Frameworks: Leaders must proactively define how GenAI-generated content is owned, used, and credited. Robust copyright ethical framework to ensure compliance with regulations and protects the organization's moral integrity.
  • Generating Value Through GenAI-Human Collaboration: Copyright isn't just about protecting content—it's about creating new business models. Leaders should leverage GenAI to generate new revenue streams and drive workforce transformation, focusing on growth instead of reduction.

Conclusion: Why Leaders Must Strike a Balance Between GenAI Intellectual Property and Human Replacement

Leaders should proactively address intellectual property and human replacement challenges, which call for intentional strategies that mix technology and human expertise. Creating programs that enhance your workforce and stakeholders aligned with your organization's mission and goals will help your organization thrive in a GenAI-driven era grounded in humans.

Leadership Reflection: Key Questions to Consider

  1. How can leaders consider new copyright challenges in GenAI-generated content to protect their assets by keeping humans in the loop?
  2. How can leaders get better returns on investments (ROI) by considering cost-effective GenAI solutions from new startups, in addition to BigTech's?
  3. What upskilling strategies can leaders implement to prepare for GenAI enhanced workforce in education, health care and financial services?
  4. How can a GenAI-driven copyrightable content creation strategy drive growth, revenues and employee satisfaction?

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 a faculty at 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 Education 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


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. GenAI tools are utilized for this series, including ChatGPT, Grammarly, Speechify,? ZoomAI, and others.


Useful Information & References

Mentions

University of San Francisco University of San Francisco School of Nursing and Health Professions AMIA (American Medical Informatics Association) American Association of Colleges and Universities (AAC&U) Coalition for Health AI (CHAI) #GenAIEthics, #DigitalHealthInformatics, #AIAccountability, #Traceability, #ResponsibleAI, #HumanCenteredTech, #Leadership, #TechnologyEthics #GenAI #AIethics #Leadership #ResponsibleAI #DigitalTransformation #FutureOfWork

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