Three breaking GenAI developments—autonomous R&D, IP collisions, and deepfake breaches—underscore why ethical leadership cannot wait.

© 2025 Freddie Seba. All rights reserved.

Introduction

GenAI is evolving faster than internal or external governance can keep up. This edition explores three critical developments that signal a growing need for leadership grounded in ethics and foresight:

• Forethought’s R&D automation scenario and the potential for a “GenAI intelligence explosion.”
• Anthropic’s legal challenge over GenAI training and copyright infringement claims
• GenNomis’ exposure of explicit AI-generated content due to failed content safeguards

As authentic leaders, we must proactively establish ethical frameworks—not as reactionary measures but as forward-looking strategies.

Autonomous R&D: Innovation on Autopilot?

GenAI is now designing, testing, and improving its models:

• Opportunities: Faster breakthroughs, exponential R&D scaling
• Risks: Loss of oversight, lack of transparency, governance gaps

Leadership Response:

• Establish GenAI governance before autonomy scales
• Maintain human-in-the-loop checks at all stages
• Document GenAI’s evolution, improvements, and risks

GenAI & Copyright: Fair Use or Legal Overreach?

Anthropic is being sued for training GenAI models on copyrighted books:

• Core Issue: Is this “fair use” or a rights violation?
• Implication: Legal ambiguity around model training and creative works

Leadership Response:

• Audit GenAI training data for provenance and IP exposure
• Develop policies in collaboration with legal counsel
• Stay updated on copyright and fair use legal trends

Content Moderation Failure: A Wake-Up Call

GenNomis exposed over 95,000 AI-generated images, including illegal content:

• Failure: No prompt filtering, content safety, or data security
• Fallout: Reputational risk, legal consequences, user harm

Leadership Response:

• Enforce AI content moderation and storage protocols
• Proactively monitor prompts and generated outputs
• Plan for misuse scenarios with mitigation playbooks

Use Cases Across Sectors

Healthcare

• One LLM misdiagnosed 83% of pediatric cases (Barile et al., 2024)
• GenAI must augment, not replace, clinical decisions

Higher Education

• GenAI detectors falsely flag non-native English writers (Liang et al., 2023)
• Focus on GenAI literacy, not policing AI use

Financial Services

• Regulators call for transparency and explainability (Phillips, 2024)
• Embed traceability and human oversight in GenAI-based decisions

Ethical Leadership Takeaways

• Build GenAI ethics frameworks before an incident
• Educate teams on GenAI’s capabilities and limits
• Keep final decisions human-led in high-impact areas
• Anticipate evolving laws and adapt policies accordingly
• Communicate transparently with internal and external stakeholders

Conclusion

GenAI is not neutral. It reflects the values—or vulnerabilities—of its creators and implementers.

To the extent that leaders act early and ethically, GenAI can support strategic growth while aligning with mission and public trust.

Building the Seba GenAI Ethics Framework

This newsletter is part of a more extensive series that informs the Seba GenAI Ethics for Leaders Framework. Previous editions cover:

• Bias and fairness
• Transparency and explainability
• Privacy and data protection
• Accountability and compliance
• GenAI in education, healthcare, and finance

Each issue contributes to a practical roadmap for responsible GenAI integration.

About the Author

Freddie Seba is a recognized thought leader in Generative AI ethics. He holds an MBA (Yale) and an MA (Stanford) and is a doctoral candidate in Organizational Leadership (USF). Freddie teaches in the Master of Science in Digital Health Informatics program at the University of San Francisco and advises institutions and industries on GenAI strategy, equity, and ethical adoption.

More: freddieseba.com | LinkedIn

Transparency Statement

This article reflects insights from ongoing research, practical leadership experience, and doctoral work on GenAI ethics. GenAI tools, including ChatGPT and Gemini, are used for drafting and analysis; the author authored, reviewed, and published the final content. Select material may also appear on LinkedIn and Substack for accessibility.

Mentions & Gratitude

University of San Francisco | USF School of Nursing and Health Professions

AMIA | AAC&U | Coalition for Health AI | Stanford HAI

#GenAI #GenAIEthics #Leadership #ResponsibleAI #AIethics #HumanCenteredAI #DigitalTransformation

References

Barile, J., Margolis, A., Cason, G., et al. (2024). Diagnostic accuracy of a large language model in pediatric case studies. JAMA Pediatrics, 178(3), 313–315. https://doi.org/10.1001/jamapediatrics.2023.575

Brittain, B. (2025, March 28). Anthropic says chatbot AI training makes fair use of books. Reuters. https://www.reuters.com/technology/anthropic-says-chatbot-ai-training-makes-fair-use-books-2025-03-28

Burgess, M. (2025). An AI image generator’s exposed database reveals what people used it for. Wired. https://www.wired.com/story/genomis-ai-image-database-exposed

Forethought. (2025, March 26). Will AI R&D automation cause a software intelligence explosion? https://www.forethought.ai/blog/ai-rd-automation-explained

Liang, W., Yuksek Gonul, M., Mao, Y., Wu, E., & Zou, J. (2023). GPT detectors are biased against non-native English writers. Patterns, 4(7), Article 100779. https://doi.org/10.1016/j.patter.2023.100779

Phillips, T. (2024, September 26). The risks of generative AI agents to financial services. Roosevelt Institute. https://rooseveltinstitute.org/publications/the-risks-of-generative-ai-agents-in-financial-services

© 2025 Freddie Seba. All rights reserved.