Why Generative AI Is Disrupting the Core of the Internet

© 2025 Freddie Seba. All rights reserved.

Introduction: GenAI Is Reshaping Online Discovery & Challenging Objectivity

The internet’s foundation—typing a query, comparing links, selecting a source—is being redefined by Generative AI (GenAI). As users turn to synthesized GenAI responses over traditional search engines, familiar information retrieval patterns, credibility, and monetization erode. Technology isn’t neutral (Winner, 1980); it reflects the power of those who design and control it. Authentic leaders must actively engage with GenAI, not passively receive it.

Recent indicators of this shift:

• MIT Technology Review (2025): “The end of internet search as we know it” highlights GenAI’s ability to bypass traditional search altogether.
• Adobe Blog (2025): A 1200% spike in U.S. retail traffic from GenAI platforms reflects changing consumer behavior.

This article explores how GenAI transforms search, its relevance to the Seba GenAI Ethics for Leaders Framework, and how leaders across industries can respond with integrity and foresight.

GenAI in Higher Education: Preserving Academic Integrity

GenAI summaries risk replacing deep inquiry and undermining source attribution in higher education. Faculty worry about the loss of traceable knowledge and weakened critical thinking.

Leadership Considerations:

• Design traceable, open-access GenAI references.
• Advance GenAI literacy among faculty and students.
• Require human validation of GenAI-generated academic content.

GenAI in Healthcare: Clinical Decision Support & Accountability

GenAI systems in triage or rare disease diagnostics synthesize journal articles, EHR data, and vitals into care suggestions. However, transparency is limited, and data integrity varies.

Leadership Considerations:

• Keep clinicians in the loop to validate synthesized summaries.
• Ensure transparency in AI-sourced medical recommendations.
• Maintain privacy standards (e.g., HIPAA) and attribution for journal data.

See Wong et al. (2021), which evaluated a widely used GenAI-based sepsis tool and found gaps in real-world performance.

GenAI in Financial Services: Risk, Search & Real-Time Decisions

Financial institutions use GenAI for real-time portfolio suggestions, credit checks, and fraud detection. But if unchecked, black-box GenAI can trigger ethical and regulatory risks.

Leadership Considerations:

• Require explainability for GenAI-generated recommendations.
• Perform fairness audits for loan and credit decisions.
• Assign human review for fraud alerts and systemic outcomes.

Ethical Framing: Centering Humans in GenAI Strategy

Like all technologies, GenAI is shaped by those who build and deploy it. Without strong ethical oversight, it risks reinforcing bias, eroding privacy, and diminishing transparency.

Guiding Principles for Leaders:

• Engage, don’t evade: Understand and shape GenAI from the outset.
• Build adaptive frameworks: Ethics and governance must evolve with the tech.
• Err on the side of humans: Where outcomes are high-stakes, preserve human judgment and accountability.

Conclusion & Recommendations

GenAI is transforming how we search, evaluate, and act on information. Prepared leaders will be better positioned to guide its integration ethically and strategically.

Recommendations:

• Create internal GenAI ethics and oversight teams.
• Increase GenAI literacy across teams and departments.
• Protect intellectual property and enforce traceability.
• Keep final decisions—especially in regulated sectors—in human hands.

About the Author

Freddie Seba is a thought leader in Generative AI ethics. He holds an MBA (Yale) and an MA (Stanford) and is a doctoral candidate at the University of San Francisco, where his research focuses on GenAI ethics. Freddie is a Silicon Valley entrepreneur, advisor, and faculty member who writes and speaks globally on responsible GenAI strategy.

More: freddieseba.com | LinkedIn

Mentions & Gratitude

University of San Francisco | USF School of Nursing and Health Professions | AMIA | AAC&U | Coalition for Health AI | Stanford HAI

#GenAIEthics #ResponsibleAI #DigitalTransformation #HumanCenteredAI #Leadership #AIAccountability

References & Useful Links

• Adobe Blog. (2025, March 17). Traffic from GenAI is up 1200%
• MIT Technology Review. (2025, January 6). The end of internet search
• Wong et al. (2021). Sepsis prediction tool evaluation

Seba GenAI Ethics for Leaders Framework: Previous Topics

• #1: Navigating Bias in GenAI Solutions – Addressing unintended machine bias.
• #2: Ensuring Data Privacy in GenAI – HITL safeguards for data compliance.
• #3: Accountability & Traceability – Responsibility in AI-driven outcomes.
• #4: Workforce & Skills – Augmenting human capability, not replacing it.
• #5: Intellectual Property & AI Content – Defining authorship and ownership.
• #6: Cost-Cutting vs. Human-Centered GenAI – Ethical scaling strategies.
• #7: Humanizing GenAI Agents – Oversight in critical decision-making.
• #8: Autonomy in Regulated Industries – Robust frameworks for compliance.