Ethics in AI: Protecting Privacy and Stakeholder Trust in Private Language Models
November 12, 2024
🌍 Exploring AI Ethics Through a Human Lens
I’m thrilled to share my recent coauthored article, "Balancing Bytes and Ethics: Stakeholder Implications of Private LLMs," published in the Journal of Applied Business & Economics. In this piece, we review the ethical implications of private large language models (PLLMs), focusing on how these technologies impact stakeholders—from shareholders to employees, customers, and communities.
Why This Research Matters
As AI technology grows, private LLMs (like GPT-based models fine-tuned for individual organizations) bring unprecedented opportunities for automation, personalization, and decision-making. Yet, these advances raise unique ethical questions, especially around privacy, data protection, and the balance of power in the digital world. This paper provides a framework to help organizations navigate these ethical waters with transparency, accountability, and a commitment to long-term value.
Who Should Read This Article?
This article is for executives, AI enthusiasts, policymakers, and professionals who want to understand how to deploy AI responsibly. If you’re in tech leadership or anyone responsible for guiding the ethical use of AI, this piece offers actionable insights.
What You’ll Learn
In "Balancing Bytes and Ethics," you’ll discover:
- The ethical framework we've proposed to help organizations balance stakeholder interests in developing and deploying PLLMs.
- Insights on privacy risks, regulatory compliance, and intellectual property concerns, each illustrated with real-world examples.
- Practical recommendations for building transparent, trustworthy AI systems that respect data rights and safeguard against misuse.
Snapshot: Key Findings from Our Study
Below is a table summarizing some of our key findings on stakeholder concerns and ethical considerations:
| Stakeholder | Primary Concerns | Ethical Considerations |
|---|---|---|
| Shareholders | Data privacy risks, compliance costs | Responsible innovation, sustainable value |
| Employees | Job displacement, skills requirements | Upskilling programs, fostering transparency |
| Customers | Data privacy, transparency of use | Secure data handling, informed consent |
| Society | Environmental impact, digital equity | Sustainable practices, fair access, and inclusion |
With this article, my coauthors and I aim to contribute a comprehensive approach to managing the ethical challenges posed by PLLMs. You’ll walk away with a deeper understanding of how to foster trust and implement AI ethically in any organization.