AI for Good: Navigating the Legal Challenges of Ethical AI

As both a startup advisor and an angel investor focused on ethical innovation, I’m often in the room when founders wrestle with tough questions about how to build AI responsibly. The energy is infectious—teams tackling climate change, improving access to mental health care, and revolutionizing how we learn. But amid the ambition, a common question arises: How do we ensure this technology serves the public good without creating new harm? That’s where the law—and ethical foresight—must step in.

From healthcare diagnostics to climate modeling, artificial intelligence is powering some of the most exciting breakthroughs of our time. But as AI becomes more capable—and more integrated into decisions that affect human lives—it also raises thorny questions about bias, accountability, and fairness. In the race to build AI for good, the legal system is still playing catch-up.

As both an attorney and an angel investor in mission-driven tech, I’ve seen this tension up close. Startups working at the intersection of AI and impact often have compelling visions—equitable access to education, real-time support for mental health, carbon tracking—but lack clear legal guardrails to guide responsible development. The result is a challenging balance between speed and ethics, innovation and liability.

Why “AI for Good” Needs Legal Infrastructure

The phrase “AI for good” has become a rallying cry for technologists, researchers, and entrepreneurs. But what does it mean in practice?

At its core, ethical AI development involves building models that are fair, transparent, and aligned with human values. But without legal standards or accountability mechanisms, those aspirations risk becoming marketing slogans rather than enforceable norms.

For example, consider an AI-powered hiring tool that promises to reduce bias in recruiting. If the training data is flawed or unrepresentative, the algorithm may reinforce existing inequalities. Even if the intent is positive, the outcome can still cause harm—and under current law, responsibility is often murky.

In these cases, legal frameworks must evolve to answer questions like:

• Who is liable when an AI system causes harm?

• What disclosures are required for users interacting with AI?

• How do we protect marginalized groups from automated discrimination?

• What standards define algorithmic fairness, and who gets to decide?

These are not theoretical issues. They are urgent questions that shape whether AI truly benefits society—or simply entrenches existing power structures under a new name.

Regulation Is Coming—But It’s Fragmented

Governments around the world are beginning to address these challenges, but progress is uneven. The European Union’s AI Act is perhaps the most comprehensive attempt to date, classifying AI systems by risk and imposing stricter rules on high-impact use cases like biometric surveillance or credit scoring.

In the United States, the approach has been more piecemeal. Agencies like the FTC and DOJ have issued guidance on AI and discrimination, while states like California are exploring their own AI laws. President Biden’s 2023 Executive Order on AI called for a coordinated federal strategy—but concrete legislation remains elusive.

For entrepreneurs and legal advisors, this fragmented landscape means constant vigilance. Startups working on ethical AI must not only design for good—but also document their decisions, monitor model behavior, and be prepared to explain how fairness and safety were prioritized throughout development.

A Role for Investors and Legal Counsel

Investors also play a critical role in shaping ethical AI. At the early stages, it’s easy to overlook compliance in favor of traction. But embedding legal and ethical considerations into the product roadmap from day one is not just a matter of risk mitigation—it’s a differentiator.

Legal advisors can add value by helping founders identify where regulation is headed, develop internal governance practices, and create meaningful transparency. For example, we’ve worked with clients to:

• Draft ethical AI policies aligned with international standards

• Conduct algorithmic impact assessments

• Develop model documentation that anticipates scrutiny

• Support teams in navigating privacy, IP, and data rights as their systems scale

The earlier these conversations begin, the more durable—and responsible—the innovation becomes.

Looking Ahead

AI will not be “good” by default. It will be as ethical, fair, and inclusive as we make it. That requires not just technical ingenuity, but legal foresight and moral clarity.

As attorneys, investors, and builders, we need to shape the frameworks that guide AI toward public benefit—especially in areas like health, climate, education, and social justice. It’s not enough to ask what AI can do. We must keep asking what it should do, and how we’ll hold ourselves accountable when the stakes are highest.

Because the real promise of “AI for good” lies not in the code—but in the courage to wield it wisely.

The road to responsible AI isn’t paved solely with technical talent—it’s built on intentional design, cross-disciplinary collaboration, and legal frameworks that evolve alongside innovation. 

If you’re a founder navigating these gray zones, an investor exploring mission-aligned AI, or a legal professional shaping the guardrails of tomorrow, I’d love to connect. Let’s keep the conversation going and build an ecosystem where “AI for good” becomes more than a motto—it becomes the standard.