When I tell people I’m pursuing IP law after earning dual doctorates in AI and Computer Science, the most common reaction is: “Why?”
It’s a fair question. I’m a Principal Software Engineer. I chair an Architecture Board for a 65,000-employee organization. I have pending patents. I run three technology ventures. By any measure, I’ve gone deep enough in technology.
So why law?
The Gap I Keep Seeing
Every week, I encounter decisions at the intersection of technology and law where the technologists don’t understand the legal implications and the lawyers don’t understand the technology. The gap is growing, and it’s dangerous.
Consider:
- AI-generated content: Who owns the output of a model trained on copyrighted data? Current copyright law wasn’t designed for this question, and the answer has massive implications for every company deploying generative AI.
- Algorithmic patents: Can you patent an AI model’s architecture? Its training methodology? The boundaries are fuzzy, and companies are making multi-million-dollar IP strategy decisions based on that fuzziness.
- Data privacy in ML: GDPR gives individuals the “right to be forgotten,” but removing a person’s data from a trained model isn’t straightforward. The technical reality and the legal requirement are in tension.
In each case, the right answer requires someone who understands both the technology and the law at a deep level. Not a technologist with a surface-level legal understanding, and not a lawyer with a surface-level technical understanding. Both.
The Technologist’s Advantage in Law
Here’s what I’ve discovered: my technical background isn’t a disadvantage in legal studies. It’s a superpower. Legal reasoning is structured analysis. It’s pattern matching across precedent. It’s constructing logical arguments from evidence. These are skills that any technologist who’s debugged distributed systems or designed enterprise architectures already possesses.
The specifics are different: case law instead of code, statutes instead of specifications, courts instead of cloud environments. But the underlying cognitive framework is remarkably similar.
What I Plan to Do With It
I’m not planning to leave technology for law. I’m planning to occupy the intersection, the space where deep technical expertise meets deep legal understanding. Specifically:
- IP strategy for AI companies: Helping technology companies protect their innovations with patent strategies that actually reflect how their technology works, not how a non-technical attorney interprets it.
- AI governance frameworks: Building governance models that satisfy legal requirements without crippling innovation, because the current approach of “let legal review everything” doesn’t scale.
- Policy contribution: Working with standards bodies (I already contribute to IEEE AI Ethics Standards and NIST AI Risk Management Framework) on policies that are technically sound, not just legally convenient.
The Bigger Point
Technology is eating the world, and law is how society decides what that means. The people writing the laws, setting the precedents, and advising the companies need to understand the technology deeply enough to get it right.
If they don’t, we’ll end up with regulations that are either toothless (because they don’t understand what they’re regulating) or destructive (because they regulate the wrong things). Neither outcome serves society.
I’m studying law because I believe the future needs people who can build the technology and shape the rules that govern it. That’s not a career change. It’s a career completion.