Connect, Collaborate, Create

Why AI Innovation Demands More Than Just Code

Hello, Friends and Colleagues,

The first time I saw a neural network visualized, I was mesmerized. It looked like a city at night—nodes and connections lighting up like a skyline. It reminded me of standing on a rooftop in New York, watching the intricate dance of movement below. Every light flickering on meant something—someone heading home, a late-night diner taking an order, a taxi switching shifts. Each point, alone, is just a bulb. But together? They create something alive.

And that’s what AI is—connections coming together to create something greater.

But here’s the thing: AI is not just about technology. It’s about people. The success of AI in business, law, and product development depends not only on the models we build but on the relationships we foster. The teams that will thrive in the AI era aren’t the ones working in isolation. They’re the ones who connect, collaborate, and create—together.

The AI Age Demands Connection

In law, we’re trained to be independent thinkers—to analyze, critique, and question. But in AI, isolation is a liability. The biggest AI failures don’t come from bad code; they come from a lack of perspective.

I once worked with a product team that built an AI-powered risk assessment tool. It was sleek, fast, and incredibly efficient—on paper. But when we tested it in the real world, it consistently flagged certain demographics as higher risk. Not because of bias in intent, but because of bias in data. The team had built in isolation, without connecting with legal, ethics, or even the communities the tool impacted.

It took real connection—across teams, disciplines, and lived experiences—to fix it. We had to sit down together, dissect the problem, and understand its impact from multiple angles. That process wasn’t just about compliance; it was about building something that actually worked for the people who would use it.

The lesson? In AI, silos kill innovation. If you’re not bringing in different perspectives early, you’re already behind.

Collaboration: The Key to AI’s Legal and Ethical Future

AI moves fast. The law, famously, does not. That tension creates a challenge—but also an opportunity.

One of the most powerful collaborations I’ve witnessed was between a legal team and a group of engineers working on an AI hiring tool. The engineers were focused on optimizing efficiency; the lawyers were concerned with bias and compliance. Initially, their meetings felt like a tug-of-war—efficiency versus ethics, speed versus scrutiny.

But then something shifted. The legal team stopped framing the issue as "What can’t you do?" and instead asked, "How can we make fairness a competitive advantage?" The engineers stopped seeing legal as a roadblock and started seeing them as problem-solvers. They built explainability into the model. They adjusted weighting to reduce bias drift. They made the system more transparent, which made it more defensible in the market.

The result? A product that wasn’t just legally sound but ethically stronger and more commercially viable.

Collaboration doesn’t slow AI down—it makes it better. The companies that embed legal and ethical thinking into AI development aren’t just reducing risk; they’re creating more valuable products.

Creativity: The Missing Ingredient in AI Governance

When people think about AI and law, creativity isn’t the first word that comes to mind. But it should be.

AI governance isn’t just about setting up guardrails; it’s about designing frameworks that evolve as AI does. The most effective product counsel teams aren’t just risk managers—they’re risk architects, designing structures that empower responsible innovation rather than stifling it.

I worked with a fintech company integrating AI into financial decision-making. The engineers were excited about its predictive power. The legal team was nervous about liability. The conversation kept hitting the same wall: Could the company be held responsible if the AI gave bad advice?

Then someone asked, "What if we designed the AI to guide, not predict?"

That shift in framing opened up new possibilities. Instead of an AI that made definitive statements, they built one that suggested options, explained reasoning, and left room for human judgment. The legal risk dropped. The user experience improved. The product became more trusted.

The best AI strategies don’t just solve legal problems—they use legal insights to create more resilient and innovative products.

Making It Actionable

AI’s biggest risks aren’t technical—they’re human. The best way to build better AI isn’t just through better code, but through better conversations and better processes.

1. Bring diverse minds into the room early. AI doesn’t fail because of bad math; it fails because of blind spots. If you’re not actively seeking different perspectives—legal, ethical, business, user experience—you’re already missing something.
2. Turn compliance into a competitive edge. AI regulation isn’t just about avoiding penalties. The companies that anticipate and embrace ethical AI design will be the ones leading the market, not scrambling to catch up.
3. Reframe legal as a creator, not a blocker. The best legal teams aren’t just identifying risks—they’re helping teams navigate them in ways that fuel innovation. AI needs lawyers who don’t just say "no," but who ask, "What if we tried this?"
4. Design for transparency, not just accuracy. If an AI model can’t explain itself, it won’t survive long-term. Customers, regulators, and courts are all demanding AI systems that are interpretable and fair. Make explainability a core feature, not an afterthought.
5. Think about unintended consequences from the start. AI is dynamic—it learns, adapts, and sometimes behaves in unexpected ways. That means risk management can’t be static. Build in monitoring, auditing, and mechanisms to course-correct over time.

The Dinner Party Test

A few years ago, I found myself in a heated discussion with an engineer about AI bias. He was frustrated. "The math doesn’t lie," he said. "If the algorithm produces this outcome, there’s a reason."

I paused. "You ever been to a bad dinner party?"

He looked at me, confused.

"You walk in, and something feels off. The lighting is too bright, the music doesn’t fit, the conversation feels forced. The host swears they did everything right—the playlist was curated, the menu was perfect, the guest list was balanced. But it doesn’t matter. If people feel uncomfortable, the party fails."

He nodded slowly.

"That’s AI," I said. "It might be mathematically sound, but if the output makes people feel excluded, overlooked, or misjudged, the system has failed. And that failure isn’t just bad ethics—it’s bad business."

That moment changed the conversation. Instead of debating technical accuracy, we started talking about real-world impact. We brought in other perspectives—designers, ethicists, legal experts—and the product shifted. It wasn’t just about making the AI work; it was about making it work for people.

This is why the future of AI isn’t just about engineering. It’s about connection, collaboration, and creativity.

Until next time,

Olga

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Olga V. Mack is a leading innovator in the legal field, driving digital transformation and championing the use of technology to modernize law. With a focus on efficiency, accessibility, and client-centric solutions, she has redefined traditional legal practices through groundbreaking tools, strategies, and advocacy. As an award-winning legal tech CEO, General Counsel, accomplished author, and sought-after thought leader, Olga is dedicated to empowering the legal profession to embrace transformative technologies and stay adaptable in an ever-evolving world.