Regulated AI: How To Protect Public Safety While Driving Innovation
Technology 5 min

Regulated AI: How To Protect Public Safety While Driving Innovation

Under-regulated AI technologies present risks ranging from privacy breaches to systemic bias and misuse. Discover expert insights and actionable strategies to balance innovation with public safety.

by Ryan Paugh on January 16, 2025

Artificial intelligence is not just a futuristic concept; it is transforming the way we live and work today. But as its applications expand, so do its risks. The question isn’t whether we should regulate AI, but how to do so without stifling its potential. Insights from SeniorExecutive.com’s AI Think Tank members, a group of experts with years of hands-on experience, provide a clear lens through which to view these challenges—and potential solutions.

The Risks of Under-Regulated AI

AI is powerful, but power without responsibility can lead to chaos. A survey of CEOs conducted by EY revealed that over half of executives fear the unintended consequences of AI adoption. These fears aren’t unfounded, as our Think Tank members point out.

“Imagine unsafe medical systems or discriminatory loan approvals—these aren’t just hypotheticals.”

– Jim Liddle, Chief Innovation Officer at Nasuni

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Think Tank member images created using Secta Labs headshot generation technology.

Unchecked Consequences

“Under-regulating AI can lead to biased systems, privacy breaches, and misuse of technologies,” explains Sarah Choudhary, CEO of Ice Innovations. Her company integrates AI and quantum solutions into industries like logistics, and she’s seen firsthand the need for ethical frameworks. “Without transparency and accountability, trust erodes—and so does progress,” she says.

Jim Liddle, Chief Innovation Officer at Nasuni, echoes these concerns. “Imagine unsafe medical systems or discriminatory loan approvals—these aren’t just hypotheticals,” he warns. His company’s AI-enhanced data solutions are a testament to how proper safeguards can unlock potential while avoiding pitfalls.

Amplified Misinformation and Bias

The risks go beyond privacy and security. “AI-generated deepfakes and misinformation can undermine public trust and even sway elections,” says Manasi Sharma, Principal Engineering Manager at Microsoft. Sharma’s team develops ethical AI frameworks to address these challenges head-on. “Clear standards for content authenticity, like digital watermarks, are critical,” she adds.

“Transparency builds public trust and mitigates misinformation risks.”

Manasi Sharma, Principal Engineering Manager at Microsoft, member of the AI Think Tank, sharing expertise on Artificial Intelligence on the Senior Executive Media site.

– Manasi Sharma, Principal Engineering Manager at Microsoft

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Research backs this up: a Pew Research study found that 75% of Americans believe AI-generated content should include credits to the sources for written text and 67% believe AI-generated images should acknowledge artist sources as well. Without such measures, the credibility of information—a cornerstone of democracy—is at stake.

How to Balance Innovation with Public Safety

Striking the right balance is tricky but essential. Here’s what the experts suggest:

Institute Collaborative Regulation

“We need regulations that grow with the technology,” says Nikhil Jathar, CTO of AvanSaber Technologies. His company’s AI solutions streamline complex operations, proving that transparency and innovation can coexist.

Daria Rudnik, founder of Aidra.ai, emphasizes early-stage ethics. “Bias audits and diverse collaboration—these should be baked into AI development, not an afterthought,” she argues. Rudnik’s leadership-coaching platform is built on these principles, ensuring AI serves all communities equitably.

Promote Adaptive Governance Models

Rodney Mason, Head of Marketing at LTK, suggests a multi-pronged approach. “Governments must consult experts and craft policies that are transparent, adaptable, and ethical,” he says. His company’s AI-enriched creator community is a prime example of innovation guided by thoughtful oversight.

Anand Santhanam, Global Principal Delivery Leader at AWS, adds, “Algorithmic transparency and ethical standards must be non-negotiable.” Collaboration between technologists, policymakers, and communities is critical, he notes.

“Using scalable, secure data frameworks can reduce risks while fostering innovation.”

Suri Nuthalapati, Data and AI Practice Lead at Cloudera, member of the AI Think Tank, sharing expertise on Artificial Intelligence on the Senior Executive Media site.

– Suri Nuthalapati, Data & AI Practice Lead, Americas at Cloudera

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Lessons from the Field

Healthcare

The healthcare industry provides a stark example of AI’s potential—and its risks. IBM Watson Health learned early on that transparency and rigorous testing were non-negotiable to ensure equitable outcomes. Other organizations must follow suit.

Finance

Algorithmic bias in financial systems has led to disproportionate loan denials for minority applicants. Solutions like the Responsible AI Toolkit developed by global think tanks are crucial to mitigate these issues.

Data Management

Suri Nuthalapati, Data and AI Practice Lead, Americas at Cloudera, highlights the importance of scalable AI frameworks in managing data. “Under-regulated AI can lead to misuse, eroding trust and creating safety risks in critical areas like healthcare and finance,” he says. Cloudera’s data platform empowers enterprises to integrate generative AI responsibly, ensuring privacy and security while delivering insights.

Marketing

Roman Vinogradov, Vice President of Product at Improvado, brings another perspective: “AI systems that lack regulation can exacerbate privacy violations and biased decision-making,” he explains. His company’s AI-powered data platform helps marketers centralize and analyze data, but Roman stresses the need for adaptable governance. “Ethical AI development is key to earning and maintaining customer trust.”

“Bias audits and diverse collaboration—these should be baked into AI development, not an afterthought.”

Daria Rudnik, founder of Aidra.ai, member of the AI Think Tank, sharing expertise on Artificial Intelligence on the Senior Executive Media site.

– Daria Rudnik, Founder of Aidra.ai

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Actionable Strategies for Leaders

So what can you, as a leader, do to navigate the complexities of AI?

  1. Embrace Transparency: Digital watermarks and clear algorithmic documentation build trust. “It’s not just about ethics; it’s good business,” says Sharma.
  2. Tailor Regulations by Sector: “High-risk industries like healthcare need stricter rules, but a one-size-fits-all approach doesn’t work,” Liddle advises.
  3. Invest in Bias Audits: Rudnik recommends regular audits and inclusive development teams to catch blind spots before they become systemic issues.
  4. Foster Open Collaboration: “Governments, tech companies, and academia must work together to keep regulations relevant,” says Choudhary.
  5. Leverage Scalable Frameworks: “Using scalable, secure data frameworks can reduce risks while fostering innovation,” adds Nuthalapati.
  6. Adopt Modular AI Approaches: “Modular AI solutions allow for flexibility, ensuring that companies can adapt their systems to evolving regulations,” says Vinogradov.

The Road Ahead

AI is a game-changer, but only if we play by the rules. “Ethical AI isn’t just a safeguard; it’s a competitive advantage,” says Justin Newell, CEO of INFORM North America. With adaptable regulations and ethical practices, we can harness AI’s potential while safeguarding public trust. Leaders who embrace this balance will not only drive innovation but shape a future we can all trust.


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