AI Ethics Expert Argues Against Slowdown, Favors Innovation

As generative AI reshapes work and daily life, prominent voices in the industry have called for regulatory slowdowns to address safety concerns. But one leading AI ethics scholar argues the opposite: that accelerating innovation, not pumping the brakes, offers the best path to managing AI's risks.

James Brusseau, PhD, a professor at Pace University who specializes in AI ethics, contends that slowing technological development means forfeiting opportunities to create tools that could protect against the very dangers AI presents. His perspective challenges the precautionist approach gaining traction among some AI company leaders.

The accelerationist case

Brusseau defines AI ethics as "the investigation of the values that surround human interaction with artificial intelligence" — values like privacy, which takes on new urgency when AI systems can gather vast personal data to model and predict human behavior.

Rather than advocating for regulatory slowdowns, Brusseau champions what he calls the accelerationist school of thought: pushing forward with innovation and allowing new technology to solve safety problems created by earlier iterations.

He points to Canadian telecommunications company Telus as an example. Instead of gradually introducing a customer-service chatbot, Telus developed a second AI agent specifically designed to attack and test the first one, identifying vulnerabilities before public deployment. "In my view, what Telus did is ultimately the best way to address the current challenges posed by AI," Brusseau said.

The regulatory capture problem

Brusseau expresses skepticism about traditional regulatory approaches, arguing that political processes designed for the industrial economy move too slowly for AI's pace of change. "It takes years to pass any kind of regulatory measure," he noted, describing a system built on hearings, voting, and deliberation that can't keep up with technological advancement.

He also warns that companies calling for AI regulation may have hidden incentives. When OpenAI and Anthropic leaders advocate for regulatory frameworks, they may be pursuing "regulatory capture" — using high compliance barriers to freeze their market positions and block new competitors. "Regulations can make it very difficult for anyone else to enter the field," Brusseau explained, comparing the dynamic to how automobile companies collectively pushed for seatbelt mandates to avoid individual competitive disadvantage.

Healthcare and insurance on the horizon

Brusseau identifies healthcare as a critical domain where AI ethics questions will intensify. The same technology powering essay-writing tools can soon generate detailed patient health profiles and predict future medical conditions with precision.

This capability raises thorny questions about insurance coverage. If AI predicts a patient will suffer a heart attack in five to seven years, then develop brain cancer shortly after recovery, will insurers cover treatment for the first condition knowing the second is inevitable? "These are the kinds of questions we've never had to ask before but are going to have to start asking them soon," Brusseau said.

Why it matters

The debate between precaution and acceleration isn't academic — it will shape whether AI development remains open to new entrants or consolidates around a few dominant players. For business leaders, Brusseau's argument suggests that investing in AI-powered safety testing and validation tools may prove more effective than waiting for regulatory clarity that may never arrive at the necessary speed.

These details were first reported by Pace University ahead of its Actionable AI conference, which convened industry leaders from Google, Zoom, Salesforce, and other companies on September 25, 2026.