Responsible AI—Leading with Ethics and Inclusion

PART 3: ATHENA AI BLOG SERIES

With great power comes great responsibility. AI’s potential is massive—but so are the risks of bias, misuse, and exclusion.

At Athena’s “Responsible AI” event hosted with Intuit, leaders from Qualcomm, Shield AI, and Arlo explored what it takes to build ethical, transparent systems.

“You can’t lead in AI without understanding how bias works,” one speaker said. “And you can’t fix bias if the leadership team is all the same.”

The Real Risks:

• Facial recognition systems that misidentify women and people of color

• Voice assistants that struggle to understand diverse accents

• Hiring algorithms that replicate old biases in new ways

How to Lead Differently

• Insist on diverse design and testing teams

• Audit systems regularly for unintended consequences

• Educate your team on explainability and accountability

Kiva Allgood of the World Economic Forum spoke about the urgent need to reframe engineering and data science through a lens of inclusion.

“We’ve shifted gender balance in engineering education programs just by reframing the narrative,” she noted. “AI for good. AI for impact. That resonates.”

Key Takeaway

Responsible AI leadership is not a technical problem—it’s a cultural one. And women have an essential role to play.