Center Stage Recaps: AI for Impact

We’re back with another HumanX 2025 Center Stage recap! Today we’re highlighting another significant session from our Grand Opening titled AI for Impact: Trust, Transparency & Real-World Change. This talk was moderated by Pedro Bizzaro of Feedzai and featured special guest speaker Rayid Ghani, Professor of Machine Learning at Carnegie Mellon University. 

Focusing on the intersection of AI, societal impact, and public trust, AI for Impact addressed one of the most critical topics in the space today. Let’s dive into the main takeaways.

Trust in AI

Professor Ghani emphasized that trust in AI is crucial for its widespread adoption and effectiveness. However, trust in AI doesn’t just come down to the technology itself; it must also be perceived positively and become accepted among the public. Professor Ghani cited AI’s opaqueness within general public understanding, in addition to bias and lack of proper transparency, all leading to today’s widespread distrust. He argued that building understanding around what AI systems are supposed to do and ensuring that they meet those expectations will greatly improve public trust. 

Transparency and Accountability

Transparency in AI processes and decision-making was underscored as a vital component for creating understanding and thereby improving trust. Professor Ghani insisted that we need better education and communication surrounding AI so that society at large can be informed participants in the AI development process. 

Real-World Applications and Risks

Professor Ghani shared personal insights about applying AI to various social issues such as homelessness, health, criminal justice, and education. He pointed out that while AI has significant potential to address these issues, it also comes with ethical risks that need to be managed. 

Policy and Regulation

The session also covered the current state of AI policy and regulation, with Professor Ghani noting that federal policies are often too weak to be effective; even more so in the emerging AI era. He suggested that more robust policies should emerge at the state level to help tighten regulation.

As with any major technology, AI poses risks if in the wrong hands, but can also massively drive innovation if in the correct ones. 

Future Challenges and Opportunities

The session concluded with a challenge to the audience to build AI systems that are trustworthy and beneficial to society. The conversation around responsible AI, Professor Ghani stressed, is just beginning and will continue to evolve. It is up to us to not let this issue fall to the wayside and maintain accountability for today’s developers. 

This discussion centered around an important AI duality, where AI has the potential to drive positive social change and significant innovation, but it cannot do so without the correct guardrails and policies in place.