Designing AI Systems for Trust

Abstract: 

As AI becomes integral to business strategy, many organizations are navigating the complex interplay between technical innovation, creating business value, and managing risk. Despite the progress, fewer than 10% of organizations have successfully deployed generative AI solutions (as of Jan 2024). In many cases challenges arise with human adoption, alignment with business values, risk management processes, and unexpectedly costly data curation efforts.

With a focus on business and technical leaders responsible for bringing AI solutions to life, we will draw from best practices in designing and deploying AI solutions across mission-critical sectors such as healthcare, energy, and financial services, where trust is critical.

Participants will walk away with some practical tools to lead their organizations in developing and deploying AI solutions that are not only technically sound but also widely trusted.

Session Outline:

Attendees will gain practical insights into:
• Best practices for responsible AI development and deployment, focusing on fairness, accountability, and transparency.
• Methods for making AI decision-making processes understandable to non-technical stakeholders, including explainable AI techniques and transparency frameworks.
• Communication strategies to articulate the value and limitations of AI technologies to non-technical stakeholders, fostering an environment of trust and informed decision-making.

Bio: 

Cal Al-Dhubaib is a data scientist, entrepreneur, and innovator in responsible artificial intelligence, specializing in high-risk sectors such as healthcare, energy, and defense. He is the founder and CEO of Pandata, a consulting company that helps organizations to design and develop AI-driven solutions for complex business challenges. Their clients include globally recognized organizations like the Cleveland Clinic, Progressive Insurance, University Hospitals, and Parker Hannifin.

Cal frequently speaks on topics including AI ethics, change management, data literacy, and the unique challenges of implementing AI solutions in high-risk industries. His insights have been featured in numerous publications such as Forbes, Ohiox, the Marketing AI Institute, Open Data Science, and AI Business News. Cal has also received recognition among Crain’s Cleveland Notable Immigrant Leaders, Notable Entrepreneurs, and most recently, Notable Technology Executives.

Open Data Science

 

 

 

Open Data Science
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