Panelist Rohan Rajput

Rohan Rajput

Headspace

United States

Rohan Singh Rajput is the personalization domain lead at Headspace and has over eight years of experience in analytics, data science, machine learning, and AI. He has developed and deployed several successful machine learning models in production and holds a patent for a method for scaling content across multiple form factors. He has been invited to speak at numerous data science conferences, has been featured in blog posts and data science podcasts, and has more than 11,500 followers on LinkedIn. Previously, he was a data scientist at Ticketmaster. Rajput has a master’s degree in computer engineering from the University of Central Florida and a bachelor’s degree in electrical and electronics engineering from Rajiv Gandhi Prodyogiki Vishwavidyalaya.

Voting History

Statement	Response
Organizations are sufficiently expanding risk management capabilities to address AI-related risks. Agree	“Organizations are progressively acknowledging the need to improve their risk management strategies to address the challenges presented by artificial intelligence. This involves fostering awareness within the organization to prioritize risk mitigation through education and training. Furthermore, companies are actively developing frameworks and policies to govern the use of AI in their products and services. There is also a noticeable increase in investments in AI risk management tools designed to detect, assess, and mitigate AI-related risks. Despite these advancements, there are still areas that require attention, particularly in addressing ethical considerations, fairness, and bias prevention. As we move forward, it is crucial for companies to develop comprehensive plans to tackle these issues, ensuring that AI is used responsibly and equitably.”

Statement

Response

Organizations are sufficiently expanding risk management capabilities to address AI-related risks. Agree

“Organizations are progressively acknowledging the need to improve their risk management strategies to address the challenges presented by artificial intelligence. This involves fostering awareness within the organization to prioritize risk mitigation through education and training. Furthermore, companies are actively developing frameworks and policies to govern the use of AI in their products and services. There is also a noticeable increase in investments in AI risk management tools designed to detect, assess, and mitigate AI-related risks.

Despite these advancements, there are still areas that require attention, particularly in addressing ethical considerations, fairness, and bias prevention. As we move forward, it is crucial for companies to develop comprehensive plans to tackle these issues, ensuring that AI is used responsibly and equitably.”