The Key Components to Building Trustworthy and Reliable AI: Expert Insights from Digital Science President Stephen Leicht

The US government is pushing forward with AI initiatives, focusing on creating more reliable and trustworthy AI tools. Digital Science President Stephen Leicht emphasized in a recent video interview that successful AI systems rely on three key components: data, technology, and people.

Leicht highlighted the importance of data as the first pillar of AI. He explained that high-quality data is essential for AI systems to generate accurate intelligence and provide better answers. Digital Science has access to the world’s largest repository of research data outputs, allowing them to make predictions about research and development priorities globally.

Companies like OpenAI, Microsoft, Google, IBM, and Meta are investing heavily in building and refining large language models that are crucial for AI advancements. Understanding how to apply technology to data effectively is vital for successful AI implementation.

Lastly, people play a crucial role in the development, iteration, and deployment of AI technologies. Leicht emphasized the importance of having skilled individuals who can understand and utilize AI technologies effectively. He stressed the need for quick action in developing the necessary talent to keep up with the rapid advancements in AI technology.

In an interview with Executive Mosaic, Leicht discussed the US’s position in the global AI competition and the importance of protecting against potential threats from these systems. The government’s commitment to building better AI tools reflects its growing importance in shaping various industries’ future.

Overall, Leicht emphasized that creating better AI tools requires collaboration between companies, academia, and governments worldwide. He believes that by working together towards shared goals