SAS will be one of more than 200 leading AI stakeholders to help advance the development and deployment of safe, trustworthy AI under new US government safety institute
AI and analytics leader SAS announced that it joined more than 200 of the nation’s leading artificial intelligence (AI) stakeholders to participate in a Department of Commerce initiative to support the development and deployment of trustworthy and safe AI. Established by the Department of Commerce’s National Institute of Standards and Technology (NIST), the US Artificial Intelligence Safety Institute Consortium (AISIC) will bring together AI creators and users, academics, government and industry researchers, and civil society organizations to meet this mission.
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“As a creator of powerful AI systems, SAS understands the promises and risks of AI. SAS is committed to developing, implementing and promoting trustworthy AI systems that help ensure sustainable improvements and responsible innovation for our customers, the economy and society,” said Reggie Townsend, Vice President of Data Ethics Practice, SAS. “The AISIC will provide a crucial service by channeling the best of AI innovation through a lens of responsibility and collaboration. We eagerly anticipate the opportunity to work alongside other organizations and individuals to put the power of AI to work for the betterment of humanity.”
“The U.S. government has a significant role to play in setting the standards and developing the tools we need to mitigate the risks and harness the immense potential of artificial intelligence. President Biden directed us to pull every lever to accomplish two key goals: set safety standards and protect our innovation ecosystem. That’s precisely what the U.S. AI Safety Institute Consortium is set up to help us do,” said Secretary Raimondo. “Through President Biden’s landmark Executive Order, we will ensure America is at the front of the pack – and by working with this group of leaders from industry, civil society, and academia, together we can confront these challenges to develop the measurements and standards we need to maintain America’s competitive edge and develop AI responsibly.”
The consortium includes more than 200 member companies and organizations that are on the frontlines of developing and using AI systems, as well as the civil society and academic teams that are building the foundational understanding of how AI can and will transform our society. These entities represent the nation’s largest companies and its innovative startups; creators of the world’s most advanced AI systems and hardware; key members of civil society and the academic community; and representatives of professions with deep engagement in AI’s use today. The consortium also includes state and local governments, as well as nonprofits. The consortium will also work with organizations from like-minded nations that have a key role to play in setting interoperable and effective safety around the world.
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Rising to an unprecedented moment
Artificial intelligence has been an integral part of SAS software for decades, helping customers in every industry capitalize on AI advancements. The explosion of generative AI has made responsible innovation a crucial priority, demanding a comprehensive approach involving people, process and technology.
While SAS has always had a culture of ethics and customer service, the rapid spread of AI prompted the company to create the SAS Data Ethics Practice (DEP). The DEP empowers SAS employees, customers and the broader analytic community to build data-driven systems that promote human well-being and agency. The DEP includes data scientists and business development specialists who work hand in hand with the people creating and evolving our AI technologies.
That includes the company’s flagship AI and analytics platform, SAS Viya, which includes trustworthy AI capabilities such as bias detection, explainability, decision auditability, model monitoring, governance and accountability. SAS also launched generative AI offerings last year focused on synthetic data, digital twins and large language models.
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