PHILADELPHIA, PA — SolasAI has joined a new cross-sector coalition seeking to establish common standards and professional practices for verifying artificial intelligence systems, as businesses in regulated industries expand their use of AI and face growing pressure to demonstrate that models behave as intended.
The Philadelphia-based AI risk-management software company is a founding member of the Partnership for Assurance, Credibility, and Trust on AI, or PACT AI, according to SolasAI.
The coalition brings together businesses, technical specialists, AI insurers and civil-society representatives to develop infrastructure for independently assessing AI systems. Its initial priorities include developing assurance policies, establishing professional practices and expanding the market for AI verification.
The effort comes as companies in finance, insurance and health care increase their deployment of AI systems, creating demand for methods to assess model fairness, explainability, reliability and other risks.
SolasAI develops software used by regulated institutions to evaluate algorithmic fairness and model risk. Joining PACT AI extends that work into an industry-level effort to develop standards and practices that could be applied across organizations.
“AI assurance can’t be optional, and it can’t be done in isolation,” SolasAI co-founder and Chief Executive Officer Larry Bradley said.
Bradley said individual technology providers cannot establish broadly accepted definitions of trustworthy AI on their own, arguing that companies, technical experts, insurers and civil-society organizations need a “shared playbook.”
PACT AI intends to focus initially on policies and professional standards for the AI assurance sector and on developing a larger market for verification services, according to SolasAI.
The coalition’s work centers on whether organizations can demonstrate that AI systems operate as represented, shifting part of the debate over responsible AI deployment from voluntary corporate commitments toward repeatable methods of testing and verification.
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