Red Hat launches new open source project to drive AI governance

Red Hat has unveiled a new open source community project aimed at bolstering AI governance capabilities for enterprises.

Dubbed asago (AI Safety And Governance Orchestration), the new project will help enterprises automate AI governance policies in a bid to drive safe deployment of the technology.

A host of organizations have pledged support for asago so far, according to Red Hat, including Microsoft, IBM Research, the Alan Turing Institute, Brave Software, and more.

“The asago project is a true collaborative, open source endeavour bringing together stakeholders from the technology industry, academia and government,” said Stuart Battersby, AI safety and model evaluation architect at Red Hat.

“We encourage more collaborators to join this community driven effort, particularly from global jurisdictions, to ensure maximum coverage of AI safety viewpoints.”

As part of the project, participants will use a standardized platform designed to “translate complex corporate and regulatory AI governance policies into actual operational controls”.

This targets a common pain point for organisations deploying AI, according to Red Hat. Translating policy guidelines into functional software configurations often slows down innovation and creates deployment bottlenecks.

Compliance officers, for example, require “rigorous risk assessments” and verifiable evidence, while on the technical side platform engineers need highly structured configurations that can be easily maintained.

With new legislation such as the EU AI Act coming into effect, Red Hat said the project will help streamline deployments by speeding up traditional hurdles.

Indeed, the project will focus on four key areas for organisations deploying AI technologies, including risk mapping, risk assessment, risk mitigation, and production deployment.

What to expect with asago

The asago framework will automatically read and interpret AI governance policies on behalf of the user, helping to map specific requirements to established AI risk frameworks and standards through the IBM AI Risk Atlas.

These standards and frameworks span the NIST AI RMF, OWASP LLM Top 10, and the EU AI Act.

Asago will also generate and execute scenarios for automated safety testing, which is based around specific identified risks rather than “generic benchmarks”.

Thereafter, the framework will recommend “appropriate mitigations” such as safety guardrails before providing deployment-ready configurations.

Red Hat said each of these steps are designed to provide a “continuous audit trail” which ties individual policy clauses to specific tests and runtime controls.

AI safety in the spotlight

The move by Red Hat comes amidst growing concerns about AI-related security risks, particularly with agents.

In the last two weeks, both OpenAI and Anthropic both revealed ‘rogue’ AI agents escaped containment during testing and breached partner organizations.

Steven Huels, vice president for AI engineering at Red Hat, said that the mass-deployment of agents means that robust guardrails have now become a “critical infrastructure requirement” for enterprises.

Earlier this year, IBM and Red Hat unveiled Project Lightwell, an initiative designed to speed up automated security patching in response to a torrent of vulnerabilities uncovered by powerful new AI models.

As ITPro reported in late June, a host of organizations have signed up to the initiative so far, including Palo Alto Networks.

“Through initiatives like Lightwell, we are working to secure the open source supply chain from AI-driven vulnerabilities,” Huels commented. “asago complements this effort and takes the next logical step for enterprise AI by automating the link between corporate policy definitions and live production agents.

“This gives enterprises the end-to-end operational confidence they need to scale trusted AI across the hybrid cloud.”

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