NARA: “Smart (Balanced) Regulation” Protects People

A new white paper from the National Association for Regulatory Administration calls for “smart (balanced) regulation” versus swinging between deregulation and stricter rules. According to NARA, modern regulation suggests the need for risk-based, responsive and outcomes-focused licensing to protect people. “Smart regulation allows agencies to maintain minimum health & safety protections while redesigning monitoring and regulatory structure to be simpler, evidence-driven, and risk focused,” the authors of the white paper explain. Anchoring Human Care Oversight in Smart (Balanced) Regulation, released in August, offers a roadmap to implement a risk-based model in a phased approach.

The Four phases of the implementation roadmap include:

  • Assessment and planning
  • System development and resource allocation
  • Pilot and rollout
  • Ongoing evaluation and adjustment

State Cybersecurity Funding Tops NASCIO’s 3 Congressional Priorities

The National Association of State Chief Information Officers asked Congress on August 31 to reauthorize the State and Local Cybersecurity Grant Program. In the letter, NASCIO pointed to recent attacks on municipal water systems as evidence of the threats targeting government networks and infrastructure. “SLCGP has provided essential resources to strengthen state and local cybersecurity capabilities and improve coordination across all levels of government,” explained NASCIO’s Executive Director Doug Robinson. “Congress should move promptly to provide a long-term and appropriately funded reauthorization of SLCGP to ensure states can continue this critical work.” Other priorities included reauthorizing First Net and preserving state authority to govern artificial intelligence. Robinson called these issues “critical to the ability of states to deliver secure, reliable and innovative technology services to the public.”

AI in Government Software: Questions to Ask Vendors

GovRAMP’s Asking Your Providers About AI guide offers a practical framework for evaluating generative AI in cloud products and understanding how these tools affect regulatory agency operations, data governance and risk management. The guide recommends multiple questions by topic. For data handling, for example, GovRAMP suggests asking: Is our data processed by AI? Is our data used to train, tune, or improve the model? Can we request deletion or expungement of our data? Other questions fall under the topics of feature activation and controls; agency and permissions; transparency, logging and change control, as well as risks, guidance and disclosure.

GovRAMP offers a way to evaluate these answers, helping governments identify strong answers. These strong answers include:

  • AI remains off by default, with separate opt-in controls for using AI and allowing data to train the model.
  • Administrators can turn off AI, control it by use case and retain or revert to a previous model version.
  • Vendors support data-use claims with evidence, not just stated.
  • Clear documentation exists, and the provider states the product’s risks and limitations.

Time to Modernize

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