AI: Promise or Peril for Patient Safety.

Patient safety advocates identify concerns for the impact of AI on patient safety. Patients identified the following 4 main areas that AI developers, regulatory bodies, and clinical users of AI are asked to consider: data integrity and bias, efficacy, payment, and transparency toward shared learning. Increased patient involvement in the development, use assessment and oversight of the technology is critical to ensure trust and trustworthiness in the use of AI in patient care.

Closing the Gap and Raising the Bar: Assessing Board Competency in Quality and Safety.

Background: Despite recognition of the important role that governance and executive leaders play in ensuring patient safety and quality, little research has examined leaders' involvement in these areas beyond surveys that assess higher-level knowledge and understanding of patient and workforce safety concepts.

Methods: A survey was sent to a convenience sample of board members and CEOs, as well as unpaired safety and quality leaders (SQLs). The survey included approximately 36 questions asking board members and other non-CEO executives their knowledge, understanding, and board activities related to safety and quality, and SQLs their perceptions of their own boards' knowledge, understanding, and activities related to safety and quality.