A group of Democratic lawmakers is proposing legislation aimed at investigating the environmental implications of artificial intelligence (AI). This act would assign fresh responsibilities to the Environmental Protection Agency (EPA), the Department of Energy (DOE), and the National Institute of Standards and Technology (NIST).
David McKeown, the Chief Information Officer (CIO) of the Department of Defense (DoD), has taken the initial steps to develop a Risk Management Framework (RMF) overlay aimed at securing the all-encompassing AI environment.
Artificial intelligence (AI) adoption within the federal government has been cautious and incremental, with concerns surrounding the ethical and responsible use of the technology being paramount. However, current developments suggest a significant acceleration in AI implementation is possible in 2024.
Heidi Shyu, Under Secretary of Defense for Research and Engineering, has offered a preview of an upcoming request for proposals (RFP) from the Pentagon. This RFP comes as part of efforts to establish a sustainable, secure, and safe bioeconomy. The original article can be found here .
Members of the Housing, Transportation, and Community Development Subcommittee are urging the implementation of a regulatory framework to oversee the use of artificial intelligence (AI) in housing and rental markets.
In line with his vision for the U.S. Cyber Command (CYBERCOM), Army Gen. Paul Nakasone reportedly highlights the rapid rotation of military forces into and out of CYBERCOM as a primary concern that needs to be addressed.
The Office of the Chief Administrative Officer (CAO) has embarked on developing a new policy dedicated to the utilization of artificial intelligence (AI) within the House. This policy aims to establish safeguards and shield against potential malicious cyber activities.
In their pursuit of a broad AI governance strategy, the Centers for Disease Control and Prevention (CDC) appears to be considering the use of “model cards.” These provide key information about generative AI models, including the contents and the creation method, potentially bringing essential clarity to AI tool deployment.