Intelligence analysis “must be objective and independent of political considerations,” according to a new “capstone” directive (pdf) issued by the Director of National Intelligence.
The directive establishes the policy framework for intelligence analysis and defines a set of methodological standards and expectations, with an emphasis on inter-agency collaboration and outreach.
“The IC will seldom have the requisite depth and breadth of expertise to provide all of the insights and detailed answers demanded by our customers. To satisfy their needs, the IC must tap outside expertise and build and expand relationships with non-intelligence government agencies, academic, business, non-governmental organizations (NGOs), and think tank communities, both domestically and internationally, while addressing the counterintelligence and security obligations that are inherent to such initiatives.”
See “Management, Integration, and Oversight of Intelligence Community Analysis,” Intelligence Community Directive (ICD) 200, January 8, 2007.
Also new is “Intelligence Community Update to DCID 6/11, ‘Controlled Access Program Oversight Committee’,” Intelligence Community Policy Memorandum (ICPM) 2006-700-10, January 12, 2007.
Americans are paying too much for almost everything, because the United States has long treated its trucking industry as an artifact to be preserved rather than as an opportunity for innovation.
These ideas aim to advance the detailed policy solutions needed to foster public trust and implement fairness in the adoption of AI across diverse domains, from healthcare and government benefits to rural access, education, and worker protections.
The evidence is clear: algorithmic pay-setting is established in app-based work, and payroll/timekeeping failures show how software can produce systemic wage harm at scale
While a few states have taken steps to implement decision-making mechanisms for certain AI systems, too many leaders are simply accepting narratives about AI’s purported public benefit at face value – jumping to the “how” of AI implementation before thoroughly vetting potential systems and deciding whether they are appropriate to use at all.