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She was listed on the inaugural TIME100 Most Influential People in AI. Tabassi led the creation of the United States Artificial Intelligence Risk Management Framework, [2] adopted by both industry and government. [3] Tabassi was selected to serve on the National Artificial Intelligence (AI) Research Resource Task Force. [4]
The Risk Management Framework (RMF) is a United States federal government guideline, standard, and process for managing risk to help secure information systems (computers and networks). The RMF was developed by the National Institute of Standards and Technology (NIST), and provides a structured process that integrates information security ...
A risk management plan is a document to foresee risks, estimate impacts, and define responses to risks. It also contains a risk assessment matrix.According to the Project Management Institute, a risk management plan is a "component of the project, program, or portfolio management plan that describes how risk management activities will be structured and performed".
Hong Kong recently introduced a "dual-track" policy for AI adoption in the financial sector, aiming to balance innovation with risk management. The initiative, announced by the Financial Services ...
NIST Special Publication 800-37 Rev. 1 was published in February 2010 under the title "Guide for Applying the Risk Management Framework to Federal Information Systems: A Security Life Cycle Approach". This version described six steps in the RMF lifecycle. Rev. 1 was withdrawn on December 20, 2019 and superseded by SP 800-37 Rev. 2. [1]
The 'ecosystem of trust' outlines the EU's approach for a regulatory framework for AI. In its proposed approach, the Commission distinguishes AI applications based on whether they are 'high-risk' or not. Only high-risk AI applications should be in the scope of a future EU regulatory framework.
Executive Order 14110 is the third executive order dealing explicitly with AI, with two AI-related executive orders being signed by then-President Donald Trump. [9] [10] The development of AI models without policy safeguards has raised a variety of concerns among experts and commentators.
AI safety is an interdisciplinary field focused on preventing accidents, misuse, or other harmful consequences arising from artificial intelligence (AI) systems. It encompasses machine ethics and AI alignment, which aim to ensure AI systems are moral and beneficial, as well as monitoring AI systems for risks and enhancing their reliability.