NIST AI Risk Management Framework
AI (artificial intelligence) is progressing quickly, and it seems to be on everyone’s mind.
AI has the potential to disrupt how businesses operate. It requires companies to consider its use and ensure that it is created, managed, and used in a way that promotes trustworthiness, security, transparency, fairness, reliability, and accountability.
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The National Institute of Science and Technology (NIST) has developed a practical framework: NIST AI Risk Management Framework or “AI RMF,” to provide a format for understanding risk and better ensuring reasonable due diligence oversight of your use of AI. 360 Advanced has years of experience working in many NIST standards and can assist in interpreting this standard and your organization taking the first steps toward building a program with this as the framework.
It is important to work with experienced cybersecurity professionals or consultants to ensure that all risks are identified and properly managed. By prioritizing AI risk management with 360 Advanced, organizations can ensure that they can leverage the benefits of AI while minimizing potential risks. Use this opportunity to be the first in your market to demonstrate your third-party assessed program and ensure you are on the right track.
Our NIST AI Risk Management Services
Assessing the risk associated with AI requires a comprehensive approach that considers the unique characteristics of AI systems.
Identify the risks associated with the AI systems being used or developed. This could include data privacy risks, cybersecurity risks, ethical risks, or other risks specific to the AI system.
Determine the potential impact of these risks on the organization. This includes assessing the potential financial, reputational, and operational impacts of a risk event.
Evaluate the likelihood of a risk event occurring. This includes assessing the probability of a risk event and the potential triggers or causes.
Assess the existing controls in place to mitigate the identified risks. This includes evaluating the effectiveness of technical controls, such as encryption and access controls, as well as organizational controls, such as policies and procedures.
Develop a risk management plan that outlines how identified risks will be addressed. This includes identifying risk mitigation strategies and assigning responsibility for risk management activities.
Regularly monitor and review the effectiveness of the risk management plan. This includes monitoring changes to the AI system or the organization’s risk profile and adjusting the risk management plan accordingly.
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