With the pervasive integration of AI across industries, the absence of robust controls can pose significant risks to civil liberties and individuals’ rights. Recognizing this urgent need, the National Institute of Standards and Technology (NIST) developed its AI Risk Management Framework. This Framework serves as a vital tool for organizations navigating the complexities of AI implementation, ensuring that ethical considerations, privacy concerns, and societal impacts are adequately addressed.
In an era where AI’s influence continues to expand, the necessity of NIST’s AI risk management framework cannot be overstated, offering a structured approach to mitigate risks and safeguard fundamental freedoms in the evolving landscape of AI-driven innovation. Businesses need to identify, assess, and effectively handle risks associated with AI, including everything from setting limits to putting controls in place — and the NIST AI RMF helps companies do that!
However, every new compliance standard is accompanied by a hundred questions related to its certification and implementation of its guidelines, which you need clarification on. Adhering to NIST AI risk management may have you feeling similarly overwhelmed. This is why we at Akitra have curated this blog for you. This article will answer the five most frequently asked questions about NIST’s AI risk management framework.
What is the NIST AI Risk Management Framework?
The NIST AI Risk Management Framework is a set of industry-neutral guidelines released by the National Institute of Standards and Technology (NIST) in January 2023 to assist organizations in evaluating and managing the risks related to the deployment and use of AI systems.
The primary objective of the Framework is to encourage the responsible development, application, and utilization of AI while ensuring that security, privacy, and ethics are taken into account at every stage of the AI system’s lifetime. The NIST AI RMF, which is made to be flexible and adaptive, may be applied to various fields and AI applications, assisting in the formation of an organization’s AI governance strategy.
The Framework follows a systematic process comprising:
- recognizing and evaluating the possible dangers of artificial intelligence;
- putting systems in place to lessen these risks; and,
- evaluating the efficacy of these controls to ensure ongoing system improvement.
The NIST AI Risk Management Framework is designed to be used cyclically and iteratively, assisting organizations in making sure their AI deployments continue to be reliable, even as they change over time.
Now, let’s deeply dive into the five most frequently asked questions about NIST’s AI risk management framework.
Five Most Frequently-Asked Questions About NIST’s AI Risk Management Framework
Here are the five most frequently-asked questions about NIST’s AI risk management framework:
- Why has NIST Developed the AI Risk Management Framework?
NIST wants to foster confidence in the design, development, application, and assessment of artificial intelligence (AI) systems and technologies in ways that strengthen economic security and raise the standard of living. Congress instructed NIST to work with the public and private sectors to create a voluntary AI RMF. The NIST AI RMF aligns with the National Security Commission on Artificial Intelligence proposal and the Plan for Federal Engagement in Developing AI Technical Standards and Related Tools.
In short, the NIST AI RMF was designed through a combined effort by the public and business sectors.
- Who is the NIST AI Risk Management Framework Intended For?
The NIST AI Risk Management Framework is helpful for individuals who create, develop, employ, or assess AI technologies. It is written in a way that is sufficiently technical to benefit practitioners in various fields and accessible to a wide audience, including non-AI experts and senior executives. The Framework must be adaptable to all kinds of organizations—public or private, working domestically or internationally, in any industry, irrespective of size.
- How is the NIST AI RMF Related to the Blueprint for the AI Bill of Rights?
AI risks that could impact people, organizations, or society as a whole need to be better managed by designers, developers, deployers, users, and evaluators of AI systems with the help of the AI RMF. The AI RMF is a framework for managing AI risks independent of industry and use case. One area of AI risks—the possibility of a significant influence on people’s and communities’ rights, opportunities, or access to essential resources or services—is the focus of the Blueprint for an AI Bill of Rights. Those looking to regulate, map, quantify, and manage such dangers may find useful information in the Technical Companion of the Blueprint for an AI Bill of Rights.
There are no contradictions. The goals of the two texts are the same: more responsible, trustworthy, and rights-preserving technologies. The Blueprint offers information to help mitigate the AI risks that affect people’s or communities’ rights, opportunities, or access to vital resources or services. The AI RMF offers the Framework for mitigating AI risks generally. Rapid advancements in AI have an impact on innovation, as well as the rights, opportunities, and access of people and communities. NIST and the Office of Science and Technology Policy (OSTP) will keep collaborating with the AI community to advance AI that upholds human rights.
- Why is a Separate Risk Management Framework Needed For AI?
Many frameworks that NIST and other organizations have established are already available to address different related challenges, including enterprise risk management, cybersecurity, and privacy. Why is a specific risk management framework necessary for controlling and mitigating AI risks?
This is because every Framework published by NIST concentrates on a distinct set of risk management difficulties. Each of these has significant variances as well as commonalities. A lot of people who are impacted by the use of AI products and services, as well as those involved in the design, development, deployment, evaluation, and monitoring of AI, have called for specific guidelines to help guarantee that AI is reliable and that associated risks are appropriately addressed throughout the AI lifecycle.
- How Can Your Company Operationalize NIST’s AI Risk Management Framework?
In order to put NIST’s Artificial Intelligence Risk Management Framework into practice, the following actions need be taken by organizations:
- Please become familiar with the AI RMF: Knowing the intricacies of the NIST AI risk management framework’s elements, policies, and procedures is essential before you start considering its implementation for your AI product or service business.
- Determine Artificial Intelligence Systems: List all the AI applications and systems used by the company, together with an explanation of their goals, data sources, results, and any usage risks.
- Perform a Risk Assessment: Conduct a comprehensive risk evaluation for every AI system owned by your company. This may include Identifying possible dangers, weak points, and potential effects of AI-related hazards on an organization’s goals and objectives.
- Sort AI Systems Into Different Risk Levels: Sort each AI system into categories based on the hazards found and prioritize the risks.
- Put Risk Mitigation Strategies into Practice: Create risk mitigation methods to address the hazards that have been identified. This can mean implementing governance procedures, process changes, or technical controls.
- Conduct Frequent Validation and Testing: To ensure AI systems work as intended, validate and test them often. If you find any potential risks, take quick action to address them immediately to avoid any unprecedented disasters in the future.
- Maintain Extensive Records: Keep thorough records of every step taken during the risk management, including tests, tactics, and evaluations.
- Observe for Risks Consistently: Use continuous observation to find and eliminate any hazards related to developing AI.
- Provide Precise Instruction to Staff: Employees should receive sufficient training to comprehend AI threats and their responsibilities in the AI risk management process. Be proactive and assign duties as and when required.
- Interact with Interest Groups: Assemble key stakeholders, including IT, business units, legal, and compliance, to develop a cooperative strategy for managing AI risk.
- Modify and Enhance the Framework as Needed: Update the risk management framework regularly based on user input, individual experiences, organizational requirements, and advancements in AI technology.
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Using automated evidence collection and continuous monitoring, together with a full suite of customizable policies and controls as a compliance foundation, our compliance automation platform and services help our customers become compliance-ready for NIST’s 800-218 Secure Software Development Framework and other security standards, such as SOC 1, SOC 2, HIPAA, GDPR, PCI DSS, ISO 27001, ISO 27701, ISO 27017, ISO 27018, ISO 9001, ISO 13485, NIST CSF, NIST 800-53, NIST 800-171, FedRAMP, CCPA, CMMC, SOX ITGC, and more such as CIS AWS Foundations Benchmark, Australian ISM and Essential Eight etc. In addition, companies can use Akitra’s Risk Management product for overall risk management using quantitative methodologies such as Factorial Analysis of Information Risks (FAIR) and qualitative methods, including NIST-based for your company, Vulnerability Assessment and Pen Testing services, Trust Center, and AI-based Automated Questionnaire Response product to streamline and expedite security questionnaire response processes, delivering huge cost savings. Our compliance and security experts also provide customized guidance to navigate the end-to-end compliance process confidently. Last but not least, we have also developed a resource hub called Akitra Academy which provides easy-to-learn short video courses on security, compliance, and related topics of immense significance for today’s fast-growing companies.
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