What is AI TRiSM – AI Trust, Risk and Security Management

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1. Overview

AI TRiSM is a comprehensive framework developed by Gartner that enables organizations to manage the trust, risk and security of their AI models. 

The framework includes multiple software segments that ensure AI model governance, trustworthiness, fairness, reliability, efficacy, security and privacy. By using the AI TRiSM framework, organizations can mitigate risks associated with AI and build trust in their AI models.

The US Department of Defense (DoD) is already using AI TRiSM framework to assess, protect and defend its AI models. It is also used by the US Department of Homeland Security (DHS) to secure critical infrastructure from cyberattacks.

The framework includes multiple software segments that ensure AI model governance, trustworthiness, fairness, reliability, efficacy, security and privacy. By using the AI TRiSM framework, organizations can mitigate risks associated with AI and build trust in their organization.

2. AI TRiSM seven key principles

AI TRiSM is built on seven key principles: 

1) Transparency and explainability of data, algorithms and results;
2) Responsibility of organizations using AI;
3) Independent validation of data, algorithms and results;
4) Security of user data and systems;
5) Privacy of user data;
6) Fairness and non-discrimination of users; and
7)Probe-ability of systems to ensure efficacy. 

The framework includes a set of best practices for developing, implementing, and maintaining security in connected systems.

3. Benefits of AI TRiSM


There are many benefits of AI Trust, Risk and Security Management. Perhaps most importantly, it helps to ensure that AI models are governed in a way that is trustworthy, fair, reliable, and effective.

Additionally, it can help to protect data and improve the security of AI systems. By utilizing AI TRiSM, businesses can gain a competitive advantage and boost their overall performance.

4. Applications of AI Trust, Risk and Security Management

The use of artificial intelligence (AI) is growing within organizations and so are the risks associated with its use. Addressing AI trust, risk and security management (TRiSM) requires a multi-pronged strategy capable of managing risks and threats while promoting trust in AI.

Organizations who use AI need to be aware of the potential risks involved in its use, such as privacy breaches and data leaks. In addition, they need to have a plan in place to address these risks. The first step is to understand the new requirements for AI TRiSM. Next, organizations should develop a comprehensive strategy that includes controls and processes to manage these risks. Finally, they should monitor AI models for changes that could impact trust or security.

By taking these steps, organizations can move more confidently towards their goals while protecting themselves from the potential risks of using AI.

5. Conclusion

The use of artificial intelligence (AI) technologies is becoming more widespread, and with it comes new trust, risk and security management requirements. This study provides a definition of AI TRiSM, discusses the challenges and benefits of AI TRiSM, and offers recommendations for how to address these issues. The study concludes that a multi-pronged approach is needed to manage risks and threats while promoting trust in AI technologies.

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