Tag: ai

As we stride towards an AI-driven future, AI Trust, Risk and Security Management (AI TRiSM) emerges as a key technology trend poised to revolutionize businesses.

This innovative AI TRiSM framework allows organisations to identify, monitor and mitigate potential risks associated with the application of AI technology, including the rapidly evolving Generative and Adaptive AI. Adherence to this framework ensures compliance with pertinent regulations and data privacy laws.

In this article, we will unpack the concept of AI TRiSM, its operational dynamics and its strategic leverage for organisations.

Building Robust AI Systems: The Importance of AI Trust, Risk, and Security Management (AI TRiSM)

Companies implementing robust Artificial Intelligence Trust, Risk and Security Management (AI TRiSM) frameworks successfully deploy more valuable AI models. So, what does it take to make AI systems both secure and effective?

AI TRiSM and Cybersecurity: A Crucial Intersection 

AI models are susceptible to cyber threats, implying that cybercriminals can manipulate these models to optimise malicious processes, such as:

• Malware Attacks
• Data Breaches
• Phishing Scams

In the first half of 2022, about 236 million ransomware attacks were reported globally, signifying a sharp rise from previous years. This surge can be attributed to the widespread adoption of novel technologies and adequate security measures.

The Imperative for an AI Bill of Rights 

The recently proposed U.S. blueprint for an AI Bill of Rights underscores the need for strict protective measures against potential AI perils, urging AI developers and users to integrate safety precautions within their AI models and strategies. This highlights the crucial need for rigorous AI TRiSM implementation.

Demystifying AI TRiSM

AI TRiSM is a comprehensive framework advocating for AI model governance, fairness, reliability, robustness, efficacy and privacy. It encompasses solutions, techniques and processes to enhance model interpretability, explainability, privacy, model operations and resistance against adversarial attacks, which is vital for both the enterprise and its customers.

IT leaders who invest time and resources into AI TRiSM can expect improved AI outcomes in terms of adoption, business goals and user acceptance. Given the relentless evolution of AI threats and compromises, AI TRiSM must be an ongoing effort.

The Rising Tide of AI TRiSM

By embracing AI transparency, trust and security, organisations are likely to witness an improvement in their AI model performance concerning adoption, business goals and user acceptance. By 2028, it’s predicted that AI-driven machines will comprise 20% of the global workforce, contributing to 40% of all economic productivity.

However, it’s important to note that several organisations have deployed countless AI models that even IT leaders find difficult to explain or interpret. Organisations failing to manage AI risk are more susceptible to negative AI outcomes, including security and privacy breaches, financial and reputational losses, and harm to individuals. Poorly managed AI could also lead to detrimental business decisions.

Strategising and Operationalising AI TRiSM

With increasing AI regulations on the horizon, it’s crucial to adopt practices promoting trust, transparency and consumer protection before such protections become mandatory. IT leaders need to adopt innovative AI TRiSM capabilities to ensure model reliability, trustworthiness, privacy and security.

Applying AI TRiSM shouldn’t wait until models are in production, as it may expose the process to potential risks. It’s advisable for IT leaders to familiarise themselves with potential compromises and utilise the AI TRiSM solution set to adequately safeguard AI.

Successful implementation of AI TRiSM requires a cross-functional team, involving legal, compliance, security, IT and data analytics staff. Establishing a dedicated team or task force is recommended to derive optimal results, with appropriate business representation for each AI project.

Benefits of AI TRiSM extend beyond mere regulatory compliance, enabling organisations to enhance the business outcomes derived from their use of AI.

Conclusion

AI TRiSM capabilities ensure model reliability, trustworthiness, security and privacy. Organisations need to manage AI trust, risk and security for better AI adoption, achieving business goals, and user acceptance. Consider AI TRiSM as a comprehensive solution set to adequately protect AI. 

In the digital era, ensuring the safety and effectiveness of AI is a necessity, not a luxury. AI TRiSM plays a pivotal role in meeting these demands, heralding a secure and promising AI future.