A Comprehensive Solution for Trustworthy and Reliable AI
Deloitte’s ‘Large Language Model Controls’ as GenAI Guardrails
The Need
Addressing users’ concerns of perceived lack of data privacy and safeguards are a great challenge that clients face in adopting Generative AI (GenAI) and Large Language Models (LLMs). AI-powered systems are transforming a multitude of sectors, but they also pose certain risks, such as data security, confidentiality leaks, regulatory compliance, and the potential for negative outcomes arising from AI-generated content. To mitigate such risks, Deloitte’s 'Large Language Model Controls' provides modular and customizable controls in addition to the services offered by Cloud providers.
Our Solution: Large Language Model Controls
Built to detect, prevent, and minimize undesirable behavior of models in GenAI applications, Deloitte’s 'Large Language Model Controls' acts as your AI model security officer. It is designed in line with the Deloitte Trustworthy AI™ framework to enable end-to-end risk management for GenAI/LLMs. Once integrated with the client’s GenAI applications, it serves as a valuable component to supplement client applications, ensuring data protection, bias reduction, and output quality. Furthermore, it ensures that AI-generated content remains accurate, clear, and helpful, aligning perfectly with our clients’ standards and objectives.
'Large Language Model Controls' offers a suite of 9 customizable controls such as Adversarial Attack Filters, PII Confidentiality Masking, Citation Retriever, Toxicity-Bias Control, RAG Evaluation, Prompt Augmentation, Randomness Detector, and Gibberish Filter. Clients utilizing Deloitte’s 'Large Language Model Controls will have the capacity to reduce risks, ensure compliance, and responsibly use AI generated content. This enhances trust and strengthens confidence in the use of GenAI technologies.
Advantages/Benefits
- Maintain security and mitigate risks, thereby reinforcing trust and confidence in using generative AI technologies.
- Maintain bidirectional guardrails, both for user prompt inputs and LLM-generated outputs, protecting the data integrity.
- Adherence to data privacy laws and regulations becomes simplified and accurate, reducing the risk of noncompliance penalties.
- Designed to prevent data loss, reduce hallucinations or false outputs, and ensure the generation of accurate, coherent results.
- Provides the flexibility to choose between or combine different controls as per users' requirement, making it a highly adaptable and scalable solution to address diverse business needs.
- Can be seamlessly integrated, making your shift towards better AI governance smooth and hassle-free.
Example Use Cases
- Safeguard AI applications from revealing high-confidential or sensitive client information via manipulative prompts.
- Adhere to rigorous data privacy laws such as the General Data Protection Regulation (GDPR) and the Federal Data Protection Act/ Bundesdatenschutzgesetz (BDSG) to maintain copyright and confidentiality standards.
- Detect and block inappropriate, offensive, or biased user prompts and generated outputs.
- Detect the level of hallucinations to enhance reliability of prompt output.
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