Every leader is conscious of the responsibility to protect their business from harm. This entails safeguarding the company’s reputation, operating legally and ethically, and taking appropriate security, compliance, and governance measures.
AI requires new governance frameworks
AI is now fully integrated with operational ecosystems. This has meant organizations must have in place specific measures to mitigate the potential risks associated with AI. It is risks such as hallucinations, toxic or mis information, data leakage, privacy violations, misuse of capabilities, and performance degradation that are forcing organizations to rewrite their governance frameworks.
Conversational AI Platforms
When considering a conversational AI platform, organizations should forensically examine the guardrail and observability capabilities on offer. With AI being held under the microscope when it comes to security, privacy, accuracy and compliance, the last thing any business wants is to be caught short in having the necessary safeguards embedded in their AI solution.
Guardrails and observability
There are two key elements to ensuring businesses protect themselves from any potential harm that may originate from AI. The first is to have the necessary guardrails in place, and the second is to have observability so you can see whether the guardrails are working as they should.
Guardrails
Guardrails are used as a defense. To create the strongest defense possible and protect a business and its customers, there are several tools and layers to consider.
Your conversational AI platform provider should be able to demonstrate how their platform has automated guardrail capabilities to:
- Detect or block malicious inputs, with prompt and input filtering
- Use instructions and bake in policies that define what a model is allowed and what it must not do
- Use only verified sources, e.g. knowledge sources, vector stores, external databases etc, and if asked something outside of scope to refuse or indicate uncertainty
- Ensure that checks are run after a model generates content, for example fact checking, consistency, safety (toxicity), relevance etc, and if issues it can/will rewrite, block, or raise an alert rather than delivering directly
- Set controls for who can use what, the contexts that are allowed, the model versions that can be used, as well as architectural controls such as sandboxing, limiting the external actions models can trigger
With these guardrails part and parcel of the conversational AI platform, organizations should then be asking about observability tools, to ensure continued AI performance standards.
Observability
Observability is the bedrock of building trust, enables AI to evolve safely, and creates more effective guardrails. It provides transparency and accountability and allows the organization to be in control.
On a good conversational AI platform an organization should enable sight of and access to:
- Detailed logs
- Debug mode
- Metrics/Dashboards
- Alerts/Anomalies
- Feedback loops/human-in-the-loop
- Model version tracking & configuration management
- Auditing & compliance documentation
V-Studio platform
Creative Virtual’s V-Studio has guardrail, observability and debug capability built-in. Organizations are given direct access to the tools needed to safeguard their business.
The observability and guardrail tools ensure that the conversational AI solution delivers a great customer experience, builds loyalty and enhances reputation. Together, these three factors enable financial growth and sustainable profitability.
