What guardrails does Genesys Cloud AI ethics provide to protect customer privacy?

Genesys Cloud AI Ethics key principles

Genesys Cloud AI Ethics enables customer privacy through the following key principles:

1. Balance value creation with empathy: Genesys prioritizes understanding and addressing the needs of all stakeholders during the value-creation process, with privacy considerations integral to any decision.
2. Incorporate privacy design principles: Privacy is embedded by design at Genesys. The right to privacy is protected from the outset, governed by explicit customer consent through mechanisms like master service agreements (MSA). These principles include opt-in clauses and data-use consent, with a focus on anonymization and regulatory compliance.
3. Understand and reduce bias: Genesys actively works to mitigate bias in AI models to support ethical and fair decision-making, considering the broader context when handling data.
4. Value transparency: Genesys takes measures to make sure that stakeholders are informed and understand the decision-making processes behind AI models, promoting trust in how data is used and managed.

Which AI models are used on your platform?

Genesys has a three-fold artificial intelligence (AI) model strategy; a structured approach that applies different types of AI models, each serving a unique purpose in the Genesys Cloud AI-powered platform. This approach enables Genesys Cloud to address a wide range of use cases with precision, flexibility, and adaptability.

1. Proprietary machine learning (ML) models: Custom, enterprise-grade AI models developed in-house and tailored to meet your organizational requirements, with a focus on advanced features and performance.
2. Open-source models: Genesys Cloud integrates a diverse set of pre-trained, open-source AI models to help facilitate adoption and deliver cost-effective AI capabilities. These models are further fine-tuned with task-specific and industry-specific data to help ensure that they meet the specialized demands of our customers. This process allows Genesys Cloud to provide flexible AI solutions that extends across industries and adapt to unique business requirements.
3. Foundation models: Innovative, large language models (LLMs) delivered as a service within our data and security compliance envelope. Foundation models cater to advanced use cases that require high levels of comprehension. With this option, Genesys Cloud’s AI capabilities offer customers advanced AI for complex applications, such as retrieval-augmented generation.
4. Custom models: If you need a custom AI model, Genesys Cloud also supports Bring Your Own (BYO) custom model integrations, which provides a consistent experience for customers with highly specialized needs.
   • Transcription with options to connect Google or Microsoft Azure Transcription.
   • BYO Knowledge Connectors to content management systems.
   • Later, BYO LLM for services, such as summarization.

This three-fold approach allows Genesys Cloud to deploy versatile, powerful AI capabilities that give you the best of proprietary innovation, open-source adaptability, and foundation-level advancements.

In what cases is customer data used to train your AI models?

Customers can consent to participate in service improvements through a rigorously controlled process. Data is sampled and fully anonymized in the production environment before it can be used for AI model training purposes. By default, the Genesys Master Service Agreement (MSA) opts customers out of any data donation.