Human-Centered Design
We design Blue Yonder AI systems around human responsibilities and business outcomes. We aim to align automation, oversight, and safeguards with the level of risk to keep accountability clear.
AI Literacy and Responsible Usage
We promote AI literacy by making role-relevant information about our AI Systems available to users where appropriate. We encourage responsible use that considers expected benefits, potential risks, and best practices, while remaining aligned with the context and intended use cases for which our AI systems were designed.
Transparency and Explainability
We aim to provide users with clear and appropriate information about Blue Yonder AI Systems, including when AI is being used. Where appropriate, we provide understandable information about relevant data sources, material factors, and human oversight behind significant AI outputs or actions so users can interpret and govern their use responsibly.
Fair, Unbiased, and Non-Discriminatory
We design and operate AI Systems with the goal of supporting fair and non-discriminatory outcomes. We put in place proportionate measures, including tools, testing, and ongoing monitoring, to identify, assess, and reduce unfair bias in data, models, and processes across the AI lifecycle.
Data Security and Privacy
We design and operate AI Systems with technical and organizational controls intended to protect customer data, consistent with customer agreements and applicable law. We aim to minimize data use to what is needed for the intended purpose and apply access, retention, and privacy protections proportionate to risk.
Responsible AI
Blue Yonder is dedicated to ethically and securely leveraging Artificial Intelligence (AI) to transform supply chain operations. We uphold the highest standards of privacy, data protection, and data security.
Guided by our core values of empathy, integrity, and teamwork, the following principles outline our responsible AI practices, our commitment to regulatory compliance (including the European Union’s Artificial Intelligence Act and the General Data Protection Regulation), and our fundamental beliefs when delivering AI solutions for the benefit of our customers.
- Responsible AI
Principles
AI Security
We build AI Systems with security and resilience in mind, including controls for AI specific threats where relevant. We use risk-based testing and vulnerability management along with detailed reporting and logging to assess and improve these controls over time.
Governance and Accountability
We use governance processes for AI Systems throughout the life cycle, including defined roles, review practices, and escalation paths. We evaluate risk to align the level of controls with the degree of impact.
Applicability
We offer AI Systems where they can deliver meaningful value for the use case and operating context. Before deploying or expanding automation, we assess fitness for purpose, limitations, and potential impacts.
Sustainability
We consider environmental sustainability in how we build and run AI Systems. Where AI-enabled optimization may improve efficiency, we aim to support reduced waste and resource use.
Trustworthy and Reliable
We design and build our AI Systems to perform reliably for their intended use through in house and real-world validation, quality controls, and continual improvement.
