Artificial Intelligence (AI) Ethics Principles
Table of Contents
Our Principles
At Dayforce, our Artificial Intelligence (AI) Ethics Principles are at the core of how we seek to design and operate AI systems. They will inform our management philosophy, guide our approach to product development, and provide our customers and partners with a framework that enables feedback and reflects our commitment to trust. These Principles form the foundation for responsible data innovation at our company, and they help us deliver on our brand promise: Makes Work Life Better™ for all.
How Dayforce Defines AI Systems
We define AI systems as any software feature that uses machine learning (ML) or natural language processing (NLP) to assist human judgment to facilitate change. Our systems—whether they are developed in-house or acquired from third parties—always serve our customers and their employees, whether it is a solution that helps reduce time-to-hire for recruiters or one that assists individuals in selecting the best healthcare plan for their families.
Our AI ethics principles inform our approach to responsible innovation.
Trust
I. Privacy and Security
Privacy and security are always top of mind
Privacy and security are at the core of our product development lifecycle. From ideation to implementation, our AI systems work securely, respect the privacy of stakeholders, and adhere to our company-wide approach to privacy and security as a Software as a Service (“SaaS”) provider.
II. Transparency
AI systems must be accessible and understandable.
AI-enhanced products will only be trusted and accepted if their models are explainable. This means that algorithms should be understood by customers and their employees. Individuals should be aware of when AI systems are used and understand how insights, inferences, or predictions are made.
III. Reliability
We prioritize dependability in our system operations
Developing and deploying dependable AI systems requires training, testing, and feedback. With this approach, we deliver AI-enhanced products that are designed with accuracy, reproducibility, and reliability in mind:
- Training - AI systems must be trained and monitored so they can learn and improve over time.
- Testing - Algorithms and the data used to feed them should be as accurate as possible. Algorithms should be continuously monitored to ensure accuracy and to avoid any unintentional bias.
- Constant Feedback - We solicit feedback from stakeholders that are impacted by Dayforce’s AI systems to increase reliability
IV. Sustainability
We prioritize environmental considerations in creating and using AI.
AI-enhanced product deployments should align with sustainability goals to ensure long-term environmental benefits. We are mindful that these technological advancements should be designed to minimize environmental impacts through actions such as right-sizing the model for the use case and through integrating sustainability considerations into our selection of public cloud providers and colocations data center partners that support our AI-enhanced products.
Employee Focus
V. Social Good
We develop technology that empowers and helps people.
We design our AI systems to help foster positive outcomes for individuals and society. We believe data is a powerful instrument for promoting equity, empowering people, and augmenting the talents of our diverse user base. Our AI systems involve human choice as an active component of decision-making, and we strive to minimize the potential adverse impacts of automated models on customers or employees.
VI. Inclusion
We strive to prevent bias in AI systems.
AI-enhanced products must be designed to empower and promote a culture of diversity, equity, and belonging. We build AI systems that foster inclusion, benefit our diverse user base, and follow best practices for AI bias minimization— including an initial evaluation of potential bias in AI models and datasets, ongoing monitoring, and appropriate internal controls.
VII. Accountability
We act with integrity at all stages of a product's lifecycle.Integrity and accountability are business imperatives. That is why we follow our company’s core values and all relevant laws and regulations. We strive to demonstrate responsible AI by being attentive to stakeholder feedback and ensuring transparency. We document trade-offs made through our AI systems and provide opportunities for redress