AI Governance

Accuracy and performance metrics: Before deploying our AI models, human evaluators rigorously assess their accuracy. For example, our content skill tagging model achieved an impressive accuracy rate exceeding 80%. Our human evaluators come from diverse backgrounds to ensure that the model results are evaluated from multiple perspectives, promoting inclusiveness. After launch, we continue to monitor key metrics, such as click-through rates (CTR). Notably, our skill suggestion tools have demonstrated a 40% CTR, substantially outperforming industry norms and highlighting the effectiveness of our AI systems.

.NET SDK for secure Degreed AI development: Our newly developed .NET SDK is tailored for internal use, facilitating the integration of the AI Platform with .NET environments while adhering to strict security protocols to ensure safe data exchanges. This SDK simplifies our teams’ access to advanced AI capabilities while maintaining our commitment to data integrity and secure communications. Although not available for external use, this SDK empowers our .NET developers to efficiently and responsibly enhance our applications with AI.

Comprehensive data protection: Degreed follows privacy by design and ensures that privacy and security experts are involved in all of our product developments. We utilize state-of-the-art controls and procedures to ensure that personal information remains secure and handled in accordance with legal obligations.

Collaborative governance structures: We’ve established a Trust Management Committee comprising members from diverse disciplines—including data science and Artificial Intelligence, engineering, legal, information security, and privacy. This group convenes regularly to update and enforce compliance policies, ensuring alignment with both internal standards and evolving external regulations.

Executive AI oversight board: This board, comprising our CEO, the President, the Chief Product Officer (CPO), and the Chief Technology Officer (CTO), is a testament to our unwavering commitment to transparency in the development and deployment of AI technologies. It plays a pivotal role in ensuring we adhere to the highest standards of accountability.

Advanced AI compliance training: Our privacy team regularly conducts detailed training sessions for our data and AI teams to ensure they are current on data and AI regulations. Our teams review regulations as they are released to stay informed and ensure our developments remain compliant with international AI laws.

User empowerment in AI interaction: Our AI-powered platforms are designed to enhance user autonomy, offering suggestions that users can freely choose to follow or ignore, thereby promoting a user-centric approach.

Dynamic feedback utilization: We actively integrate feedback from clients across different industries to refine and enhance our AI. This responsive approach allows our solutions to meet diverse societal needs and expectations effectively.

In-depth AI documentation: We provide exhaustive documentation for our AI systems, including data flow diagrams and algorithm descriptions. This transparency helps stakeholders understand how AI functions within our products and ensures accountability.

Broad data sources: Our AI models benefit from a rich array of data sources, including strategic partnerships and public data sets from various industries and countries, ensuring our tools are informed by a diverse and comprehensive data set for more accurate and inclusive outputs.