Creates realistic job applicant profiles with identical qualifications but varying demographic attributes to isolate bias effects.
Calculates multiple statistical fairness metrics including demographic parity, equal opportunity, predictive parity, and disparate impact ratios.
Generates heatmaps, disparity charts, and interactive visualizations showing where bias occurs across different job categories and demographic intersections.
Connects directly to existing hiring platforms via REST APIs to audit production systems without disrupting normal operations.
Tracks bias metrics over time to measure improvement from debiasing interventions and detect regression in fairness.
Allows customization of audit parameters including job types, qualification levels, demographic attributes, and geographic variations.
HR software companies use Themis to audit their AI-powered hiring platforms before releasing updates to clients. By running comprehensive bias tests across different job categories and demographic groups, they can identify discriminatory patterns and implement fixes proactively. This helps vendors meet client requirements for fair hiring tools and reduce legal liability from biased algorithmic decisions.
Large enterprises with internal recruitment teams deploy Themis to validate that their automated resume screening systems don't undermine diversity initiatives. The tool helps quantify whether AI hiring tools are disproportionately rejecting qualified candidates from underrepresented groups. Companies use these insights to adjust algorithms or implement human oversight where bias is detected.
Labor departments and equal employment opportunity agencies use Themis to audit employers' hiring systems for compliance with anti-discrimination laws. Regulators can test whether companies' automated hiring tools exhibit patterns that would violate laws like Title VII or the ADA. The standardized metrics provide objective evidence for enforcement actions or guidance development.
Researchers studying bias in hiring algorithms use Themis as a standardized framework for comparative studies. The tool's controlled experiments and consistent metrics enable reproducible research on how different AI techniques affect hiring fairness. Academic institutions contribute back improvements to the open-source codebase, advancing the field of algorithmic fairness.
HR consulting and diversity advisory firms incorporate Themis into their service offerings to help clients audit hiring systems. Consultants use the tool to generate detailed fairness reports with specific recommendations for mitigation. This transforms subjective diversity assessments into data-driven engagements with measurable improvement targets.
Large organizations with dedicated audit functions integrate Themis into their regular compliance checklists. Internal auditors schedule periodic bias tests whenever hiring algorithms are modified or new job categories are added. This creates an ongoing fairness assurance program rather than reactive investigations after complaints arise.
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15Five operates in the people analytics and employee experience space, where platforms aggregate HR and feedback data to give organizations insight into their workforce. These tools typically support engagement surveys, performance or goal tracking, and dashboards that help leaders interpret trends. They are intended to augment HR and management decisions, not to replace professional judgment or context. For specific information about 15Five's metrics, integrations, and privacy safeguards, you should refer to the vendor resources published at https://www.15five.com.
20-20 Technologies is a comprehensive interior design and space planning software platform primarily serving kitchen and bath designers, furniture retailers, and interior design professionals. The company provides specialized tools for creating detailed 3D visualizations, generating accurate quotes, managing projects, and streamlining the entire design-to-sales workflow. Their software enables designers to create photorealistic renderings, produce precise floor plans, and automatically generate material lists and pricing. The platform integrates with manufacturer catalogs, allowing users to access up-to-date product information and specifications. 20-20 Technologies focuses on bridging the gap between design creativity and practical business needs, helping professionals present compelling visual proposals while maintaining accurate costing and project management. The software is particularly strong in the kitchen and bath industry, where precision measurements and material specifications are critical. Users range from independent designers to large retail chains and manufacturing companies seeking to improve their design presentation capabilities and sales processes.
3D Generative Adversarial Network (3D-GAN) is a pioneering research project and framework for generating three-dimensional objects using Generative Adversarial Networks. Developed primarily in academia, it represents a significant advancement in unsupervised learning for 3D data synthesis. The tool learns to create volumetric 3D models from 2D image datasets, enabling the generation of novel, realistic 3D shapes such as furniture, vehicles, and basic structures without explicit 3D supervision. It is used by researchers, computer vision scientists, and developers exploring 3D content creation, synthetic data generation for robotics and autonomous systems, and advancements in geometric deep learning. The project demonstrates how adversarial training can be applied to 3D convolutional networks, producing high-quality voxel-based outputs. It serves as a foundational reference implementation for subsequent work in 3D generative AI, often cited in papers exploring 3D shape completion, single-view reconstruction, and neural scene representation. While not a commercial product with a polished UI, it provides code and models for the research community to build upon.
