Board Governance | Bias Monitoring | Policy Setting
The Rewarded Efforts Company believes in the principle of "ethics at scale". This means that AI/ML platforms serve as multipliers for existing human behavior. Organizations that maintain robust compliance and CSR programs are able to capitalize on ML concepts. Comparatively, organizations that lack a strong culture in ethical business will experience added challenges as AI/ML models reinforce negative practices through automation.
Human behavior drives machine behavior.
Ethical AI should be proactively managed.
The board and C-suite have meaningful roles.
Focus on structure and policy goals.
Act on negative findings immediately.
Helping Organizations Evolve Their Maturity Model
Industry Use Cases
Our data scientists specialize in using computer vision and natural language processing (NLP) to extract patterns in employee sentiment. This includes key emotions, topic modeling, propensity matching, and links to key corporate programs.
It's critical for companies to develop learning curriculums that ensure equitable opportunities for all employees to develop their technical and leadership skills. ML platforms help identify preferred courses, learning pathways, and mentors.
Data driven criteria to assist executives in early talent identification, alongside rating employees across the potential, performance, and readiness spectrum. All within an Ethical AI framework that reduces bias.
Organizational Network Analysis (ONA) assists leaders with understanding how employees are connecting with each other. This includes ensuring that D&I hires are building connections, while operations teams are collaborating.
Understanding the reasons why employees choose to leave versus the reasons why they choose to stay are critically important. The ability to diagnose structural vs. leadership tendencies helps ensure that interventions match the need.
Ethical AI is a critical aspect of the talent acquisition process. This includes ensuring that resume screening and interviews are linked to D&I goals, while ensuring that the top candidates are interviewed.
Identifying and developing future leaders is a critical process for all organizations. Ethical AI helps establish automated processes for reviewing assessments and managing development assignments.
Employee productivity requires ethical management to limit the negative perceptions associated with employee monitoring. This includes optimizing workflow procedures and driving automation.
Rewarded Efforts works with clients to build tailored benchmarking models to determine industry competitiveness within all phases of the HIRE-TO-RETIRE lifecycle. This includes web scraping.
CHROs need assistance with developing robust governance models in the areas of employee privacy, data protection, and data leakage. This includes developing a chain of custody with the IT, data engineering, and people teams.
At the core of Ethical AI is the importance of employee privacy and data protection. In today's marketplace, it's critical for senior leaders to view data as part of the employee experience. This means that executives have a responsibility to protect confidential data, while developing policies for how information will be used in key decisions such as promotions, succession planning, hiring and terminations, and professional development.
Chain of Data Custody | Global Privacy Regulations | Violation Reporting