AI Safety At TMS Associates

TMS Associates leverages artificial intelligence—including large language models (LLMs) and conversational speech models (CSMs)—to enhance our talent advisory, recruitment, and business process improvement solutions. We recognize that AI safety is mission-critical when serving healthcare providers who depend on us to build high-performing teams that directly impact patient outcomes. Our AI practices align with our commitment to confidentiality as outlined in our Privacy Policy, where we state that "confidentiality is the cornerstone of trust" in our vision to become the healthcare industry's most trusted talent and advisory partner.

TMS Associates maintains a comprehensive AI safety framework built on human-centered decision making, data protection, bias mitigation, and accuracy standards. All AI-assisted recommendations for leadership and clinical placements undergo human review by our experienced talent advisors. Final hiring decisions always rest with our healthcare clients and their leadership teams. We ensure transparent communication about AI involvement in our processes while maintaining the highest ethical standards. As stated in our Privacy Policy, we employ "industry-best practices to protect all information, including encrypted data storage, restricted system access, and monitoring protocols" that extend to all AI-powered services.

Our AI systems operate within the same robust security framework detailed in our Privacy Policy. Personal and professional information is encrypted and access-controlled within our Zoho One ecosystem, leveraging Zoho Corporation's 256-bit Advanced Encryption Standard (AES) encryption for data at rest. AI processing occurs within secure, compliant environments with no sensitive healthcare data used to train external AI models. Consistent with our Privacy Policy commitment, "only authorized personnel, bound by confidentiality obligations, have access to client or candidate information." All data handling meets applicable privacy regulations, and we maintain strict consent-driven disclosure protocols where "we never share information without explicit, written permission from the respective party."

Key Point. Our AI model uses over 1.75 trillion internal settings (“parameters”), which is roughly ten times larger than earlier models like those with 175 billion parameters.

Simple Analogy. Imagine trying to count one setting per second: it would take over 55,000 years to reach 1.75 trillion—this highlights its vast size, not a literal process. Compared to the human brain’s estimated 86 billion neurons, it’s like managing a library far larger than most people have ever seen.

Why Size Matters (and Doesn’t Guarantee Perfection). More parameters can help the AI catch subtler patterns and give richer, more context-aware suggestions, but real accuracy also depends on training data quality, ongoing monitoring, and human review. Large models need significant computing resources and careful validation, so we combine automated outputs with confidence scores and expert checks before using recommendations.

Takeaway for Non-Technical Readers. A model this large can offer more nuanced insights, but it isn’t infallible. Think of it as a very extensive reference tool: powerful when used correctly, yet always paired with human oversight to ensure reliability.

LLMs analyze candidate profiles and job requirements to identify optimal matches, with automated initial screening followed by human validation for all shortlisted candidates. We provide skills gap analysis and development recommendations while maintaining human oversight for diversity, equity, and inclusion considerations. Transparent scoring methodologies are available to clients upon request. All talent matching activities comply with our Privacy Policy's consent requirements and mutual NDA protections that "safeguard all parties by outlining strict guidelines on how information is exchanged and protected."

CSMs handle initial inquiries and appointment scheduling through Voxia, with AI-powered chatbots providing 24/7 client support and seamless human handoff capabilities. Our SMS communications through AI systems comply with our Privacy Policy's 10DLC regulations and TCPA requirements, obtaining "prior express written consent before sending promotional text messages." Automated follow-up communications include personalization review to ensure appropriate tone and content for healthcare industry communications, with clear opt-out mechanisms as detailed in our Privacy Policy.

Predictive models analyze healthcare staffing trends and market demands while performance analytics track placement success and client satisfaction. Risk assessment protocols evaluate challenging placements in critical care roles. All analytical insights undergo human interpretation before strategic recommendations are presented to clients. Our analytics practices maintain the same confidentiality standards outlined in our Privacy Policy, ensuring that "financial, operational, or personal data remains strictly confidential throughout every phase of our engagement."

Enhanced safety measures apply to positions directly impacting patient care and medical education, with primary focus on Graduate Medical Education (GME) program development and enhancement across all organizational levels. Mandatory human review is required for all AI recommendations involving the full spectrum of GME roles including Designated Institutional Officials (DIOs), Program Directors, Associate Program Directors, Core Faculty, Chief Residents, GME Administrators, Program Coordinators, Education Specialists, and other essential GME support staff. While we maintain rigorous standards for physician, advanced practitioner, and executive leadership searches when supporting client needs, our specialized expertise centers on comprehensive GME program staffing where additional validation steps ensure ACGME compliance requirements, clinical competency standards, educational oversight qualifications, and administrative proficiency are properly assessed and documented. For all GME positions, AI assessments include verification of relevant credentials, educational experience, program administration capabilities, and demonstrated understanding of residency training requirements at both institutional and program levels. These protections reflect our Privacy Policy commitment to understanding "the additional nuances and regulatory requirements inherent in healthcare—ranging from personal privacy to organizational compliance," with specialized attention to the complex regulatory environment governing medical education, resident training programs, institutional accreditation standards, and the operational infrastructure that supports successful GME programs.

Clients are informed when AI tools contribute to candidate evaluations, with clear documentation of AI involvement in recruitment processes. We maintain open communication about AI limitations and human oversight requirements, ensuring clients understand the balance between automated efficiency and human expertise. Our transparency aligns with our Privacy Policy commitment to "clear permission protocols" and our dedication to "transparency and confidence, enabling healthcare employers to share proprietary data and healthcare professionals to discuss career aspirations without worry."

Real-time alerts detect unusual AI behavior or recommendations, with regular performance reviews comparing AI suggestions to actual outcomes. Client feedback is integrated into ongoing safety improvements, and system performance metrics are tracked continuously to maintain optimal service quality. Our monitoring protocols extend the same "cybersecurity standards [that] are continuously assessed and updated to align with evolving regulatory requirements," detailed in our Privacy Policy.

Our cross-functional team includes clinical advisors, data scientists, and client representatives who review AI safety protocols quarterly and investigate any reported concerns. The committee ensures ethical AI practices align with healthcare industry standards and client expectations while driving continuous improvement in our AI safety framework. Ethics committee decisions uphold our Privacy Policy commitment that "our obligations to maintain confidentiality extend beyond the conclusion of any specific project or search assignment."

Independent third-party reviews of our AI systems occur annually, with findings shared with key clients and incorporated into safety improvements. Internal audits are conducted quarterly to assess compliance with established AI safety protocols and identify opportunities for enhancement. Our audit practices complement the security measures outlined in our Privacy Policy and ensure ongoing compliance with applicable U.S. federal and state privacy laws.