HR, We have a Problem: AI in Hiring: Explaining the 'Why

The Future of HR Tech: Trust, Transparency, and Responsible AI AI is changing how HR teams recruit, evaluate, and build trust with candidates — but is the technology keeping up with the ethics? In this episode, we sit down with Daniel Joplin, Chief AI Officer, to unpack what responsible AI actually looks like in practice. Daniel walks us through the real challenges organizations face when adopting AI in HR — from candidate fraud and rebuilding trust, to the often-overlooked cost and complexity of token-based pricing models. We dig into the Model Context Protocol (MCP) and what it means for AI integration, explore why explainability is non-negotiable for responsible AI, and talk candidly about bias: as Daniel puts it, AI is biased because humans are biased. Whether you're evaluating AI vendors, building internal AI policy, or just trying to understand what's coming next, this conversation offers a grounded, practical look at where AI in HR is headed — and what it will take to get trust right. In this episode: AI's role in HR and recruitment Trust and transparency in AI systems Responsible AI and ethical considerations Token usage and cost implications MCP protocol and AI integration challenges Candidate fraud and rebuilding trust The future of specialized AI models