Conversational AI has become the de facto interface for quick answers and friction-free productivity; yet studies show that mainstream chatbots reinforce confirmation bias, reward shallow prompt–response cycles, and invite users to offload rather than refine their thinking. This chapter confronts that dilemma through ERWIN Voice, the voice enabled second iteration of ERWIN, a low affect, minimally anthropomorphic sparring partner designed not to please but to press its interlocutor toward deeper dialogic reasoning. It prompts users to think aloud, refine ideas, and co-produce knowledge rather than consume AI-generated answers. Building on studies in conversational analysis, socially augmented argumentation, and trust research in voice anthropomorphism, we frame a trust paradox: social cues are needed for engagement, yet overt human-like mimicry triggers skepticism and ethical alarm. ERWIN resolves this paradox by combining an emotionally restrained synthetic voice with dialogic reasoning to prompt users to externalize, challenge, and refine their arguments. Early exploratory sessions with a small convenience sample in higher education and corporate foresight settings suggested more clarification and counterargument moves than we observed with a baseline chatbot (formal evaluation is forthcoming). We critique the limitations of current conversational agents, outline ERWIN’s design workflow, and discuss future iterations. We identify design guidelines and a roadmap for future work, a self-voice-clone prototype that lets users “spar dialogically with their consciousness,” extending think-aloud protocols into a circular, self-reflexive loop, nurturing human criticality rather than displacing it. We believe that dialogic voice agents can scale cultural participation without generating additional e-waste, thereby supporting diversified and sustainable practices.