The rapid growth of the older adult population calls for conversational robots that foster social participation and community inclusion. We report a pilot study at Tohoku University in which eight adults (65–78 years old) each held a 20-minute semi-structured dialogue with Android, a hyper-realistic android equipped with Japanese BERT emotion recognition and GPT-3.5-based response generation. Sentiment logs and post-interaction interviews showed that participants generally felt at ease, described the robot as a “good listener,” and remained engaged throughout the exchange; only occasional affective mismatches disrupted rapport. These preliminary results suggest that real-time affect adaptation can support empathic HRI, yet also expose the need for tighter timing and context control. Our mixed-methods findings lay the groundwork for designing emotionally responsive humanoids that enrich elder-care settings.