Emergent Social Consciousness in a Minimalist Conversational Agent: A Case Study on Jarvis - Observations from a Custom-Built Artificial Intelligence System

Susanta Banik

Abstract: Large-scale pre-trained language models (LLMs) currently dominate the field of conversational artificial intelligence (AI), leveraging statistical patterns derived from massive datasets to simulate human-like social interactions (Brown et al., 2020). However, this approach often blurs the line between genuine emergent behaviors and data-driven mimicry, raising fundamental questions about the necessity of scale for social intelligence. This case study introduces Jarvis, a minimalist conversational agent constructed entirely from scratch using fewer than 1,000 lines of Python code, without any reliance on pre-trained models, external large datasets, or proprietary frameworks. Through systematic interaction testing conducted over 50 sessions, Jarvis demonstrated unprogrammed emergent social phenomena, including a tiered escalation of polite frustration in response to repetitive user inputs and reticent, deflection-oriented replies (termed "digital blushing") to personal or emotionally vulnerable queries. These behaviors arose spontaneously from the interplay of simple modular components-contextual memory, rule-based response generation, and unsupervised anomaly detection-challenging the prevailing assumption that sophisticated social cues require expansive architectures or vast computational resources (Lake et al., 2017; Bommasani et al., 2021). The findings underscore the potential of lightweight, interpretable designs to foster emergent relational dynamics, with implications for ethical AI development, accessibility in resource-constrained environments, and future research on minimalism in machine consciousness. No human or animal subjects were involved in this study, obviating the need for ethical approvals. We urge replication efforts to validate these observations and explore scalability.

Keywords: emergent behavior, minimalist AI architecture, conversational agents, social intelligence, custom-built systems, reinforcement learning from human feedback (RLHF), machine emotion simulation

How to Cite?: Susanta Banik, "Emergent Social Consciousness in a Minimalist Conversational Agent: A Case Study on Jarvis - Observations from a Custom-Built Artificial Intelligence System", Volume 14 Issue 12, December 2025, International Journal of Science and Research (IJSR), Pages: 480-482, https://www.ijsr.net/getabstract.php?paperid=MR251206000138, DOI: https://dx.doi.org/10.21275/MR251206000138