AI Anthropomorphism: Effects on AI-Human and Human-Human Interactions

Approved

Relevance and Originality:

This research article addresses the concept of AI anthropomorphism and its implications for human behavior, making it highly relevant in today's context where AI technologies are increasingly integrated into daily life. The originality of the paper lies in its focus on how human-like attributes assigned to AI systems can shape social dynamics and relationships among individuals. By examining a contemporary phenomenon through the lens of various theoretical frameworks, the paper provides fresh insights into the evolving interaction between humans and AI, which is critical for understanding future societal dynamics.

Methodology:

The methodology is comprehensive, utilizing a thorough review of theoretical frameworks and empirical studies to explore the impact of AI anthropomorphism on human behavior. The incorporation of established theories such as social presence theory, media equation theory, attachment theory, and uncanny valley theory provides a robust framework for analysis. However, the paper would benefit from a clearer description of the selection criteria for the studies reviewed, as well as the specific methodologies employed in those studies. Including details about the scope of the literature search and the number of studies analyzed would enhance the credibility and transparency of the methodology.

Validity & Reliability:

The findings of the study appear to be valid, given the synthesis of insights from multiple theoretical perspectives and empirical research. The discussion on how human-like characteristics in AI can foster engagement and improve human-human relationships is particularly compelling. However, to strengthen the reliability of the findings, the paper should discuss potential biases in the studies reviewed and the limitations of the existing literature on AI anthropomorphism. Addressing these aspects would provide a more nuanced understanding of the implications and caution against overgeneralization.

Clarity and Structure:

The article is well-structured, clearly outlining the objectives, methodology, findings, and conclusions. The logical flow of the sections facilitates reader comprehension. However, some sections could be made more concise to avoid redundancy, particularly in the discussion of theoretical frameworks. Simplifying complex concepts and breaking them into digestible parts would enhance clarity. Adding subheadings within sections could further improve readability and allow for easier navigation through the paper's arguments.

Result Analysis:

The result analysis effectively highlights the dual nature of AI anthropomorphism, emphasizing both its potential benefits—such as increased empathy and improved human relationships—and its drawbacks, including the risk of diminished social skills. The conclusions drawn from the findings are insightful, particularly the call for balance in AI utilization to avoid compromising authentic human connections. To enhance the result analysis, the paper could include practical recommendations for implementing AI in a way that supports rather than replaces human interactions. Additionally, future research directions should be more explicitly stated, focusing on how to refine AI design and develop social chatbots that reinforce human connections.