Assessing Sentience in Artificial Intelligence: A Structured Literature Review of Theories, Indicators, and Evaluation Frameworks (2020–2025)
International Journal of Research and Innovation in Social Science January 1, 2026 DOI: 10.47772/ijriss.2025.91200245 (opens in new tab) via OpenAlex
Summary
AI-generated from the abstractArtificial intelligence has become integral to knowledge generation, decision-making, and ethical discourse. Rapid advances in self-reflective and adaptive AI have intensified debates about machine consciousness in business, science, and academia. This review examines methods for detecting signs of consciousness in artificial systems and identifies three primary trends from 2020 to 2025 that have shaped research on artificial consciousness.
Study at a glance
| Characteristics | Review Peer reviewed |
|---|---|
| Keywords | Sentience Clarity Consciousness Context archaeology Field mathematics |
| Key finding | Identifies three primary trends from 2020 to 2025 that have influenced research on artificial consciousness. |
Abstract
Artificial Intelligence (AI) has evolved from a specialised field of computing into a vital part of how we generate knowledge, make decisions, and address ethical issues (OpenAI 2025). As these developments occur rapidly, progress in self-reflective and adaptive AI has amplified debates about whether machines can have consciousness in business, science, and academia. To provide clarity on navigating this complex area, this review looks at ways to detect signs of consciousness in artificial systems. Specifically, from 2020 to 2025, three primary trends have influenced research on artificial consciousness, establishing the context for this review.