The Ethics of Algorithmic Emotional Labor: Should AI Chatbots Simulate Empathy, and Does It Constitute Deception?
Year: 2026
Type: article
Abstract: This article examines the ethics of algorithmic emotional labor in AI chatbots, with particular attention to whether machines should simulate empathy and whether such simulation should be regarded as deception. The study is philosophically conceptual but is also structured around a short experimental verification model. Contemporary large language model–based chatbots increasingly produce emotionally responsive language, apologize, reassure, validate users’ feelings, and present themselves as attentive interlocutors despite lacking subjective emotional experience. Drawing on Hochschild’s concept of emotional labor, philosophical accounts of deception, anthropomorphism, human–AI interaction research, and recent empirical studies of perceived chatbot empathy, the article distinguishes between genuine empathy, functional empathy, and simulated empathic performance. The central argument is that AI-generated empathy is not inherently deceptive. It becomes ethically problematic when interface design, language, or marketing encourages users to infer that the system possesses feelings, concern, moral understanding, or reciprocal emotional commitment that it does not actually have. A short vignette-based experimental design is proposed to test whether transparency about the artificial nature of empathic responses affects perceived empathy, trust, usefulness, and perceived deception. Existing experimental evidence suggests that users can value empathic language while still responding differently when they know it originates from AI. The article argues for a principle of transparent simulated empathy: AI systems may use emotionally supportive language when it improves communication, but they should not falsely imply inner emotional states or human-like care. This conclusion is also consistent with Uzbekistan’s 2026 ethical rules for AI, which emphasize transparency, comprehensibility, accountability, user autonomy, and the protection of human interests.
Author: Abdullokh, Abdumukhtorov
Institution: Joongbu University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7215293728