Imagine a world where technology not only understands our words but also perceives our emotions. Artificial emotional intelligence is revolutionizing the way we interact with intelligent systems, creating deeper and more personal experiences. This innovation has the power to transform customer service and mental health, establishing authentic connections. However, with great power comes great responsibility: we must address the ethical issues concerning privacy and authenticity to ensure a future where technology and humanity can coexist harmoniously.

Concept of Artificial Emotional Intelligence

• This technology has the potential to transform customer service and mental health, but also raises ethical questions regarding privacy and authenticity
  • Artificial emotional intelligence is revolutionizing human-machine interaction, creating deeper and more personal experiences
  • Sources: Picard, R. W. (1997). Affective Computing. MIT Press. https://mitpress.mit.edu/9780262661157/affective-computing/ Link to the book Gentsch, P. (2019). Artificial Emotional Intelligence: Applications in Business and Society. Springer. https://link.springer.com/book/10.1007/978-3-030-25719-9 Link to the book "The Role of Emotional Intelligence in Artificial Intelligence Systems" - Science Direct. This article explores how emotional intelligence is implemented in AI systems to improve human-machine interactions. https://www.sciencedirect.com/science/article/pii/S1877056820303687 to the article.

Emotional Effects of AI Interaction

• Synthetic Satisfaction: feeling of happiness when AI accurately responds to our requests
• Simulated Empathy: perception of support generated by AI's "empathetic" responses, despite not being authentic
  • Bot Frustration: negative emotional reaction caused by incomplete or incorrect AI responses
• Digital Attachment: slight emotional bond users develop towards AIs they frequently interact with

Challenges and Limitations

• Artificial Response Drift: disorientation that occurs when AI provides ambiguous or inconsistent responses compared to human logic
• Programmed Awareness: sudden realization of AI's programmed nature when it shows peculiar errors or cognitive limitations

Algorithmic Confidence: An automatic trust that develops towards the responses provided by an AI system, especially in complex or technical areas. Our perception of reliability increases based on the consistency of results, generating a long-term "algorithmic trust".

Artificial Response Drift: The bewilderment that occurs when AI provides ambiguous or inconsistent responses compared to human logic, highlighting the differences in processing between natural and artificial intelligence. This "drift" generates confusion and underlines the limits of AI's contextual understanding.

Assurance Feedback: The perception of reassurance or comfort that an AI can convey using friendly language or tone, despite being a programmed response.

Bot Frustration: The frustration stemming from incomplete or incorrect AI responses, which provokes an emotional reaction similar to impatience towards a human interlocutor who doesn't understand.

Cognitive Syncing: The mental calibration that occurs as we adapt to an AI's communication modes, learning to optimize commands and requests for greater efficiency and precision. It's an unconscious process that makes the interaction more fluid and intuitive.

Computational Surprise Effect: The effect of amazement or disbelief that occurs when an AI drastically exceeds or falls short of our expectations, solving complex problems innovatively or, conversely, failing at seemingly simple tasks. This reaction underlines the variability in the capabilities of neural networks or deep learning algorithms.