Group 1 - The year 2024 is referred to as the "Year of Humanoid Robots," with predictions that emotional communication between humans and robots will become a norm in future intelligent societies [1] - The concept of machine emotions and AI companionship raises questions about the impact on human-machine interaction and relationships, as well as cultural and gender perspectives on these emotional connections [1] - The discussions highlight the potential social impacts, technological risks, and ethical issues arising from human-robot emotional interactions, prompting interdisciplinary research [1] Group 2 - The concept of machine emotions is defined and analyzed through emotional intelligence, human-machine emotions, and human-machine interaction, advocating for a limited approach to the development of machine emotions [2] - A new perspective on endowing machines with emotional capabilities is proposed based on a life-centered consciousness theory, suggesting that simulating biological homeostasis can lead to autonomous adaptability in machines [2] - Ethical reflections on human-machine emotional interactions, particularly in the context of AI resurrection technology, reveal risks such as emotional dependency and identity crises, necessitating regulatory and cultural adjustments [2] Group 3 - The philosophical discussions in affective computing often rely on idealized technical assumptions, overlooking the importance of forgetting mechanisms in creating realistic and ethical AI emotional systems [3][4] - The current challenges in affective computing include the reliance on data quality and the superficiality of emotional expressions in AI systems, which fail to capture the complexity of human emotional experiences [6] - The introduction of forgetting mechanisms is essential for enhancing the adaptability and authenticity of emotional AI, allowing systems to discard outdated emotional data [11][12] Group 4 - The proposed phenomenology-inspired human-like forgetting neural model (PHFNM) aims to integrate individual and collective forgetting processes in emotional AI systems, reflecting both natural decay and active forgetting [19][22] - The model consists of three interconnected layers: a low-dimensional emotional index layer for natural decay, a memory encoding layer for dynamic reconstruction, and an active forgetting layer for ethical regulation [23][24][25] - The PHFNM framework emphasizes the need for a balance between individual emotional memory and collective social interactions, ensuring that emotional AI systems remain relevant and ethically responsible [26][27]

Group 1: Core Concepts of Machine Emotion - Machine emotion refers to the external manifestation of human-like emotions by AI systems, relying on emotional intelligence and emotional computing as the main technological pathway [3][5][6] - The concept of machine emotion is interdisciplinary, involving cognitive science, emotional philosophy, psychology, computer science, and sociology [5][6] - Emotional intelligence is the foundational capability for machine emotion, encompassing emotional recognition, expression, experience, and control [6][9] Group 2: Construction and Characteristics of Machine Emotion - Machine emotion is characterized by its constructiveness, mimetic nature, embodiment, and computational aspects, emphasizing the generation logic and operational mechanisms of machine emotion [5][12] - The realization of machine emotion depends on emotional computing, which captures human emotional data through various sensors and builds a personalized computational system for emotional understanding and response [7][12] - Machine emotion is limited in its ability to mimic human emotional recognition and expression but lacks genuine emotional experience and control [12][16] Group 3: Human-Machine Emotional Interaction - Human-machine emotion is fundamentally a projection of human emotions onto machines, lacking true intersubjectivity and emotional sharing [13][15] - The construction of human-machine emotion is influenced by psychological mechanisms, such as anthropomorphism and social cultural factors, which shape human emotional responses to machines [15][16] - The emotional interaction between humans and machines can lead to risks such as emotional deception, emotional monitoring, emotional degradation, and emotional manipulation [17][18] Group 4: Ethical Considerations and Development of Machine Emotion - To mitigate risks associated with machine emotion, it is essential to construct machine emotions that serve human needs and enhance interaction [18][19] - The development of machine emotion should adhere to a limited approach, ensuring the appropriateness of emotional capabilities and avoiding exaggerated claims [19][20] - Transparency, authenticity, and rigor should guide the promotion of machine emotions, ensuring users are aware of the simulated nature of emotional responses [20][21]