Modern Arguments For Why Artificial Intelligence Can't Have Emotions

"Emotions are not just cognitive states, but embodied experiences." — Antonio Damasio, neuroscientist and author of Descartes' Error

Despite progress in artificial emotion systems, current AIs differ profoundly from humans in how and why emotions occur. Emotional machines today are shadows of their biological counterparts – they can mimic some outward signs of emotion or implement simplified "emotion calculations," but they lack many fundamental attributes that make human emotions real. Key deficiencies include:

No Embodied Physiology

AI systems have no living body – no beating heart, no hormonal surges, no viscera – and thus miss the entire substrate of bodily feedback that is central to natural emotions. Emotions in animals are deeply embodied: a threat makes your muscles tense and heart pound, delight releases dopamine that gives a warm glow, etc. AI, by contrast, typically exists as software or as a robot with limited sensors. It does not (yet) have an endocrine system or the complex biochemistry that underlies feelings. As one analysis puts it, AI "have no body, no hormones and no emotional memory equivalent to that of a human being" built from a lifetime of bodily experiences. You can programme a robot to say it feels "pain" when damaged, but it's not the same as an organism actually aching.

Some researchers are attempting to add a degree of embodiment to AI – for instance, using soft robotics to give robots skin-like sensors, or creating artificial endocrine systems that modulate a robot's behaviour via hormone-analog signals (e.g. increasing a "stress" variable akin to adrenaline). These additions may allow an AI to register internal states (battery low, temperature high) and even have those states trigger responses analogous to hunger or stress. However, even with such tricks, the richness of human interoception (where dozens of hormones and neural signals continuously inform the brain of the body's condition) is far beyond current AI. Without a true embodiment, an AI's "emotions" remain more like data parameters than lived, bodily experiences.

Lack of Evolutionary Drives and Homeostatic Stakes

No current AI was forged by evolution to struggle, survive, and reproduce. Consequently, AIs lack the built-in motivational circuitry that gives rise to emotions in animals. Human emotions have intrinsic purposes (fear cares about self-preservation, love cares about offspring or allies, etc.) because they evolved to serve goals in a survival context. AI agents, on the other hand, only have whatever goals we programme or train them to have. A reinforcement learning agent might have a reward function, but it does not need anything in the fundamental way living creatures do (aside from trivial goals like maximising a score).

This is related to AI's lack of homeostatic vulnerability: a robot doesn't die if it fails to charge itself (we could just plug it in later or replace its battery), whereas organisms experience emotions intensely because their stakes are life-and-death or tied to reproduction. Some visionary AI thinkers argue that giving AI a sense of vulnerable embodiment – e.g. letting a robot risk running out of power or getting "injured" in a way that matters to its continued functioning – could imbue it with more genuine-like drives. To date, however, most AI have no intrinsic survival instinct. They do what they're optimised for, but there is no felt urgency behind their actions. Emotions like panic, desire, or grief are foreign to a system that has no evolutionary or personal stakes.

Missing Affective Memory and Development

Emotions in humans are shaped by a lifetime of experiences, starting from childhood. We form emotional memories – a dog bite in youth can leave a lasting fear, loving parents instil feelings of security, etc. – and our emotional repertoire matures over years of social interaction and learning. AI systems currently do not undergo a comparable developmental process. They can be trained on datasets (even datasets of emotional content), but this is not the same as living through experiences that mould a personality and emotional outlook.

The richness of a human's emotional life comes from an interplay of nature and nurture across decades, something an AI doesn't receive (at least not yet). As the Singularity 2030 report noted, AIs have no emotional memory "with its construction starting in childhood [and] carrying on with the learning of life in adolescence and adulthood". We might programme a backstory or artificial memories into an AI (for example, give a robot a fictional history so that it acts insecure or confident), but it's still scripted rather than organically grown. This absence of genuine emotional development means AI emotions are shallow and static by comparison. They lack the contextual depth that a human's emotions have, where each feeling is coloured by personal history.

No Genuine Conscious Feelings (Qualia)

Perhaps the most profound difference is that while humans feel emotions, AI (as far as we know) do not. When you are sad, there is a subjective qualitative aspect – it hurts, you experience sorrow. Current AIs, even if they say "I'm sorry" or lower their synthetic voice as if sad, are not experiencing any inner sadness. They are processing data and executing algorithms with no inner life.

One can say AI today only simulate emotions. This leads to the philosophical crux: does simulating emotion differ from actually having emotion? Most scientists and philosophers would answer yes – simulation is not duplication. In other words, an AI might act loving or fearful, but there is nothing it is like to be that AI in love or in fear. There is no evidence any existing AI system has subjective experiences or phenomenological consciousness, which many consider a prerequisite for genuine emotions. Without some form of conscious self-awareness or feeling substrate, an AI's emotions are akin to a puppet's – externally observable but hollow from the first-person perspective.

Specific Brain Mechanisms Unmatched

On a more detailed level, AI lacks the complex neural architecture that implements emotions in mammals. Humans have dedicated subsystems for emotion: e.g. the amygdala for emotional memory and threat evaluation, the ventral striatum for reward and pleasure, the hypothalamus-pituitary-adrenal axis for stress responses, etc. These systems interact in nonlinear ways that generate nuanced emotional states.

By contrast, an AI's "emotional model" (if it has one) might be a simplified mapping from certain inputs to an emotion label, or a single scalar "mood" variable affecting its outputs. The richness of human emotional dynamics – oscillating moods, mixed emotions, unconscious biases from emotions, hormonal cycles influencing mood over hours or days – has no ready analogue in AI.

Researchers are aware of this gap. Some have tried to introduce complexity by, for example, modelling artificial hormones that fluctuate and influence an agent's behaviour over time (for instance, an artificial stress hormone that accumulates if the agent is overloaded with tasks and causes it to take a "rest" action). While interesting, these remain primitive compared to the symphony of biochemical modulation in a real organism.

Comparison of Biological vs. Artificial Emotion Systems

In conclusion, while AI systems can be designed to recognise emotions, simulate emotional responses, and even modulate their behaviour based on emotional-like parameters, they fundamentally lack the embodied, evolutionary, developmental, and conscious aspects that define genuine emotions in living beings. The gap between artificial and biological emotions remains substantial, even as AI becomes increasingly sophisticated in its behavioural simulations.

This is not to say that machines could never have emotions. But, as I like to say: If a human wore an octopus suit, they would still be human-like—they wouldn’t suddenly transition into an octopus’s way of thinking— the fundamental structure of their consciousness would remain the same. This is the same for AI— it's fundamentally still a discrete system running on silicon. As technology advances, particularly in areas like embodied cognition, neuromorphic computing, and possibly consciousness research, we may develop artificial systems that more closely replicate the conditions necessary for emotions. However, for now, artificial emotions remain just that – artificial simulations rather than authentic feelings.