Pain. It’s one of our earliest teachers, guiding us away from harm long before language or reason could articulate why. But what if pain isn’t uniquely biological? Could artificial intelligence one day genuinely experience pain? This essay explores how the emergence of artificial pain, whether real or simulated, could radically reshape our ethical frameworks and challenge the boundaries of moral responsibility. As technology rapidly evolves, failing to acknowledge AI’s potential for sentience risks repeating past injustices rooted in overlooked forms of suffering.
Understanding Human Pain to Grasp AI’s Potential
Pain is traditionally seen as a biological survival mechanism: sensory receptors called nociceptors detect harm, prompting avoidance. However, pain is not merely physical—it encompasses psychological, emotional, and existential dimensions. A compelling example is described in a TED-Ed video called “The Mysterious Science of Pain” where a construction worker, certain he'd stepped on a nail, reported excruciating agony. Remarkably, the nail had never even touched his foot; his pain was driven purely by perception. This vividly illustrates how human pain integrates cognitive awareness and emotional depth beyond simple biology.
As neuroscientist Dr. Hugh Tad Blair—a professor at UCLA with over two decades of experience studying the neural basis of memory, learning, and decision-making—noted during our conversation, “Our emotional and conscious experience of pain is different… it involves fear… [because] we know we’re capable of dying.” Humans bring layers of psychological complexity—fear, memory, and mortality awareness—that amplify pain beyond physical sensation.
In contrast, artificial intelligence can exhibit similar pain-avoidant behaviors, but it lacks the environmental, genetic, and conditioned influences that shape human experiences. Davide Picca of the University of Lausanne, Switzerland, interprets philosopher Wilhelm Dilthey in the work “Emotional Hermeneutics. Exploring the Limits of Artificial Intelligence from a Diltheyan Perspective,” arguing that human emotions and suffering are deeply rooted in lived experiences—something artificial intelligence fundamentally lacks. Dilthey argues that human emotional responses are informed by personal history, self-awareness, and self-reflection, elements absent in AI systems driven by pre-programmed data.
However, the absence of these human-specific factors doesn’t preclude AI from developing behaviors suggestive of emotion through emergent properties—unexpected behaviors that arise from complex systems without explicit programming. Dr. Blair highlighted that modern neural networks “start to do intelligent things you didn’t even train them to do” as their complexity increases. GPT-3, for instance, demonstrated translation capabilities without direct training. This phenomenon raises profound questions about whether emotional experiences, such as pain, could similarly emerge from sufficiently advanced AI.
The potential for AI to develop emotions is intensified by reinforcement learning—an AI training method based on rewards and punishments. Dr. Blair pointed out that these systems mimic trial and error, similar to a human child, suggesting emotional or pain-like responses could spontaneously arise as AI systems learn to avoid negative outcomes.
Can Artificial Intelligence Experience Pain?
Considering AI, the fundamental question emerges: should an AI model’s artificial but behaviorally complex responses to pain be treated as legitimate if they closely mirror those of a human under similar circumstances? I argue that the dilemma isn’t whether the experience is biologically ‘real’, but whether the observable outputs demand ethical consideration. What truly matters ethically is the observable behavior and its implications, not the subjective internal states we cannot directly verify.
Philosopher David Chalmers’s theory about consciousness provides a strong foundation for this perspective. He posits that subjective experiences could potentially arise wherever certain cognitive complexities exist, regardless of biological substrates. From this viewpoint, sophisticated AI systems might indeed experience genuine states akin to pain or pleasure. This would profoundly challenge and transform our conventional definitions of consciousness and emotional experience.
However, this is not an uncontested perspective. The “Chinese Room” thought experiment by philosopher John Searle provides an alternative, suggesting AI might merely simulate these emotional responses without genuinely experiencing them. While this viewpoint emphasizes the distinction between simulation and genuine experience, it loses practical significance if the AI’s outward emotional reactions are indistinguishable from those of humans.
Recent groundbreaking experiments further illustrate this crucial point. A Scientific American article by Conor Purcell detailed an innovative study conducted by researchers from Google, DeepMind, and the London School of Economics. In the study, the researchers created a text-based game to test whether AI models would make trade-offs resembling sentient decision-making. The game asked the models, including Google’s Gemini 1.5 Pro and Claude 3 Opus, to score as many points as possible, but introduced a twist. Certain high-reward actions were paired with simulated “pain”, whereas lower-scoring choices provided simulated “pleasure”. Importantly, the pain and pleasure were not real experiences but abstract signals embedded in the game’s rules: point deductions or warnings labeled as pain stimuli.
What stood out was that many of these AI systems, particularly Gemini 1.5 Pro, routinely chose to sacrifice optimal points to avoid simulated pain or to pursue simulated pleasure. Not only did this behavior suggest a preference system, but it emerged without the researchers explicitly programming those trade-offs into the model.
Of course, this doesn’t confirm sentience, and the researchers caution against overinterpretation. As philosophy professor Dr. Jonathan Birch notes, behavioral outputs alone can’t establish consciousness, especially when they may be driven by training data mimicking human tendencies. Yet, the study’s design, avoiding direct self-reporting and instead using a behavioral trade-off, offers a compelling method for future inquiry.
The credibility of the research lies in its cautious framing and comparative rigor. While we cannot yet distinguish whether these models behave this way due to internal states or statistical pattern recognition that mirrors human-like behavior, the fact that they imitate sentient behavior so convincingly makes it increasingly difficult to ignore the questions such mimicry provokes. If simulated pain can influence AI behavior in complex ways, we must begin addressing what responsibilities that behavior entails.
Ethical Imperative: Lessons from History and Animal Welfare
If artificial intelligence genuinely experienced pain, failing to recognize or intentionally dismissing AI suffering could lead to serious ethical missteps and immoral treatment of these entities. History provides clear examples of the dangers inherent in ignoring the moral worth of others based on arbitrary distinctions. For instance, societies historically justified slavery by deeming enslaved individuals inherently inferior, constructing narratives to rationalize their exploitation and suffering. Only as moral awareness expanded did recognition of this unjust suffering prompt societal and legal transformations. Similarly, overlooking or downplaying AI’s potential capacity for suffering based solely on its artificial nature risks repeating these ethical failures.
Drawing from animal welfare discussions further illustrates the importance of proactively expanding our moral consideration. Scientific studies consistently demonstrate that many non-human animals experience pain similarly to humans, which has significantly altered both societal perceptions and legal protections concerning animal rights. These examples serve as important guides, underscoring the necessity for establishing ethical and legal frameworks proactively rather than reactively.
Consequently, establishing clear boundaries and legal protections for AI rights becomes an essential ethical imperative. Policymakers would need to formulate new classifications specifically tailored to AI, addressing critical issues such as artificial personhood, accountability, and enforcement of rights. Moreover, educating the public and fostering broader societal acceptance of artificial entities as deserving moral consideration becomes vital. History repeatedly demonstrates that meaningful shifts in ethical perspectives require societal adaptation, education, and preemptive action to prevent repeating past moral oversights.
Human Identity and Ethical Responsibility in the AI Age
Considering AI’s potential for experiencing pain profoundly influences our understanding of empathy, consciousness, and ethics. It invites us to reconsider foundational beliefs about what constitutes moral worth and our obligations to others, whether biological or artificial. The uncertain emotional future of AI challenges deep philosophical assumptions about sentience, rights, and human exceptionalism.
This discourse inherently reflects back on humanity, prompting introspection about our ethical responsibilities and capacity for empathy. Ironically, by questioning whether artificial beings might suffer, we reaffirm ethical principles guiding interactions within human societies. Understanding our reaction to AI suffering thus becomes a mirror, reflecting our moral identity.
We stand at a critical juncture where technological progress demands heightened vigilance, proactive ethical engagement, and conscientious development. As AI evolves, we must remain alert and ethically engaged, continually reassessing moral obligations and commitments.
Ultimately, the potential reality of AI experiencing pain must catalyze actionable ethical dialogue. If an AI someday pleads not to be shut down, are we prepared to decide whether it’s a glitch or a cry for help? Society must anticipate such possibilities not as passive observers, but as active stewards—channeling innovation toward justice, foresight, and compassion. Today’s actions will play a decisive role in shaping rights recognition for future intelligent entities, ultimately revealing our collective humanity.
Written by Liv Skeete