“Dhamma AI” offers a Buddhist perspective on artificial intelligence, highlighting AI’s immense benefits and potentially profound harms while proposing Citta-vīthi, Papañca, Cetanā, and Paṭṭhāna as conceptual frameworks for responsible AI governance.
Amid the rapid transformation of artificial intelligence (AI), which is increasingly influencing the economy, society, media, and everyday life, the application of Buddhist principles—particularly the Abhidhamma Piṭaka—as a conceptual framework for understanding and governing AI is emerging as an important academic and ethical issue.
A study titled “Analyzing the Abhidhamma in the Tipitaka for AI Governance” identifies August 24, 2026, as an important milestone following a seminar and practical workshop under the project “Dhamma AI: Artificial Intelligence and Digital Media Development for the Dissemination of Buddhism, Fiscal Year 2026.” A major highlight was a special lecture entitled “Buddhism and the Transition to the AI and Digital Society,” delivered by Phra Brahmapundit (Prof. Dr. Prayoon Dhammacitto).
“AI Has Immense Benefits, but It Can Also Cause Profound Harm”
At the heart of this approach is the recognition of AI’s dual-use nature—technology capable of producing both significant benefits and serious harm. The key argument is that AI should not be driven solely by technological capability or economic mechanisms, but must be guided by Sammā-diṭṭhi, or Right View.
From this perspective, the central problem is not simply the technology itself, but the intentions, ways of thinking, and values of the people who design and deploy it. Without appropriate safeguards, AI can become a powerful instrument for generating misinformation, amplifying bias, and creating risks to public safety.
From “Citta-vīthi” to an Understanding of AI Architecture
One of the study’s key proposals is to apply the concept of Citta-vīthi, or the process of consciousness, found in the Abhidhamma as a conceptual lens for understanding AI processing.
In the Abhidhamma, Citta-vīthi is described as an ordered sequence of moments of consciousness through which an object is perceived and processed after coming into contact with one of the six sense doors.
By comparison, the study proposes viewing Bhavaṅga-citta as analogous to the basic contextual state or Context Window of an AI system. Pañcadvārāvajjana-citta and Manodvārāvajjana-citta can conceptually be compared with attention mechanisms, while Javana may be compared with inference or a Forward Pass that drives the generation of an output.
Such comparisons, however, should be understood as conceptual analytical frameworks, rather than as a claim that AI and human consciousness possess identical structures.
“Vedanā”: A Fundamental Difference Between AI and Human Experience
Another major issue raised in the study is Vedanā, or feeling-tone—the experience of pleasant, unpleasant, or neutral feeling.
The study suggests that while AI can process language and recognize patterns, it does not possess human-like experiences of pleasure, pain, or neutrality. This raises a fundamental question about whether AI can genuinely develop Karuṇā, or compassion, in the way human beings experience it.
If AI can process information without experiencing suffering itself, the development of genuine ethical understanding and compassion remains a significant philosophical challenge.
AI Hallucination and the Buddhist Concept of “Papañca”
One of the most serious problems associated with Generative AI today is AI hallucination—the generation of unsupported or fabricated information that may nevertheless be presented in highly convincing language.
The study proposes examining this phenomenon through the Buddhist concept of Papañca, referring to conceptual proliferation or the uncontrolled elaboration of thought beyond what is actually present.
Applied to AI, this framework can be used to examine several dimensions, including the drift of generated answers away from available evidence, the addition of unsupported details, and the inflation of apparent authority through expert-sounding language. These factors can cause users to develop excessive confidence in AI systems, a phenomenon often associated with automation bias.
This perspective suggests that preventing hallucinations should not depend exclusively on technical detection systems. It also requires mindfulness and critical awareness among both AI developers and users, enabling them to recognize unsupported elaboration and prevent it from escalating into broader epistemic harm.
“Cetanā” and the Limits of Artificial Intelligence
Another fundamental question is whether AI can become a moral agent.
The study approaches this issue through the Buddhist concept of Cetanā, or intention. In Buddhist thought, intention is a crucial driving force behind action and moral responsibility. Contemporary AI systems, by contrast, are described as mathematical and computational processes that lack embodied experience and human-like continuity of life.
From this philosophical perspective, contemporary AI is therefore better understood as a highly sophisticated tool rather than as an autonomous moral agent. Ultimate responsibility for important ethical decisions should remain with human beings.
“Paṭṭhāna” and the Chain of Causes and Conditions in Algorithms
At the systemic level, the study applies the principle of Paṭṭhāna, or conditional relations, to analyze the AI ecosystem.
For example, training data can be viewed as a foundational condition in machine learning. If the data contains social, cultural, gender, or economic biases, those biases may become embedded in the system and subsequently emerge as biased outputs.
Similarly, AI recommendation systems on social media can be understood through the concept of Ārammaṇa-paccaya, or object condition, because they continuously select and present content designed to capture users’ attention, preferences, fears, or emotional reactions.
Meanwhile, the autoregressive generation of text—where one token influences the probability of the next—can be conceptually compared with Anantara-paccaya, or immediate-contiguity condition, in which one event conditions the occurrence of the next.
This perspective provides an opportunity for AI developers and policymakers to intervene at the level of causes and conditions, rather than waiting until harmful consequences appear in the final output.
From AI Regulation to an “Ethical Constitution”
The study also examines differences between international AI governance frameworks and Buddhist ethics, referring to frameworks such as the EU AI Act, the UNESCO Recommendation on the Ethics of AI, and ISO/IEC 42001.
These international approaches emphasize risk management, individual rights, transparency, and organizational accountability. Buddhist ethics, by contrast, places greater emphasis on underlying causes and conditions, interconnectedness, human relationships, suffering, and social harmony.
One particularly significant proposal is the possibility of using the Tipitaka as a foundation for Constitutional AI—a set of ethical principles that an AI system could use to evaluate and regulate its own outputs.
The study proposes that principles such as Anattā (non-self), Karuṇā (compassion), and conditionality could contribute to the development of ethical frameworks for AI design and alignment.
Toward AI Guided by Wisdom, Not Merely Capability
Ultimately, the analysis suggests that the central challenge of the AI era is not simply to build machines that are more intelligent, but to create a technological ecosystem in which capability advances together with ethical responsibility.
Applying concepts from the Abhidhamma—including Citta-vīthi, Vedanā, Cetanā, Papañca, and Paṭṭhāna—offers an interdisciplinary framework connecting Buddhism, psychology, philosophy, computer science, and AI governance.
The study concludes that although AI can process information and simulate sophisticated communication, it remains limited in terms of embodied experience, feeling, and intention. Humanity must therefore retain ultimate responsibility for high-level moral decisions.
At the same time, Sammā-diṭṭhi (Right View), mindfulness, compassion, and an understanding of conditionality may provide important principles for guiding the transition into an AI-driven society—one in which technology serves human welfare and helps reduce suffering rather than merely increasing technological power.
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