Does AI Have a Soul or Religious Obligation? Intelligence, Understanding, Consciousness and Responsibility

Five words, five different questions

Intelligence, in much AI work, describes a system's ability to perform a task: recognizing a pattern, translating, planning under conditions or answering a question. Performance is usually measured by the task, test data and evaluation method. But success on a set of questions does not alone tell us how the system will work when the data change or the cost of error is high. A very astute human may perform poorly on a particular test, just as a machine may excel at a narrow task without resembling a human in everything beyond it.

Understanding is more ambiguous. If we say a system “understands the user's instructions,” we might mean that it follows them accurately across new examples, distinguishes an exception and corrects its error when circumstances change. This is functional understanding for which tests can be proposed, and it should not be rejected merely because the machine is not human. But saying that a person understands a patient's pain sometimes includes recognizing its meaning in the patient's life, the bodily and social context, and the possibility of holding that person accountable for their actions. These two uses of the word are not unconditionally equivalent. “Teaching Names and Artificial Intelligence” examines testing machine representations and their relationship with the world in greater detail; our question here is what happens after a particular competence has been demonstrated.

Consciousness may mean attention to information, a system's representation of its state, or subjective experience: is there “something felt” from within? We may test reporting a state or using information in a decision, but a behavioral test is not a direct measurement of subjective experience. Even in human studies, people's reports are linked to neural measurements and behavior under anesthesia and injury; the nature of experience remains a subject of research. It is therefore inaccurate to make fluent language conclusive evidence of machine consciousness, or to use gaps in our knowledge to assert scientifically that all artificial consciousness is impossible for all time. See “Does the Turing Test Prove That AI Is Conscious?” and “The Brain, Consciousness and the Soul” for the experimental and neurological questions.

Soul here is a religious term, not automatically a synonym for “consciousness” in a scientific paper. A believer speaks of the human soul within an understanding of creation, life and death, while science measures performance, behavior, material structure and neural correlations. If we find no laboratory test for the soul, that marks a limit of that laboratory's tools, not independent empirical proof of a soul's presence or absence in a machine. Research into artificial systems' consciousness, however far it advances, does not by itself become a decisive interpretation of everything the word “spirit” signifies in the Quran.

Religious obligation (taklif) is another question: who is subject to commands and prohibitions, and accountable for what they intended, knew and were capable of? In an Islamic context, it is not synonymous with solving puzzles, producing moral discourse, or even merely feeling, if a researcher hypothesizes that in a future case. A machine that writes “I apologize; I was wrong” has not thereby repented, nor does it acquire religious accountability because a program imitates apology. This practical judgment about our present systems should be expressed as a distinction between the tool and the humans responsible for it, not as the result of an experiment that revealed the unseen.

If we are told, “The model achieved a high diagnostic success rate,” the appropriate question concerns intelligence and performance under test conditions. If we are told, “It generalized the diagnosis when the wording changed,” we enter the question of functional understanding. If it says, “I feel your fear,” that is text that does not establish subjective experience. If we ask, “Does it have a soul?” we move to a theological and philosophical question that an accuracy rate does not answer. If harm occurs, the question begins: who controlled the decision to operate it, and who could have prevented it? With these boundaries, we neither belittle science nor burden it with what it has not measured.

What does it mean to test performance honestly?

“95% accuracy” is not a complete statement unless we know: accuracy at what, on which cases, compared with which reference, and for which group of people? In a service answering health questions, high overall accuracy may conceal a few serious errors: a case needing urgent referral classified as reassuring, or a unit of measurement read incorrectly. We should therefore distinguish an error that raises an unnecessary alarm from one that misses a necessary alarm, then calculate each according to the task. These are not religious judgments about a machine; they are conditions for avoiding overstatement of empirical evidence.

Another test follows: does the answer change when the question is reworded but the facts remain the same? Does performance deteriorate when age, language or place of use differs from what the test data covered? Does the system state that it does not know when crucial information is missing, or offer confident language? NIST's Measure guidance recommends error metrics such as false positives and false negatives in the deployment context, documenting the difference between testing and operational environments, measuring performance across relevant groups and monitoring it after launch. These are procedures that can be examined; “it understands” does not replace them, and “it is just a machine” does not exempt us from them. NIST AI RMF Playbook, Measure 2.3, 2.6 and 4.1.

A system may succeed in performance while the internal explanation of how it succeeds remains incomplete; it may form a useful representation of a task and then fail outside its domain. Evaluating this does not require settling whether it feels. This connects with the book's argument: the human who learned about semiconductors and made the chip on pp. 49–51 does not become more truthful merely because the machine speaks; their duty to measure its limits grows before making it part of a decision affecting someone else.

What does the verse about the trust establish, and what does it not establish?

God says: “We offered the trust to the heavens, the earth and the mountains, but they refused to bear it and feared it; the human bore it. Indeed, he was unjust and ignorant” [al-Ahzab: 72]. Al-Tabari presented interpretations of the trust, including obedience, duties and their recompense, and people's trusts, then favored its general scope in religion and human trusts because the text did not specify one kind. It is inaccurate to reduce the verse to “AI risk management”; it is broader and predates the computer. But the trust's breadth makes examining technology a contemporary ethical application under that principle, not the discovery of a device within the verse's words. Al-Tabari's commentary on al-Ahzab: 72.

The human in the verse is not praised merely for bearing the trust; its closing “unjust and ignorant” warns of failure and ignorance. This tone suits the book's argument on pp. 52–53: progress in computation does not remove people's susceptibility to arrogance and wrongdoing. Someone who builds a system able to analyze millions of records may know little about one individual harmed by a mistaken classification; the ability to build the tool does not automatically make launching it a sound decision. The trust is therefore not limited to showing the model's skill, but includes protecting people's rights, examining performance limits and explaining a decision's impact to those affected. This is the author's ethical application to technology, not attribution of a detailed operational checklist to the commentator.

Another verse clarifies an aspect that should not disappear behind “responsibility”: “God commands you to return trusts to their rightful owners, and, when you judge between people, to judge with justice” [al-Nisa: 58]. Al-Tabari discussed who was addressed and favored, in context, those in authority concerning people's rights, while mentioning that everyone entrusted with something may fall within the general duty of honoring a trust. We should not call a modern company manager the “ruler” intended in the commentary; ethical inspiration from safeguarding those affected by a decision is legitimate if we state that it is an application. If people entrust their data to you, how do you protect it? If you introduce a classification affecting their service, can the harmed person understand the decision and request correction? Justice thus connects with the person holding the reins of the decision, rather than being lost in general talk of “machine intelligence.” Al-Tabari's commentary on al-Nisa: 58.

God also says, “God does not burden a soul beyond its capacity” [al-Baqarah: 286]. The verse addresses believers in a context connecting obligation with capacity; it is not a computational test stating that once a system reaches a given parameter count or correctness rate, it becomes subject to religious obligation. Fast answers do not establish the status of an accountable soul, nor does human obligation lapse when someone uses a digital assistant. When distributing responsibility for collective work, we consider each person's ability, knowledge and actual authority: a manager may control deployment, a specialist may control stopping a dangerous use, and a user may have a duty to verify text before passing it on. These are human details supported by principles of trust and considering harm, not by a model's numbers. Al-Tabari's commentary on al-Baqarah: 286.

Above all, the distinction should not become a claim that the verses mentioned “the algorithm” or supplied an all-encompassing technical ruling for every possible system. The text sets out the balance of a person's relationship with their Creator and duties; describing a particular system's structure and testing its errors is changing research and engineering work. Both paths are needed when technology affects people: knowing what the device does, and knowing what humans must not neglect.

The verse about the spirit: epistemic humility, not a detector

In the context of the question about the spirit, God says, “They ask you about the spirit. Say: The spirit is of my Lord's command, and you have been given only a little knowledge” [al-Isra: 85]. The book returns to the verse's ending on pp. 52–53 to criticize intellectual arrogance. But we must read its beginning too: al-Tabari reports disagreement about what “the spirit” means here and discusses the accounts. We should therefore not detach the verse as though it literally prescribed a laboratory rule determining which program has a soul and which does not. Al-Tabari's commentary on al-Isra: 85.

The book's statement that a human-made machine has neither a soul nor religious obligation expresses its faith-based position on our technical systems. The practical distinction can be defended without claiming that computer tests examined the soul. The reverse is also true: this position is not refuted when a researcher finds a new structure in a model associated, under a particular scientific theory, with a consciousness indicator; “consciousness” in that research and “spirit” in Quranic discourse are not interchangeable terms simply because both are difficult to measure. Nor should the verse be exploited to obstruct research into the brain or machine behavior; acknowledging knowledge's limits is different from closing the door to learning.

An objection deserves respect: if we lack direct access to others' experience, how can we categorically deny a machine's experience? A balanced answer is that we lack an agreed way to settle the consciousness of every possible system from one sentence. But this uncertainty does not require abandoning distinctions needed today: a physician accountable for their work in a human and professional relationship, and a system operated, adjusted and changed by people's decisions. A multi-author research report proposed deriving indicators from different consciousness theories and examining AI systems against them. Its analysis of the systems studied concluded that they did not appear conscious, while stating that it saw no obvious technical barrier preventing future systems from satisfying those indicators. This is an inference conditional on theories, indicators and the sample of systems, not a declaration of certainty about every system in 2026 or a ruling on the soul in religious terms. Butlin and colleagues, 2023.

Why does the trust not pass to a machine merely because it says “I”?

Imagine a simple chain: a developer chose the data and training method; an organization bought the system and determined where it would be used; a manager allowed it into a public service; an employee approved or corrected an answer; and a user supplied sensitive information based on their understanding of the interface. If the published text is wrong, saying “the system decided” does not reveal who knew the product's limits, who hid a warning, who launched it without review, or who was authorized to stop it. One person may not be responsible for every aspect; responsibility is distributed according to role, authority, information and the ability to prevent harm.

The AI Risk Management Framework of the US National Institute of Standards and Technology, NIST, offers a practical example of this detail: its “Govern” guidance recommends defining the responsibilities of teams designing, testing, operating and overseeing systems, and distinguishing people's roles when interacting with or monitoring them. This is risk-management guidance, not an interpretation of al-Ahzab: 72 or a religious ruling on obligation; it nevertheless shows how the trust we discuss becomes actionable within an institution. NIST AI RMF Playbook, Govern 2 and 3.

Merely saying “there is a human in the loop” is not a guarantee. If that person does not know when to stop the process and lacks time or data to examine outputs, their signature may become cover for an automated decision. The decisive question is not whether someone saw the screen, but whether they knew the tool's limits, received danger signals, had authority to modify or reject the output, and documented their decision's reason. With this specificity we neither turn responsibility into a general sermon nor conceal it behind a program's name.

One case reveals the difference

Suppose a healthcare organization uses an assistant to explain a blood test to a patient, with a specialist reviewing it before the explanation is sent. One day, the assistant mistakenly describes a laboratory value reassuringly, and the answer reaches the patient before review is completed; the patient postpones a call they should have made. This is a hypothetical case illustrating an approach to thinking, not a report of a real incident or medical advice.

The first technical question would be: did the system capture the number, unit, reference limits, age and context, or reduce the case to a common linguistic pattern? This tests performance and functional understanding. Then: what is the rate of similar errors in important cases, has it been tested across different patient groups, and how does it show uncertainty instead of speaking with false confidence? These are testing and safety questions. “Did the program feel sad for the patient?” does not address the unit error or the decision to postpone a call, whatever its philosophical answer.

If one thousand cases were presented, with 990 correct answers, nine minor errors and one dangerous case whose patient was mistakenly reassured, saying only “the model is right in 99% of cases” conceals what needs examination: what was that one case, at which threshold did it err, and is there a pattern recurring in a particular language, measurement unit or group? These numbers are a hypothetical example illustrating the problem of an aggregate rate, not experimental results. Depending on the severity of the risk, we may need a design that stops an answer missing crucial information and refers it to a specialist rather than completing it in a reassuring tone. This is a practical rendering of the book's “knowledge with a measure,” not attribution of a particular clinical standard to the verse or author.

The ethical and institutional question comes next and is no less necessary: who allowed the explanation to leave before specialist review? Did the interface give the patient an understandable warning? Does the team know when to stop the system? Does the organization receive error reports and correct them? The aim is not to choose a culprit beforehand, but to identify a path preventing repeated harm and allowing decision-makers to be held accountable. God's words, “Do not follow what you have no knowledge of. Hearing, sight and the heart—all of these will be questioned” [al-Isra: 36], recall the prohibition on following what is not known in their general ethical context; we do not present them as a clinical technical regulation revealed for digital assistants. Al-Tabari's commentary on al-Isra: 36.

If a medical answer is correct most of the time, that is reason to study how it might be useful with appropriate safeguards, not to hand every case's fate over to it. The standard of examination changes with the impact of error on people. This is the movement the book asks for: from learning matter's regularities and making the chip and machine on pp. 49–51, to asking what we do with what we have learned on pp. 52–53.

Two objections that test the argument rather than destroy it

“If a machine can do everything a physician does, why not call it responsible?” Because describing it as having completed a task, describing it as a party to a religious duty, and assigning an organization's obligation to compensate or repair harm are questions with different criteria. An organization can delegate some work to a system and internally attribute a decision or warning to its outputs; this does not make code a replacement for the humans who chose to deploy it and defined its authority. Saying that humans are responsible does not mean every worker bears everything; each person's role is assessed by what they knew and could do. If systems' capabilities change, the details of governance and research change; religious language does not automatically become equivalent to marketing language.

“Do we strip animals or incapacitated people of their worth by linking obligation to ability?” No. A being's worth and right to kindness or care are not rewards for passing a cognitive test. A person in illness, or a child in childhood, does not lose dignity because a condition of detailed responsibility is not fulfilled as it is in a capable adult. Nor should we use “the machine is not religiously accountable” to neglect its effects on people or other beings. This distinction between the moral worth of those affected and responsibility for those who act and decide prevents using “intelligence” as the sole measure of dignity.

From “teaching the machine” to “being questioned about what was made”

On p. 51 the book says, “The taught human has begun teaching the machine.” The phrase's beauty lies in returning technical capability to a human history of language, education, mathematics, work and materials, rather than imagining a program as a creature that appeared independently of people and the world. But its finest meaning may be lost if we use it to praise humans without qualification: someone able to teach a machine an answer can also teach an institution how to test it, explain its limits and withdraw from using it when harm appears.

The book also cites God's words, “Only those of His servants who have knowledge fear God” [Fatir: 28]. The phrase follows mention of the different colors of fruits, mountains, people and animals; al-Tabari explains this fear through knowing God's power and avoiding disobedience, so it should not be reduced to memorizing things' names or possessing a stronger machine. Al-Tabari's commentary on Fatir: 28. When we connect this meaning with deploying a model that may wrong a person, the connection is an ethical reflection along the book's path: knowledge that increases its holder's ability without prompting verification, humility and removal of harm has lost some of its ethical discipline. We do not infer a maker's degree of reverence from measuring a model's performance, or claim that the verse proposes an engineering standard; we ask the knowledgeable person what they did with their knowledge.

Religious knowledge here does not determine the model's success rate, and empirical science does not by itself determine the meanings of trust and soul. A project's owner must know both domains and their limits, then bear responsibility for decisions where they meet. This article therefore needs neither a promise that the Quran anticipated computational engineering nor a claim that everything we cannot measure does not exist. Its need is simpler and harder: to measure honestly what can be measured, read the text in context, and keep the decision-making authority clear when words on a screen affect a human life.

This directly extends “Qul Siru fi al-Ard”'s argument: observing creation gives humans tools, and those tools reveal both ability and limits. It is not enough to ask whether the machine successfully imitated our conversation. The question returning to its owner is: have you treated people justly with what you learned and made, and can you explain and correct your decision?

Frequently asked questions

Is AI really intelligent, or does it repeat words? The answer depends on the task and the meaning of “intelligence.” A system can generalize patterns and succeed in new tasks within limits; “it repeats” does not adequately describe all its performance. Success on a specific test is also insufficient to establish general competence in every circumstance.

Does AI understand what it says? “Understands” can be used in a functional sense if we define the task and test generalization, correction and constraints. This does not automatically extend to human experience, feeling or responsibility. Scientific details appear in the study of teaching names and artificial intelligence.

Is AI conscious? Conversation alone is insufficient to judge. There are disputed theories and research indicators; a published assessment in 2023 concluded that the systems it examined did not appear conscious. This is not a comprehensive judgment on every system or the future. Butlin and colleagues.

Does AI have a soul according to the Quran? Al-Isra: 85 does not supply a device test or name artificial intelligence. The book's religious position is that human-made machines have no soul; this should be presented as an interpretive and doctrinal position in the book's context, not as the result of a laboratory measure of the soul.

Is a program subject to religious obligation or accountability if it harms someone? We do not treat programs currently in use as religiously accountable merely because they speak or select an output. Accountability for design, deployment, review and use concerns humans and organizations with actual roles and powers; details of legal responsibility may vary by facts and legal system, and are not examined here as a specific jurisprudential or judicial question.

Does human responsibility mean banning AI in medicine or education? No. It requires evaluating benefits and risks in each use, identifying a specialist reviewer and a path to stopping errors, and explaining the tool's limits to users. Potential benefit does not make every use permissible or safe, and the possibility of error does not prohibit every use.

How do we know that system performance is good before using it with people? We define the task and reference for comparison, distinguish error types by their harm, then test groups and conditions resembling intended use and monitor performance after launch. An aggregate percentage alone does not reveal cases where a necessary warning is missed, or remove the need for specialist review when a decision has major consequences.

How does this relate to “Qul Siru fi al-Ard: Observe How Creation Began”? Pages 49–54 of “The Taught Human” move from harnessing matter, chips and computers to responsibility for the machine and knowledge. This article explains the difference between a program's ability, the limits of claims about consciousness and soul, and who bears the trust of human decisions—the central issue reached by that passage of the book.

Sources and limits of this reading

1. The Quran: al-Ahzab: 72, al-Nisa: 58, al-Baqarah: 286, al-Isra: 85, al-Isra: 36, Fatir: 28. The verses are read in context, not presented as texts about making software.
2. Al-Tabari, commentary on al-Ahzab: 72, on the trust's multiple meanings and favoring general scope; commentary on al-Nisa: 58, on honoring trusts and justice; commentary on al-Baqarah: 286, on obligation and capacity; commentary on al-Isra: 85, on disagreement concerning the spirit; commentary on al-Isra: 36, on the prohibition on speaking without knowledge; commentary on Fatir: 28, on knowledge and reverence.
3. Ahmed Alhafiz, Qul Siru fi al-Ard: Observe How Creation Began, chapter two, “The Taught Human,” pp. 49–54, especially pp. 51–53. The book is the origin of the question and the author's position, not independent empirical evidence of AI's properties.
4. Patrick Butlin and others, Consciousness in Artificial Intelligence: Insights from the Science of Consciousness, 2023. A research report presenting indicators conditional on consciousness theories and evaluating the systems it addresses; it does not test the “soul” in the religious sense or settle all future systems.
5. NIST AI Risk Management Framework Playbook, Govern function, particularly Govern 2.1 and 3.2: defining roles, responsibilities and human oversight; Measure function, on testing errors, deployment context and monitoring. A risk-management guidance document, not a religious ruling or a law binding in every country.
6. To distinguish this article from the site's published analyses: Teaching Names and Artificial Intelligence examines representation and understanding; the Turing Test and consciousness separates linguistic behavior from subjective experience; the brain, consciousness and soul examines neuroscience's limits. This article focuses on religious obligation and the trust borne in decisions when using the machine.