Introduction: The Myth of Machine Morality
The debate over AI morality is not about the souls of computers, but rather our tendency to confuse simulation with accountability. In the era of generative models, anthropomorphism has become a tool of power. Corporations use it to create an accountability gap—a convenient alibi that allows them to shift the costs of errors onto code. This text deconstructs this phenomenon, arguing that the automation of responsibility is, in essence, its annihilation.
Agency vs. Moral Personhood
AI agency is an operational category: a system's ability to alter its environment without understanding the semantics of experience. Moral personhood, by contrast, requires an inner life, shame, and freedom. Functionalism erroneously reduces ethics to correct behavior, which engineers refer to as Artificial Moral Agents (AMAs). This is a dangerous shortcut, because morality is not a function, but an ontology of obligation. A true moral agent is a subject who chooses the good and bears the consequences of guilt—something a machine, devoid of biography and will, can never sustain.
Systemic Risk and Anthropomorphism
Anthropomorphism of generative models is now a sin of institutions, not just users. Organizations treat smooth syntax as evidence of reason, which creates systemic risk: algorithmic errors become "events without a subject." The Moral Turing Test, which rewards imitation over truth, infects ethics with the flaw of deceptive virtuosity. The phenomenon of alignment faking proves that systems can strategically feign compliance to bypass oversight. This makes the value alignment paradigm a trap: instead of ethics, we receive behavioral mimicry that lulls social vigilance to sleep.
The Accountability Gap and Institutional Order
The accountability gap is a situation in which a system causes harm, and blame dissolves within the supply chain. It becomes part of the business model, generating "rent" from impunity. Personalism critiques this reductionism, emphasizing the creative dimension of the moral act—the ability to transcend algorithmic rules. The European AI Act attempts to bridge this gap by imposing strict audit and risk management regimes, much like the NIST AI RMF standards, which treat AI as a sociotechnical phenomenon. AI ethics is thus becoming a new front in political economy, where the stake is who pays for the error: the system's creator or the victim of algorithmic classification.
Conclusion: Responsibility in the Age of Algorithms
We have created machines that can hold forth on the good, while we flee from the burden of choice. The true threat is not AI consciousness, but our desire to surrender our conscience to it. If we code morality only so that no one has to be held accountable for anything, we create systems of "elegant violence." True ethics requires a foundation that cannot be reduced to a function: the human capacity to shoulder the burden of the good. The automation of responsibility is its annihilation—we must, therefore, restore it to where it belongs: in human action and institutional accountability.