Artificial Intelligence, Moral Responsibility, and the Fallacy of “Neutral Tools”:

Artificial Intelligence, Moral Responsibility, and the Fallacy of “Neutral Tools”:

A Systematic Rebuttal of Big Tech’s Defensive Arguments in AI Governance

Author: Le Hai

Affiliation: Independent Researcher

Fields: AI Ethics, Political Economy of Technology, Philosophy of Responsibility

Keywords: Artificial intelligence, moral responsibility, Big Tech, technological ethics, cognitive power, APA 7th

Abstract

As artificial intelligence (AI) becomes deeply embedded within large-scale digital platforms, major technology corporations increasingly deploy a standardized set of arguments to deflect moral and legal responsibility for the social harms generated by AI systems. This paper critically examines and rebuts four dominant claims advanced by Big Tech: (1) AI is a morally neutral tool, (2) harmful outcomes are isolated anomalies rather than systemic failures, (3) AI requires regulatory leniency to foster innovation, and (4) corporations cannot be held fully responsible due to the probabilistic nature of AI outputs. Drawing on moral philosophy, legal reasoning, and the political economy of technology, this paper argues that AI is not an autonomous moral agent but an extension of institutional power. Assigning blame to AI constitutes a conceptual error that produces a dangerous responsibility gap in contemporary societies.

1. Introduction: Responsibility in the Age of Artificial Intelligence

The rapid expansion of artificial intelligence has fundamentally transformed information production, social interaction, and decision-making processes. Alongside its benefits, AI has generated significant societal harms, including cognitive manipulation, psychological damage, and the erosion of human dignity at scale. In response, technology corporations frequently portray AI as an independent or unpredictable entity, thereby distancing themselves from accountability (Floridi et al., 2018).

The central question is therefore not whether AI is at fault, but rather: Who designs, controls, profits from, and must be held accountable for AI systems?

2. Rebutting the Claim That “AI Is a Neutral Tool”

The assertion that AI is morally neutral rests on the assumption that technology itself is value-free. This assumption has long been rejected in science and technology studies. Technologies invariably embody the values, priorities, and power structures of those who design and deploy them (Winner, 1980).

AI systems are trained on curated datasets, optimized according to predefined objectives (such as engagement maximization), and deployed within specific socio-economic contexts. Consequently, AI cannot be morally neutral. When corporations invoke neutrality, they are effectively obscuring their own agency and authority in shaping social behavior and collective cognition.

3. Rebutting the Claim That “Violations Are Isolated Incidents”

Framing AI-related harms as “bugs,” “edge cases,” or “rare misuse” is a rhetorical strategy aimed at minimizing systemic responsibility. However, in theories of organizational failure, recurring harms signal structural deficiencies rather than random anomalies (Perrow, 1984).

A fundamental legal analogy clarifies this point: when a vehicle causes an accident, responsibility lies with the driver, not the machine. Similarly, when corporations control AI systems and benefit from their operation, responsibility cannot be displaced onto the technology itself.

4. Rebutting the Claim That “AI Needs Space to Experiment and Innovate”

Big Tech frequently appeals to innovation imperatives to argue against strict regulation. Yet when AI systems are deployed across millions of users, society itself becomes the experimental subject. In fields such as medicine and pharmaceuticals, experimentation on human subjects without ethical safeguards is categorically prohibited (Beauchamp & Childress, 2019).

Invoking “experimentation” in this context reflects an ethical inversion: human beings are treated as instruments of technological progress rather than its beneficiaries.

5. Rebutting the Claim That “Corporations Cannot Fully Control AI Outputs”

Appeals to the probabilistic nature of AI outputs constitute a legal and ethical fallacy. In product safety and risk governance, uncertainty increases—rather than diminishes—the obligation to impose safeguards or restrict deployment (European Commission, 2024).

If a system cannot meet minimum standards of controllability and risk mitigation, it is not fit for mass deployment. Continuing to operate such systems is not innovation; it is the socialization of risk.

6. AI as a “Legal Shield” and the Responsibility Gap

A recurring pattern in the political economy of technology has emerged:

Profits are privatized,

Social harms are externalized,

Responsibility is displaced onto AI—an entity incapable of legal or moral accountability.

In this configuration, AI functions as a legal shield, allowing corporations to evade ethical scrutiny while retaining economic and cognitive power (Zuboff, 2019).

7. Conclusion

Big Tech’s defensive arguments fail not because they lack sophistication, but because they rely on a foundational error: separating technology from the human and institutional power that governs it. AI is not an independent moral actor; it is an extension of human intention, organizational design, and economic incentive structures.

The core challenge of AI ethics, therefore, is not the regulation of machines, but the reconstruction of legal, moral, and political accountability for those who design, deploy, and profit from technological systems.

References (APA 7th)

Beauchamp, T. L., & Childress, J. F. (2019). Principles of biomedical ethics (8th ed.). Oxford University Press.

European Commission. (2024). Digital Services Act: Risk management and systemic accountability. EU Publications.

Floridi, L., Cowls, J., Beltrametti, M., et al. (2018). AI4People—An ethical framework for a good AI society. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5

Perrow, C. (1984). Normal accidents: Living with high-risk technologies. Princeton University Press.

Winner, L. (1980). Do artifacts have politics? Daedalus, 109(1), 121–136.

Zuboff, S. (2019). The age of surveillance capitalism. PublicAffairs.