Introduction: Old Code, New Technology
Artificial intelligence (AI) is reshaping how we work, communicate, and make decisions. Autonomous vehicles, algorithmic decision systems, generative models, and robotics are now involved in contexts where serious harm can occur. This has led many commentators to ask a provocative question:
Do we need an entirely new criminal code designed specifically for AI?
Some argue that existing criminal law is rooted in human agency and cannot cope with algorithmic actors, distributed responsibility, and black-box systems. Others insist that the core concepts of harm, intent, negligence, and causation are still valid, and that only targeted adaptations are needed.
This article examines the arguments for and against a new AI-specific criminal code, and suggests a more nuanced path: modernization and targeted reform, rather than wholesale replacement.
1. What Criminal Law Is For — And Why AI Challenges It
Criminal law serves several core functions:
- Protecting legal interests (life, bodily integrity, property, privacy, public order),
- Expressing societal condemnation of particularly serious wrongdoing,
- Deterring harmful behavior,
- Reinforcing basic norms of coexistence.
AI challenges the application of these functions because:
- Harm is often indirect and mediated through complex systems,
- Responsibility is distributed across developers, companies, and users,
- Behavior may be unpredictable or opaque even to experts.
The question is not whether criminal law’s goals have changed — they have not — but whether its doctrines and structures are flexible enough to deal with AI without a brand new code.
2. The Case for a New AI Criminal Code
Supporters of a new, AI-specific criminal code advance several arguments:
2.1. Anthropocentric Concepts Don’t Fit
Classic criminal law is built around:
- Human intent (mens rea),
- Human conduct (actus reus),
- Human capacity and culpability.
AI systems do not “intend” in the human sense; they are not conscious and lack moral understanding. As a result, concepts like intent, recklessness, and negligence may seem ill-suited when AI is centrally involved in harm.
2.2. New Types of Harm and Risk
AI enables novel harms that existing codes do not explicitly foresee, such as:
- Deepfake-based reputational destruction,
- Mass automated manipulation of voters or consumers,
- AI-enabled surveillance at unprecedented scale,
- Algorithmic discrimination driven by opaque models.
Proponents argue these harms may require new offense definitions and new protected interests (e.g., “algorithmic integrity”, “data dignity”).
2.3. Legal Certainty and Symbolic Value
A dedicated AI criminal code could:
- Provide clear guidance to developers and companies,
- Signal that AI-related risks are taken seriously,
- Avoid stretching old provisions to cover situations they were never meant to address.
For these reasons, some call for a special AI code with new offenses, liability rules, and sanctions.
3. The Case Against a Separate AI Criminal Code
Critics of an AI-specific criminal code warn of serious downsides.
3.1. Fragmentation and Redundancy
Many AI-related harms are simply new ways of committing old crimes:
- Fraud remains fraud, whether done via email or AI-generated messages,
- Harassment remains harassment, whether automated or manual,
- Data breaches remain data breaches, regardless of the tools used.
Creating a separate AI code risks:
- Duplicating existing offenses in slightly modified form,
- Creating gaps or conflicts between the general code and the AI code,
- Making criminal law more complex and less coherent.
3.2. Technological Obsolescence
AI evolves quickly. A detailed AI criminal code risks becoming:
- Outdated as new techniques and architectures emerge,
- Overly focused on specific technologies (e.g., “deepfakes”, “neural networks”),
- Difficult to adapt without constant legislative overhaul.
General criminal codes, by contrast, are designed to be technology-neutral, focusing on conduct and harm rather than tools.
3.3. Overcriminalization and Chilling Effects
A separate AI code could encourage legislators to:
- Create broad, vague offenses out of fear of the unknown,
- Criminalize experimental or benign uses of AI,
- Discourage innovation and research.
Critics argue that criminal law should be a last resort, not the primary instrument of AI governance.
4. What Existing Criminal Law Already Covers
Before drafting new codes, it is crucial to assess what current criminal law can already handle:
- Homicide and bodily harm – when autonomous vehicles or robots cause deadly accidents due to negligent design or operation;
- Cybercrime – AI used to hack systems, steal data, or install malware;
- Fraud and forgery – AI-generated deepfakes or synthetic content to deceive for gain;
- Harassment, threats, hate speech – AI automating or amplifying prohibited communications;
- Privacy and secrecy violations – unlawful surveillance or data misuse enabled by AI;
- Corporate criminal liability – companies deploying unsafe or exploitative AI systems.
In many cases, the underlying conduct already fits existing offences. The law may need interpretive guidance and perhaps modest amendments, but not an entirely new code.
5. Where Gaps Really Exist
That said, there are areas where existing law may be insufficient or unclear:
- Attribution problems – complex AI systems make it difficult to identify the responsible human or entity;
- Systemic, statistical harms – algorithmic discrimination or biased decision patterns that harm groups rather than individuals;
- Purely informational manipulation – large-scale micro-targeted influence campaigns that do not fit neatly into traditional fraud or coercion;
- Duties specific to high-risk AI – such as mandatory risk assessments, testing, and oversight.
These gaps point not to the need for a separate code, but for:
- New duty-based offences (e.g., failure to implement required safeguards in high-risk AI),
- Clarifications on causation and culpability in AI-driven contexts,
- Better integration of regulatory frameworks with criminal sanctions.
6. Regulatory vs Criminal Responses: Getting the Order Right
Many AI-related risks are better addressed initially through regulatory law:
- Licensing and registration of high-risk AI systems,
- Impact assessments and transparency obligations,
- Standards for robustness, safety, and human oversight,
- Audits and administrative sanctions (fines, suspensions, corrective orders).
Criminal law should then step in when:
- Regulatory duties are seriously or repeatedly violated,
- Violations lead to significant harm,
- There is clear recklessness or intent.
Instead of creating a new AI criminal code, a more coherent approach is:
Regulation first, criminal liability as the sharp end of enforcement.
7. A Middle Path: Targeted AI-Relevant Reforms
Rather than drafting a separate AI criminal code, many systems may benefit from targeted reforms within the existing framework, such as:
- Explicit aggravating factors for AI-enabled crimes (e.g., scale, sophistication, impact);
- New offences for serious violations of AI-specific safety and transparency obligations;
- Clarification that corporations can be criminally liable for autonomous system misconduct;
- Updated definitions of documents, signatures, and identity to include AI-generated content;
- Provisions on evidentiary rules for AI-generated evidence and logs.
This approach preserves the unity and technology-neutrality of the criminal code, while acknowledging the specific challenges posed by AI.
8. Guiding Principles for AI and Criminal Law Reform
Any reform, whether minor or major, should adhere to certain principles:
- Technology-neutral language
- Focus on conduct, harm, and duties, not specific tools.
- Subsidiarity of criminal law
- Use criminal sanctions only when regulatory tools and civil liability are insufficient.
- Protection of fundamental rights
- Ensure that new offences do not unduly restrict freedom of expression, research, or innovation.
- Clarity and foreseeability
- Actors must be able to predict, with reasonable effort, which AI-related behaviors are criminal.
- Proportionality
- Sanctions should match the seriousness of harm and culpability, not the level of public anxiety about AI.
9. Conclusion: No Parallel AI Penal Code — But Serious Modernization Is Needed
So, do we need a completely new criminal code for AI? The answer is most likely no — but doing nothing is not an option either.
Key conclusions:
- AI does not invalidate the basic foundations of criminal law; harm, culpability, and responsibility remain central.
- Many AI-related behaviors can be addressed by existing offences, especially when combined with corporate and individual liability.
- Real gaps lie in areas like attribution, systemic harms, and enforcement of AI-specific duties — best handled by targeted reforms and regulatory–criminal interaction, not by a siloed AI code.
- A separate AI criminal code risks fragmentation, obsolescence, and overcriminalization, without clear benefits.
Rather than writing a new penal code from scratch, legal systems should adapt and modernize their existing codes to the realities of AI — carefully, incrementally, and with a clear commitment to preserving human accountability in a technologically complex world.
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