Introduction: When Code Meets Criminal Intent
Modern artificial intelligence (AI) and software systems are the result of a division of labor: programmers design and implement the tools, while users decide how and for what purposes those tools are used. When AI systems are involved in crime — fraud, cyber-attacks, discrimination, harassment, or physical harm through autonomous devices — a key question arises: who bears criminal responsibility, the programmer or the user, and in what proportion?
Sometimes the answer seems obvious: a user weaponizes a generally lawful tool, so the user is to blame. In other cases, however, programmers may have deliberately enabled misuse, ignored clear risks, or marketed systems for borderline or illegal purposes. This article analyzes the criminal responsibility of programmers vs. users, focusing on intent, knowledge, foreseeability, and the structure of participation in AI-related offenses.
1. Classical Model: The Tool vs. the User
Traditionally, criminal law distinguishes between:
- The tool – a neutral instrument (knife, car, computer) that has no responsibility;
- The user – the human actor who decides to employ the tool for lawful or unlawful purposes.
Under this model:
- A knife manufacturer is not usually criminally liable for a stabbing,
- A car maker is not normally liable for reckless driving,
- A general-purpose software developer is not liable every time their code is misused.
The key idea is that the user’s intent transforms a neutral tool into a means of crime. The default position in criminal law is therefore:
Users are primary offenders; programmers are not automatically responsible for user crimes.
AI complicates this picture but does not entirely overturn it.
2. Programmers as Potential Offenders: When Code Becomes Complicity
Programmers can, however, become criminally responsible when their role goes beyond providing a neutral tool. Several pathways exist:
- Direct perpetration – writing malicious code specifically designed to commit crime (e.g., ransomware, spyware, automated phishing systems);
- Aiding and abetting – providing tools or tailored modifications with knowledge that they will be used for criminal purposes;
- Conspiracy or joint enterprise – collaborating with users as part of a shared criminal plan.
Key factors for programmer liability include:
- Intent – did the programmer want or accept the commission of crimes?
- Knowledge – did they know, or were they willfully blind, to the criminal use?
- Control – did they have the practical ability to enable or disable the harmful functionality?
When the answers point toward deliberate or knowing participation, programmers can be treated not as neutral toolmakers, but as co-offenders.
3. Users as Primary Actors: Exploiting General-Purpose AI Systems
In many scenarios, users remain the primary criminal actors, especially when they:
- Use a general-purpose AI tool (e.g., text, image, or code generator) to plan or execute crime,
- Bypass safety measures and terms of service,
- Combine multiple tools to orchestrate fraudulent, violent, or oppressive actions.
Examples:
- Generating phishing emails or deepfakes using a general AI model,
- Using AI to automate harassment or targeted hate campaigns,
- Employing AI-based translation or anonymization tools to evade detection.
In such cases, unless the programmer specifically intended or encouraged these uses, criminal law typically treats:
- The user as the principal offender,
- The tool as a neutral instrument,
- The developer as non-culpable, assuming no special circumstances.
4. Dual-Use AI Systems: Where Things Get Complicated
AI tools are often dual-use: they have legitimate applications but can be misused for crime. Examples:
- Large language models used for education, but also for social engineering;
- Image generation models used for art, but also for non-consensual explicit images or propaganda;
- Code generation tools used to build software, but also to create malware.
In dual-use contexts, the criminal responsibility of programmers depends on how they manage foreseeable risks.
Key questions include:
- Did the programmers implement reasonable safeguards (filters, abuse monitoring, rate limits)?
- Did they actively promote the system for questionable or illegal use cases?
- Were they aware of systematic misuse and fail to take meaningful corrective action?
If programmers knowingly tolerate or encourage criminal misuse, they may cross the line into aiding and abetting or reckless facilitation.
5. Intent, Knowledge, and Willful Blindness
The distinction between programmers and users hinges heavily on mental states.
5.1. Clear Intent
Programmers may be primarily responsible when:
- They design software for criminal purposes (e.g., tailored tools for hacking, fraud, illegal surveillance),
- They customize or modify systems at a user’s request knowing the aim is criminal,
- They participate in profit-sharing or operational decisions in a clearly criminal enterprise.
Here, programmers are comparable to manufacturers of illicit tools; they can be convicted as principal offenders or conspirators.
5.2. Knowledge and Willful Blindness
Even without direct intent, responsibility may arise when programmers:
- Know that a particular client is using their tools systematically for crime,
- Ignore obvious signals of large-scale abuse,
- Deliberately avoid learning details (“don’t ask, don’t tell”) to maintain plausible deniability.
Criminal law often treats willful blindness as equivalent to knowledge, especially where serious harm is at stake. Programmers cannot safely hide behind technical distance if evidence of misuse is overwhelming.
6. Negligence and Recklessness: When Programmers Fail to Implement Safeguards
Beyond intention and knowledge, programmers may incur liability under negligence-based or recklessness-based offenses, especially in high-risk domains:
- Autonomous vehicles and robotics,
- Medical diagnosis and treatment,
- Critical infrastructure control systems,
- Predictive policing and security.
Here, the issue is not that programmers want crime or harm, but that they:
- Fail to meet reasonable safety standards,
- Ignore widely known risks of misuse or malfunction,
- Deploy dangerous systems without adequate testing or monitoring.
When such failures lead to death or serious harm, developers may face criminal negligence charges, while users might still be liable for their own actions (such as over-reliance or misuse).
7. Users’ Responsibility: From Misuse to Abuse
While much attention is paid to programmer liability, users often bear direct and obvious responsibility:
- They decide whether to commit the crime,
- They select the target,
- They initiate and control the overall criminal plan.
User liability includes:
- Direct perpetration – using AI tools as instruments of fraud, harassment, theft, or violence;
- Misuse of authorized access – using legitimate access credentials to commit crime with AI;
- Circumvention of safeguards – hacking, jailbreaking, or otherwise disabling protections implemented by developers.
Users cannot usually defend themselves by claiming, “the AI told me to do it” or “I trusted the system”. Unless there is serious manipulation or incapacity, they remain autonomous moral agents responsible for their choices.
8. Allocating Responsibility in Practice: Shared and Layered Liability
In many real-world cases, responsibility will be shared rather than exclusive.
Possible configurations:
- User-only liability
- The AI tool is general-purpose,
- The developer implemented reasonable safeguards,
- The user intentionally misused the system.
- Programmer + user liability (co-offending)
- The programmer designs or adapts tools specifically for the user’s criminal scheme,
- Both share intent or at least knowledge of the unlawful purpose.
- Corporate liability with individual responsibility
- The AI system is developed and deployed by a company,
- Organizational policies and culture incentivize risky behavior,
- Both the corporation and specific managers may be liable, while individual programmers might not be.
- Negligent programmer vs. culpable user
- Developers fail to implement adequate safety features in a high-risk application,
- Users then commit crimes using the system,
- Developers may face negligence-based charges; users remain liable for intentional offenses.
Criminal law must therefore be sensitive to different roles, mental states, and power structures in AI ecosystems.
9. Principles for Distinguishing Programmer and User Responsibility
To navigate future AI cases, several guiding principles can be proposed:
- Maintain the primacy of user intent
- Users who choose to commit crimes with AI should remain primary offenders.
- Treat programmers as neutral by default
- Programmers are not strictly liable for all misuse of their tools; liability requires intent, knowledge, or serious negligence.
- Impose heightened duties in high-risk contexts
- The more dangerous and autonomous the system, the greater the developer’s duty to anticipate and mitigate harm.
- Scrutinize conscious facilitation and willful blindness
- Developers who profit from known misuse or close their eyes to obvious criminal uses may be treated as accomplices.
- Use corporate criminal liability for systemic failures
- Where harm stems from organizational decisions, corporate liability can more accurately reflect collective responsibility.
10. Conclusion: Code Is Written by People — and So Is Guilt
The debate over the criminal responsibility of programmers vs. users is ultimately a debate about how to preserve human accountability in an age of powerful tools.
Key takeaways:
- AI systems and software are not moral agents; responsibility attaches to humans who design and use them.
- Users are generally the primary offenders when they choose to employ tools for crime.
- Programmers may become co-offenders or negligent actors when they intentionally enable crime, knowingly tolerate misuse, or recklessly ignore clear risks.
- Criminal law must balance innovation with protection, avoiding both over-criminalization of honest developers and under-regulation of reckless or complicit actors.
In short, code may run by itself, but guilt never does. It follows the intentions, knowledge, and choices of the humans — programmers and users alike — who bring AI systems into the moral and legal world.
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