WHAT ARE LEGAL RISKS OF USING AI IMAGE GENERATORS LIKE MIDJOURNEY AND DALL-E?

INTRODUCTION

AI is now foundational to contemporary creativity: programs like DALL-E and Midjourney can promptly generate lifelike illustrations, photographs, or artworks from written prompts. Thus, for designers, marketers, and casual creators alike, this technology provides unprecedented productivity.

However, the same technology that enables access to creativity also raises a variety of legal and ethical issues. When an AI system produces an image, it relies on massive amounts of pre-existing data—some of which may be protected by copyright or depict real individuals. Users and organizations must therefore ask: who owns the generated image, and could using it expose them to liability? The following sections examine the principal legal risks of AI image generators and ways to mitigate them.

1. COPYRIGHT AND OWNERSHIP ISSUES

The dispute can be boiled down to the question of who owns works generated by AI. While AI systems use algorithms to independently interpret prompts, not human creativity, copyright law tends to favor human authorship. This means that content created entirely by machines cannot be protected by copyright in the majority of jurisdictions.

The U.S. Copyright Office has clarified that works “produced by a machine or mechanical process that operates without human authorship” are ineligible for registration. Similar interpretations exist in the U.K. and the European Union, where human intellectual input is required. Consequently, when someone uses Midjourney to generate an image, they may have no exclusive ownership rights over it. It's a significant challenge for businesses. A firm that creates a logo or advertisement from scratch through AI may find that competitors can legally, with proper attribution, simply use or modify that image. Creators will want to preserve their rights as authors by adding substantial human modification or involvement in the product. Then, the creation is a derivative work subject to copyright law as a "work of authorship."

2. INFRINGEMENT RISKS IN AI DATA TRAINING

AI models utilize massive datasets scraped from the web, which frequently comprise copyrighted art and photos. Several creators claim that their creations have been incorporated in these datasets without their consent or any form of payment.

Copyright infringement at a massive scale is the allegation in the lawsuits in which Stability AI, OpenAI, and Midjourney are defendants and which have been filed in the US and the UK. The question of legality turns on whether their use of copyrighted material qualifies as “fair use.” Proponents say that training data has a transformative, non-expressive purpose: teaching the AI to recognize patterns, not to reproduce creative content. Critics counter that when an AI model produces instantly recognizable styles or familiar compositions, it is infringement. Risk for users occurs when the AI outputs are strongly similar to protected works.

If the AI generates an image strongly resembling that of a known artist, the user could potentially have secondary liability. For this reason, commercial users should avoid prompts that reference living artists or copyrighted images and should consider validating outputs with a reverse-image search before publishing.

3. TRADEMARK AND BRAND MISUSE

Brand imagery and trademarked symbols pose an additional risk. AI tools can quickly produce images that mimic well-known companies' logos, goods, or packaging. For example, requesting that DALL-E "create a car advertisement in the style of Tesla" could result in the incorporation of Tesla's trademarks. Using or distributing such content could amount to trademark infringement or brand dilution, even if unintentional.

Trademark law protects not only identical copies but also confusingly similar designs that may mislead consumers. Businesses are particularly vigilant in policing unauthorized reproductions of their marks.

To minimize exposure, users should avoid using brand names or distinctive product descriptions while prompting. If AI output inadvertently contains recognizable logos or other symbols, these should be edited out before public or commercial use.

4. PRIVACY AND PERSONALITY RIGHTS

AI can generate realistic human faces, sometimes based on actual individuals without their knowledge or permission. Risks associated with generating or distributing some of these images might fall under privacy statutes or publicity rights statutes. These statutes or laws exist to protect someone from the unauthorized commercial utilization of their likeness. Producing, or delivering, an image of a famous, or non-famous, individual in a misleading context could invite claims for defamation or misappropriation.

In the European Union, the General Data Protection Regulation (GDPR) considers personal likeness as personal data and provides individuals with rights to control the use of their likeness in ways that the individual did not authorize. Some states in the United States, including California, have laws that regulate publicity rights that provide similar protection as the GDPR.

As a best practice, users should not make prompts that would reference an identifiable individual. Additionally, users should never use an AI-generated portrait for advertising, voting (political), or defamation without consent from the party that is the subject of the likeness.

5. EVOLVING LEGAL AND ETHICAL RESPONSES

Governments and organizations have started to develop frameworks that tackle AI risks. The AI Act of the European Union, fully effective by 2026, demands transparency in that users must be informed when the content was machine-generated.

The U.S. Federal Trade Commission has issued similar guidance that warns companies against misleading consumers with AI-generated content. Meanwhile, developers are experimenting with ethical data practices: things like opt-out systems for artists, "clean" training datasets, and digital watermarking that identifies AI-generated images.

These measures aim to balance innovation with accountability. The ethical implications of transparency extend beyond strict legal compliance. Giving credit to artists whose styles are emulated, avoiding deceitful representations, and acknowledging AI’s contribution to content creation contribute to equitability and confidence in dealing with these emerging assets. Ethical awareness, even beyond strict legal compliance, is likely to mold public acceptance of generative AI.

CONCLUSION

Generative AI image generators, such as Midjourney and DALL-E, heralded a new frontier in creative expression. Yet they also blur the boundaries between human authorship and algorithmic production, creating legal uncertainties under copyright, trademark, and even privacy law. Users of these tools need to be aware that not every generated image of AI is without legal constraint.

For safe use, creators should combine human input with the assistance of AI, not use brand or individual references in prompts, and verify the originality of the image before using it commercially. As the laws change, education and caution remain the strongest protections. Balancing creativity with responsibility will ensure that AI continues to empower, and not endanger, the artistic community.