AI Glossary

A statutorily defined range of compensation for copyright infringement, independent of proven actual damage; in cases of mass infringement it can reach astronomical sums and creates an incentive to settle.

Liability for damage arising regardless of fault, based on the mere occurrence of a harmful outcome; under consideration for the operation of risky AI systems.

A mode in which a model returns a response in a predefined format (e.g., JSON) so that it can be automatically processed by other systems.

Generating content that imitates the distinctive creative style of a particular author or artist; this raises both legal and ethical questions.

The use of AI to imitate the characteristic creative style of a particular author or artist, which gives rise to disputes over personality rights and unfair competition.

A technology that enables transferring the visual or artistic style of one work onto another.

The use of techniques that operate beyond a person's conscious perception with the aim of influencing their behavior.

A substantial modification of an AI system after it has been placed on the market, which may affect compliance with requirements and require a new assessment.

The music AI services Suno and Udio faced lawsuits from the music industry for training on copyrighted recordings. Warner Music subsequently settled the disputes and announced the launch of joint platforms for music creation.

A mechanism under which the Commission periodically reviews and may update the list of prohibited practices in line with the development of technologies and risks.

Machine learning on data provided with correct answers, from which the model learns to predict outputs for new data.

An artificially created digital character appearing in audiovisual content in place of a real actor.

Text, images, audio, or video created by artificial intelligence without directly capturing reality.

Artificially created data that mimics the properties of real data.

The creation of artificial data that mimics the properties of real data, used for training when data is scarce or to protect privacy.

A set of artificially generated data (often by the model itself) used for training or testing instead of real data.

Content created or substantially modified by artificial intelligence.

A hidden instruction defining the rules and behavior of an AI system.

A weakness that can be exploited to compromise the security of a system.

A risk arising from the most capable models that may manifest at scale across the value chain, for example in cybersecurity, disinformation or misuse.

A reservation of rights under the rules on text and data mining, by which a rightsholder prevents the use of its content for automated analysis and training. Want to learn more? Our colleague Hana Krajčíková has prepared, for Section 39c of the Copyright Act, a commentary on this issue on Zákony pro lidi.

A set of documents describing the design, operation, purpose and legal compliance of an AI system.

A set of technical rules used to demonstrate compliance with legal requirements.

A parameter influencing the randomness of the output; a lower value leads to more predictable responses, a higher value to more varied and creative ones.

Data used to verify whether an AI system achieves the required results after the completion of development.

Computing power expended at the response stage (not during training), the increase of which can improve output quality for demanding tasks.

The automated analysis of texts, images or data in order to extract information. Want to know more? Our colleague Hana Krajčíková has written a commentary on this topic on Section 39c of the Czech Copyright Act for Zákony pro lidi.

A provision of the EU Directive on Copyright in the Digital Single Market that, under certain conditions, permits the automated analysis of protected works; it may be used for commercial purposes provided that the rights holder has not reserved such use.

A US case addressing whether a work created entirely by a machine, with no human author, can enjoy copyright protection. The courts upheld the US Copyright Office's position that human authorship is a prerequisite for protection.

We analyzed the case in detail in our article Artificial intelligence is not the author of a work – Thaler v. Perlmutter.

The phenomenon whereby European AI rules effectively become a global standard, because multinational providers apply them outside the EU as well.