Skip to main content

Protection of Copyrights in the Era of Generative Artificial Intelligence

  • Conference paper
  • First Online:
Progress in Artificial Intelligence (EPIA 2024)

Abstract

The historical evolution of terms such as artificial intelligence and related concepts has perpetuated a misconception conflating machine intelligence with human cognition. Recent strides in generative AI technology have exacerbated this phenomenon by enabling AI systems to simulate human behaviors. The progress in generative AI has facilitated the production of convincingly human-like texts, images, music, videos, and other forms of media, thereby intensifying significant legal concerns regarding the safeguarding of intellectual property. Judicial precedents and legislative measures have begun grappling with issues surrounding AI-generated content, sparking debates on matters concerning copyright protections and liabilities for potential infringements. Key focal points of analysis include the copyright status of works generated by AI tools and the implications of their potential infringement on existing copyrights. Furthermore, these discussions underscore the need for further research to address emerging questions in this evolving field.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    Some bestselling books, such as Nick Bostrom’s “Superintelligence” [1] and Ray Kurzweil’s “The Age of Spiritual Machines” [2], reinforce the public perception that computers will inevitably dominate the world. We discern these viewpoints as hasty and alarmist, contributing little to the broader understanding of the matter.

  2. 2.

    To illustrate the algorithm’s functionality without delving deeply into mathematics, consider the autocorrect feature on a cell phone. When composing a message, this feature typically suggests three words based on the likelihood predicted by a simple model: each word typed influences the probability of the next suggested word. Selecting a suggested word increases its likelihood of being recommended in similar contexts. Thus, the autocorrect operates not by thinking, but by employing probabilistic and statistical principles as an algorithm to suggest and interpret contextual words [9].

  3. 3.

    In the author’s words: “Once in use, successful AI systems were simply considered valuable automatic helpers [...] If you could see how it was done, people seemed to think, then it couldn’t be intelligence - a fancy that many people entertain to this day.” (op. cit., p. 423).

  4. 4.

    Flach [13] organizes ML algorithms into six groups: binary classification, concept learning, tree models, rule models, linear models, and distance-based models. Murphy [14] presents a typology related to the underlying statistical procedures, including generative models, Gaussian processes, Bayesian methods, frequentist approaches, linear regression, logistic regression, Bayesian networks, latent variable models, sparse linear models, kernel methods, Markov models, state space models, variational inference, Monte Carlo methods, clustering, graphical models, and deep learning. Zaki and Meira [15] discuss Data Mining and ML together, categorizing models into four major groups: frequent pattern mining, clustering, classification, and regression. Neural networks and deep learning are included in the classification and regression groups in their book.

  5. 5.

    Copyright is “the right to copy, spec., a property right in an original work of authorship (including literary, musical, dramatic, choreographic, pictorial, graphic, sculptural, and architectural works; motion pictures and other audiovisual works; and sound recordings) fixed in any tangible medium of expression, giving the holder the exclusive right to reproduce, adapt, distribute, perform, and display the work. [17]”.

  6. 6.

    To demonstrate the idea to the reader, we have created a simple GUI using GPT 3.5 with the following simple prompt: “Generate html javascript code for a web page of a product catalog register form. Use Boostrap and Jquery. Make it beautiful and futuristic.” The resulting interface sample was neither beautiful nor futuristic unfortunately. Nevertheless, it could save a programmer hours of tedious boilerplate coding work, and some tweaking of the prompt could easily improve its aesthetics. The source code generated can be accessed at https://github.com/rvnovaes/epia2024/blob/main/index.html and the GUI itself on https://rvnovaes.github.io/epia2024.

  7. 7.

    The CJEU ruled in paragraphs 92–93 that, “By making those various choices, the author of a portrait photograph can stamp the work created with his ‘personal touch’. Consequently, as regards a portrait photograph, the freedom available to the author to exercise his creative abilities will not necessarily be minor or even non-existent” [25].

  8. 8.

    In this case it was decided (par. 45 et seq.) that the storing and subsequent printing of an extract from a newspaper article that contains the search word and the five words preceding and following it must be considered a reproduction within the meaning of Art. 2 of Infosoc Directive.

References

  1. Bostrom, N.: Superintelligence: Paths, Dangers. Strategies. Oxford University Press, Oxford (2014)

    Google Scholar 

  2. Kurzweil, R.: The Age of Spiritual Machines: When Computers Exceed Human Intelligence. Penguin, New York (1999)

    Google Scholar 

  3. Dartmouth University. https://home.dartmouth.edu/about/artificial-intelligence-ai-coined-dartmouth, Accessed 20 May 2024

  4. McCorduck, P.: Machines who Think: A Personal Inquiry into the History and Prospects of Artificial Intelligence, 2nd edn. A K Peters, Natick (2004)

    Book  Google Scholar 

  5. Hopcroft, J.E., Motwani, R., Ullman, J.D.: Introduction to Automata Theory, Languages and Computation, 3rd edn. Pearson Addison Wesley, Boston (2007)

    Google Scholar 

  6. Rich, E.: Automata, Computability and Complexity: Theory and applications. Peason Prentice Hall, Upper Saddle River (2008)

    Google Scholar 

  7. Wiener, N.: Cybernetics or Control and Communication in the Animal and the Machine, 2nd edn. The MIT Press, Cambridge (1965)

    Google Scholar 

  8. Britannica, T. Editors of Encyclopaedia. Cybernetics. https://www.britannica.com/science/cybernetics, Accessed 20 May 2024

  9. Manjoo, F.: Yes, Ill Matty You: how your cell phone’s autocorrect software works, and why it’s getting better. https://slate.com/technology/2010/07/how-your-cell-phone-s-autocorrect-software-works-and-why-it-s-getting-better.html, Accessed 17 May 2024

  10. Mohri, M., Rostamizadeh, A., Talwalkar, A.: Fountations of Machine Learning. The MIT Press, London (2012)

    Google Scholar 

  11. Holdsworth, J., Scapicchio, M.: What is Deep Learning?. https://www.ibm.com/topics/deep-learning, Accessed 03 Jul 2024

  12. McCulloch, W., Pitts, W.: A logical calculus of the ideas imminent in nervous activity. Bull. Math. Biophys. 5, 115–133 (1943). https://doi.org/10.1007/BF02478259

    Article  MathSciNet  Google Scholar 

  13. Flach, P.: Machine Learning: the Art and Science of Algorithms that Make Sense of Data. Cambridge University Press, Cambridge (2012)

    Book  Google Scholar 

  14. Murphy, K.: Machine Learning: A probabilistic perspective. The MIT Press, Cambridge (2012)

    Google Scholar 

  15. Zaki, M.J., Meira, W., Jr.: Data Mining and Machine Learning: Fundamental concepts and Algorithms, 2nd edn. Cambridge University Press, Cambridge (2020)

    Book  Google Scholar 

  16. Goodfellow, I., Bengio, Y., Courville, A.: Deep Learning. The MIT Press, Cambridge (2016)

    Google Scholar 

  17. Garner, B. (ed.): Black’s Law Dictionary, 8th edn. Thompson Reuters, St. Paul (2004)

    Google Scholar 

  18. Joyce, C.P., Patterson, L.R.: Copyright in 1791: An Essay Concerning the Founders’ View of the Copyright Power Granted to Congress in Article I, Section 8, Clause 8 of the U.S. Constitution. Emory Law J. 52, 909-952 (2003). https://ssrn.com/abstract=559145, Accessed 06 Jul 2024

  19. Madison, J. Federalist No. 43: The same subject continued: the powers conferred by the Constitution further considered. https://guides.loc.gov/federalist-papers/full-text, Accessed 03 Jun 2024

  20. United States Copyright Office (2022), Copyright Law of United States and Related Laws Contained in Title 17 of the United States Code. https://www.copyright.gov/title17/title17.pdf, Accessed 06 Jul 2024

  21. Thaler v Perlmutter, Civil Action No. 22-1564, United States District Court, District of Columbia (2023). https://caselaw.findlaw.com/court/us-dis-crt-dis-col/114916944.html, Accessed 08 Jul 2024

  22. Pelham GmbH and Others v Ralf Hütter and Florian Schneider-Esleben, Case C-476/17, CJEU, Judgment of the Court Grand Chamber (2019). https://eur-lex.europa.eu/legal-content/en/TXT/?uri=CELEX:62017CJ0476, Accessed 08 Jul 2024

  23. Bezpečnostní softwarová asociace - Svaz softwarové ochrany v Ministerstvo kultury, Case C-393/09, CJEU, Judgment of the Court Third Chamber (2010). https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A62009CJ0393, Accessed 08 Jul 2024

  24. Infopaq v Danske Dagblades Forening, Case C-5/08, CJEU, Request from the Højesteret Denmark (2009), https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A62008CA0005, Accessed 11 Jul 2024

  25. Eva-Maria Painer v Standard VerlagsGmbH and Others, Case C-145/10, CJEU, C-145/10 Judgment of the Court Third Chamber (2011). https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A62010CJ0145, Accessed 08 Jul 2024

  26. EU AI Act: shaping Copyright compliance in the age of AI Innovation (2024). https://keanet.eu/eu-ai-act-shaping-copyright-compliance-in-the-age-of-ai-innovation/, Accessed 11 Jul 2024

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Roberto Vasconcelos Novaes or Francesca Flávio Ferraz .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2025 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Novaes, R.V., Ferraz, F.F. (2025). Protection of Copyrights in the Era of Generative Artificial Intelligence. In: Santos, M.F., Machado, J., Novais, P., Cortez, P., Moreira, P.M. (eds) Progress in Artificial Intelligence. EPIA 2024. Lecture Notes in Computer Science(), vol 14967. Springer, Cham. https://doi.org/10.1007/978-3-031-73497-7_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-73497-7_27

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-73496-0

  • Online ISBN: 978-3-031-73497-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics