DRUŠTVENI RIZICI PRIMENE VEŠTAČKE INTELIGENCIJE I NJENO REGULISANJE U PRAVU EVROPSKE UNIJE

Veštačka inteligencija se primenjuje u gotovo svim oblastima života. Pravna regulativa ne može da prati njen brz i razgranat razvoj. Dosadašnje iskustvo u vezi sa primenom postojeće slabe inteligencije dovodi do uočljivih i ozbiljnih društvenih rizika. Iz tog razloga u Evropskoj uniji donet je Zakon o veštačkoj inteligenciji kojim je regulisan načelni odnos društva prema ovom fenomenu. Zakon je zasnovan na ozbiljnosti rizika u primeni, pa određene oblike smatra zabranjenim, a dozvoljava veštačku inteligenciju visokog rizika, postavljajući visoke uslove za njeno prihvatanje. Pri tome, predmet ovog zakona nije definisanje prava, obaveza ili pravne zaštite koja bi se odnosila na samu veštačku inteligenciju kao subjekta prava

KEYWORDS / KLJUČNE REČI: 

slaba veštačka inteligencija, jaka veštačka inteligencija, zabranjena veštačka inteligencija, sistemi visokog rizika, transparentnost

ACKNOWLEDGEMENT / PROJEKAT:

REFERENES / LITERATURA:

• Akula, A.R., Wang, K., Liu, C., Saba-Sadiya, S., Lu. H., Todorovic, S., Chai, J., Zhu, S.C., CX-ToM: counterfactual explanations with theory-of-mind for enhancing human trust in image recognition models, i-Science 25(1) 2022.
• Alpaydin, E., Introduction to Machine Learning (4th Edition), MIT Press, 2020, dostupno na: https://mitpress.mit.edu/books/introduction-machine-learning-fourth-edition
• Acemoglu, D., Restrepo, P., Artificial Intelligence, Automation, and Work, NBER Working Paper No. 24196, 2018, dostupno na: https://www.nber.org/papers/w24196
• Armstrong, S., Sandberg, A., Bostrom, N., Thinking inside the box: Controlling and using an oracle AI, Minds and Machines, 22(4) 2012.
• Ji, Z. et. al., Survey of Hallucination in Natural Language Generation, ACM Computing Surveys (CSUR), 55(12) 2022.
• Kariluoto, A., Kultanen, J., Soininen, J., Pärnänen, A., Abrahamsson, P., Quality of Data in Machine Learning, 2021, dostupno na: DOI: 10.1109/QRS-C55045.2021.00040
• Kar, K., Kornblith, S., Fedorenko, E., Interpretability  of artificial neural  network  models  in artificial intelligence  vs. Neuroscience, dostupno na: DOI: 10.48550/arXiv.2206.03951
• Li, L., Allamanis, M., Brockschmidt, M., Gaunt, A., Competition-Level Programming Challenge with AlphaCode, Nature, 607/2022.
• Mavrogiorgos, K., Kiourtis, A., Mavrogiorgou, A., Menychtas, A., Kyriazis, D., Bias in Machine Learning: A Literature Review, Department of Digital Systems, dostupno na: https://doi.org/10.3390/app14198860
• Nguyen, T. T. et. al., Deep Learning for Deepfakes Creation and Detection: A Survey, dostupno na: https://doi.org/10.48550/arXiv.1909.11573
• Momand, Z., Chan, H. J., Mongkolnam, P., Immersive Technologies in Virtual Companions:A Systematic Literature Review, dostupno na: https://www.researchgate.net/publication/373686231_Immersive_Technologies_in_Virtual_Companions_A_Syematic_Literature_Review
• Santoro, A., Lampinen, A., Mathewson, K., Lillicrap, T., Raposo, D., Symbolic Behaviour in Artificial Intelligence, 2022, dostupno na: https://doi.org/10.48550/arXiv.2102.03406
• Skoudis, E., Zeltser, L., Malware: Fighting Malicious Code, Prentice Hall PTR, New Jersey, 2004.
• Sutton, R. S., Barto, A. G., Reinforcement Learning: An Introduction (2nd edition), MIT Press, 2018, dostupno na: http://incompleteideas.net/book/the-book-2nd.html
• Frey, C. B., Osborne, M. A., The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114/2017.
• Fritsch, L., Jaber, A., Yazidi, A., An Overview of Artificial Intelligence Used in Malware, In: Zouganeli, E., Yazidi, A., Mello, G., Lind, P. (eds) Nordic Artificial Intelligence Research and Development. NAIS 2022. Communications in Computer and Information Science, vol 1650. Springer, Cham, dostupno na: https://doi.org/10.1007/978-3-031-17030-0_4
• Chen, M., Mao, S., Liu, Y., Big Data: A Survey, Mobile Networks and Applications, 19(2) 2014.ArtenvonKI: Definition, Abgrenzung&Anwendung, Otrissoftware, https://www.otris.de/wiki/ arten-von-ki/, 10.4.2025.
• GefahrendurchKI: EinBlickaufdieRisikenderkünstlichenIntelligenz, https://www.moin.ai/chatbot -lexikon/gefahren-durch-ki, 07.04.2025.;
• DieGefahrenundRisikenvonKünstlicherIntelligenz (KI), https://www.ki-company.ai, 07.04.2025.
• KI-SystemeKönnenLügenUndBetrügen, https://www.it-daily.net/shortnews/ki-systeme-koennen-luegen-und-betruegen, 07.04.2025.
• KI-Gesetz: ersteRegulierungderkünstlichenIntelligenz, https://www.europarl.europa.eu/topics/de/ article/20230601STO93804/ki-gesetz-erste-regulierung-der-kunstlichen-intelligenz, 02.04.2025.
• KI-Gesetz, https://digital-strategy.ec.europa.eu/de/policies/regulatory-framework-ai, 02.04.2025.
• KünstlicheIntelligenz, https://digital-strategy.ec.europa.eu/de/policies/artificial-intelligence, 02.04.2025.
• KünstlicheIntelligenzundDigitalisierung: WelcheChancenundRisikengibtes?, https://ambient.digital/ wissen/blog/kuenstliche-intelligenz-chancen-risiken/, 07.04.2025.
• Regulativa (EU) 2024/1689 Evropskog parlamenta i Savetaod 13. juna 2024. godine, kojom se utvrđuju usklađena pravila o veštačkoj inteligenciji i menja Regulativa (EZ) br. 300/2008, (EU) br. 167/2013, (EU) br. 168/2013, (EU) 2018/858, (EU) 2018/1139 i (EU) 2019/2144, kao i Direktive 2014/90/EU, (EU) 2016/797 i (EU) 2020/1828 (Zakon o veštačkoj inteligenciji) (Regulation (EU) 2024/1689 of the European Parliament and of the Council of 13 June 2024 laying down harmonised rules on artificial intelligence and a mending Regulations (EC) No 300/2008, (EU) No 167/2013, (EU) No 168/2013, (EU) 2018/858, (EU) 2018/1139 and (EU) 2019/2144 and Directives 2014/90/EU, (EU) 2016/797 and (EU) 2020/1828 (Artificial Intelligence Act)).
• Chancen, GrenzenundRisikenderkünstlichenIntelligenz – vonihrselbsterklärt, https://www.argus datainsights. ch/de/blog/chancen-grenzen-und-risiken-der-kuenstlichen-intelligenz-von-ihr-selbst-erklaert, 07.04.2025.