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Hukuk’ta Yapay Zeka: Çalışmalar ve Gelecek Öngörüleri

Yıl 2020, Cilt 11, Sayı 2, 246 - 255, 07.12.2020
https://doi.org/10.29048/makufebed.748843

Öz

Son yıllarda internet teknolojilerinin gelişmesi, bilgisayarların işlem gücünün artması ve bulut bilişim ile milyonlarca verinin depolanabilmesi sonucunda, yapay zeka çalışmalarının hızlı bir şekilde arttığı görülmektedir. Tıp, mühendislik, sağlık, savunma, ticaret, güvenlik gibi birçok alanda yapay zeka çalışmaları hayatımızı kolaylaştıran çözümler ile karşımıza çıkmaktadır. Hukuk alanında elde edilen veriler üzerinde yapay zeka sistemleri ile çözümler bulmak ise yeni bir kavramdır. Hukuk verilerinin yapay zeka ile değerlendirilmesi, daha kısa sürede daha çok işlemin gerçekleşmesi ve rutin işlemlerin otomatikleştirilmesi olarak düşünülmelidir. Bu çalışmada günümüzde yapay zeka teknolojisinin yasal alandaki durumunu ve gelişimi incelenmektedir. Ayrıca gelecekte yapılabilecek çalışmalara öngörü sunularak, bu alanın gelişmesine katkıda bulunması hedeflenmektedir.

Kaynakça

  • Chalkidis, I., Fergadiotis, M., Malakasiotis, P., Aletras, N., Androutsopoulos, I. (2019). Extreme Multi-Label Legal Text Classification: A Case Study in EU Legislation. Proceedings of the Natural Legal Language Processing Workshop 2019, June 7, 2019, Minneapolis, Minnesota, 78–87p.
  • Chalkidis, I., Kampas, D. (2019). Deep Learning in Law: Early Adaptation and Legal Word Embedding’s Trained on Large Corpora. Artificial Intelligence and Law, 27: 171 – 198p.
  • Chen, S., Wan, P., Fang, W., Deng, X., Zhang, F. (2019). Learning To Predict Charges for Judgment with Legal Graph, Proceedings of 28th International Conference on Artificial Neural Networks, September 17–19, 2019, Munich, Germany, Part IV, 262 – 274p.
  • He, C., Peng, L., Le, Y., He, J., Zhu, X. (2019). Secaps: A Sequence Enhanced Capsule Model for Charge Prediction, Proceedings of 28th International Conference on Artificial Neural Networks, September 17–19, 2019, Mu-nich, Germany, Part IV, 171 – 198p.
  • Howe, J., Khang, L., Chai, I. (2019). Legal Area Classification: A Comparative Study of Text Classifiers on Singapore Supreme Court Judgments. Proceedings of the Natural Legal Language Processing Workshop, June 7, 2019, Minneapolis, Minnesota, 67 – 77p.
  • Lage-Freitas, A., Allende-Cid,H., Santana, O., Oliveira-Lage L. (2019). Predicting Brazilian Court Decisions. arXiv:1905.10348v1, April 20, 2019.
  • Li, P., Zhao, F., Li, Y., Zhu, Z. (2018). Law Text Classification Using Semi-Supervised Convolutional Neural Networks. Proceedings of 2018 Chinese Control and Decision Conference, June 9-11, 2018, Shenyang, China, 309 – 313p.
  • Li, S., Zhang, H., Ye, L., Guo, X. Fang, B. (2019). Mann: A Multichannel Attentive Neural Network for Legal Judgment Prediction. IEEE Access 7: 151144 – 151155.
  • Long, S., Tu, C., Liu, Z., Sun, M. (2019). Automatic Judgment Prediction via Legal Reading Comprehension. Proceedings of 18th China National Conference, October 18–20, 2019, Kunming, China, 558 – 572p.
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  • Xiao, C., Zhong, H., Guo, Z., Tu, C., Liu, Z. (2018). Cail2018: A Large-Scale Legal Dataset for Judgment Prediction. arXiv: 1807.02478, July 4, 2018.
  • Yan, G., Li, Y., Shen, S., Zhang, S., Liu, J. (2019). Law Article Prediction Based on Deep Learning. Proceedings of 2019 IEEE 19th International Conference on Software Quality, Reliability and Security Companion, July 22-26, 2019, Sofia, Bulgaria, 281-284p.
  • Yang, W., Jia, W., Zhou, X., Luo, Y. (2019). Lega judgment Prediction via Multi-Perspective Bi-Feedback Network. Proceedings of Twenty-Eighth International Joint Con-ference on Artificial Intelligence, August 10-16, 2019, Macao, China, 4085 – 4091p.
  • Yang, Z., Wang, P., Zhang, L., Shou, L. (2019). A Recurrent Attention Network for Judgment Prediction. Proceedings of 28th International Conference on Artificial Neural Networks, September 17–19, 2019, Munich, Germany, Part IV, 253 – 266p.
  • Yin, Y., Yang, H., Zhao, Z., Chen, S. (2019). A Judicial Sentencing Method Based on Fused Deep Neural Networks. Proceedings of 28th International Conference on Artificial Neural Networks, September 17–19, 2019, Munich, Germany, Part IV, 213 – 226p.
  • Zhong, H., Xiao, C., Guo, Z., Tu, C., Liu, Z. (2018). Overview of Caıl2018: Legal Judgment Prediction Competition. arXiv:1810.05851v1, October 13, 2018.

Artificial Intelligence in Law: Studies and Future Insights

Yıl 2020, Cilt 11, Sayı 2, 246 - 255, 07.12.2020
https://doi.org/10.29048/makufebed.748843

Öz

In recent years, as a result of the development of internet technology, increasing the computing power of computers and storing millions of data with cloud computing, artificial intelligence studies have been increasing rapidly. Artificial intelligence studies in many fields such as medicine, engineering, health, defense, trade and security come up with solutions that make our lives easier. Finding solutions with artificial intelligence systems on the data obtained in the field of law is a new concept. Evaluation of legal data with artificial intelligence should be considered as more transactions in less time and automation of routine transactions. This study examines the current status and development of artificial intelligence technology in the legal field. In addition, it is aimed to contribute to the development of this area by making predictions for future studies.

Kaynakça

  • Chalkidis, I., Fergadiotis, M., Malakasiotis, P., Aletras, N., Androutsopoulos, I. (2019). Extreme Multi-Label Legal Text Classification: A Case Study in EU Legislation. Proceedings of the Natural Legal Language Processing Workshop 2019, June 7, 2019, Minneapolis, Minnesota, 78–87p.
  • Chalkidis, I., Kampas, D. (2019). Deep Learning in Law: Early Adaptation and Legal Word Embedding’s Trained on Large Corpora. Artificial Intelligence and Law, 27: 171 – 198p.
  • Chen, S., Wan, P., Fang, W., Deng, X., Zhang, F. (2019). Learning To Predict Charges for Judgment with Legal Graph, Proceedings of 28th International Conference on Artificial Neural Networks, September 17–19, 2019, Munich, Germany, Part IV, 262 – 274p.
  • He, C., Peng, L., Le, Y., He, J., Zhu, X. (2019). Secaps: A Sequence Enhanced Capsule Model for Charge Prediction, Proceedings of 28th International Conference on Artificial Neural Networks, September 17–19, 2019, Mu-nich, Germany, Part IV, 171 – 198p.
  • Howe, J., Khang, L., Chai, I. (2019). Legal Area Classification: A Comparative Study of Text Classifiers on Singapore Supreme Court Judgments. Proceedings of the Natural Legal Language Processing Workshop, June 7, 2019, Minneapolis, Minnesota, 67 – 77p.
  • Lage-Freitas, A., Allende-Cid,H., Santana, O., Oliveira-Lage L. (2019). Predicting Brazilian Court Decisions. arXiv:1905.10348v1, April 20, 2019.
  • Li, P., Zhao, F., Li, Y., Zhu, Z. (2018). Law Text Classification Using Semi-Supervised Convolutional Neural Networks. Proceedings of 2018 Chinese Control and Decision Conference, June 9-11, 2018, Shenyang, China, 309 – 313p.
  • Li, S., Zhang, H., Ye, L., Guo, X. Fang, B. (2019). Mann: A Multichannel Attentive Neural Network for Legal Judgment Prediction. IEEE Access 7: 151144 – 151155.
  • Long, S., Tu, C., Liu, Z., Sun, M. (2019). Automatic Judgment Prediction via Legal Reading Comprehension. Proceedings of 18th China National Conference, October 18–20, 2019, Kunming, China, 558 – 572p.
  • URL-1. (2020). https://tr.euronews.com/2020/02/23/yapay-zeka-teknolojisi-savasin-karakterini-nasil-degistirecek (Erişim Tarihi: 04.03.2020)
  • URL-2. (2019). https://www.ntv.com.tr/saglik/yapay-zeka-gogus-rontgeninden-hastalik-teshisini-hizlandiracak,W3Jg_ENqrUKDgw300w_e8g (Erişim Ta-rihi: 04.03.2020)
  • URL-3. (2019). https://medium.com/@ayyucekizrak/yapay-zeka-kullan%C4%B1m-alanlar%C4%B1-ve-uygulamalar%C4%B1na-derinlemesine-bir-bak%C4%B1%C5%9F-d0fecaf7f61b (Erişim Tarihi: 04.03.2020)
  • URL-4. (2018). https://rossintelligence.com/ (Erişim Tarihi: 15.12.2019)
  • URL-5. (2019). https://adalethanim.com/tag/arama-motoru/ (Erişim Tarihi: 16.12.2019)
  • URL-6. (2018). https://www.cnnturk.com/turkiye/yargitay-davalarinda-yapay-zekali-tahmin (Erişim Tarihi: 17.12.2019)
  • URL-7. (2018). https://github.com/thunlp/CAIL/blob/master/README_en.md (Erişim Tarihi: 16.12.2019)
  • URL-8. (2019). https://teknolojivehukuk.com/proje.php?ID=30&x=YAPAY%20ZEKA%20AVUKAT:%20ROSS (Erişim Tarihi: 15.12.2019)
  • URL-9. (2019). https://bilimkafasi.com/yapay-zeka-avukatlara-karsi-yapay-zekanin-gelecegi-ve-hukuk/ (Eri-şim Tarihi: 15.12.2019)
  • URL-10. (2019). https://adalethanim.com/ (Erişim Tarihi: 16.12.2019)
  • URL-11. (2019). https://www.kodexbilisim.com/ (Erişim Tari-hi: 16.12.2019)
  • URL-12. (2019). https://www.istanbulbarosu.org.tr/HaberDetay.aspx?ID=15324 (Erişim Tarihi: 25.12.2019)
  • Xiao, C., Zhong, H., Guo, Z., Tu, C., Liu, Z. (2018). Cail2018: A Large-Scale Legal Dataset for Judgment Prediction. arXiv: 1807.02478, July 4, 2018.
  • Yan, G., Li, Y., Shen, S., Zhang, S., Liu, J. (2019). Law Article Prediction Based on Deep Learning. Proceedings of 2019 IEEE 19th International Conference on Software Quality, Reliability and Security Companion, July 22-26, 2019, Sofia, Bulgaria, 281-284p.
  • Yang, W., Jia, W., Zhou, X., Luo, Y. (2019). Lega judgment Prediction via Multi-Perspective Bi-Feedback Network. Proceedings of Twenty-Eighth International Joint Con-ference on Artificial Intelligence, August 10-16, 2019, Macao, China, 4085 – 4091p.
  • Yang, Z., Wang, P., Zhang, L., Shou, L. (2019). A Recurrent Attention Network for Judgment Prediction. Proceedings of 28th International Conference on Artificial Neural Networks, September 17–19, 2019, Munich, Germany, Part IV, 253 – 266p.
  • Yin, Y., Yang, H., Zhao, Z., Chen, S. (2019). A Judicial Sentencing Method Based on Fused Deep Neural Networks. Proceedings of 28th International Conference on Artificial Neural Networks, September 17–19, 2019, Munich, Germany, Part IV, 213 – 226p.
  • Zhong, H., Xiao, C., Guo, Z., Tu, C., Liu, Z. (2018). Overview of Caıl2018: Legal Judgment Prediction Competition. arXiv:1810.05851v1, October 13, 2018.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Derleme Makale
Yazarlar

Tülay TURAN (Sorumlu Yazar)
BURDUR MEHMET AKİF ERSOY ÜNİVERSİTESİ, TEKNİK BİLİMLER MESLEK YÜKSEKOKULU
0000-0002-0888-0343
Türkiye


Nazan KEMALOĞLU
BURDUR MEHMET AKİF ERSOY ÜNİVERSİTESİ BİLGİ TEKNOLOJİLERİ UYGULAMA VE ARAŞTIRMA MERKEZİ
0000-0002-6262-4244
Türkiye


Ecir KÜÇÜKSİLLE
SÜLEYMAN DEMİREL ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ
0000-0002-3293-9878
Türkiye

Yayımlanma Tarihi 7 Aralık 2020
Yayınlandığı Sayı Yıl 2020, Cilt 11, Sayı 2

Kaynak Göster

APA Turan, T. , Kemaloğlu, N. & Küçüksille, E. (2020). Hukuk’ta Yapay Zeka: Çalışmalar ve Gelecek Öngörüleri . Mehmet Akif Ersoy Üniversitesi Fen Bilimleri Enstitüsü Dergisi , 11 (2) , 246-255 . DOI: 10.29048/makufebed.748843

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