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Record W7025106537

The urgency artificial intelligence regulation in indonesia in an effort to realize the ideals of national law

2023· dissertation· id· W7025106537 on OpenAlexaff

Bibliographic record

VenueeTheses of Maulana Malik Ibrahim State Islamic University (Maulana Malik Ibrahim State Islamic University) · 2023
Typedissertation
Languageid
FieldSocial Sciences
TopicIndonesian Legal and Regulatory Studies
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsComputational intelligenceLegal normApplications of artificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

INDONESIA: \n \nPerkembangan Artificial Intelligence di Indonesia telah dirasakan oleh sebagian besar masyarakat. Akan tetapi, hingga saat ini tidak ada aturan yang mengatur terkait Artificial Intelligence. Oleh karena itu, diperlukan adanya regulasi yang mengatur Artificial Intelligence di Indonesia. \nTujuan penelitian ini adalah untuk mengetahui dan menganalisis Urgensi Regulasi Artificial Intelligence di Indonesia dalam Upaya Mewujudkan Cita Hukum Nasional serta telaah dalam Perspektif Teori Hukum Responsif dan Sadd Al-Dzariah \nPenelitian ini menggunakan jenis penelitian yuridis normatif, dengan pendekatan statue approach, conceptual approach, dan comparative approach. Sumber bahan hukum yang digunakan yaitu bahan hukum primer, sekunder, dan tersier, yang dianalisis menggunakan metode deskriptif dan komparatif. \nHasil penelitian ini menunjukkan: 1) Urgensi regulasi Artificial Intelligence sebab banyaknya permasalahan Artificial Intelligence yang juga tidak dilindungi oleh Undang-Undang, telah sejalan dengan perwujudan Cita Hukum Nasional untuk memberikan Kepastian Hukum, Keadilan, dan Kemanfaatan yang dapat dirasakan oleh seluruh masyarakat di Indonesia 2) Urgensi regulasi Artificial Intelligence di Indonesia telah sejalan dengan teori Hukum Responsif sebagai bentuk respon pemerintah terhadap kepastian hukum masyarakat dalam memanfaatkan Artificial Intelligence kedepannya. Selaras dengan Sadd Al-Dzariah yang hadir sebagai jalan tengah terhadap banyaknya permasalahan Artificial Intelligence yang dapat ditimbulkan karena mengandung kemudharatan yang dapat merugikan masyarakat. \n \nENGLISH: \n \nThe development of Artificial Intelligence in Indonesia has been felt by most people. However, until now there are no rules governing Artificial Intelligence. Therefore, there is a need for regulations governing Artificial Intelligence in Indonesia. \nThe purpose of this study is to know and analyze the Urgency of Artificial Intelligence Regulation in Indonesia in an effort to Realize the Ideal of National Law as well as a study in the Perspective of Responsive Legal Theory and Sadd Al-Dzariah \nThis study used a type of normative juridical research, with a statute approach, conceptual approach, and comparative approach. The sources of legal materials used are primary, secondary, and tertiary legal materials, which are analyzed using descriptive and comparative methods. \nThe results of this research show: 1) The urgency of Artificial Intelligence regulation due to the many problems of Artificial Intelligence that are also not protected by law, has been in line with the realization of the National Legal Ideal to provide Legal Certainty, Justice, and Benefits that can be felt by all people in Indonesia. 2) The urgency of Artificial Intelligence Regulation in Indonesia is in line with the Responsive Law as a form of government response to the legal certainty of the community in utilizing Artificial Intelligence in the future. In line with Sadd Al-Dzariah which is present as a middle way to the many problems of Artificial Intelligence that can be caused because it contains harm to society. \n \nARAB: \n \nلقد شعر معظم الناس بتطوير الذكاء الاصطناعي في إندونيسيا. ومع ذلك ، حتى الآن لا لقد شعر معظم الناس بتطوير الذكاء الاصطناعي في إندونيسيا. ومع ذلك ، حتى الآن لا توجد قواعد تحكم الذكاء الاصطناعي. لذلك ، هناك حاجة للوائح تحكم الذكاء الاصطناعي في إندونيسيا \nالغرض من هذه الدراسة هو معرفة وتحليل الحاجة الملحة لتنظيم الذكاء الاصطناعي في إندونيسيا في محاولة لتحقيق المثل الأعلى للقانون الوطني وكذلك دراسة في منظور النظرية القانونية المستجيبة وسد الدزارية. \nيستخدم هذا البحث الأساليب القانونية المعيارية ، مع نهج تمثال ، ونهج مفاهيمي ، ونهج مقارن. مصادر المواد القانونية المستخدمة هي المواد القانونية الأولية والثانوية والثالثية ، والتي يتم تحليلها باستخدام الأساليب الوصفية والمقارنة. \nتظهر نتائج هذا البحث: 1) إن الحاجة الملحة لتنظيم الذكاء الاصطناعي بسبب العديد من مشاكل الذكاء الاصطناعي التي لا يحميها القانون أيضا ، تتماشى مع تحقيق المثل الأعلى القانوني الوطني لتوفير اليقين القانوني والعدالة والفوائد التي يمكن أن يشعر بها جميع الناس في إندونيسيا. 2) تتماشى الحاجة الملحة لتنظيم الذكاء الاصطناعي في إندونيسيا مع قانون الاستجابة كشكل من أشكال استجابة الحكومة لليقين القانوني للمجتمع في استخدام الذكاء الاصطناعي في المستقبل. تماشيا مع سد الدزارية الموجود كطريق وسط للعديد من مشاكل الذكاء الاصطناعي التي يمكن أن تحدث لأنها تحتوي على ضرر للمجتمع

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.005
Scholarly communication0.0070.002
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.281
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2023
Admission routes1
Has abstractyes

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