From Automation to Autonomous Systems: A Legal Phenomenology with Problems of Accountability
Authors: Ugo Pagallo
IJCAI 2017 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | The paper offers a concise phenomenology on how automation and the development of artificial intelligence ('AI')systems have affected pillars of the law. |
| Researcher Affiliation | Academia | Ugo Pagallo University of Turin, Italy, Law School EMAIL |
| Pseudocode | No | The paper, being a legal phenomenology, does not contain any pseudocode or algorithm blocks. |
| Open Source Code | No | This is a theoretical research paper focusing on legal aspects of AI and does not describe a software methodology, therefore, it does not provide open-source code. |
| Open Datasets | No | This is a theoretical research paper and does not involve empirical data or model training, thus no dataset is mentioned for public access or training. |
| Dataset Splits | No | This is a theoretical research paper and does not involve empirical data analysis or model validation, thus no training/test/validation dataset splits are specified. |
| Hardware Specification | No | This is a theoretical research paper focusing on legal analysis and does not involve experimental work requiring hardware specifications. |
| Software Dependencies | No | This is a theoretical research paper and does not involve computational experiments that would require detailing software dependencies with version numbers. |
| Experiment Setup | No | This is a theoretical research paper and does not involve experimental setup details such as hyperparameters or training configurations. |