Responsible Autonomy
Authors: Virginia Dignum
IJCAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we describe leading ethics theories and propose alternative ways to ensure ethical behavior by artificial systems. Given that ethics are dependent on the socio-cultural context and are often only implicit in deliberation processes, methodologies are needed to elicit the values held by designers and stakeholders, and to make these explicit leading to better understanding and trust on artificial autonomous systems. |
| Researcher Affiliation | Academia | Virginia Dignum Delft University of Technology m.v.dignum@tudelft.nl |
| Pseudocode | No | The paper does not contain any pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | No | The paper does not provide any concrete access to source code for the methodology described. It is a theoretical paper and does not involve software implementation. |
| Open Datasets | No | The paper does not describe experiments using a specific dataset, nor does it provide information about dataset availability or access. It uses the "trolley problem scenario" as an illustration rather than a dataset for training or evaluation. |
| Dataset Splits | No | The paper does not conduct empirical experiments or use datasets that would require training, validation, or test splits. It is a theoretical paper. |
| Hardware Specification | No | The paper is a theoretical discussion and does not describe any experiments that would require specific hardware for execution. |
| Software Dependencies | No | The paper is a theoretical discussion and does not describe any specific software implementations or dependencies with version numbers. |
| Experiment Setup | No | The paper is a theoretical discussion of responsible autonomy and ethical considerations in AI. It does not describe any empirical experiments, therefore, no experimental setup details, hyperparameters, or training configurations are provided. |