Tag: Responsible Artificial Intelligence
-
Transparency and Responsibility in Artificial Intelligence
Author: N/A; Publisher: Deloitte; Publication Year: 2019. The following publication emphasizes the need for artificial intelligence (AI) that is transparent and responsible in that it has been thoroughly tested, is explainable, and has undergone many…
-
4 Principles of Responsible AI and Best Practices to Adopt Them
Data Access, Data Classification, Data Encryption, Fairness, Representation in Training Datasets, Responsible Artificial Intelligence, Synthetic Data, Training Data, Transparency, Usage RestrictionsAuthor: Cem Dilmegani; Publisher: AI Multiple; Publication Year: 2022. The following article explores 4 principles for responsible AI design and recommends best practices. The 4 principles, along with best practices, include: 1). achieving fairness by…
-
Mapping AI and Data Ethics
Artificial Intelligence, Data Justice, Data Visualizations, Disciplinary Isolation, Ethical Relevance, Non-Dominant Perspectives, Responsible Artificial IntelligenceAuthor: N/A; Publisher: The Ada Lovelace Institute; Publication Year: N/A. The following resource explains the major challenge in mapping AI and data ethics concerns what constitutes AI and data ethics in the first place. The…