Academic
Academic
Data augmentation for fairness-aware machine learning
Researchers and practitioners in the fairness community have highlighted the ethical and legal challenges of using biased datasets in data-driven systems, with algorithmic bias being …
Natural Language, Legal Hurdles: Navigating the Complexities in Natural Language Processing Development and Application
This article delves into the legal challenges faced in developing and deploying Natural Language Processing (NLP) technologies, focusing particularly on the European Union’s legal framework, …
Legal Implications of Using Artificial Intelligence (AI) Technology in Electronic Transactions
The advancement of technology, including the use of Artificial Intelligence (AI) in everyday life, has brought about significant changes and substantial impacts, especially in electronic …
Algorithmic discrimination in the credit domain: what do we know about it?
Abstract The widespread usage of machine learning systems and econometric methods in the credit domain has transformed the decision-making process for evaluating loan applications. Automated …
Bias in data‐driven artificial intelligence systems—An introductory survey
Abstract Artificial Intelligence (AI)‐based systems are widely employed nowadays to make decisions that have far‐reaching impact on individuals and society. Their decisions might affect everyone, …
Litigation Outcome Prediction of Differing Site Condition Disputes through Machine Learning Models
The construction industry is one of the main sectors of the U.S. economy that has a major effect on the nation’s growth and prosperity. The …