Hayden Tafs (University of Wisconsin – Whitewater) has posted Ethical Challenges and Algorithmic Bias in Artificial Intelligence on SSRN. Here is the abstract:
Artificial Intelligence (AI) is rapidly growing and becoming an increasingly important part of many industries, but it also raises significant ethical and social concerns. This paper looks at how algorithmic bias, which can come from bad data, poor sampling, labeling mistakes, and old patterns in society, can make unfairness worse in AI systems. These problems are not random but show deeper social issues that affect fairness, trust, and accountability. The paper explains how a lack of openness and oversight makes it hard to find and fix bias. To solve these issues, researchers suggest using clear data practices, regular checks on algorithms, and strong legal and ethical rules. Building fairness into AI from the start is key to making it more trustworthy. In the end, the paper argues that responsible and transparent AI can help technology support fairness and honesty in society.