How can we manage biases in artificial intelligence systems – A systematic literature review

Abstract

Artificial intelligence is similar to human intelligence, and robots in organisations always perform human tasks. However, AI encounters a variety of biases during its operational process in the online economy. The coded algorithms helps in decision-making in firms with a variety of biases and ambiguity. The study is qualitative in nature and asserts that AI biases and vulnerabilities experienced by people across industries lead to gender biases and racial discrimination. Furthermore, the study describes the different types of biases and emphasises the importance of responsible AI in firms in order to reduce the risk from AI. The implications discuss how policymakers, managers, and employees must understand biases to improve corporate fairness and societal well-being. Future research can be carryout on consumer bias, bias in job automation and bias in societal data.

Keywords

• Artificial intelligence
• Bias
• Vulnerabilities
• Responsible Ai
• AI ethics
• AI systems