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@article{182710,
        author = {Bidhan Kumar Rout},
        title = {Artificial Intelligence in Recruitment: A Critical Study of Amazon’s AI Hiring Tool},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {2},
        pages = {3176-3180},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=182710},
        abstract = {Many companies are making a strong investment into the future of AI to optimise their operations in the age of cognitive systems. A remarkable case in point was witnessed in 2014, as Amazon built an AI recruiting tool by utilizing Natural Language Processing (NLP) and Machine Learning (ML). The goal of this system was to automate the process of screening job applications and to identify best candidates by analyzing resumes. It leveraged cutting-edge text analysis to parse out critical information and provide insights to guide hiring. The system had initially been hailed as an encouraging step toward eliminating human bias and making hiring more efficient. But in practice the system was found to be inadvertently discriminating against them. This was an AI model that started favoring male employees (particularly if they were applying for technical positions), simply because it had been trained on historical hiring data, and hiring history had been sexist. This has raised significant ethical questions of fairness and accountability in automated decision making. Due to these problems, Amazon pulled the plug on the project. The episode underscored the dangers of using AI in sensitive areas such as hiring, and it offered a warning to business leaders about the necessity of unbiased data and ethical AI development. Consequently, Amazon opted to discontinue the AI-based hiring system.},
        keywords = {artificial intelligence, gender bias, technology, talent and recruiting, human resources, machine learning, hiring, technical, automated},
        month = {July},
        }