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@article{179506,
        author = {Janhavi and Chhavi Rana},
        title = {Ethical Concerns in AI Datasets},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {6919-6925},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179506},
        abstract = {The rapid development of artificial
intelligence (AI) has led to its widespread adoption in a
variety of fields, which has raised serious concerns
about the moral and practical issues surrounding
training and evaluation datasets. We also investigate
how security flaws, scalability, and dataset quality
affect AI applications. To address these issues, this
paper emphasizes the urgent need for standardized
guidelines, strong data governance frameworks, and
ethical AI practices by examining various case studies
and existing mitigation techniques. This research
paper's goal is to investigate important concerns
related to AI datasets, such as biases, privacy
violations, a lack of transparency, and data integrity.
The risks of personal data being misused in machine
learning models, the difficulties of guaranteeing
accountability in AI decision-making, and the
examination of biased or unrepresentative datasets
that can support discrimination are all included. Our
results highlight how crucial it is to promote equity,
responsibility, and openness in dataset curation in
order to guarantee responsible AI development and
application. Additionally, this paper provides an
overview of the datasets, their use, and specific
metrics.},
        keywords = {Artificial Intelligence, Dataset Bias, Privacy Concerns, Ethical AI, Data Governance, Machine Learning, Transparency, Accountability.},
        month = {May},
        }