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Ensuring Inclusivity and fairness in AI-generated content.

  • Unique Paper ID: 180542
  • Volume: 12
  • Issue: 1
  • PageNo: 1464-1467
  • Abstract:
  • Bias and fairness in NLP models are of the highest priority to ensure AI-generated text stays balanced and impartial. NLP models, having been trained on large datasets to receive social biases which may result in fair or unfair results. This project is about searching, researching, and mitigation of text biases generated by AI using fairness-aware algorithms. The method involves choosing well balanced datasets, employing involving training, and adding fairness rules to reduce gender and culture biases. The project includes a fairness inspection process to identify potential weaknesses before it is launched. By following responsible AI guidelines and regulations, this approach seeks to develop NLP that is easier to understand, more ethical, and socially responsible. AI fairness models that generate fair text content. Fairness inspection help identify unfairness, weaknesses, and security risks in a system and while pure fairness is hard to achieve, continuous efforts can reduce harm and promote Equality in AI.
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  • ISSN: 2349-6002
  • Volume: 12
  • Issue: 1
  • PageNo: 1464-1467

Ensuring Inclusivity and fairness in AI-generated content.

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Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

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