Biases in Artificial Intelligence Applications A ffecting H uman L ife : A Review
Ravindra Kumar
Ravindra Kumar*, Technical Account Manager, Navvis Healthcare, St. Louis, USA.
Manuscript received on March 11, 2021. | Revised Manuscript received on April 30, 2021. | Manuscript published on May 30, 2021. | PP: 54-55 | Volume-10 Issue-1, May 2021. | Retrieval Number: 100.1/ijrte.A57190510121 | DOI: 10.35940/ijrte.A5719.0510121
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The introduction of Artificial Intelligence has improved operations in almost every sector, industry, and part of human life. The use of AI has been vital in the department of justice, recruitment by organizations, facial recognition by police, and school admissions. The aim of introducing AI algorithms in various fields was to reduce human bias in decision-making. Despite the progress, there are ethical concerns that the AI algorithms also exhibit biases. The main reason behind the claim is because human developers are in charge of training data used by the algorithms. There are areas where the issue of biases affects human life directly and can do damages to a person, physically or emotionally. Some examples are college admissions, recruitment, administration of justice at the courts, public benefits systems, police, public safety, and healthcare. There are high chances that the development process introduced biases in artificial intelligence algorithms, knowingly or unknowingly, during any area mentioned above. The paper provides background knowledge on AI bias and possible solutions to solve the problem.
Keywords: Biases In AI, AI, Artificial Intelligence, social AI