1.3. Literature

• Glazko, K., Mohammed, Y., Kosa, B., Potluri, V., & Mankoff, J. (June 2024). Identifying and Improving Disability Bias in GPT-Based Resume Screening. In The 2024 ACM Conference on Fairness, Accountability, and Transparency (pp. 687-700). https://doi.org/10.1145/3630106.3658933.
• Kirkpatrick, K. (2023). The Carbon Footprint of Artificial Intelligence. Commun. ACM 66, 8 (August 2023), 17–19. https://doi.org/10.1145/3603746.
• Kotsar, E. (2024). Tehisintellektil põhineva vestlusrobot ChatGPT kasutamise kogemused Tartu Ülikooli sotsiaalteaduste valdkonna üliõpilaste näitel. Magistritöö. Tartu Ülikool. https://dspace.ut.ee/items/9abc8662-7bff-497d-842f-c5097f0ec383.
• PlanBe. (2024). AI’s carbon footprint: How does the popularity of artificial intelligence affect the climate? PlanBe Eco. https://planbe.eco/en/blog/ais-carbon-footprint-how-does-the-popularity-of-artificial-intelligence-affect-the-climate/.
• Ray, P.P. (2023). ChatGPT: A Comprehensive Review on Background, Applications, Key Challenges, Bias, Ethics, Limitations and Future Scope. Internet of Things and Cyber-Physical Systems, 3, 121-154. https://doi.org/10.1016/j.iotcps.2023.04.003