ETHICAL CHALLENGES IN THE DEVELOPMENT OF AI: A GUIDE FOR TECHNOLOGISTS

Abstract

Abstract. Analyzing the ethical issues faced by artificial intelligence (AI) systems, the study covers algorithmic bias, privacy violations, and lack of explanation in judgments. An ethical framework for AI development is proposed, consisting of explainability methods (SHAP, LIME), federated learning, data documentation, and diverse teams. Evaluation through frequent audits and the ability to adapt to the cultural environment makes the process fair and transparent, and therefore, trustworthy for AI systems in the financial, medical, and judicial sectors. It is proven that the implementation of a comprehensive ethical approach to the development and use of AI systems helps minimize the risks of discrimination and increase the level of social responsibility of technological solutions. The need to create interdisciplinary regulatory standards that will ensure a balance between innovation and respect for human rights is outlined. The results of the study can be used to formulate practical recommendations for the ethical integration of artificial intelligence into various areas of social activity. The importance of constant monitoring and updating of ethical protocols in accordance with the dynamic development of artificial intelligence technologies is emphasized. Prospects for further research lie in the development of universal methods for assessing the ethics of AI systems and their practical testing in real operating conditions.