Existing challenges in ethical AI

The current growth of Artificial Intelligence (AI) is enormous, and has the potential of changing industries, economies and societies in the today’s world. Nevertheless, as AI is more and more involved in decision-making processes, the ethical issues come out and affect trust, fairness, and accountability of these systems. From the reviewed literature, this paper identifies five key ethical issues in AI: Algorithmic Bias, Fairness, Transparency, Accountability, and Privacy. Nevertheless, the current AI systems have a tendency to mimic the prejudices which have existed throughout history, which presents threats to society equity. Furthermore, a question of accountability and explanation of every decision made by AI brings the question of the explainability of AI and the ability to track the reasoning of an AI model. There are also issues to do with privacy as much of the data needed for training AI models is personal data and this is a major issue of privacy. The paper elaborates these challenges and recommends the following solutions: design non-discriminatory and accountable AI systems; follow ethical principles in AI development; test AI systems for biases; and encourage interdisciplinary cooperation. The paper also seeks to discuss the most effective ways of incorporating ethical principles into the AI development process and supports the element of regulation to enhance the existing rules. Through addressing these significant concerns, this paper seeks to contribute theoretical and practical recommendations towards the proper creation and application of AI-based solutions for the collective benefit of society and creating confidence in the system.