The problem of consciousness in artificial intelligence systems

This study explores the possibility of consciousness emerging in artificial intelligence systems from philosophical, technical, and societal perspectives. Artificial intelligence is defined—based on institutions like McCarthy, the OECD, the European Commission, and the Turkish Language Association—as systems that mimic human intelligence with abilities such as learning, reasoning, and problem-solving. The literature traces the foundations of modern AI through historical figures like Al-Jazari, Leibniz, Turing, and Ada Lovelace. The role of consciousness in AI is examined through thought experiments such as the Turing Test and the Chinese Room. Supporting arguments highlight the potential of machines to simulate human intelligence, while critics like John Searle argue that syntactic processing alone lacks meaning and subjectivity. The thesis aims to question whether AI systems can truly possess consciousness by weighing arguments for and against. It also covers technical applications such as natural language processing, machine learning, and deep learning, alongside societal issues like ethics, data privacy, algorithmic bias, and employment. Looking to the future, advancements in general AI, autonomous systems, quantum computing, and neuromorphic hardware are seen as shaping the evolution of AI, emphasizing the need for interdisciplinary approaches to address the complex issue of machine consciousness.