The 1975 ACM Turing Award was jointly given to Allen Newell and Herbert A. Simon for their contributions to artificial intelligence, psychology of human cognition, and list processing. Their work over twenty years, including collaborations with J.C. Shaw and Carnegie-Mellon University colleagues, established artificial intelligence as a scientific field and advanced understanding of human problem-solving and cognitive processes. They are credited with inventing list processing and contributing to software technology and the concept of computers as symbolic systems. Computer science is an empirical discipline, involving experimentation and observation. Newell and Simon argue that computer science should be viewed as an empirical inquiry, similar to other sciences, where phenomena are studied through experimentation. They emphasize that computer science is not just about building machines and programs for economic use, but also about discovering new phenomena and analyzing known ones. Newell and Simon's work highlights the importance of symbols and search in computer science. They developed the concept of physical symbol systems, which are systems that can process symbols and are essential for intelligent action. This hypothesis, known as the Physical Symbol System Hypothesis, suggests that any system capable of general intelligent action must be a physical symbol system. The paper also discusses the development of heuristic search as a key mechanism in problem-solving. Heuristic search involves using strategies to efficiently find solutions, which is crucial for intelligent systems. This hypothesis, the Heuristic Search Hypothesis, states that problem solutions are represented as symbol structures and that physical symbol systems solve problems through search processes. The paper emphasizes the empirical nature of computer science, using examples from artificial intelligence and cognitive psychology to illustrate how computer science is a field of empirical inquiry. It highlights the importance of experimentation and observation in understanding computer science phenomena, and the role of symbol systems and search in achieving intelligent behavior. The paper concludes that computer science is a scientific enterprise, with hypotheses that can be tested through empirical inquiry.The 1975 ACM Turing Award was jointly given to Allen Newell and Herbert A. Simon for their contributions to artificial intelligence, psychology of human cognition, and list processing. Their work over twenty years, including collaborations with J.C. Shaw and Carnegie-Mellon University colleagues, established artificial intelligence as a scientific field and advanced understanding of human problem-solving and cognitive processes. They are credited with inventing list processing and contributing to software technology and the concept of computers as symbolic systems. Computer science is an empirical discipline, involving experimentation and observation. Newell and Simon argue that computer science should be viewed as an empirical inquiry, similar to other sciences, where phenomena are studied through experimentation. They emphasize that computer science is not just about building machines and programs for economic use, but also about discovering new phenomena and analyzing known ones. Newell and Simon's work highlights the importance of symbols and search in computer science. They developed the concept of physical symbol systems, which are systems that can process symbols and are essential for intelligent action. This hypothesis, known as the Physical Symbol System Hypothesis, suggests that any system capable of general intelligent action must be a physical symbol system. The paper also discusses the development of heuristic search as a key mechanism in problem-solving. Heuristic search involves using strategies to efficiently find solutions, which is crucial for intelligent systems. This hypothesis, the Heuristic Search Hypothesis, states that problem solutions are represented as symbol structures and that physical symbol systems solve problems through search processes. The paper emphasizes the empirical nature of computer science, using examples from artificial intelligence and cognitive psychology to illustrate how computer science is a field of empirical inquiry. It highlights the importance of experimentation and observation in understanding computer science phenomena, and the role of symbol systems and search in achieving intelligent behavior. The paper concludes that computer science is a scientific enterprise, with hypotheses that can be tested through empirical inquiry.