Computer science is a rapidly evolving discipline, with new paradigms constantly emerging that emphasize the balance between performance and correctness. Analyze the unique way computer science has developed compared to theories of scientific revolutions and explore the impact of the latest technologies, such as artificial intelligence and quantum computing, on its progress.

Introduction

Computer science is a discipline that, despite its short history, has experienced very rapid change. Computer science has made rapid advances in many areas in a short period of time, and the pace of progress continues today. For example, the Intel Xeon 3.6 GHz of 2005 is 6505 times faster than the VAX-11/780 of 1978, and more recently, the clock speed of CPUs has reached its limits, leading to a paradigm shift to multi-core processors. These and other technologies are constantly changing computer science, and their impact on modern life is profound.
In the 1940s, computers were huge machines that could fill a room, but now, thanks to the proliferation of smartphones, we are in the era of “one person one computer,” which allows us to do many things. Unlike other scientific disciplines, computer science has evolved through performance improvements and paradigm shifts, a phenomenon that is noteworthy from the philosophical perspective of scientific revolution. Let’s take a look at how computer science has developed and where it is headed, centered on the theory of scientific revolutions.

Thomas Kuhn and Karl Popper’s arguments about scientific revolutions

Scientific revolutions have a profound impact not only on the discipline but also on society as a whole. Thomas Kuhn describes scientific revolutions as “paradigm shifts,” where a paradigm is a scientific achievement that raises important questions for researchers. According to Kuhn, when a paradigm is working effectively, existing theories are expanded and clarified, and scientists are able to conduct normal science. However, when the existing paradigm fails to adequately explain natural phenomena, a new paradigm is proposed and a scientific revolution occurs.
Karl Popper argued that for science to progress, it should not be through the verification of hypotheses but through their disprovals. He believed that scientific discoveries are not definitive and that no hypothesis can be 100% certain. Popper argued that scientific truth should be sought through constant doubt and criticism, and that this process is the essence of scientific progress. This aspect of Popper’s philosophy is known as falsificationism.

How computer science evolved from a scientific revolution perspective

Computer science is a discipline that evolves primarily with the goal of improving performance. New methodologies are constantly being proposed to maximize performance at different layers: hardware devices, operating systems, and application software. In this process, it’s not only performance that matters, but also correctness. In computer science, correctness is an important criterion for determining whether a system works correctly, and there is a philosophy that no matter how high the performance, it should never deviate from correctness.
Unlike other sciences, new paradigms are proposed and validated very quickly in computer science. For example, in CPU instruction execution, the sequential execution method ensured correctness, but performance was low, so new methodologies such as pipelined execution and non-sequential execution were proposed. These methodologies aim to improve performance, but they must also come with solutions to ensure correctness in the process.

Modern advances in computer science: the rise of artificial intelligence and quantum computing

Another important development in modern computer science is the rise of artificial intelligence (AI) and machine learning (ML). In recent years, AI has gone from simple data processing to enabling complex tasks such as autonomous driving, natural language processing, and image recognition. It’s not only improving the performance of computer science, but it’s also fundamentally changing the way we interact with machines. Advances in deep learning, in particular, are providing the ability to rapidly process large amounts of data and identify complex patterns within it, solving problems that are difficult for humans to solve.
Quantum computing also offers a new paradigm that goes beyond traditional binary logic-based computing. Quantum computers have the potential to rapidly solve complex problems that classical computers cannot, which is expected to revolutionize fields as diverse as cryptography, chemical simulation, and optimization problems. These technologies are currently driving the advancement of computer science and are seen as a major paradigm shift in the future.

Differentiating computer science from scientific revolutions

While there are some similarities to the existing theories of scientific revolutions, there are also differences. In Kuhn’s scientific revolutions, paradigm shifts occur mainly when existing theories reveal their limitations and a new theory replaces them. In computer science, on the other hand, the existing paradigm is often maintained, improving performance or pointing to new directions. Because computer science does not build on past accomplishments, but rather rapidly emerges new methodologies as needed, it is difficult to explain its progress using the traditional framework of scientific revolutions.
The advent of mobile environments and the rise of new paradigms such as artificial intelligence show that computer science is a discipline that develops in many directions simultaneously. This is why computer science needs a more flexible theory of scientific revolutions.

Conclusion

Computer science has evolved in such a short period of time and undergone such rapid changes that the traditional framework of scientific revolutions cannot fully explain its development. Computer science, with its constant balancing act between performance improvements, correctness, and the introduction of new paradigms, can be seen as one of the prime examples of a scientific revolution theory, and the possibilities for further development are endless.