Computer science is one of the most popular and fastest growing fields of study today. With technology rapidly advancing and integrating into nearly every industry, there is an increasing demand for skilled computer scientists and programmers.
But there remains an ongoing debate around how computer science should be classified academically. Is it a pure science, like physics or chemistry? Or is it an applied science, used to solve real-world problems?
In this comprehensive article, we’ll examine the arguments on both sides and look at the evidence to determine whether computer science qualifies as an applied science.
Defining Applied Sciences
Applied sciences refer to the practical application of scientific knowledge to solve real-world problems. Unlike pure sciences, which focus on understanding the fundamental principles and theories, applied sciences take this knowledge and use it to address specific issues in various fields.
This practicality sets applied sciences apart and makes them highly valuable in today’s society.
Practical application of scientific knowledge
In applied sciences, the emphasis is on taking scientific theories and putting them into practice. This involves using research and experimentation to develop innovative solutions that can be implemented in real-world scenarios.
For example, engineers apply scientific principles to design and build structures, while computer scientists use their knowledge to develop software and algorithms that solve complex problems.
One example of applied science in action is the field of medicine. Medical professionals use their understanding of biology, chemistry, and other scientific disciplines to diagnose and treat illnesses.
They apply this knowledge to develop new drugs, medical devices, and treatment methods that improve patient outcomes and save lives.
Using math and theory to solve real-world problems
Applied sciences also rely heavily on mathematical models and theoretical frameworks to solve practical problems. These models help scientists and engineers analyze data, make predictions, and optimize solutions.
By using math and theory, applied scientists can develop more efficient and effective solutions that address complex challenges.
Computer science, for instance, uses mathematical algorithms and computational theory to solve problems ranging from data analysis to artificial intelligence. These mathematical models enable computer scientists to develop algorithms that can process vast amounts of information and make accurate predictions.
This has led to significant advancements in fields such as machine learning and data analytics.
Examples include engineering, computer science, nursing
Several fields fall under the category of applied sciences. Engineering, for example, applies scientific principles to design and build structures, machinery, and systems. It encompasses various disciplines such as civil, mechanical, electrical, and aerospace engineering.
Engineers use their scientific knowledge to create practical solutions that meet specific needs and requirements.
Computer science is another example of an applied science. It combines mathematical theory, logic, and computational thinking to develop software and technology solutions. Computer scientists work on a wide range of applications, from developing operating systems and programming languages to creating algorithms for data analysis and artificial intelligence.
Nursing is yet another example of an applied science. Nurses apply their knowledge of biology, anatomy, and medical principles to provide direct patient care. They use evidence-based practices and scientific research to make informed decisions and deliver high-quality healthcare.
Key Characteristics of Computer Science
Based on mathematical theory and logic
Computer Science is a discipline that is deeply rooted in mathematical theory and logic. It involves the study of algorithms, data structures, and computational processes. By applying mathematical principles, computer scientists are able to analyze and solve complex problems efficiently.
Mathematics provides the foundation for understanding the fundamental concepts of computer science, such as computational complexity, cryptography, and machine learning.
Involves experimentation and testing hypotheses
Computer Science is not just about abstract theories and equations; it also involves experimentation and testing hypotheses. Computer scientists design and conduct experiments to validate their ideas and theories.
They use various tools and techniques to collect and analyze data, enabling them to make informed decisions and improve the efficiency and effectiveness of computer systems. This scientific approach allows computer scientists to push the boundaries of what is possible in the field.
Results in practical applications and technologies
Computer Science is not limited to theoretical concepts; it has a strong focus on practical applications and technologies. The field has given rise to groundbreaking innovations that have transformed various industries.
From artificial intelligence and machine learning to cybersecurity and data analytics, computer science has paved the way for practical solutions that have revolutionized our daily lives. These advancements have led to the development of new software, hardware, and systems that power our modern world.
Interdisciplinary field drawing from math, science, engineering
Computer Science is an interdisciplinary field that draws from mathematics, science, and engineering. It combines elements of these disciplines to solve complex problems and create innovative solutions.
For example, computer scientists often use principles from mathematics to analyze algorithms, apply scientific methods to conduct experiments, and utilize engineering principles to design and build computer systems.
This interdisciplinary approach allows for a holistic understanding of computer science and enables collaboration across different fields.
Practical Applications of Computer Science
Computer science is not just a theoretical field; it has numerous practical applications that impact our daily lives. From software engineering to cybersecurity, computer science plays a crucial role in shaping the modern world.
Software engineering is a practical application of computer science that focuses on the design, development, and maintenance of software systems. It involves the application of engineering principles to create efficient and reliable software solutions.
Software engineers use their knowledge of programming languages, algorithms, and data structures to develop innovative software products that meet the needs of users.
Computer programming is at the core of computer science. It involves writing instructions in programming languages to create computer programs that perform specific tasks. Programmers use their problem-solving skills and logical thinking to design algorithms and implement them in code.
The ability to code is essential for anyone pursuing a career in computer science.
Developing algorithms is a fundamental aspect of computer science. Algorithms are step-by-step procedures or formulas designed to solve specific problems. They are used in various fields, such as data analysis, optimization, and cryptography.
Computer scientists develop and refine algorithms to improve efficiency and solve complex problems.
Artificial Intelligence and Machine Learning
Artificial intelligence (AI) and machine learning (ML) are rapidly growing fields within computer science. AI focuses on creating intelligent machines capable of mimicking human cognitive functions, while ML involves training algorithms to learn from data and make predictions or decisions.
These technologies have practical applications in areas such as autonomous vehicles, natural language processing, and medical diagnosis.
Computer graphics involve creating and manipulating visual content using computers. This field encompasses areas like 3D modeling, animation, and virtual reality. Computer graphics have applications in various industries, including entertainment, advertising, and architecture.
They enable the creation of realistic simulations and immersive experiences.
Database systems are essential for managing and organizing large amounts of data. They provide efficient storage and retrieval mechanisms for structured and unstructured data. Database administrators design and maintain database systems to ensure data integrity and availability.
These systems are used in various domains, including finance, healthcare, and e-commerce.
Computer networking involves the design and implementation of communication systems that allow computers to exchange data. Networking technologies enable the creation of local area networks (LANs), wide area networks (WANs), and the internet.
Network engineers configure and maintain network infrastructure to ensure efficient and secure data transfer.
Cybersecurity is a critical field within computer science that focuses on protecting computer systems and networks from unauthorized access, attacks, and data breaches. Cybersecurity professionals use their expertise to develop security measures, detect vulnerabilities, and respond to incidents.
With the increasing threat of cybercrime, cybersecurity has become a vital aspect of our digital lives.
Counterarguments Against Computer Science as Applied Science
Pure sciences seek knowledge for its own sake
One of the main counterarguments against considering computer science as an applied science is that pure sciences are typically driven by the pursuit of knowledge for its own sake. Fields like physics, chemistry, and biology focus on understanding the fundamental principles of the natural world.
In contrast, computer science is seen as more practical and goal-oriented, focusing on the development of software, algorithms, and technologies to solve specific problems.
Applied sciences focused on practical use of knowledge
Applied sciences, on the other hand, are characterized by their emphasis on the practical application of knowledge to real-world problems. Engineering disciplines such as mechanical, civil, and electrical engineering are typically considered as applied sciences because they involve the design, construction, and implementation of tangible products and systems.
Computer science, while often seen as applied due to its practical nature, also includes a significant amount of theoretical research.
Computer science includes pure theoretical research
Computer science encompasses both theoretical and practical aspects. While it is true that computer science is heavily involved in developing practical solutions, it also includes pure theoretical research.
Areas like algorithms, complexity theory, and cryptography delve into abstract concepts and mathematical foundations. Computer scientists often work on theoretical models and proofs that may not have immediate practical applications but contribute to the advancement of the field as a whole.
Much of the field is closer to pure math than engineering
Another argument against considering computer science as an applied science is the fact that much of the field is closer to pure mathematics than traditional engineering disciplines. Computer scientists often rely on mathematical principles and formal logic to design algorithms, analyze computational complexity, and solve complex problems.
The focus on abstract mathematical concepts sets computer science apart from applied sciences that are more directly associated with physical systems and tangible products.
While computer science does have practical applications and is often used to solve real-world problems, it is important to recognize that it also encompasses pure theoretical research and shares similarities with pure mathematics.
The interdisciplinary nature of computer science allows for contributions from both applied and pure sciences, making it a unique and dynamic field.
Examining the Evidence
CS incorporates pure science, math, engineering
Computer Science (CS) is often considered an applied science due to its strong foundation in pure science, mathematics, and engineering principles. CS researchers and practitioners draw upon a wide range of scientific knowledge to develop innovative solutions to complex problems.
From algorithm design to data analysis, CS integrates theories from various disciplines to create practical applications.
Knowledge for knowledge’s sake vs solving problems
One argument against considering CS as an applied science is the emphasis on knowledge for knowledge’s sake. Critics argue that CS research is often driven by curiosity rather than practical problem-solving.
While it is true that CS researchers explore theoretical concepts, their ultimate goal is to apply these ideas to real-world challenges. By studying the fundamental aspects of computer systems, CS professionals gain insights that enable them to develop practical solutions.
Most CS research has real-world goals and applications
The majority of CS research is guided by real-world goals and has tangible applications. Researchers in areas such as artificial intelligence, cybersecurity, and data science work towards solving pressing societal issues.
For example, researchers develop algorithms to improve healthcare diagnostics, create encryption techniques to protect sensitive information, and analyze big data to uncover patterns and trends. These applications demonstrate the practical nature of CS as an applied science.
CS degree paths focus on practical skills like programming
CS degree programs are designed to equip students with practical skills that can be applied in the real world. While theoretical concepts are covered, the primary focus is on developing expertise in programming languages, software development methodologies, and system design.
Students gain hands-on experience through projects and internships, preparing them for the practical challenges they will face in their careers. This practical approach further supports the notion that CS is indeed an applied science.
Demand for CS driven by industry need for solutions
The high demand for computer science professionals in various industries is a testament to the applied nature of the field. Companies across sectors rely on CS experts to develop innovative software solutions, design efficient algorithms, and analyze complex data.
The ever-evolving technological landscape requires constant problem-solving and practical applications, which highlight the applied nature of CS. This demand-driven industry growth further solidifies the argument that computer science is an applied science.
In summary, while computer science contains elements of pure theoretical science, the evidence strongly suggests it should be classified as an applied science. The primary goal of most computer science research is to create new technologies and find solutions to real-world problems in areas like business, medicine, and communication.
While driven by math and theory, computer science directly results in practical innovations that integrate into people’s lives. The criteria for an applied science are met by computer science’s focus on experimentation, developing algorithms and protocols, programming languages, and technologies that aid human processes and systems.