Collection Introduction

The American Society for Cybernetics is honored and proud to be able to present to the public The Collected Works of Warren S. McCulloch (second edition).

McCulloch was a seminal figure in psychology, neuroscience, and cybernetics. His work with Walter Pitts on neurons paved the way for much of the smart technology that powers our present twenty-first-century world. Despite McCulloch’s importance to the history of science and thought, much of his work has not received the scholarly attention it deserves. When Rook McCulloch (Warren’s wife) gathered his works together and commissioned an immense four volume set (the first edition), she had no idea that her chosen publisher was in the throes of financial difficulties. When Intersystems Publications failed, a mere 300 copies of the collected works had been printed. For more than 30 years, that is where things stood—important work lost to the much of the world due to a bankrupt publisher.

The McCulloch family reached out to the American Society for Cybernetics in 2018 in a “hail-Mary” attempt to rescue this critical work. At the ASC, we worked tirelessly to gather the requisite permissions, scan and re-typeset the papers, and then to develop a means of placing the works in context. We hope to continue with a third edition to include papers from those whose work has been influenced by McCulloch’s work and ideas. Rook McCulloch had a similar thought when she edited the first edition—it contains more than two dozen pieces by scientists whose work McCulloch influenced.

Warren McCulloch was an American neurophysiologist and cybernetician who played a crucial role in the development of the field of artificial intelligence. His work helped to lay the foundation for modern computational neuroscience and cognitive science, and his pioneering ideas about the brain and its computational capabilities have continued to influence research in these fields to this day.

One of the most important contributions made by McCulloch was his work on the mathematical modeling of neural networks. He recognized that the brain was not simply a collection of isolated neurons, but rather a complex network of interconnected cells that work together to process information. To better understand how these networks functioned, McCulloch developed mathematical models that could simulate the behavior of these networks in response to various stimuli.

Context dependence and self-awareness of context were important concepts in his work, particularly in his ideas about the functioning of the brain and its relationship to the environment. McCulloch believed that the brain operates in a context-dependent manner, meaning that its function is influenced by the specific context in which it operates. This context can include a variety of factors, such as sensory inputs, motor outputs, and internal physiological states. According to McCulloch, the brain is constantly adapting to the current context in order to optimize its processing and behavior.

McCulloch's ideas about the brain and its function were ahead of their time, and his work has continued to influence research in these fields to this day. For example, his emphasis on the importance of context in the brain's function has been borne out by modern research in cognitive science and neuroscience. Studies have shown that the brain's processing and behavior are heavily influenced by the context in which it operates, including sensory inputs, motor outputs, and internal physiological states. This context-dependent function is now recognized as a key aspect of the brain's operation, and it has been incorporated into modern models of neural processing and behavior.

One of McCulloch's key insights was the idea that the brain is able to generate a sense of self-awareness of context. This means that the brain is not only able to adapt to the current context, but it is also able to recognize and monitor its own internal state in relation to the external environment. This self-awareness allows the brain to make more accurate predictions about future events, and to adjust its behavior accordingly.

McCulloch's work helped to pave the way for the development of artificial intelligence, by providing a theoretical framework for understanding how machines could be designed to mimic the behavior of the brain. His work inspired many researchers to develop new algorithms and techniques for machine learning, which have now become the foundation for many of the most powerful AI applications in use today.

McCulloch was also a pioneer in the field of cybernetics, which is the study of control and communication in living and non-living systems. He recognized that many of the same principles that apply to the brain and its networks could also be applied to other complex systems, such as machines and organizations. One of the key insights of cybernetics is that complex systems can be controlled and regulated by feedback mechanisms, which provide information about the system's current state and allow for adjustments to be made to maintain stability and optimize performance. McCulloch's work on cybernetics helped to inspire new approaches to designing and managing complex systems, including automated control systems and artificial intelligence applications. For example. reinforcement learning is used in a variety of applications, including game playing, robotics, and self-driving cars, and it relies on principles of feedback and control that were first explored by McCulloch in his work on cybernetics.

Yet, perhaps the most important legacy of McCulloch's work is his emphasis on the importance of interdisciplinary collaboration in scientific research. He recognized that the most interesting and important problems often require insights and expertise from multiple fields, and he actively sought out collaborations with researchers in diverse fields such as mathematics, physics, and philosophy.

This interdisciplinary approach has become increasingly important in modern science, as researchers are faced with increasingly complex and interconnected problems that require a broad range of knowledge and skills to address. McCulloch's work provides a model for how researchers can work together across disciplinary boundaries to tackle these challenges and make new discoveries.

McCulloch's work on neural networks provided a theoretical foundation for machine learning algorithms that are now used in a wide range of applications, including natural language processing. McCulloch's work on cybernetics and feedback mechanisms has influenced the development of reinforcement learning algorithms, which use feedback signals to adjust a model's behavior over time.

It is important to remember that McCulloch's ideas about the brain and its function were developed during a very different era, and it is not clear how well they translate to the modern era of AI and machine learning. Some of his ideas may be outdated or overly simplistic given the rapid pace of technological development in recent years. His emphasis on the importance of the body and sensory experience for intelligence has been difficult to translate into the development of AI systems. McCulloch's work focused primarily on the theoretical underpinnings of the brain and its function, rather than on the practical application of these ideas to real-world problems. As a result, his work has been criticized for being overly abstract and disconnected from practical applications. While AI systems have made significant strides in recent years, they still struggle to replicate the complex sensory-motor coordination that is essential for many everyday human activities.

Despite these limitations, McCulloch's legacy remains significant. His pioneering ideas about neural networks and cybernetics have inspired generations of researchers, and his emphasis on interdisciplinary collaboration continues to shape the way we approach scientific research today. Interdisciplinary collaboration has become increasingly important in the era of big data and complex systems, where researchers from a variety of fields must work together to address complex problems. McCulloch's work on neural networks and cybernetics laid the groundwork for the development of modern AI applications, and his insights into the context-dependent processing of the brain have influenced recent developments in deep learning and other machine learning algorithms. As AI and other emerging technologies continue to transform the world, it is critical that researchers remain grounded in the values of collaboration, curiosity, and ethical responsibility that underlie McCulloch's work.

McCulloch was instrumental in laying the foundation for modern computational neuroscience, cognitive science, and artificial intelligence. His legacy serves as a reminder of the power of scientific curiosity and the importance of working together to solve the most challenging problems facing humanity.

Warren S. McCulloch was an intellectual giant. We are grateful for the opportunity to help others appreciate his contributions. The McCulloch family and the American Society for Cybernetics are proud to bring back to the world the Collected Works of Warren McCulloch.