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Knowledge and Developing New Information Technologies

Knowledge and Developing New Information Technologies

  • by Jacob Bensimon

One important dimension of human behavior is the capability to plan and engage in tactics such as learning a new activity or attempting to beat your personal best. It may be a less obvious dimension, but it’s just as important: the ability to save up knowledge over the years to be able to tackle a challenge, such as learning to play the piano, or navigating a new country.

The ability to retrieve the accumulated knowledge is increasingly important to many professions, such as medicine. But it’s also important in other fields. Anyone who wanted to launch a business or find a job can do so by accessing digital content.

There is a shift in the way scientists think about human behavior. People used to think of knowledge as “stuff,” stored in libraries or brain cells, providing insights about what happens in the present. Today, we are beginning to acknowledge that knowledge is not static. It accumulates over time and even decades.

How we use this knowledge is a critical component in developing new information technologies. These technologies enable us to develop new services and industries, create new knowledge and strategies, and enhance creativity.

At the same time, we are witnessing a gradual change in the way we use brain science. Brain sciences are largely concerned with how to translate knowledge. But this is rapidly becoming more difficult. A lot of knowledge is already in the cloud, but most of it is not accessible to neuroscientists.

One example is how to use cloud services to identify people with learning disabilities. We know that there are people with learning disabilities. We are just not yet able to identify them — and probably won’t be for decades.

Why is this so important? According to one study, learning disabilities hinder individuals from taking advantage of learning opportunities that may greatly improve their life chances. This is a natural resource that we may have to wait decades to develop.

The true value of learning is not in the particular techniques we can develop, but rather in how we use knowledge over time. We can’t easily access knowledge for some time, but it accumulates.

An important part of this process involves storing things in the cloud, and deciding on appropriate conditions for retrieving information. This is a task that is becoming increasingly complex and still evolving rapidly.

In the past, neuroscientists were viewed as specialists in particular tasks. But now it’s becoming more acceptable to study knowledge as well as cognitive and psychological processes. Learning to use knowledge is becoming the new frontier of neurobiology.

For example, when we talk about neural networks, we are talking about new organizations, methods, and processes. Understanding neural networks is relevant in many other disciplines as well, such as medicine, the computer industry, robotics, and psychology.

This new field is expanding into fields such as economics.

People tend to look at cognitive science and technology in terms of trends and developments. The recent challenge is to create knowledge that is relevant to current challenges in the neurobiology of cognition.

As neuroscientists develop new knowledge and tools, it is important to acknowledge that technology has also evolved. The changes are happening so quickly that we can’t make sure the opportunities are correctly identified, measured, and stored for future use.

Our goal is to establish new management and educational tools that encourage people to constantly revisit their knowledge — and that build this knowledge into better organizations and educational environments.

In this process, we will also need tools to manage knowledge that may have changed significantly over time, and we can start to do this today.

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