What Computers Still Need to Learn: Theories of Information and Being Bought to be Brought the Right Information

What Computers Still Need to Learn: Theories of Information and Being Bought to be Brought the Right Information

From The Future of Work – April 2006

Last week I had a discussion about information with Dr. Carsten Sorensen of the London School of Economics. We ended up talking around an idea I floated several years ago as an analyst at the Giga Information Group (acquired by Forrester Research): namely this: as yet, the computer industry has failed to come up with a theory of work around information. In fact, the computer industry has yet come up with a theory of information so that computing devices understand the data which resides on them.

Computers understand data as a representation of bits they can move. They can move them to printers, to disk drives, to monitor, but they have very little knowledge about what they know. As we have moved from characters to highly graphical interfaces, computers know more about format, but they still do not understand the underlying processes, the meaning of unstructured content or the relationships between data not make explicit in relational database table.

For the industry to make its next great leap, we need to take the technology that is so focused on understanding us so websites can customize advertising, and apply that to all of the information we have. Imagine hundreds of personal profiles (all secured privately) converging. Imagine computers that know your projects, your information, your relationships, your appointments, your communication channels, how you use applications, your location, etc. and bringing those items together into a Venn diagram that specifies what you need to know in the context of your work. This is the way ad hoc processes will eventually need to be implemented.

Currently, people provide the context. We decide what we need to know, how we need to arrange our screens, what applications we need, what data will information our intuition, etc. Computers can learn that, and that will make them helpful assistants rather than tools. Shovels and drill presses are helpful tools, but they know nothing about digging or about drilling until people put them to work. The promise of computing is that it will be able to anticipate our needs, act as our proxy—but we have yet to invest and deliver in systems that are capable of understanding our world. This may sound like artificial intelligence, and the underlying technology that makes this possible does come from that discipline. But this is not science fiction, it is just a choice of investment priorities – and the knowledge by information workers that they should demand this, and the bravery of computer companies to overcome the issue of privacy (both through technology, education and investment in trust capital) that will give people a feeling of safety when they do eventually ship this kind of technology. I am very happy when Amazon makes a good recommendation (which is rare, but it does make me happy when it happens) but Amazon knows very little about me. If Amazon knew my current reading, the contents of my library and my current projects, it could make much better recommendations, and perhaps save me a lot of time searching for books to support my research. I’m willing to give to get.

In a conversation with a security expert recently, I was informed that our personal information is worth about as much as a T-shirt. I’m willing to wear a lot of branded T-shirts if my computer starts telling me what I want to know when I want to know it. I guess I’m as easily bought as the next guy.

Daniel W. Rasmus

Daniel W. Rasmus, Founder and Principal Analyst of Serious Insights, is an internationally recognized speaker on the future of work and education. He is the author of several books, including Listening to the Future and Management by Design.

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