Making the World Work Better: Q&A with authors and editor discussion
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Making the World Work Better
Pioneering the Science of Info
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Questions for Kevin Maney
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Betsy
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Nov 03, 2011 12:54PM
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I knew early-IBM as well as anyone. I deeply researched its history up until 1956 for my biography of Thomas Watson Sr. I also knew IBM well as a reporter from about 1985 to the present. But I had a hole in my knowledge in the middle. What surprised me is how much invention happened in that hole. In the 1960s and 1970s, IBM came up with the relational database, DRAM, RISC, computer languages, the bar code system...and on and on. In fact, invention-wise, that period might have been IBM at its most profound.
IBM has achieved so much I had to keep reminding myself as I read "Making the World Work Better" that it was the story of one company and not necessarily a comprehensive history of computing. Did you ever find this frustrating? Was it a challenge to stay within scope?
The funny thing is -- it's not just about one company. The book is, in fact, about the broad evolution of computing over the past 100 years, and includes things like Intel's microprocessors and Bell Labs' invention of the transistor. But when you look at the broad history, IBM has contributed so much over every decade...it starts to look like it's all about IBM.
Kevin - to me this is the most amazing part. IBM seems to have their hands in so many different technologies, and opinions about technologies. For every bet that paid off, there must have been tons of flops. I think my favorite story is of Professor Wood (pg 104) and the eventual test-scoring machines. Though currently many teachers see standardized testing as a bane to the US Education System and a technology that holds us back instead of propelling us forward.
Did your research uncover any new ways we might see the science of information applied to the field of education? There seem to be many pressures on the new field of information -- not to collect the sum of the masses but instead now to create individualized reporting and make intelligent recommendations based on the 1 vs the many.
