I confess that my core concept of the post-information age comes from Blade Runner. In that movie, there were large bricks-and-mortar corporations that controlled much of the world's industry (constructing dangerous androids, conducting off-world mining operations, etc.), and there were solo contractors who worked in the back rooms of antique stores and noodle shops and who made the android skin or nano-bots or psionic circuits and what-not for the replicants and the off-world mining operations, etc. The idea is that the large companies dealt with the macro-economics but that the little guys had the specialized expertise that was used by the large corporations.
This is how I think of the post-information age. Big corporations like Microsoft and Google will dominate the information world, but highly trained free-lancers will do some of their most specialized work. In the biomedical world, large academic universities and federal and private funding agencies will spearhead huge initiatives (hundreds of millions of dollars), but the most fastidious work will be done by free-lancers.
Why is this? Why won't specialized work be done in-house? When large corporations hire, they are looking for people with a generalized skill-set that is appropriate for the activities of a department. So a Department of Surgery hires lots of surgeons. They may even hire an information officer or two. But they will never be in a position to hire (and keep) someone with all of the computational skills needed for a complex project that collects clinical data and integrates it with biomedical data from heterogeneous sources. It just makes sense to identify one of the few people in the world with the needed skills and have that person help out, when the need arises, for a negotiated fee.
In the post-information age, everyone has access to computers and software and lots of people have access to information. In the case of biomedicine, this information would be public biological databases, and de-identified medical databases, and associated ontologies, nomenclatures and classifications that help integrate all the data. The free-lancers would be hired to add value to or make sense of the data or write software to handle some specific purpose, that sort of thing. In the next few blogs I'll provide some examples.
- Copyright (C) 2008 Jules J. Berman
key words: biomedical informatics, medical informatics, common disease, orphan disease, orphan drugs, genetics of disease, disease genetics, rules of disease biology, rare disease, pathology
In June, 2014, my book, entitled Rare Diseases and Orphan Drugs: Keys to Understanding and Treating the Common Diseases was published by Elsevier. The book builds the argument that our best chance of curing the common diseases will come from studying and curing the rare diseases.
I urge you to read more about my book. There's a generous preview of the book at the Google Books site.
