From AI to IA
Engelbart founded the precursor to the Augmentation Research Center at Stanford the same year that mathematician John McCarthy established the Stanford Artificial Intelligence Laboratory. While McCarthy began the long climb toward artificial intelligence (he's the man who actually coined the term), Engelbart sought to use computers and computer networks to improve human productivity and expand access to information, a process known as intelligence augmentation (IA) [sources: Caruso; Markoff; Markoff].
Science fiction authors have long explored lowering the barriers between human and machine in examples ranging from plugs that "jack" directly into virtual worlds of data, to "cyberbrains" -- surgically implanted computer cores linked to the worldwide network of information. But we need not go so far to imagine the ways that networked computers can change our lives. Search engines, especially Google, already provide instant access to global information (however dubious its source). Smartphones let users mine advice and opinions from the online community on the fly and will soon provide augmented reality.
All of this nibbles somewhat at the edges of the full potential of IA to, as Engelbart put it, "raise our collective IQ" and create "high-performance organizations." The problem, according to Engelbart and his colleagues, is that we lack a true study of the coevolution of people, computers and networks [source: Caruso].
Even as the Internet has evolved to insinuate itself into seemingly every aspect of our daily lives, it has failed to live up to Engelbart's vision of coevolution, of a system in which people could work together in a shared information space that enabled them to improve their work, as well as the process of improvement itself. Groupware -- group collaboration improved through software -- which Engelbart is credited with inventing, represents only the first faltering step in this direction [source: Caruso].
Through crowdsourcing, we begin to see programs that unite human capacities to recognize patterns or solve problems: FoldIt uses a rules-based game that lets visitors help solve protein folding problems; EteRNA lets users design synthetic RNA with potential applications in biology and nanotechnology; and Galaxy Zoo relies on users to classify a million-plus galaxies found by telescopes such as the Sloan Digital Sky Survey. Yet we still have not achieved Engelbart's vision, which he now pursues with his daughter through his nonprofit research organization, the Doug Engelbart Institute [sources: Caruso; DEI].
He'll have a tough row to hoe. Consortiums of businesses, especially ones dependent upon sharing trade secrets, tend to collapse under their own self-interest -- even when sharing would be to their mutual benefit. Still, if there's one thing the Internet Age has taught us, it's that you can't keep a powerful idea down [source: Caruso].
One of the initial ways he envisioned this process involved a coevolution between organizations and their tools that occurred on three levels, which he termed "A, B and C." "A" refers to the work a company does; "B" encompasses efforts to improve how A gets done, and "C" entails improving on B.
Engelbart believed this final level, C, which does not involve trade secrets per se, would be sharable among organizations and improve productivity across the board, but industry remains lukewarm on the idea [sources: Caruso; DEI].