James Mark Baldwin was at the height of his fame in 1910, but a visit to the brothel changed all that.
Though he managed to convince a U.S. court that he was only tagging along with a “”friend,”” he lost his position as the leader of an academic association, was stripped of his professorship
at John Hopkins University and removed as the organizer of a prestigious research conference. These were the days when a sex scandal led not to a sleazy sort of celebrity but a flight from everyone you’ve known and loved. In this case, Baldwin fled to Paris, and most of his theories on evolutionary biology went with him. That was really our loss, because his work did more than contribute to our knowledge of the way animals change over time. Taken a step further, I think they introduce a way of thinking about technology products and may give us some clues into how convergence will occur in hardware.
Baldwin’s work is slowly being rediscovered now, thanks to authors like Daniel Dennet, who wrote Darwin’s Dangerous Idea. The so-called Baldwin Effect refers to the idea that individual learning tends to enhance evolutionary learning at the species level. In other words, changes in our behavior as a result of learning can cause changes in our genetic makeup over time. Even before his fall from grace, Baldwin had his detractors, who saw the Baldwin Effect as too close to the theories of Jean-Baptiste Lamarck. The most common example of Lamarckian thinking is the notion that giraffes’ necks grew because they kept trying to reach food that was high above them in trees.
This notion has generally been discredited in the North American biology community, but it has many echoes in the way hardware companies design next-generation devices. Most mobile computing innovations, for example, are predicated upon the hardware companies’ idea of how enterprise workers behave on the road. In the beginning, everyone assumed that they all wanted to recreate their desktop experience in a small form factor. Laptops — with a flat screen that folds into the keyboard — are almost like the opposite Lamarkian solution to the giraffe food-gathering problem: instead of expanding like a giraffe’s neck, the laptop compacted the PC.
The Baldwin Effect works on a more complex level. In his book, Dennet uses lactose tolerance (the ability to digest milk) as an example of the effect in action. In pre-argicultural societies, infant mammals lost the enzyme that allowed them to drink their mother’s milk shortly after they had been weaned off it. Once human beings started the practice of keeping animals for farming (animal husbrandry), milk became a food source and over time, most people developed this enzyme again.
According to Paul Thompson, a professor on ethics and biology at the University of Toronto who recently gave a lecture on the Baldwin Effect, lactose tolerance doesn’t do justice to the idea. This was a case where enzymes were simply moved around, he says. Real evolution changes our genetic makeup in brand-new ways.
Similarly, hardware convergence is at a stage right now where we’re simply shifting things around. We are moving between cell phones, personal digital assistants, pagers and back to old dinosaurs like PCs and laptops. The computing experience hasn’t changed much in and of itself. That won’t happen until we see a more significant shift in the way people behave with technology — when it becomes more than a matter of merely carrying data around. Hamilton, Ont.-based inventor Steve Mann has suggested in his book Cyborg that wearable computers are the natural next step, but this seems too Lamarckian to me.
The keys to convergence may lie not in the way people move with devices but in the sort of data they process. We are already seeing cell phones, for example, experiment with better ways to display spreadsheets and sales information. If more advanced forms of audio and visual data come close to surpassing text on the Internet, it may prove more instrumental in hardware design than mere mobility.
There is obviously a limit to how far you can compare human evolution with that of technology devices, but some analogies can be made. The data could be seen as the genetic code of the device. If Baldwin was right, the way we learn can influence how those genes are treated within the system. The major difference here is that human evolution is governed by nature — some would say God. In IT, we’re the gods. There’s the dangerous idea.
