The U.S. government is pouring billions of dollars into understanding genetics and the human brain — and how to manipulate those systems.
The future of evolution is now in our hands. Or rather, the godlike power to alter biology rests in a few scientists’ hands, and we’re all going to pay for it, one way or another. The U.S. government is pouring billions of dollars into understanding genetics and the human brain, and most consequentially, how to manipulate those systems.
Last week, the National Institutes of Health (NIH) launched its “BRAIN 2.0” initiative (Brain Research through Advancing Innovative Neurotechnology), ramping up an existing program started eight years ago. Comparable to the Human Genome Project in scope and scale, BRAIN 2.0 grants $600 million to fully map our 86 billion neurons and their uncounted connections. The project is expected to reach a grand total cost of $5 billion by 2026.
In theory, once scientists have created this detailed brain atlas in silico, they can directly alter neural function using digital devices. The director of the BRAIN Initiative, John Ngai, exhibits a troubling fixation on this method.
In a recent interview with Stat News, Ngai noted two concrete results of his current neuro-mapping efforts. One is an advanced brain-computer interface — implanted last year at the University of California, San Francisco — that allows for astounding thought-to-text communication. The other is a major breakthrough in deep brain stimulation at Baylor University, where electrodes are implanted to alter mood and behavior, relieving depression and obsessive-compulsive disorder.
Ngai’s cyborg obsession is shared by his close government partner, the Defense Advanced Research Projects Agency (DARPA), where “man-computer symbiosis” has been a longstanding paradigm. The defense agency’s involvement in the BRAIN Initiative is open and well documented. However, beyond the NIH’s declared mission to heal, our top military minds also have a deep interest in human enhancement.
“DARPA has been a pioneer in brain-machine interface technology since the 1970s, but we began investing heavily in the...
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