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The first article is the best example of the problem. That technology has absolutely 0 to do with breaking the mind machine interface. They're effectively looking to measure the brain's output in response to various stimuli and create a correlationary mapping. This, for instance, is the exact same science used in lie detector machines. The only difference is you're directly measuring brain activity as opposed to pulse, temperature, respiration, etc.
The big issue is causation vs correlation. With correlations you can create quite a large number of predictive tools or useful interfaces. But without causation you'll perpetually be an observer and not a 'player.'. Take for instance depression. What causes depression? It's a trick question since the real answer is we have absolutely no clue. If you thought the answer had to do with serotonin, you'd be incorrect. What we do know is that there is a correlation between SSRIs and positive changes in regards to depression, but we have no clue what or why this is. It may not even have anything to do with seratonin but instead be another change with the brain and overall physiology that the SSRIs trigger. This is the difference between causation and correlation. And causation is an area where we are still literally at 0 in terms of knowledge as it relates to the brain.
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[–] ideasware [S] ago
http://futurism.com/us-militay-to-create-chip-that-translates-human-brain-activity-to-binary-code/
https://www.youtube.com/watch?v=TcX_7SVI_hA
http://futurism.com/new-algorithm-may-someday-enable-scientists-to-regrow-limbs-and-replace-damaged-organs/
http://venturebeat.com/2016/01/18/netflixs-reed-hastings-says-battle-to-rule-earth-will-be-fought-between-ai-machines-and-genetically-modified-humans/
[–] rwbj 0 points 2 points 2 points (+2|-0) ago
The first article is the best example of the problem. That technology has absolutely 0 to do with breaking the mind machine interface. They're effectively looking to measure the brain's output in response to various stimuli and create a correlationary mapping. This, for instance, is the exact same science used in lie detector machines. The only difference is you're directly measuring brain activity as opposed to pulse, temperature, respiration, etc.
The big issue is causation vs correlation. With correlations you can create quite a large number of predictive tools or useful interfaces. But without causation you'll perpetually be an observer and not a 'player.'. Take for instance depression. What causes depression? It's a trick question since the real answer is we have absolutely no clue. If you thought the answer had to do with serotonin, you'd be incorrect. What we do know is that there is a correlation between SSRIs and positive changes in regards to depression, but we have no clue what or why this is. It may not even have anything to do with seratonin but instead be another change with the brain and overall physiology that the SSRIs trigger. This is the difference between causation and correlation. And causation is an area where we are still literally at 0 in terms of knowledge as it relates to the brain.