“Reverse-Engineering the Brain” is one of the modern world’s Grand Challenges for Engineering. Artificial intelligence/machine learning is revolutionizing the way we think of computers and showcasing the incredible impact computers can have on society. Discovering how to mirror a human brain in all its capabilities could have tremendous implications in so many fields of study, ranging from medicine to transportation.
As artificial intelligence continues to grow in popularity, more people and institutions are realizing the potential of reverse-engineering the brain. Just as aeronautical engineers studied flying birds when designing aircraft, artificial intelligence is best advanced by studying what it is modeled off of--the human brain. There has been increased emphasis on the intersection of the fields of robotics and cognition, with researchers studying mouse and monkey brains to strengthen their understanding of the brain’s inner workings, and then attempting to replicate those ideas through robotics. The human aspect of speech has also been simulated through AI algorithms that are used for speech recognition (natural language processing), which has likely been experienced by many people through smart assistants. Artificial limbs are becoming an ambitious project too.
The major technical obstacle engineers are facing is that in order to realize the brain’s potential and how it can be replicated in machines, we need more technology to understand the brain in the first place, which could involve procedures seen as unethical by some. In addition, since cognitive sciences and engineering have not always been two intertwined fields, bringing them closer together can also be a challenge, and economically, the money required to both understand brain function and then translate that to technology would be a very large investment. However, the future research that goes into solving this challenge will certainly have the ability to transform society.
Works Cited
“Grand Challenges - Reverse-Engineer the Brain.” Engineeringchallenges.org,
http://www.engineeringchallenges.org/challenges/9109.aspx. Accessed 16 May 2023.
Schierwagen, A. On reverse engineering in the cognitive and brain sciences. Nat Comput 11,
141–150 (2012). https://doi.org/10.1007/s11047-012-9306-0
Spice, Byron. “Carnegie Mellon Joins IARPA Project To Reverse-Engineer Brain Algorithms.”
Carnegie Mellon University, 3 February 2016,
https://www.cmu.edu/news/stories/archives/2016/february/computers-learn-like-humans.
html. Accessed 16 May 2023.
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