Cognition

The introduction to Cognitive Science class, Cognition, was one of my favorite classes at Hopkins so far. Not only did it delve into topics such as phonetics and speech perception but also consciousness and artificial intelligence. No way could I expand on every topic in one blog post but I will attempt to share some of my favorites.

Speech Perception: I learned both in my Developmental Psychology class and Cognition that babies have this amazing ability to distinguish the tiniest difference between sounds. We lose this ability over time because, depending on the language you're exposed to, there are only a certain number of sounds you're learning and your brain becomes fine tuned at hearing those particular sounds and no longer distinguishes sounds seem similar. This ability gives evidence to what Noam Chomsky describes as Universal Grammar, or the idea that language is innate, "hard-wired" into the brain.

Visual Perception, LGN and Ganglion Cells: LGN and Ganglion cells are a portion of the visual system dedicated to detecting changes in luminance edges in a visual scene. This change in luminance helps you distinguish objects from each other as well as perceive depth. Ganglion cells have specific orientations for light coming into the eye based on the orientations of the stimuli themselves. These receptors are defined by on/off centers and on/off surrounds. Depending on the stimulus coming from the light entering your eye, these cells fire at a certain rate. The combined rate from all your ganglion, LGN and other luminance detecting cells create a visual scene. Every time your eyes move they are receiving a completely different stimuli that your visual system has to organize to create a visual scene. The processing power of the visual system, just one function of the brain, is astounding.

Artificial Intelligence: I learned there are two types of artificial intelligence, weak and strong, defined by John Searle and his Chinese Room experiment and others like Hofstadter. Weak AI is designed to compliment something a human can already do. It is only one or more functions that a human brain can perform. For example, a human can do math so a calculator would be considered weak AI. Strong AI is the idea that artificial intelligence is matching the functions that a human brain can perform, like consciousness. In the Chinese Room experiment Searle argued that AI doesn't have the ability to have beliefs, desires and awareness and therefore can't reach the distinction of strong AI. An example that could counter a lot of people's opinions of this is Watson, the machine that beat all the previous winner in Jeopardy!. The argument is that even though Watson had a huge data set of information and the ability to come up with answers to questions, it didn't actually know that it had won Jeopardy!, something that a human could easily point out, and therefore it's not designated as strong AI.

These are just a few general explanations to some of the topics from Cognition. There's much more to come, especially on consciousness and free will.



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