Geeking Out-Deep Learning

http://www.sciencemag.org/…/ai-detectives-are-cracking-open…

Geeking out. There are many overlaps with how we teach the decision making processes to interpreting students. How many times has someone told you it depends? This is typically the standard answer because there are so many variables to the dynamic environments in which we work. Interpreting students and interpreters, in turn, use DC-S, ethical decision-making steps, language prompts, etc. as a ‘rule set’ to make accurate decisions.

I’m fascinated with how this applies to the interpreting field or academia in general. I like how by using this you can latch human decision making with a network, with more deep networks. Anchoring experiences with an already structured system become the proxy for what the student is thinking and the skills they are developing. The idea of students doing Think Aloud Processes (TAP) which allows students to examine their own processes against the data and deep networks of the scenario so they can begin to connect dots and fill in gaps in their own neural networks.

“If you have a result and you don’t understand why you made that decision, how could you really advance in your research.” Powerful. Bringing students to the place where they understand the theory behind what they are doing and apply it to experience is vital so they can talk about it, they can explain it, they can then replicate it in their professional careers.  We have much to learn.

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