Learn Like Humans

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Artificial intelligence is a frequent and reoccurring theme in educational technology. One I’ve touched on before from a perspective of surveillance, but want to explore a bit more.

What is it about artificial intelligence that makes it seem more worthy of praise, worthy of modeling learning after? What about efficiency, speed, and a false-notion of “unbiased” makes artificial intelligence more appealing than the labor of love and empathy? Than taking our time to process and reflect and consider? Than humanity?

I say “unbiased” pointedly; after all, a human has to code up the artificial: give it it’s marching orders, set constraints and boundaries. Even when the unintentional occurs–like the twitter bot that made it 24hours before turning racist, and robots upholding racist notions of beauty–it is because of the underlying humanity that is programmed into them. That they acquire from the humans they are modeled after.

So how is that better than praising the actual human-ness of humanity?

Why should we “learn to learn” (a phrase I absolutely loathe) like machines: stiff and constrained, efficient but limited in perspectives and empathy?

Machines don’t learn from failure; machines can’t grow. Even artificial intelligence, based on machine learning and neural networks, isn’t truly learning… its ranking and comparing and reordering statistical likelihoods. If the system is wrong, if something doesn’t work as intended (by the human programmers) the machine will never know.

We don’t need to learn to learn like a machine.

We need for authentic intelligence. Authentic experiences. Authenticity over artificial. We need to dig deep into our humanity and embrace love in our work and actions, seek out empathy and sympathy for those around us, and practice kindness and collective social concern. We need to learn like humans.

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