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🔥Quick thread explaining Artificial Intelligence, Machine Learning, Algorithms and more! Lets begin...What if the algorithms that calculate all those decisions that affect the minutiae of our lives, have programmed themselves in ways that we cannot understand their behavior?
In earlier iterations, Artificial Intelligence (AI) was constructed in that #AI ought to be reasoned according to rules/logic, making their inner workings transparent...
But now, machines are constructed like biology, and learn by observing and experiencing.
Instead of a programmer writing commands to solve a problem, the program generates its own algorithm based on example data and a desired output, the machine programs itself.
This creates the bigly problem, you can’t look inside a computer neurological network to see how it works
A network’s reasoning is embedded in the behavior of thousands of simulated neurons. The neurons in 1st layer receive an input & then perform a calc before outputting a new signal.
These outputs are fed to the neurons in the next layer…
Until an overall output is produced
Within, there is a process "back-propagation" -tweaks the calcs of individual neurons in a way that lets network learn to produce a desired output
The many layers in a network enable it to recognize things at different levels of abstraction.
In a system designed to recognize dogs the lower layers will recognize simple things like outlines or color; higher layers recognize more complex stuff like fur or eyes; and the topmost layer identifies it all as a dog.
Just as aspects of human behavior are impossible to explain in detail, maybe it isn’t possible for AI to explain everything it does to our feeble minds. I think if we’re going to use these things and rely on them, then let’s get our grips on how/why they’re giving us ‘answers’.
...but since there may be no perfect answer, we should be as cautious of AI explanations as we are of each others.

Interrogating an Algorithm should be a Human Right
Oops! I got more to say #Townsend2020 wants to share some more details, lets go:
What is AI?
There is no consensus definition of what ‘it’ is, this constrains any real "policy infrastructure"
Heres some iterations of AI:
a) Machine Learning: algorithms capable of ‘self-learning,’ & improving their output through experience =supervised learning by humans, and there is unsupervised learning , for example how Netflix recommends the next movie you should watch
b) Deep Learning: are the high hanging fruit problems and is quickly approaching human-level performance on some object recognition benchmarks and object detection
c) Reinforcement Learning: interacts with its environment, observing consequences/actions, alter its behavior in response to rewards
d) Deep Reinforcement Learning: capable of learning how to adapt in the real world.

Now you know everything in the world, you're complete
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