The way we talk about Ethics is broken

An analogy with the Neural Network Algorithm

Read as ‘the activation a of a neuron is the sigmoid g of the sum of each of the previous neuron’s output x multiplied by the strength of the connection from that previous neuron theta. Finally, the prediction h is again the sigmoid g of the linear combination of the appropriate weights theta and activations a.
From Wikipedia
Read as: (1) The greatest value V* to be derived in a situation s is defined as the best action a which can be taken from that situation s which is defined as (2) the action which you expect to yield the best outcome, which is the same as (3) the action which will put you in the best position to make the next good decision, which means that (6) you should choose the action a from situation s which has the highest probability P of getting you to another situation s’ where you’ll be able to make a series of great decisions in the future.
Jeremy Bentham (Utilitarianism) , and Immanuel Kant (Kantianism)
Imagine here a projection of the infinite space of situations onto a single dimension (the x axis), which captures all the many subtleties of human life. We also project the infinite space of decisions onto a single dimension y which similarly captures all the information of the higher dimensional space. Then a coordinate in this space is a scenario and decision, and a system of ethics is a function f(x, y) on that domain which determines how ethical the decision taken from that situation may be, where 1 is maximally ethical, and -1 is maximally unethical.
A linear classifier, hypothetically dividing ‘right’ from ‘wrong’
Inputs that may play into a human’s decision in the trolley problem, which traditional formulations don’t take into account. When the trolley problem is presented to someone, all sorts of assumptions about the situation play a much larger part in the decision someone professes they would take than we might think.



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