Machine Learning and Deep Learning

Although it is not, abstractedly speaking, of importance to know who first made a most valuable experiment, or to what individual the community is indebted for the invention of the most useful machine, yet the sense of mankind has in this, as in several other things, been in direct opposition to frigid reasoning; and we are pleased with a recollection of benefits, and with rendering honour to the memory of those who bestowed them. Were public benefactors to be allowed to pass away like hewers of wood and drawers of water, without commemoration, genius and enterprise would be deprived of their most coveted distinction, and after-times would lose incentives to that emulation which urges us to cherish and practise what has been worthy of commendation or imitation in our forefathers; and to make their works, which may have served for a light and been useful to the age in which they lived, a guide and a spur to ourselves

If machines produce everything we need, the outcome will depend on how things are distributed. Everyone can enjoy a life of luxurious leisure if the machine-produced wealth is shared, or most people can end up miserably poor if the machine-owners successfully lobby against wealth redistribution. So far, the trend seems to be toward the second option, with technology driving ever-increasing inequality.

Once upon a time we were just plain people. But that was before we began having relationships with mechanical systems. Get involved with a machine and sooner or later you are reduced to a factor.