An Understandable Alternative to AI
Understandable AI is a recent phrase, particularly in the military arena. It refers to the complexity of current implementations for artificial intelligence. Complexity has gotten out of hand.
Many concepts of mimicking human intelligence flow from academia. An unfortunate majority of these papers demonstrate notional cross-breeding. It is as if they have lost their way.
Academics hired into federal agencies such as Darpa and others had pressed for “bio-mimetic” solutions to human processes. Conversely, they themselves are now being pressed for an “understandable AI”.
For example, take the neural cluster typically defined for so-called Machine Learning. However, this operation constitutes an estimated 6% of the cortical brain function.
Functionally it is a correlator (a pattern detector), a sensor or detector. Today, attempts are being made to apply the sensor to the thought or decision processes. There appears to be no equivalent human psychological thought process.
Machine learning is the hammer whose wielder sees nails everywhere. The resulting systems have escaped understanding except by their most dedicated adherents.
Machine intelligence is in a restart. Do you remember your first attempts at using Google? You probably entered a whole sentence and never expected a dump truck of those “search results”! You never wanted search results in the first place. You wanted answers, but were instead handed a list of educated guesses. Missed Expectations There … Read more
The failures of artificial intelligence (AI) are a remarkable disappointment to science, industry and government. In this paper, we explore both the successes and failures of AI. A machine that acts like a human has interested even the non-scientist. The discussions and dreams that began in the 1930s still continue after 80 years. The ENIAC … Read more