Many speakers have pointed to various challenging ethical and design dilemmas raised by AI technology—we will describe 10 of the most prominent ones in this column. The first few are mostly technical; they arise from seemingly impenetrable complexity of the new technology. The final few ethical and design dilemmas include strong social dimensions; they arise from the difficulty of resolving emotional value conflicts to everyone's satisfaction.
The most common AI technology is the artificial neural network (ANN). An ANN consists of many layers of artificial neurons interconnected via weighted links. ANNs are not programmed in the conventional way by specifying the steps of an algorithm. Instead they are trained by showing them large numbers of examples of input-output pairs and adjusting their internal connection weights so that every input gives a correct output. The matrix of connection weights can amount to several gigabytes of storage. In effect, an ANN encodes the training examples of a function in its connection matrix and extrapolates them to estimate the outputs for data not in the training examples.
Another article on AI without a definition of what they are talking about.
The following comment/response is from Peter J. Denning and Dorothy E. Denning.
Experts on AI do not agree among themselves how to define AI. Too bad we didn't include "definition of AI" as another dilemma. In our American Scientist article, Ted Lewis I tried to address "what does it mean to be an AI machine?" (http://denninginstitute.com/pjd/PUBS/amsci-2019-ai-hierachy.pdf)
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