Bypassing the Algorithmic Black Box:A Preliminary Study of Establishing Trust in Algorithm through Algorithmic Spokespersons
The continuous development of artificial intelligence(Al)has transformed Al technology from a simple tool to a complex engineering technolo-gy,and the algorithms that support their operation have also become more complex.However,the internal structures of complex algorithms are like opaque black boxes,and how to explain their outputs has become a thorny issue.There are two main approaches to enhancing the transparency of algorithms:one involves pursuing technological breakthroughs so as to completely resolve the black box problem,while the other is to make the opaque algorithms trustwor-thy through human interpretation.It seems that the latter one is more promising.According to this idea,people can identify a spokesperson for one specif-ic algorithm based on the extended mind thesis,so that the spokesperson can utilize his or her dual understanding of humans and this algorithm to interpret the output of the algorithm in a flexible and diverse way.This solution can help people better evaluate algorithms and guard against potential pitfalls of al-gorithms while recognizing the existence of the black box problem,and thus selectively building trust in algorithms.
artificial intelligencealgorithmic black boxdeep learningextended mindalgorithmic spokespersons
万方数据
维普
