The inscrutability of the Black Box

Black Box AI is adopted as a metaphor to express the phenomenon of the system used in AI. The system allows the bystander to observe either what inputs are entering to the Black Box or what outputs are leaving from the Black Box, however, the process of the values inside the matrices cannot be explained or followed by a third eye.

Under this challenge, FICO states its own concerns due to the inscrutability of the Black Box and its’ impacts on the financial world. In respect to FICO’s concerns, they urging scientist to solve the inscrutability issue with regards to biases and discriminative decisions and adapt the method for solutions into the finance worlds. More sophisticated machine learning techniques that offer the promise of increased accuracy with clarity should mean more access to credit for qualified borrowers and lower risk for financial institutions. However, the black-box nature of ADM illustrates that they are currently cannot be explainable nor can be intervened. Without accurate explanations, these algorithms cannot correspond to the due process of law, therefore, cannot be approved by the finance world and would likely not be accepted by consumers.

Finally, this paper draws a scheme to understand yet again why explicability is needed:

Sum up, method of explanation is a crucial vehicle for justifying Algorithm based decisions, to solve the inscrutability nature of the decision-making systems and developing the trust between machine and human.

accessed 12 April 2019.

accessed 12 April 2019.

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