MACHINE ASSISTED HUMAN DECISION MAKING

被引：0

作者：

Mourad, Sara ^{[1
]}

Tewfik, Ahmed ^{[1
]}

机构：

[1] Univ Texas Austin, Dept Elect & Comp Engn, Austin, TX 78712 USA

来源：

2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2018年

关键词：

Cognitive biases; Subset selection; Bayesian; Hypothesis Testing; Man-Machine; STARTING POINT BIAS; VALUATION; MODEL;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

Artificial intelligence is often touted as the ultimate automation technology capable of outperforming humans. It is also feared by some because of its potential to eliminate certain jobs. In this paper, we describe scenarios in which man-machine symbiosis, or properly designed combinations of man and machine, can actually outperform man and machine. We also present a statistical solution to a constrained version of a generic problem in man-machine symbiosis. Specifically, we solve the problem of optimal selection, ordering and presentation of data to a human to solve a class of problems that artificial intelligence can fail to solve on its own, such as fraud detection. The man-machine symbiosis solution we present overcomes human cognitive biases which stand in the way of their rational decision making.

引用

页码：6981 / 6985

页数：5

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