Controllable Artificial Intelligence

被引:0
|
作者
Kieseberg, Peter [1 ]
Tjoa, Simon [1 ]
Holzinger, Andreas [2 ]
机构
[1] St Polten UAS, St Polten, Austria
[2] Univ Nat Resources & Life Sci, Vienna, Austria
来源
ERCIM NEWS | 2024年 / 136期
关键词
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The burgeoning landscape of AI legislation and the ubiquitous integration of machine learning into daily computing underscore the imperative for trustworthy AI. Yet, prevailing definitions of this concept often dwell in the realm of the abstract, imposing robust demands for explainability. In light of this, we propose a novel paradigm that mirrors the strategies employed in navigating the opaqueness of human decision-making. This approach offers a pragmatic and relatable pathway to cultivating trust in AI systems, potentially revolutionising our interaction with these transformative technologies.
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页码:46 / 47
页数:2
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