Watershed of Artificial Intelligence: Human Intelligence, Machine Intelligence, and Biological Intelligence
Authors: Li Weigang, Liriam Enamoto, Denise Leyi Li
This article reviews the "Once learning" mechanism that was proposed 23 years ago and the subsequent successes of "One-shot learning" in image classification and "You Only Look Once - YOLO" in objective detection. Analyzing the current development of Artificial Intelligence (AI), the proposal is that AI should be clearly divided into the following categories: Artificial Human Intelligence (AHI), A...
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
Authors: Amina Adadi, Mohammed Berrada
At the dawn of the fourth industrial revolution, we are witnessing a fast and widespread adoption of artificial intelligence (AI) in our daily life, which contributes to accelerating the shift towards a more algorithmic society. However, even with such unprecedented advancements, a key impediment to the use of AI-based systems is that they often lack transparency. Indeed, the black-box nature of t...
Probability Judgement in Artificial Intelligence
Authors: Glenn Shafer
This paper is concerned with two theories of probability judgment: the Bayesian theory and the theory of belief functions. It illustrates these theories with some simple examples and discusses some of the issues that arise when we try to implement them in expert systems. The Bayesian theory is well known; its main ideas go back to the work of Thomas Bayes (1702-1761). The theory of belief function...
Possible Future Impacts of Artificial Intelligence
Authors: Jerry Kaplan
<p>Is progress in AI accelerating?</p>
<p>Not all subfields of AI proceed at the same pace, in part because they build on progress in other fields. For example, improvements in the physical capabilities of robots have been relatively slow, since they are dependent on advances...</p>
📅 Published: 2016-11-24
🔗 Source: CrossRef
The potential for artificial intelligence in healthcare
Authors: Thomas H. Davenport, Ravi Kalakota
The complexity and rise of data in healthcare means that artificial intelligence (AI) will increasingly be applied within the field. Several types of AI are already being employed by payers and providers of care, and life sciences companies. The key categories of applications involve diagnosis and treatment recommendations, patient engagement and adherence, and administrative activities. Although ...