scholarly journals Explaining Factor Ascription

2021 ◽  
Author(s):  
Jack Mumford ◽  
Katie Atkinson ◽  
Trevor Bench-Capon
Keyword(s):  
Machine Learning ◽  
Hybrid System ◽  
System Approach ◽  
Legal Decisions ◽  
Relevant Topic

Explanation and justification of legal decisions has become a highly relevant topic in light of the explosion of interest in the use of machine learning (ML) approaches to predict legal decisions. Current suggestions are to use the established factor based explanations developed in AI and Law as the basis for explaining such programs. We, however, identify factor ascription as an important aspect of explanation of case outcomes not currently covered, and argue that explanations must also include this aspect. Finally, we outline our proposal for a hybrid system approach that combines ML and Abstract Dialectical Framework (ADF) layers to engender an explainable process.

The Bright but Modest Potential of Algorithms in the Courtroom

2020 ◽  
pp. 113-132
Author(s):  
Andrew Higgins ◽  
Inbar Levy ◽  
Thibaut Lienart
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Human Error ◽  
Civil Justice ◽  
Human Judgment ◽  
Judicial Decision ◽  
Judicial Decision Making ◽  
Legal Decisions ◽  
Human Skills ◽  
Civil Justice System

This chapter investigates the potential of algorithms and machine learning (ML) to improve decision-making. It considers the best roles for algorithms while maintaining important elements of human judgment. There are essential human skills in judging, but algorithms could help systematize the judicial function and thus reduce the risk of human error, inconsistency, and individual bias. Algorithmic decision-making and ML could in principle mitigate these problems since algorithms are more consistent and rely on and can synthesize more data than a human. Yet, recent proposals to use algorithms in the civil justice system are still underdeveloped and face scepticism. This chapter evaluates the risks and benefits of using algorithms in adjudication by pointing out specific elements of legal skill and expertise and identifying tasks better suited for an algorithm. While there are significant reliability and fairness limitations in using AI to make legal decisions, it is important to recognize that many of these weaknesses already exist to varying degrees in human judicial decision-making.

scholarly journals Hybrid-system approach to fault-tolerant quantum communication

2013 ◽  
Vol 87 (5) ◽  
Author(s):  
Ashley M. Stephens ◽  
Jingjing Huang ◽  
Kae Nemoto ◽  
William J. Munro
Keyword(s):  
Hybrid System ◽  
System Approach ◽  
Quantum Communication ◽  
Fault Tolerant

A hybrid-system approach for W state and cluster state generation

2014 ◽  
Vol 310 ◽  
pp. 166-172 ◽  
Author(s):  
Xin Tong ◽  
Chuan Wang ◽  
Cong Cao ◽  
Ling-yan He ◽  
Ru Zhang
Keyword(s):  
Hybrid System ◽  
System Approach ◽  
Cluster State ◽  
W State ◽  
State Generation

Hybrid System Based Analytical Approach for Optimal Gear Shifting Schedule Design

2015 ◽  
Author(s):  
Chaozhe R. He ◽  
Wubing B. Qin ◽  
Necmiye Ozay ◽  
Gábor Orosz
Keyword(s):  
Hybrid System ◽  
System Approach ◽  
Analytical Approach ◽  
Pi Controller ◽  
Longitudinal Motion ◽  
Scheduling Problem ◽  
Systematic Design ◽  
Shifting Strategy ◽  
Schedule Design

In this paper, we present a systematic design for gear shifting using a hybrid system approach. The longitudinal motion of the vehicle is regulated by a PI-controller that determines the required axle torque. The gear scheduling problem is modeled as a hybrid system and an optimization-based gear shifting strategy is introduced, which guarantees that the propulsion requirements are delivered while minimizing fuel consumption. The resulting dynamics is proved to be stable theoretically. In a case study, we compare our strategy with a standard approach used in the industry and demonstrate the advantages of our design for class 8 trucks.

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