The Experts below are selected from a list of 171424218 Experts worldwide ranked by ideXlab platform
Fabio Massimo Zanzotto - One of the best experts on this subject based on the ideXlab platform.
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Viewpoint: Human-in-the-Loop Artificial Intelligence
Journal of Artificial Intelligence Research, 2019Co-Authors: Fabio Massimo ZanzottoAbstract:Little by little, newspapers are revealing the bright future that Artificial Intelligence (AI) is building. Intelligent machines will help everywhere. However, this bright future may have a possible dark side: a dramatic job market contraction before its unpredictable transformation. Hence, in a near future, large numbers of job seekers may need financial support while catching up with these novel unpredictable jobs. This possible job market crisis has an antidote inside. In fact, the rise of AI is sustained by the biggest knowledge theft of the recent years. Many learning AI machines are extracting knowledge from unaware skilled or unskilled workers by analyzing their interactions. By passionately doing their jobs, many of these workers are shooting themselves in the feet. In this paper, we propose Human-in-the-Loop Artificial Intelligence (HitAI) as a fairer paradigm for AI systems. Recognizing that any AI system has humans in the loop, HitAI will reward these aware and unaware knowledge producers with a different scheme: decisions of AI systems generating revenues will repay the legitimate owners of the knowledge used for taking those decisions. As modern Merry Men, HitAI researchers should fight for a fairer Robin Hood Artificial Intelligence that gives back what it steals. This article is part of the special track on AI and Society.
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Human-in-the-Loop Artificial Intelligence
arXiv: Artificial Intelligence, 2017Co-Authors: Fabio Massimo ZanzottoAbstract:Little by little, newspapers are revealing the bright future that Artificial Intelligence (AI) is building. Intelligent machines will help everywhere. However, this bright future has a dark side: a dramatic job market contraction before its unpredictable transformation. Hence, in a near future, large numbers of job seekers will need financial support while catching up with these novel unpredictable jobs. This possible job market crisis has an antidote inside. In fact, the rise of AI is sustained by the biggest knowledge theft of the recent years. Learning AI machines are extracting knowledge from unaware skilled or unskilled workers by analyzing their interactions. By passionately doing their jobs, these workers are digging their own graves. In this paper, we propose Human-in-the-Loop Artificial Intelligence (HIT-AI) as a fairer paradigm for Artificial Intelligence systems. HIT-AI will reward aware and unaware knowledge producers with a different scheme: decisions of AI systems generating revenues will repay the legitimate owners of the knowledge used for taking those decisions. As modern Robin Hoods, HIT-AI researchers should fight for a fairer Artificial Intelligence that gives back what it steals.
R. Stanciu - One of the best experts on this subject based on the ideXlab platform.
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ICRA - Feedforward control for Human-in-the-Loop camera systems
IEEE International Conference on Robotics and Automation 2004. Proceedings. ICRA '04. 2004, 2004Co-Authors: R. StanciuAbstract:Cameras are often mounted on platforms that can move like rovers, booms, gantries and aircraft. People operate such platforms to capture desired views of a scene or a target. To avoid collisions with the environment and occlusions, such platforms often possess redundant degrees-of-freedom. As a result, manual manipulating of such platforms demands much skill. Visual-servoing some degrees-of-freedom may reduce operator burden and improve tracking performance. This concept, which we call Human-in-the-Loop visual-servoing, is demonstrated And applies a /spl alpha/ /spl rarr/ /spl beta/ /spl rarr/ /spl gamma/ filter and feedforward controller to a broadcast camera boom.
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Feedforward-output tracking regulation control for Human-in-the-Loop camera systems
Proceedings of the 2005 American Control Conference 2005., 1Co-Authors: R. StanciuAbstract:Platforms like gantries, booms, aircraft and submersibles are equipped with cameras. People teleoperate such platforms to capture desired views of a scene or a target. To avoid collisions with the environment and occluded views, such platforms are often equipped with redundant degrees-of-freedom. The operator must manually coordinate multiple degrees-of-freedom in order to get desired views. Tracking moving targets becomes especially tedious and often requires several highly skilled operators. Visual-servoing some degrees-of-freedom may reduce operator burden and improve tracking performance. This paper builds upon previous successes with Human-in-the-Loop visual-servoing by integrating the platform's dynamics with computer vision. A broadcast boom is modelled and both simulation and experimental tests contrasting trained and untrained camera operators are presented.
David Nunes - One of the best experts on this subject based on the ideXlab platform.
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Human-in-the-Loop Connectivity Management in Smartphones
2016Co-Authors: David Nunes, Carlos Herrera, Jorge Silva, Fernando BoavidaAbstract:Cyber-Physical Systems which detect and use human psychological and physiological states as feedback to their control-loop are known as Human-in-the-Loop (HITL). The current understanding of the general requirements and theory behind this new class of systems is, however, still limited. This paper attempts to contribute towards their development by presenting a conceptual model that integrates some of the major ideas spread throughout the literature. In addition, it also discusses how the acquisition of a human’s state requires reliable networking. In this respect, an architecture for HITL management of networking configurations is presented. This architecture is implemented in an experimental scenario where a smartphone system attempts to positively impact mood by dynamically adapting privacy settings and networking interfaces to the user’s emotions. In this scenario, good hand-off performance is crucial for improving Quality of Experience and reliability. Several experiments regarding emotional classification and mobile handoff are also presented and discussed.
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WWIC - Human-in-the-Loop Connectivity Management in Smartphones
Lecture Notes in Computer Science, 2016Co-Authors: David Nunes, Carlos Herrera, Jorge Sa Silva, Fernando BoavidaAbstract:Cyber-Physical Systems which detect and use human psychological and physiological states as feedback to their control-loop are known as Human-in-the-Loop (HITL). The current understanding of the general requirements and theory behind this new class of systems is, however, still limited. This paper attempts to contribute towards their development by presenting a conceptual model that integrates some of the major ideas spread throughout the literature. In addition, it also discusses how the acquisition of a human’s state requires reliable networking. In this respect, an architecture for HITL management of networking configurations is presented. This architecture is implemented in an experimental scenario where a smartphone system attempts to positively impact mood by dynamically adapting privacy settings and networking interfaces to the user’s emotions. In this scenario, good hand-off performance is crucial for improving Quality of Experience and reliability. Several experiments regarding emotional classification and mobile handoff are also presented and discussed.
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A Survey on Human-in-the-Loop Applications Towards an Internet of All
IEEE Communications Surveys & Tutorials, 2015Co-Authors: David Nunes, Pei Zhang, Jorge Sa SilvaAbstract:Our tools and appliances are becoming increasingly more intelligent and interconnected, giving birth to an “Internet of Things” that can be used to support new types of cyber-physical systems (CPSs). While many CPSs are human-centric applications where humans are an essential part of the system, unfortunately, most of these systems still consider the human as an external and unpredictable element to the control loop. In order for these systems to better serve human needs, future CPSs will need to bolster a closer tie with the human element, through Human-in-the-Loop controls that take into consideration human intents, psychological states, emotions and actions inferred through sensory data. This area is a natural confluence of multidisciplinary focus but currently lacks a general understanding of the underlying requirements, principles and theory. As far as we know, this survey is the first effort towards extending the field's knowledge through an in-depth research of the state-of-the-art and a critical overview of the current taxonomic efforts in the area of Human-in-the-Loop CPSs. On top of this research, a novel taxonomic exercise focused on the general roles of the human component together with a requirement analysis, are presented.
Shankar Sastry - One of the best experts on this subject based on the ideXlab platform.
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Experimental Design for Human-in-the-Loop Driving Simulations
arXiv: Systems and Control, 2014Co-Authors: Katherine Driggs-campbell, Guillaume Bellegarda, Victor Shia, Shankar Sastry, Ruzena BajcsyAbstract:This report describes a new experimental setup for Human-in-the-Loop simulations. A force feedback simulator with four axis motion has been setup for real-time driving experiments. The simulator will move to simulate the forces a driver feels while driving, which allows for a realistic experience for the driver. This setup allows for flexibility and control for the researcher in a realistic simulation environment. Experiments concerning driver distraction can also be carried out safely in this test bed, in addition to multi-agent experiments. All necessary code to run the simulator, the additional sensors, and the basic processing is available for use.
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TACAS - Synthesis for Human-in-the-Loop Control Systems
Tools and Algorithms for the Construction and Analysis of Systems, 2014Co-Authors: Dorsa Sadigh, Shankar Sastry, Sanjit A. SeshiaAbstract:Several control systems in safety-critical applications involve the interaction of an autonomous controller with one or more human operators. Examples include pilots interacting with an autopilot system in an aircraft, and a driver interacting with automated driver-assistance features in an automobile. The correctness of such systems depends not only on the autonomous controller, but also on the actions of the human controller. In this paper, we present a formalism for Human-in-the-Loop (HuIL) control systems. Particularly, we focus on the problem of synthesizing a semi-autonomous controller from high-level temporal specifications that expect occasional human intervention for correct operation. We present an algorithm for this problem, and demonstrate its operation on problems related to driver assistance in automobiles.
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CDC - A POMDP framework for Human-in-the-Loop system
53rd IEEE Conference on Decision and Control, 2014Co-Authors: Chi-pang Lam, Shankar SastryAbstract:Human operators are involved in many real world systems such as automobile systems. Traditional human-assistance features such as warning systems in the aircraft and automatic braking systems in automobile only monitor the states of the machine in order to prevent human errors and enhance safety. We believe that next generation systems should be able to monitor both the human and the machine and give an appropriate feedback to them. Although having human in the control loop has its advantage, it lacks a unified modeling framework to manage the feedback between the human and the machine. In this paper, we will present how partially observable Markov decision process (POMDP) can be used as a unified framework for the three main components in a Human-in-the-Loop control system—the human model, the machine dynamic model and the observation model. We use simulations to show the benefits of this framework. Finally, we outline the key challenge to advance this framework.
Fernando Boavida - One of the best experts on this subject based on the ideXlab platform.
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Human-in-the-Loop Connectivity Management in Smartphones
2016Co-Authors: David Nunes, Carlos Herrera, Jorge Silva, Fernando BoavidaAbstract:Cyber-Physical Systems which detect and use human psychological and physiological states as feedback to their control-loop are known as Human-in-the-Loop (HITL). The current understanding of the general requirements and theory behind this new class of systems is, however, still limited. This paper attempts to contribute towards their development by presenting a conceptual model that integrates some of the major ideas spread throughout the literature. In addition, it also discusses how the acquisition of a human’s state requires reliable networking. In this respect, an architecture for HITL management of networking configurations is presented. This architecture is implemented in an experimental scenario where a smartphone system attempts to positively impact mood by dynamically adapting privacy settings and networking interfaces to the user’s emotions. In this scenario, good hand-off performance is crucial for improving Quality of Experience and reliability. Several experiments regarding emotional classification and mobile handoff are also presented and discussed.
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WWIC - Human-in-the-Loop Connectivity Management in Smartphones
Lecture Notes in Computer Science, 2016Co-Authors: David Nunes, Carlos Herrera, Jorge Sa Silva, Fernando BoavidaAbstract:Cyber-Physical Systems which detect and use human psychological and physiological states as feedback to their control-loop are known as Human-in-the-Loop (HITL). The current understanding of the general requirements and theory behind this new class of systems is, however, still limited. This paper attempts to contribute towards their development by presenting a conceptual model that integrates some of the major ideas spread throughout the literature. In addition, it also discusses how the acquisition of a human’s state requires reliable networking. In this respect, an architecture for HITL management of networking configurations is presented. This architecture is implemented in an experimental scenario where a smartphone system attempts to positively impact mood by dynamically adapting privacy settings and networking interfaces to the user’s emotions. In this scenario, good hand-off performance is crucial for improving Quality of Experience and reliability. Several experiments regarding emotional classification and mobile handoff are also presented and discussed.