scholarly journals Performance vs. competence in human–machine comparisons

2020 ◽  
Vol 117 (43) ◽  
pp. 26562-26571 ◽  
Author(s):  
Chaz Firestone
Keyword(s):  
Systems Approach ◽  
Brain Activity ◽  
Human Mind ◽  
Learning Systems ◽  
Behavioral Differences ◽  
Biologically Inspired ◽  
Playing Field ◽  
Intelligent Machines ◽  
The World ◽  
Exciting Possibility

Does the human mind resemble the machines that can behave like it? Biologically inspired machine-learning systems approach “human-level” accuracy in an astounding variety of domains, and even predict human brain activity—raising the exciting possibility that such systems represent the world like we do. However, even seemingly intelligent machines fail in strange and “unhumanlike” ways, threatening their status as models of our minds. How can we know when human–machine behavioral differences reflect deep disparities in their underlying capacities, vs. when such failures are only superficial or peripheral? This article draws on a foundational insight from cognitive science—the distinction between performance and competence—to encourage “species-fair” comparisons between humans and machines. The performance/competence distinction urges us to consider whether the failure of a system to behave as ideally hypothesized, or the failure of one creature to behave like another, arises not because the system lacks the relevant knowledge or internal capacities (“competence”), but instead because of superficial constraints on demonstrating that knowledge (“performance”). I argue that this distinction has been neglected by research comparing human and machine behavior, and that it should be essential to any such comparison. Focusing on the domain of image classification, I identify three factors contributing to the species-fairness of human–machine comparisons, extracted from recent work that equates such constraints. Species-fair comparisons level the playing field between natural and artificial intelligence, so that we can separate more superficial differences from those that may be deep and enduring.

Research on Human Cognition for Biologically Inspired Developments

2017 ◽  
pp. 83-116 ◽  
Author(s):  
Marko Wehle ◽  
Alexandra Weidemann ◽  
Ivo Wilhelm Boblan
Keyword(s):  
Role Model ◽  
Cognitive Model ◽  
Human Robot Interaction ◽  
Human Cognition ◽  
Biologically Inspired ◽  
Robot Interaction ◽  
Intelligent Machines ◽  
The World ◽  
Conducting Research ◽  
Interaction Research

Robotic developments are seen as a next level in technology with intelligent machines, which automate tedious tasks and serve our needs without complaints. But nevertheless, they have to be fair and smart enough to be intuitively of use and safe to handle. But how to implement this kind of intelligence, does it need feelings and emotions, should robots perceive the world as we do as a human role model, how far should the implementation of synthetic consciousness lead and actually, what is needed for consciousness in that context? Additionally in Human-Robot-Interaction research, science mainly makes use of the tool phenomenography, which is exclusively subjective, so how to make it qualify for Artificial Intelligence? These are the heading aspects of this chapter for conducting research in the field of social robotics and suggesting a conscious and cognitive model for smart and intuitive interacting robots, guided by biomimetics.

Research on Human Cognition for Biologically Inspired Developments

2020 ◽  
pp. 1507-1532
Author(s):  
Marko Wehle ◽  
Alexandra Weidemann ◽  
Ivo Wilhelm Boblan
Keyword(s):  
Role Model ◽  
Cognitive Model ◽  
Human Robot Interaction ◽  
Human Cognition ◽  
Biologically Inspired ◽  
Robot Interaction ◽  
Intelligent Machines ◽  
The World ◽  
Conducting Research ◽  
Interaction Research

Robotic developments are seen as a next level in technology with intelligent machines, which automate tedious tasks and serve our needs without complaints. But nevertheless, they have to be fair and smart enough to be intuitively of use and safe to handle. But how to implement this kind of intelligence, does it need feelings and emotions, should robots perceive the world as we do as a human role model, how far should the implementation of synthetic consciousness lead and actually, what is needed for consciousness in that context? Additionally in Human-Robot-Interaction research, science mainly makes use of the tool phenomenography, which is exclusively subjective, so how to make it qualify for Artificial Intelligence? These are the heading aspects of this chapter for conducting research in the field of social robotics and suggesting a conscious and cognitive model for smart and intuitive interacting robots, guided by biomimetics.

scholarly journals A study of right and left brain dominant students at IB&M with respect to their gender, age and educational background.

2017 ◽  
Vol 3 (9) ◽  
pp. 115
Author(s):  
Ayesha Ameen
Keyword(s):  
Scientific Method ◽  
Brain Activity ◽  
Business Students ◽  
Educational Background ◽  
Human Mind ◽  
Teaching Methodology ◽  
Left Brain ◽  
Right Brain ◽  
The World ◽  
The Right

Managers all over the world each day combat the challenges associated with Managing the workforce. In order to unravel their truest potential managers have to understand them and motivate or sometimes above that i.e. to ignite the spark that gives the momentum to their capabilities that make them productive and give them an everlasting happiness.Management is termed as Right brain activity. It involves dealing with the human mind and emotions which are very complex and variable unlike the scientific method which we perceive management to be.In order to check the co-relation of the right and left brain people research was carried out. This study was conducted with approximately 50 Business students with a survey, as well as a comprehensive review and analysis of literature concerning the brain.This study would help the instructors to understand the fact Management is not a science and based on the number of left or right Brain students the current teaching methodology of Business students can either be revised or transformed altogether.

scholarly journals A Framework for Long-Term Learning Systems

2017 ◽  
Author(s):  
Diana Benavides-Prado
Keyword(s):  
Machine Learning ◽  
Computer Science ◽  
Efficient Algorithms ◽  
Learning Systems ◽  
Machine Learning Techniques ◽  
Intelligent Machines ◽  
Learning Techniques ◽  
The World ◽  
Design And Application

Increasing amounts of data have made the use of machine learning techniques much more widespread. A lot of research in machine learning has been dedicated to the design and application of effective and efficient algorithms to explain or predict facts. The development of intelligent machines that can learn over extended periods of time, and that improve their abilities as they execute more tasks, is still a pending contribution from computer science to the world. This weakness has been recognised for some decades, and an interest to solve it seems to be increasing, as demonstrated by recent leading work and broader discussions at main events in the field [Chen and Liu, 2015; Chen et al., 2016]. Our research is intended to help fill that gap.

Platform for Analysing and Encouraging Student Activity on Contest and E-learning Systems

2018 ◽  
Vol 12 ◽  
pp. 85-98
Author(s):  
Bojan Kostadinov ◽  
Mile Jovanov ◽  
Emil STANKOV
Keyword(s):  
Machine Learning ◽  
Data Collection ◽  
Educational Policy ◽  
Learning Systems ◽  
Data Sources ◽  
Or Education ◽  
Student Activity ◽  
The World ◽  
E Learning ◽  
Analyse Data

Data collection and machine learning are changing the world. Whether it is medicine, sports or education, companies and institutions are investing a lot of time and money in systems that gather, process and analyse data. Likewise, to improve competitiveness, a lot of countries are making changes to their educational policy by supporting STEM disciplines. Therefore, it’s important to put effort into using various data sources to help students succeed in STEM. In this paper, we present a platform that can analyse student’s activity on various contest and e-learning systems, combine and process the data, and then present it in various ways that are easy to understand. This in turn enables teachers and organizers to recognize talented and hardworking students, identify issues, and/or motivate students to practice and work on areas where they’re weaker.

EDUCATION – RETURN TO REALITY

2020 ◽  
Vol 11 (1) ◽  
pp. 127-130
Author(s):  
Alexander Lukankin ◽  
Keyword(s):  
High Schools ◽  
Basic Education ◽  
Formal Method ◽  
Human Mind ◽  
Production Sector ◽  
The World ◽  
Soviet Russia ◽  
Correct Understanding ◽  
Natural Science Education ◽  
Technical Professions

The post-socialist transformation of general and vocational education system has led to the loss of many positive gains that were already achieved earlier. The polytechnic character of our school and its practice-oriented foundations, based on a reasonable combination of basic education and professional and applied training, were seriously undermined. Modern Russian secondary schools have become something like pre-revolutionary classical high schools, without taking into account the significant fact that in pre-Soviet Russia, along with high schools, there was a wide network of real schools. They focused students on further mastering technical professions and active participation in the production sector of the country. Today we are witnessing a global revolution in the spiritual sphere, aimed at changing the very essence of a man. Note that natural science education is valuable not only for its formal method, but also for providing the basis for a correct understanding of the world. It fosters independence of thought and distrust of other people’s words and authorities. This is the best protection of the human mind from all sorts of superstitions delusions and mysticism.

A Decade of the World Trade Organization and the Trade Performance of Muslim Countries

2010 ◽  
Vol 27 (4) ◽  
pp. 23-44
Author(s):  
Ruzita Mohd. Amin
Keyword(s):  
Developing Countries ◽  
World Trade Organization ◽  
World Trade ◽  
Developed Countries ◽  
Playing Field ◽  
Muslim Countries ◽  
The World ◽  
The Developed Countries ◽  
Merchandise Trade ◽  
Wto Agreements

The World Trade Organization (WTO), established on 1 January 1995 as a successor to the General Agreement on Tariffs and Trade (GATT), has played an important role in promoting global free trade. The implementation of its agreements, however, has not been smooth and easy. In fact this has been particularly difficult for developing countries, since they are expected to be on a level playing field with the developed countries. After more than a decade of existence, it is worth looking at the WTO’s impact on developing countries, particularly Muslim countries. This paper focuses mainly on the performance of merchandise trade of Muslim countries after they joined the WTO. I first analyze their participation in world merchandise trade and highlight their trade characteristics in general. This is then followed by a short discussion on the implications of WTO agreements on Muslim countries and some recommendations on how to face this challenge.

Kant’s ‘Transcendental Deduction’

2018 ◽  
Author(s):  
Barry Stroud
Keyword(s):  
A Priori ◽  
Human Mind ◽  
Critical Assessment ◽  
Structural Description ◽  
A Posteriori ◽  
Human Knowledge ◽  
Transcendental Deduction ◽  
The World ◽  
Empirical Realism

This chapter presents a straightforward structural description of Immanuel Kant’s conception of what the transcendental deduction is supposed to do, and how it is supposed to do it. The ‘deduction’ Kant thinks is needed for understanding the human mind would establish and explain our ‘right’ or ‘entitlement’ to something we seem to possess and employ in ‘the highly complicated web of human knowledge’. This is: experience, concepts, and principles. The chapter explains the point and strategy of the ‘deduction’ as Kant understands it, as well as the demanding conditions of its success, without entering into complexities of interpretation or critical assessment of the degree of success actually achieved. It also analyses Kant’s arguments regarding a priori concepts as well as a posteriori knowledge of the world around us, along with his claim that our position in the world must be understood as ‘empirical realism’.

scholarly journals Jumping over baselines with new methods to predict activation maps from resting-state fMRI

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eric Lacosse ◽  
Klaus Scheffler ◽  
Gabriele Lohmann ◽  
Georg Martius
Keyword(s):  
Resting State ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Behavioral Differences ◽  
Large Variability ◽  
Single Vertex ◽  
Spontaneous Brain Activity ◽  
New Methods ◽  
Group Averaging ◽  
Proposed Modification

AbstractCognitive fMRI research primarily relies on task-averaged responses over many subjects to describe general principles of brain function. Nonetheless, there exists a large variability between subjects that is also reflected in spontaneous brain activity as measured by resting state fMRI (rsfMRI). Leveraging this fact, several recent studies have therefore aimed at predicting task activation from rsfMRI using various machine learning methods within a growing literature on ‘connectome fingerprinting’. In reviewing these results, we found lack of an evaluation against robust baselines that reliably supports a novelty of predictions for this task. On closer examination to reported methods, we found most underperform against trivial baseline model performances based on massive group averaging when whole-cortex prediction is considered. Here we present a modification to published methods that remedies this problem to large extent. Our proposed modification is based on a single-vertex approach that replaces commonly used brain parcellations. We further provide a summary of this model evaluation by characterizing empirical properties of where prediction for this task appears possible, explaining why some predictions largely fail for certain targets. Finally, with these empirical observations we investigate whether individual prediction scores explain individual behavioral differences in a task.

What Can Experimental Studies of Bias Tell Us About Real-World Group Disparities?

2021 ◽  
pp. 1-82
Author(s):  
Joseph Cesario
Keyword(s):  
Real World ◽  
Experimental Studies ◽  
White Men ◽  
Human Mind ◽  
Behavioral Differences ◽  
Social Categories ◽  
Systematic Testing ◽  
Black And White ◽  
Research Tradition ◽  
The Social

Abstract This article questions the widespread use of experimental social psychology to understand real-world group disparities. Standard experimental practice is to design studies in which participants make judgments of targets who vary only on the social categories to which they belong. This is typically done under simplified decision landscapes and with untrained decision makers. For example, to understand racial disparities in police shootings, researchers show pictures of armed and unarmed Black and White men to undergraduates and have them press "shoot" and "don't shoot" buttons. Having demonstrated categorical bias under these conditions, researchers then use such findings to claim that real-world disparities are also due to decision-maker bias. I describe three flaws inherent in this approach, flaws which undermine any direct contribution of experimental studies to explaining group disparities. First, the decision landscapes used in experimental studies lack crucial components present in actual decisions (Missing Information Flaw). Second, categorical effects in experimental studies are not interpreted in light of other effects on outcomes, including behavioral differences across groups (Missing Forces Flaw). Third, there is no systematic testing of whether the contingencies required to produce experimental effects are present in real-world decisions (Missing Contingencies Flaw). I apply this analysis to three research topics to illustrate the scope of the problem. I discuss how this research tradition has skewed our understanding of the human mind within and beyond the discipline and how results from experimental studies of bias are generally misunderstood. I conclude by arguing that the current research tradition should be abandoned.

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