scholarly journals The Achilles' heel hypothesis: misinformed keystone individuals impair collective learning and reduce group success

2016 ◽  
Vol 283 (1823) ◽  
pp. 20152888 ◽  
Author(s):  
Jonathan N. Pruitt ◽  
Colin M. Wright ◽  
Carl N. Keiser ◽  
Alex E. DeMarco ◽  
Matthew M. Grobis ◽  
...  
Keyword(s):  
Information Quality ◽  
Group Performance ◽  
Collective Learning ◽  
Accurate Information ◽  
Inaccurate Information ◽  
Proper Functioning ◽  
Trained Individual ◽  
Group Success ◽  
Keystone Individual ◽  
Animal Societies

Many animal societies rely on highly influential keystone individuals for proper functioning. When information quality is important for group success, such keystone individuals have the potential to diminish group performance if they possess inaccurate information. Here, we test whether information quality (accurate or inaccurate) influences collective outcomes when keystone individuals are the first to acquire it. We trained keystone or generic individuals to attack or avoid novel stimuli and implanted these trained individuals within groups of naive colony-mates. We subsequently tracked how quickly groups learned about their environment in situations that matched (accurate information) or mismatched (inaccurate information) the training of the trained individual. We found that colonies with just one accurately informed individual were quicker to learn to attack a novel prey stimulus than colonies with no informed individuals. However, this effect was no more pronounced when the informed individual was a keystone individual. In contrast, keystones with inaccurate information had larger effects than generic individuals with identical information: groups containing keystones with inaccurate information took longer to learn to attack/avoid prey/predator stimuli and gained less weight than groups harbouring generic individuals with identical information. Our results convey that misinformed keystone individuals can become points of vulnerability for their societies.

scholarly journals Algorithmic and human prediction of success in human collaboration from visual features

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Martin Saveski ◽  
Edmond Awad ◽  
Iyad Rahwan ◽  
Manuel Cebrian
Keyword(s):  
Machine Learning ◽  
Visual Cues ◽  
Success Factors ◽  
Group Performance ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Adventure Game ◽  
Group Success ◽  
The Relationship ◽  
Better Than

AbstractAs groups are increasingly taking over individual experts in many tasks, it is ever more important to understand the determinants of group success. In this paper, we study the patterns of group success in Escape The Room, a physical adventure game in which a group is tasked with escaping a maze by collectively solving a series of puzzles. We investigate (1) the characteristics of successful groups, and (2) how accurately humans and machines can spot them from a group photo. The relationship between these two questions is based on the hypothesis that the characteristics of successful groups are encoded by features that can be spotted in their photo. We analyze >43K group photos (one photo per group) taken after groups have completed the game—from which all explicit performance-signaling information has been removed. First, we find that groups that are larger, older and more gender but less age diverse are significantly more likely to escape. Second, we compare humans and off-the-shelf machine learning algorithms at predicting whether a group escaped or not based on the completion photo. We find that individual guesses by humans achieve 58.3% accuracy, better than random, but worse than machines which display 71.6% accuracy. When humans are trained to guess by observing only four labeled photos, their accuracy increases to 64%. However, training humans on more labeled examples (eight or twelve) leads to a slight, but statistically insignificant improvement in accuracy (67.4%). Humans in the best training condition perform on par with two, but worse than three out of the five machine learning algorithms we evaluated. Our work illustrates the potentials and the limitations of machine learning systems in evaluating group performance and identifying success factors based on sparse visual cues.

The Quality Analysis of Hallux Valgus Videos on YouTube

2021 ◽  
Author(s):  
Enes Sari ◽  
Levent FAZLI Umur
Keyword(s):  
Hallux Valgus ◽  
Information Quality ◽  
Statistical Significance ◽  
Poor Quality ◽  
Quality Analysis ◽  
Accurate Information ◽  
Youtube Videos ◽  
The Mean ◽  
The Difference

BACKGROUND:The aim of this study was to evaluate the information quality of YouTube videos on hallux valgus. METHODS:A YouTube search was performed using the keyword 'hallux valgus' to determine the first 300 videos related to hallux valgus. A total of 54 videos met our inclusion criteria and evaluated for information quality by using DISCERN, Journal of the American Medical Association (JAMA) and hallux valgus information assessment (HAVIA) scores. Number of views, time since the upload date, view rate, number of comments, number of likes, number of dislikes, video power index (VPI) values were calculated to determine video popularity. Video length (sec), video source and video content were also noted. The relation between information quality and these factors were statistically evaluated. RESULTS:The mean DISCERN score was 30.35{plus minus}11.56 (poor quality) (14-64), the mean JAMA score was 2.28{plus minus}0.96 (1-4), and the mean HAVIA score was 3.63{plus minus}2.42 (moderate quality) (0.5-8.5). Although videos uploaded by physicians had higher mean DISCERN, JAMA, and HAVIA scores than videos uploaded by non-physicians, the difference was not statistically significant. Additionally, view rates and VPI values were higher for videos uploaded by health channels, but the difference did not reach statistical significance. A statistically significant positive correlation was found between video length and DISCERN (r= 0.294, p= 0.028), and HAVIA scores (r= 0.326, p= 0.015). CONCLUSIONS:This present study demonstrated that the quality of information available on YouTube videos about hallux valgus was low and insufficient. Videos containing accurate information from reliable sources are needed to educate patients on hallux valgus, especially in less frequently mentioned topics such as postoperative complications and healing period.

scholarly journals Measuring User Assessments and Expectations: The Use of WebQual 4.0 Method and Importance-Performance Analysis (IPA) to Evaluate the Quality of School Websites

2019 ◽  
Vol 4 (1) ◽  
pp. 76
Author(s):  
Aulia Akhrian Syahidi ◽  
Arifin Noor Asyikin ◽  
Subandi Subandi
Keyword(s):  
Performance Analysis ◽  
Digital Media ◽  
User Satisfaction ◽  
Structural Equation ◽  
Information Quality ◽  
Equation Modeling ◽  
Accurate Information ◽  
Data Processing Software ◽  
A Value ◽  
School Websites

As time goes by and technology advances, any information can be easily obtained from many media, both from various print media or digital electronic media. One of the fastest growing digital media and the main choice for individuals or agencies to get fast and accurate information is the website. One of the benefits of the website is that it can be used as an effective promotional media because it can be accessed by anyone and at any time. This study discusses the evaluation of school websites with a case study at the SMK Muhammadiyah 1 Banjarmasin using the WebQual 4.0 and Importance-Performance Analysis (IPA) methods. This study aims to measure user ratings of performance and expectations of users/visitors to the website of the SMK Muhammadiyah 1 Banjarmasin. The data in this study were obtained from the questionnaire using a sample of web visitors themselves, both through online based questionnaires and offline questionnaires with paper. This study uses data processing software, namely Structural Equation Modeling (SEM) 2.0. It can be concluded that in this study the results are measured by the level of performance (actual) and the level of importance (expectations) which shows that there is an overall gap for all dimensions -0.38 ie the website needs improvement and tends to still not be as expected. The biggest gap is in the Usability dimension with the largest value being -1.07 on USE5 variables, which means that the appearance of this website tends to be unattractive, not in line with expectations, and needs improvement. Then the acquisition of the value of R Square for the variable user satisfaction is 0.61, which means that the value indicates that the variable user satisfaction can be explained by usability, information quality, and service interaction with a value of 67.7%, while the remaining 32.3% is influenced by variables others not found in the research model.

Information Valuation Policies for Explainable Trustworthiness Assessment in E-Services

2011 ◽  
pp. 168-197
Author(s):  
Karen K. Fullam ◽  
K. Suzanne Barber
Keyword(s):  
Information Source ◽  
Accurate Information ◽  
Service Users ◽  
Multiple Sources ◽  
Face To Face ◽  
Inaccurate Information ◽  
Assessment Decisions ◽  
Information Valuation ◽  
Information Providers ◽  
Relational History

Information e-services are useful for exchanging information among many users, whether human or automated agent; however, e-service users are susceptible to risk of inaccurate information, since users have no traditional face-to-face interaction or past relational history with information providers. To encourage use of information e-services, individuals must have technology to assess information accuracy and information source trustworthiness. This research permits automated e-service users—here called agents—acting on behalf of humans, to employ policies, or heuristics, for predicting information accuracy when numerous pieces of information are received from multiple sources. These intuitive policies draw from human strategies for evaluating the trustworthiness of information to not only identify accurate information, but also distinguish untrustworthy information providers. These policies allow the agent to build a user’s confidence in the trust assessment technology by creating justifications for trust assessment decisions and identifying particular policies integral to a given assessment decision.

scholarly journals Retraction: The Achilles’ heel hypothesis: misinformed keystone individuals impair collective learning and reduce group success

2020 ◽  
Vol 287 (1931) ◽  
pp. 20200255
Author(s):  
N. Pinter-Wollman ◽  
C. M. Wright ◽  
C. N. Keiser ◽  
A. DeMarco ◽  
M. M. Grobis
Keyword(s):  
Collective Learning ◽  
Group Success

scholarly journals Adaptation of .NET MVC Framework in Developing an Agriculture Sources Inventory System

2018 ◽  
Vol 3 (3) ◽  
pp. 6-13
Author(s):  
Ray Adderley Jm Gining ◽  
Shukor Sanim Mohd Fauzi ◽  
Nabil Fikri Jamaluddin ◽  
Nursyamimi Aima Mohd Azmi ◽  
Muhamad Arif Hashim ◽  
...  
Keyword(s):  
Inventory Management ◽  
Management System ◽  
Inventory System ◽  
Accurate Information ◽  
Wrong Decision ◽  
Inaccurate Information ◽  
Inventory Management System ◽  
Model View Controller ◽  
Main Components ◽  
A Minor

A viable inventory management system is crucial to an organization, especially those who deals with stock going in and out of their premise. The system should cover several aspects in managing the collection of the available stocks to ensure an efficiency. An inventory management system comprises crucial functions that the goal is to produce accurate information – a minor mis-information could lead to a wrong decision making. Improper system design could lead to the problem; thus, the design of this inventory system is supported by .NET Model View Controller (MVC) Framework as its backbone. The .NET MVC Framework is one of the most widely used framework that is written in C# programming language. By utilizing the MVC Framework, its three main components; data model (Model), user interface (View), and business logic (Controller) can be managed separately without affecting the entire system. Thus, the risk of the system functions to produce inaccurate information is reduced significantly. Moreover, MVC also supports scalability, extend-ability and maintainability which is a very important aspect for an information system with growing needs of new functions.

scholarly journals Public Psychosocial and Behavioral Responses in the First Wave of COVID-19 Pandemic: A Large Survey in China

2021 ◽  
Vol 12 ◽  
Author(s):  
Huayu Yang ◽  
Xiaomeng Xian ◽  
Jing Hu ◽  
J. Michael Millis ◽  
Haitao Zhao ◽  
...  
Keyword(s):  
Prevention And Control ◽  
Control Strategies ◽  
Behavioral Responses ◽  
Control Measures ◽  
Natural Phenomenon ◽  
Accurate Information ◽  
Inaccurate Information ◽  
Medical Supplies ◽  
Degree Of Satisfaction ◽  
And Control

Background: The COVID-19 has grown into a global pandemic. This study investigated the public psychosocial and behavioral responses through different time periods of the pandemic, and assessed whether these changes are different in age, gender, and region.Methods: A three-phase survey was conducted through the DaDui Social Q&A Software for COVID-19. A total of 13,214 effective responses of COVID-19 were collected. Statistical analysis was performed based on their basic information and psychosocial responses.Results: The degree of attention, understanding, and cooperation with preventive and control measures of the disease increased and then decreased. The panic level gradually increased with the epidemic process. The degree of satisfaction with management measures and of confidence in defeating COVID-19 increased throughout the survey. Compared with residents in other areas, respondents from the COVID-19 epicenter (Wuhan) reported a higher degree of self-protection during the outbreak and a significantly lower degree of satisfaction with respect to government prevention and control measures during all phases. Shortages of medical supplies and low testing capacity were reported as the biggest shortcoming in the prevention and control strategies during COVID-19, and an abundance of disorderly and inaccurate information from different sources was the primary cause of panic.Conclusions and Relevance: Major public health events elicit psychosocial and behavioral changes that reflect the different phases of the biologic curve. Sufficient medical supplies and improved organization and accurate information during epidemics may reduce panic and improve compliance with requested changes in behavior. We need to recognize this natural phenomenon and our public policy preparedness should attempt to move the social/psychological curve to the left in order to minimize and flatten the biologic curve.

scholarly journals Internal Information Environment and Labor Investment Efficiency

2020 ◽  
Vol 9 (4) ◽  
pp. 70
Author(s):  
Xin Luo ◽  
Fan Zhang
Keyword(s):  
Information Quality ◽  
Optimal Level ◽  
Information Environment ◽  
Accurate Information ◽  
Investment Efficiency ◽  
High Quality ◽  
Union Coverage ◽  
Internal Information

This study investigates the relation between internal information environment and labor investment efficiency. We argue that better internal information quality allows managers to obtain more timely and accurate information from subordinates and therefore make better decisions in labor investments. Our results suggest that the labor investments of firms with high quality internal information have less deviation from the optimal level. This association holds for both companies in industries with high and low union coverage.

scholarly journals DEVELOPMENT OF INTELLIGENT SELF-BALANCING E-BIKE USING MACHINE LEARNING

2021 ◽  
pp. 966-979
Keyword(s):  
Machine Learning ◽  
The Body ◽  
Gradient Algorithm ◽  
Accurate Information ◽  
Reaction Wheel ◽  
Power Requirement ◽  
Inaccurate Information ◽  
Autonomous Cars ◽  
Learning Technique ◽  
Policy Gradient

The self-driving autonomous cars is becoming an increasingly popular concept all around the world but the area of self-driving two wheelers is still under developed. For developing countries like India, two wheelers are affordable than cars for most of the population. The project aims at developing intelligent self-balancing bike using artificial intelligence because the major problem in developing an autonomous bike is in the area of balancing. Even though there are many working mechanisms available for self-balancing of bike, the implementation of AI will be an edge over others from the point of computational power requirement and the programming complexity incurred. A prototype of the bike was developed with reaction wheel mechanism for self-balancing. The mechanism was fully controlled by AI by preventing the need of explicit programming for balancing which was the earlier technique used in self-balancing bike. Reinforcement learning, a type of machine learning technique is adopted for this purpose. The policy gradient algorithm was used to make the bike learn by itself for balancing. Even though the AI algorithm worked well in the virtual environment (balancing a cart-pole) it fails in the real environment. (i.e. it fails to balance the bike). It is because of the noisy data from the sensor, which gives inaccurate information about the orientation of the bike. The noise in the data is due to the vibration of the body when the reaction wheel rotates. This could be solved if the AI is fed with accurate information about the orientation of the vehicle.

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