Collective hybrid intelligence: towards a conceptual framework

Implementation of a Decision Support System to Enhance Movement Proficiency Assessment in Sport

Background/Objectives: This study aimed to determine the relationships between seven descriptors of movement proficiency used by an expert to grade an athlete's single-leg squat and the overall subjective 'grade' and the ability to predict a 'grade' based on the descriptors. A secondary aim was to determine the relationships between biomechanical data, the expert-defined descriptors, and the subjective 'grade' and its ability to predict the descriptors' presence and the overall 'grade'. Methods: Single-leg squats in 55 male athletes were graded using expert evaluation, synchronized video, biomechanical data, and decision tree and logistic regression analysis. Results: The model that most accurately predicted 'grade' (94.7%) was a decision tree with the descriptors as inputs. The model with biomechanical data for the descriptor 'foot' was the most accurate one (96.3%), followed by 'lumbar' and 'depth' (85.2%), 'knee' (81.2%), 'pelvis/hip' (71.7%), and 'trunk' (62.3%). These accuracies followed similar order to the intra-rater agreement: 'foot' (0.789), 'lumbar' (0.776), 'knee' (0.725), 'depth' (0.682), 'pelvis/hip' (0.662), and 'trunk' (0.637), indicating that 'trunk', 'pelvis/hip', and 'depth' are potentially the hardest descriptors to assess by the expert. Conclusions: The models developed in this study demonstrate that subjective perceptions can be somewhat accurately explained through a small number of biomechanical indicators. The results of this study support the notion that human movement evaluations should consider both subjective and objective assessments in a complementary manner to accurately evaluate an athlete's movement proficiency.

Artificial Collective Intelligence Engineering: A Survey of Concepts and Perspectives

Collectiveness is an important property of many systems-both natural and artificial. By exploiting a large number of individuals, it is often possible to produce effects that go far beyond the capabilities of the smartest individuals or even to produce intelligent collective behavior out of not-so-intelligent individuals. Indeed, collective intelligence, namely, the capability of a group to act collectively in a seemingly intelligent way, is increasingly often a design goal of engineered computational systems-motivated by recent technoscientific trends like the Internet of Things, swarm robotics, and crowd computing, to name only a few. For several years, the collective intelligence observed in natural and artificial systems has served as a source of inspiration for engineering ideas, models, and mechanisms. Today, artificial and computational collective intelligence are recognized research topics, spanning various techniques, kinds of target systems, and application domains. However, there is still a lot of fragmentation in the research panorama of the topic within computer science, and the verticality of most communities and contributions makes it difficult to extract the core underlying ideas and frames of reference. The challenge is to identify, place in a common structure, and ultimately connect the different areas and methods addressing intelligent collectives. To address this gap, this article considers a set of broad scoping questions providing a map of collective intelligence research, mostly by the point of view of computer scientists and engineers. Accordingly, it covers preliminary notions, fundamental concepts, and the main research perspectives, identifying opportunities and challenges for researchers on artificial and computational collective intelligence engineering.

CAPTCHA for crowdsourced image annotation: directions and efficiency analysis

Purpose

Image annotation plays an important role in image retrieval process, especially when it comes to content-based image retrieval. In order to compensate the intrinsic weakness of machines in performing cognitive task of (human-like) image annotation, leveraging humans’ knowledge and abilities in the form of crowdsourcing-based annotation have gained momentum. Among various approaches for this purpose, an innovative one is integrating the annotation process into the CAPTCHA workflow. In this paper, the current state of the research works in the field and experimental efficiency analysis of this approach are investigated.

Design/methodology/approach

At first, and with the aim of presenting a current state report of research studies in the field, a comprehensive literature review is provided. Then, several experiments and statistical analyses are conducted to investigate how CAPTCHA-based image annotation is reliable, accurate and efficient.

Findings

In addition to study of current trends and best practices for CAPTCHA-based image annotation, the experimental results demonstrated that despite some intrinsic limitations on leveraging the CAPTCHA as a crowdsourcing platform, when the challenge, i.e. annotation task, is selected and designed appropriately, the efficiency of CAPTCHA-based image annotation can outperform traditional approaches. Nonetheless, there are several design considerations that should be taken into account when the CAPTCHA is used as an image annotation platform.

Originality/value

To the best of the authors’ knowledge, this is the first study to analyze different aspects of the titular topic through exploration of the literature and experimental investigation. Therefore, it is anticipated that the outcomes of this study can draw a roadmap for not only CAPTCHA-based image annotation but also CAPTCHA-mediated crowdsourcing and even image annotation.

Economic Efficiency of Outsourcing Business Models: A Comparative Assessment

This study aims to form a methodological approach to assess outsourcing business models and identify the most acceptable one for a modern enterprise. The research methodology is based on the author's approach, which includes cognitive map analysis and a simplicial complex. The study was tested on two Information Technology companies in Russia. Based on the determination of the profit elasticity on the manageable vertices of outsourcing business models, the most attractive in terms of efficiency criterion in the form of profit is the outsourcing business model of developing in-house non-IT services. The analysis of structural connectivity made it possible to rank the factors by the level of importance for the preservation of the business model. Modeling the effectiveness of implementing the formed outsourcing business models provided an opportunity to increase profits for the investigated IT companies by increasing the number of single-type projects. The conducted modeling of changes in relations with customers in the studied IT enterprises shows the inexpediency of changing customer relations in BM3. It is proved that certain factors can be replaced without losing the integrity of the business model. The scientific contribution of this study is the proposed methodological approach for assessing the effectiveness of an outsourcing business model. Based on the application of this methodology, the strategic objectives are linked to the business model in the process of achieving them (the achievement of strategic objectives under the influence of the selected outsourcing business model is shown).

Rogue people: on adversarial crowdsourcing in the context of cyber security

Purpose

Over the past decade, many research works in various disciplines have benefited from the endless ocean of people and their potentials (in the form of crowdsourcing) as an effective problem-solving strategy and computational model. But nothing interesting is ever completely one-sided. Therefore, when it comes to leveraging people's power, as the dark side of crowdsourcing, there are some possible threats that have not been considered as should be, such as recruiting black hat crowdworkers for organizing targeted adversarial intentions. The purpose of this paper is to draw more attention to this critical issue through investigation of its different aspects.

Design/methodology/approach

To delve into details of such malicious intentions, the related literature and previous researches have been studied. Then, four major typologies for adversarial crowdsourced attacks as well as some real-world scenarios are discussed and delineated. Finally, possible future threats are introduced.

Findings

Despite many works on adversarial crowdsourcing, there are only a few specific research studies devoted to considering the issue in the context of cyber security. In this regard, the proposed typologies (and addressed scenarios) for such human-mediated attacks can shed light on the way of identifying and confronting such threats.

Originality/value

To the best of the authors' knowledge, this the first work in which the titular topic is investigated in detail. Due to popularity and efficiency of leveraging crowds' intelligence and efforts in a wide range of application domains, it is most likely that adversarial human-driven intentions gain more attention. In this regard, it is anticipated that the present research study can serve as a roadmap for proposing defensive mechanisms to cope with such diverse threats.