This paper introduces a concept called task muddiness as a metric for higher intelligence. Task muddiness is meant to be inclusive and expendable in nature. The intelligence required to execute a task is measured by the composite muddiness of the task described by multiple muddiness factors. The composite muddiness explains why many challenging tasks are muddy and why autonomous mental development is necessary for muddy tasks. It facilitates better understanding of intelligence, what the human adult mind can (...) do, and how to build a machine to acquire higher intelligence. The task-muddiness indicates a major reason why a higher biological mind is autonomously developed from autonomous, simple-to-complex experience. The paper also discusses some key concepts that are necessary for understanding the mind and intelligence, such as intelligence metrics, the mode a task is conveyed to the task executor, a human and a machine being a joint task performer in the traditional artificial intelligence (AI), a developmental agent (human or machine) being a sole task performer, and the need for autonomy in task-nonexplicit learning. (shrink)

As artificial intelligence (AI) deployment is growing exponentially, questions have been raised whether the developed AI ethics discourse is apt to address the currently pressing questions in the field. Building on critical theory, this article aims to expand the scope of AI ethics by arguing that in addition to ethical principles and design, the organizational dimension (i.e. the background assumptions and values influencing design processes) plays a pivotal role in the operationalization of ethics in AI development and deployment contexts. (...) Through the prism of critical theory, and the notions of underdetermination and technical code as developed by Feenberg in particular, the organizational dimension is related to two general challenges in operationalizing ethical principles in AI: (a) the challenge of ethical principles placing conflicting demands on an AI design that cannot be satisfied simultaneously, for which the term ‘inter-principle tension’ is coined, and (b) the challenge of translating an ethical principle to a technological form, constraint or demand, for which the term ‘intra-principle tension’ is coined. Rather than discussing principles, methods or metrics, the notion of technical code precipitates a discussion on the subsequent questions of value decisions, governance and procedural checks and balances. It is held that including and interrogating the organizational context in AI ethics approaches allows for a more in depth understanding of the current challenges concerning the formalization and implementation of ethical principles as well as of the ways in which these challenges could be met. (shrink)

Alternative models of similarity judgments that do not rest on metric space assumptions are known to be better descriptions of actual human behaviour but are ignored by Edelman. The internal spaces he postulates are a convenient fiction for artificial intelligence, but not compatible with what is now known about psychophysics at both behavioural and neurological levels of perceptual processing.

The physical and relational structure of the biologic continuum (both internal and external to the organism) creates the information signature that is the basis for the origination of meaning in the living system. A meaning metric can be grounded in the significance of that information to the stability of the system during the process of adaptive reconciliation of divergences from the steady state condition. From this perspective, an information-theoretic formulation of the process for translating incident information into adaptive action is (...) proposed that can be practically used in defining and quantifying the meaning of that information for the living system. (shrink)

This book is open access under a CC BY 4.0 license. This timely book addresses the conflict between globalism and nationalism. It provides a liberal communitarian response to the rise of populism occurring in many democracies. The book highlights the role of communities next to that of the state and the market. It spells out the policy implications of liberal communitarianism for privacy, freedom of the press, and much else. In a persuasive argument that speaks to politics today from Europe (...) to the United States to Australia, the author offers a compelling vision of hope. Above all, the book offers a framework for dealing with moral challenges people face as they seek happiness but also to live up to their responsibilities to others and the common good. At a time when even our most basic values are up for question in policy debates riddled with populist manipulation, Amitai Etzioni’s bold book creates a new frame which introduces morals and values back into applied policy questions. These questions span the challenges of jobless growth to the unanswered questions posed by the role of artificial intelligence in a wide range of daily life tasks and decisions. While not all readers will agree with the communitarian solutions that he proposes, many will welcome an approach that is, at its core, inclusive and accepting of the increasingly global nature of all societies at the same time. It is a must read for all readers concerned about the future of Western liberal democracy. Carol Graham, Leo Pasvolsky Senior Fellow, The Brookings Institution and College Park Professor/University of Maryland In characteristically lively, engaging, and provocative style Etzioni tackles many of the great public policy dilemmas that afflict us today. Arguing that we are trapped into a spiral of slavish consumerism, he proposes a form of liberal communitarian that, he suggests, will allow human beings to flourish in changing circumstances. Jonathan Wolff, Blavatnik Chair of Public Policy, Blavatnik School of Government, University of Oxford. (shrink)

According to how AI has defined itself from its beginning, thinking in non-living matter, i.e., without life, is possible. The premise of symbolic AI is that operating on representations of reality machines can understand it. When this assumption did not work as expected, the mathematical model of the neuron became the engine of artificial “brains.” Connectionism followed. Currently, in the context of Machine Learning success, attempts are made at integrating the symbolic and connectionist paths. There is hope that Artificial General (...) Intelligence (AGI) performance can be achieved. As encouraging as neuro-symbolic AI seems to be, it remains unclear whether AGI is actually a moving target as long as AI itself remains ambiguously defined. This paper makes the argument that the intelligence of machines, expressed in their performance, reflects how adequate the means used for achieving it are. Therefore, energy use and the amount of data necessary qualify as a good metric for comparing natural and artificial performance. (shrink)

Automated neuropsychiatric batteries have been used in research and clinical practice, including for chronic diseases, such as Systemic Lupus Erythematosus. The Pediatric Automated Neuropsychological Assessment Metrics battery, originally developed for use in American-English speaking individuals, allows tracking of cognitive functions. It can be applied to people over 9 years old. The aim of this study was to translate and present initial validation data from the Ped-ANAM into Brazilian-Portuguese. We translated the battery according to Beaton’s guidelines. Psychometric properties were tested, (...) internal consistency was analyzed by Cronbach’s alpha coefficient, test-retest reliability by the intraclass correlation coefficient. Further, we measured the test execution speed at both times as a temporal stability. Principal component analysis was used for structural validity. Evidence of construct validity was assessed through assessment of the relationships with the Wechsler Intelligence Scales. All participants prior to the start of study related activities signed an informed consent form approved by the local ethics committee. A sample of 230 individuals [mean of age: 23 years; 65% females] was included; a subset of 51 individuals [mean of age: 18 years, 59% female] completed the Ped-ANAM twice to assess test-retest reliability, and another subset of 54 individuals [mean of age: 20.4 years; 67% female] completed the Wechsler Intelligence Scales for Children and Adult for assessment of the Ped-ANAM’s construct validity. Our results suggest that the internal consistency of the Ped-ANAM and its subtest test-retest reliability were excellent. There was no clustering in the Principal Components Analysis, suggestive of non-grouping of the evaluated variables. Construct validity assessment to the Wechsler Scales showed expected ranges of low to strong correlations. We concluded that, based on the results of this study, a cross-culturally validated Brazilian-Portuguese version of the Ped-ANAM has been developed and it is a reliable tool for the screening cognitive function. (shrink)

Estimation of discharge flowing through rivers is an important aspect of water resource planning and management. The most common way to address this concern is to develop stage-discharge relationships at various river sections. Various computational techniques have been applied to develop discharge ratings and improve the accuracy of estimated discharges. In this regard, the present study explores the application of the novel hybrid multigene genetic programming-generalized reduced gradient technique for estimating river discharges for steady as well as unsteady flows. It (...) also compares the MGGP-GRG performance with those of the commonly used optimization techniques. As a result, the rating curves of eight different rivers were developed using the conventional method, evolutionary algorithm, the modified honey bee mating optimization algorithm, artificial neural network, MGGP, and the hybrid MGGP-GRG technique. The comparison was conducted on the basis of several widely used performance evaluation criteria. It was observed that no model outperformed others for all datasets and metrics considered, which demonstrates that the best method may be different from one case to another one. Nevertheless, the ranking analysis indicates that the hybrid MGGP-GRG model overall performs the best in developing stage-discharge relationships for both single-value and loop rating curves. For instance, the hybrid MGGP-GRG technique improved sum of square of errors obtained by the conventional method between 4.5% and 99% for six out of eight datasets. Furthermore, EA, the MHBMO algorithm, and artificial intelligence models performed satisfactorily in some of the cases, while the idea of combining MGGP with GRG reveals that this hybrid method improved the performance of MGGP in this specific application. Unlike the black box nature of ANN, MGGP offers explicit equations for stream rating curves, which may be counted as one of the advantages of this AI model. (shrink)

The Turing Test is of limited use for entities differing substantially from human performance levels. We suggest an extension of Turing’s idea to a more differentiated measure - the "Turing Ratio" - which provides a framework for comparing human and algorithmic task performance, up to and beyond human performance levels. Games and talent levels derived from pairwise comparisons provide examples of the concept. We also discuss the related notions of intelligence amplification and task breadth. Intelligence amplification measures total (...) computational efficiency (the computational benefit gained relative to investment, including programmer time, hardware, and so on); we argue that evolutionary computation is a key amplifier of human intelligence. Task breadth is an attempt to weight Turing Ratios by the frequency and importance of the task they measure - doing well at a broad range of tasks is an empirical definition of “intelligence”. Measuring Turing Ratios and considering task breadth, prior knowledge, and time series of the measures may yield long-term insight into both open-ended computational approaches and the underlying task domains being measured. (shrink)

If a trademark becomes a generic term, it may be cancelled under trademark law, a process known as genericide. Typically, in genericide cases, consumer surveys are brought into evidence to establish a mark’s semantic status as generic or distinctive. Some drawbacks of surveys are cost, delay, small sample size, lack of reproducibility, and observer bias. Today, however, much discourse involving marks is online. As a potential complement to consumer surveys, therefore, we explore an artificial intelligence approach based chiefly on (...) word embeddings: mathematical models of meaning based on distributional semantics that can be trained on texts selected for jurisdictional and temporal relevance. After identifying two main factors in mark genericness, we first offer a simple screening metric based on the ngram frequency of uncapitalized variants of a mark. We then add two word embedding metrics: one addressing contextual similarity of uncapitalized variants, and one comparing the neighborhood density of marks and known generic terms in a category. For clarity and validation, we illustrate our metrics with examples of genericized, somewhat generic, and distinctive marks such as, respectively, DUMPSTER, DOBRO, and ROLEX. (shrink)

We review the literature on how perceiving an AI making mistakes violates trust and how such violations might be repaired. In doing so, we discuss the role played by various forms of algorithmic transparency in the process of trust repair, including explanations of algorithms, uncertainty estimates, and performance metrics.

Amblyopia, or lazy eye, is a neurological vision disorder that studies have shown to affect two to five percent of the population. Current methods of treatment produce the best visual outcome, if the condition is identified early in the patient's life. Several early screening procedures are aimed at finding the condition while the patient is a child, including an automated vision screening system. This paper aims to use artificial intelligence techniques to automatically identify children who are at risk for (...) developing the amblyopic condition and should therefore be referred to a specialist, i.e., pediatric ophthalmologist. Three techniques, namely, decision tree learning, random forest, and artificial neural network, are studied in this paper in terms of their effectiveness, using metrics of sensitivity, specificity, and accuracy. The features used by the techniques are extracted from images of patient eyes and are based on the color information. The efficacy of pixel color data is investigated with respect to the measurement of the rate of change of the color in the iris and pupil, i.e., color slope features. A 10-fold stratified cross validation procedure is used to compare the effectiveness of the three AI techniques in this medical application domain. (shrink)

Intelligent communication processing in English aims to obtain effective information from unstructured text data using various text processing techniques. Text vector representation and text similarity calculation are important fundamental tasks in the whole field of natural language processing. In response to the shortcomings of existing sentence vector representation models and the singularity of text similarity algorithms, improved models and algorithms are proposed based on a thorough study of related domain technologies. This paper presents an in-depth and comprehensive study of text (...) vectorization representation and text similarity calculation algorithms in the field of natural language processing. The existing text vectorized representation models and text similarity computation algorithms are described, and their shortcomings are summarized to provide a basis for the background and significance of this paper, as well as to provide ideas for improvement directions. It is experimentally verified that the sentence vector model proposed in this paper achieves higher accuracy than the SIF sentence vector model for text classification tasks. In the task of text similarity computation, it achieves better results in three evaluation metrics: accuracy, recall, and F1 value. The algorithm also improves the computational efficiency of the model to a certain extent by removing feature words with low feature contribution. The algorithm first improves the deficiencies of the traditional word-shift distance algorithm by defining multifeature fusion weights and realizes a text similarity calculation algorithm based on multifeature weighted fusion with better similarity calculation results. Then, a linear weighting model is constructed to further combine the similarity calculation results of the hierarchical pooled IIG-SIF sentence vectors to realize the multimodel fusion text similarity calculation algorithm. (shrink)

The present study examined the psychometric properties of the Chinese version of the Trait Emotional Intelligence Questionnaire Short Form (TEIQue-SF). Analyses were performed using a sample of undergraduates (N = 585) recruited from four universities across China. Confirmatory factor analysis of the Chinese TEIQue-SF supported the one-factor structure of trait emotional intelligence. Measurement invariance analyses were conducted across the Chinese sample and a sample of Canadian undergraduate students (N = 638). Although the two samples demonstrated configural and partial (...) metric invariance, scalar invariance was not found. Cross-cultural implications and explanations of the present findings, as well as suggestions for future research are discussed. (shrink)

Working memory has been shown to be strongly related to fluid intelligence; however, our goal is to shed further light on the process of information compression in working memory as a determining factor of fluid intelligence. Our main hypothesis was that compression in working memory is an excellent indicator for studying the relationship between working-memory capacity and fluid intelligence because both depend on the optimization of storage capacity. Compressibility of memoranda was estimated using an algorithmic complexity metric. (...) The results showed that compressibility can be used to predict working-memory performance and that fluid intelligence is well predicted by the ability to compress information. We conclude that the ability to compress information in working memory is the reason why both manipulation and retention of information are linked to intelligence. This result offers a new concept of intelligence based on the idea that compression and intelligence are equivalent problems. (shrink)

This paper offers a short and biased overview of the history of discussion and controversy about the role of different forms of representation in intelligent agents. It repeats and extends some of the criticisms of the `logicist' approach to AI that I first made in 1971, while also defending logic for its power and generality. It identifies some common confusions regarding the role of visual or diagrammatic reasoning including confusions based on the fact that different forms of representation may be (...) used at different levels in an implementation hierarchy. This is contrasted with the way in the use of one form of representation (e.g. pictures) can be {\em controlled} using another (e.g. logic, or programs). Finally some questions are asked about the role of metrical information in biological visual systems. (shrink)

Mayer, Caruso, and Salovey provide useful updates to the EI ability model and related concepts. However, they do not acknowledge conceptual limitations with the MSCEIT proportion scoring algorithm. In our view, failure to recognize these limitations has impeded refinements to the EI ability model and delayed support for positioning EI within the Cattell-Horn-Carroll three-stratum theory of intelligence. Fully appreciating algorithm-related issues justifies the reanalysis of MSCEIT data and may expand the range of metrics that are available to refine (...) EI theory. (shrink)

Cloud computing deals with voluminous heterogeneous data, and there is a need to effectively distribute the load across clusters of nodes to achieve optimal performance in terms of resource usage, throughput, response time, reliability, fault tolerance, and so on. The swarm intelligence methodologies use artificial intelligence to solve computationally challenging problems like load balancing, scheduling, and resource allocation at finite time intervals. In literature, sufficient works are being carried out to address load balancing problem in the cloud using (...) traditional swarm intelligence techniques like ant colony optimization, particle swarm optimization, cuckoo search, bat optimization, and so on. But the traditional swarm intelligence techniques have issues with respect to convergence rate, arriving at the global optimum solution, complexity in implementation and scalability, which limits the applicability of such techniques in cloud domain. In this paper, we look into performance modeling aspects of some of the recent competitive swarm artificial intelligence based techniques like the whale, spider, dragonfly, and raven which are used for load balancing in the cloud. The results and analysis are presented over performance metrics such as total execution time, response time, resource utilization rate, and throughput achieved, and it is found that the performance of the raven roosting algorithm is high compared to other techniques. (shrink)

The internal structure of ability emotional intelligence tests at item level has been hardly studied, and if studied often the predicted structure did not show. In the present study, an a priori model for responses to EI ability items using Likert response scales with a Situational Judgement Test format is investigated with confirmatory factor analysis. The model consists of a target EI ability factor, an acquiescence factor, which is a method factor induced by the Likert response scales, and design-based (...) error covariances, which are induced by the SJT format. It is investigated whether this a priori model can account for the observed associations between the raw item responses of the Components of Emotion Understanding Test-24. The CEUT-24 is a new test developed to assess emotion understanding, a key aspect of the EI ability construct, based on the componential emotion framework. The sample consisted of 1184 participants from four European countries speaking four different languages. Findings showed that the a priori model fitted the data well in all four languages. Furthermore, measurement invariance testing gave evidence for a well-fitting configural, metric, and partial scalar invariance model. The conclusion is that within a regular CFA framework using raw observed items responses, method factors can be disentangled from the targeted EI ability factor. (shrink)

Social service organizations have long used data in their efforts to support people in need for the purposes of advocacy, tracking, and intervention. Increasingly, such organizations are joining forces to provide wrap-around services to clients in order to “move the needle” on intractable social problems. Groups using these strategies, called Collective Impact, develop shared metrics to guide their work, sharing data, finances, infrastructure, and services. A major emphasis of these efforts is on tracking clients and measuring impacts. This study (...) explores a particular type of Collective Impact strategy called Promise Neighborhoods. Based on a federal grant program, these initiatives attempt to close the achievement gap in particular geographic communities. Through an analysis of publicly available documents and information, the study analyzes the ways these strategies enact a collective intelligence for the common good. The analysis focuses specifically on issues surrounding data collection and use, youth agency, leadership and governance, and funding streams. Together, these foci develop a story of an increasingly used “intelligence” with a limited sense of “collective” and a narrow vision of a “common good.” Using this as a platform, the paper explores alternatives that might develop more robust practices around these concepts. (shrink)

Corporate governance delivers feasible and controlled company operations using a group of common shareholders and appropriate policies. The roles and responsibilities of the shareholders suggest and improve corporate development through monotonous and independent rights. The implication of artificial intelligence provides knowledgeable insights for decision-making and control management. This article introduces a Mutual Consent-based Governance Regulation Model for dissimilarity mitigation in corporate rule implications. The proposed model exploits transfer learning for balanced rule implication and decision-making. The learning states are defined (...) based on mutual agreement, individual interest, and operational features. Based on the governance policies, the above rules are employed without hindering the pioneer regulations implemented in different periods. Therefore, artificial intelligence technology is utilized for prompt and swift governance decisions in delivering special rights for consumers and shareholders. The performance of this model is validated and verified using data sources related to governance policies from a real-time industry. The impact of varying policy features with dissimilarity is analyzed for varying occurrences. The analysis is given based on the considered data sources for which the classification and its impact over reports, sharing, voting, complaint, and market are analyzed. The availability before and after the proposed improves the above metrics by 10.48, 10.65, 9.78, 13.39, and 9.26%. (shrink)

It is a popular view thatpractical deliberation excludes foreknowledge of one's choice. Wolfgang Spohn and Isaac Levi have argued that not even a purely probabilistic self-predictionis available to thedeliberator, if one takes subjective probabilities to be conceptually linked to betting rates. It makes no sense to have a betting rate for an option, for one's willingness to bet on the option depends on the net gain from the bet, in combination with the option's antecedent utility, rather than on the offered (...) odds. And even apart from this consideration, assigning probabilities to the options among which one is choosing is futile since such probabilities could be of no possible use in choice. The paper subjects these arguments to critical examination and suggests that, appearances notwithstanding, practical deliberation need not crowd outself-prediction. (shrink)