The rapid pace of development over the last few decades in the domain of machine learning mirrors the advances made in the field of quantum computing. It is natural to ask whether the conventional machine learning algorithms could be optimized using the present-day noisy intermediate-scale quantum technology. There are certain computational limitations while training a machine learning model on a classical computer. Using quantum computation, it is possible to surpass these limitations and carry out such calculations in an optimized manner. (...) This study illustrates the working of the quantum support vector machine classification model which guarantees an exponential speed-up over its typical alternatives. This research uses the quantum SVM model to solve the classification task of a malignant breast cancer diagnosis. This study also demonstrates a comparative analysis of distinct forms of SVM algorithms concerning their time complexity and performances on standard evaluation metrics, namely accuracy, precision, recall, and F1-score, to exemplify the supremacy of quantum SVM over its conventional variants. (shrink)

Depiction of etiquette or good manners in Mahābhārata, Hindu classical epic.

In this paper, a HIV-TB co-infection model is explored which incorporates a non-linear treatment rate for TB. We begin with presenting a HIV-TB co-infection model and analyze both HIV and TB sub-models separately. The basic reproduction numbers corresponding to HIV-only, TB-only and the HIV-TB full model are computed. The disease-free equilibrium point of the HIV sub-model is shown to be locally as well as globally asymptotically stable when its corresponding reproduction number is less than unity. The HIV-only model exhibits a (...) transcritical bifurcation. On the other hand, for the TB sub-model, the disease-free equilibrium point is locally asymptotically stable but may not be globally asymptotically stable. We have also analyzed the full HIV-TB co-infection model. Numerical simulations are performed to investigate the effect of treatment rate in the presence of resource limitation for TB infected individuals, which emphasize the fact that to reduce co-infection from the population programs to accelerate the treatment of TB should be implemented. (shrink)

Research on the ethics of algorithms has grown substantially over the past decade. Alongside the exponential development and application of machine learning algorithms, new ethical problems and solutions relating to their ubiquitous use in society have been proposed. This article builds on a review of the ethics of algorithms published in 2016, 2016). The goals are to contribute to the debate on the identification and analysis of the ethical implications of algorithms, to provide an updated analysis of epistemic and normative (...) concerns, and to offer actionable guidance for the governance of the design, development and deployment of algorithms. (shrink)

Research on the ethics of algorithms has grown substantially over the past decade. Alongside the exponential development and application of machine learning algorithms, new ethical problems and solutions relating to their ubiquitous use in society have been proposed. This article builds on a review of the ethics of algorithms published in 2016, 2016). The goals are to contribute to the debate on the identification and analysis of the ethical implications of algorithms, to provide an updated analysis of epistemic and normative (...) concerns, and to offer actionable guidance for the governance of the design, development and deployment of algorithms. (shrink)

Cognitive control enables people to adjust their thoughts and actions according to the current task demands. Response inhibition and response adjustment are two key aspects of cognitive control. Here, we examined how the implicit processing of emotional information influences these two functions with the help of the double-step saccade task. Each trial had either a single target or two sequential targets. Upon a single target onset, participants were required to make a quick saccade, but upon two target onsets, participants were (...) instructed to inhibit their initial saccades and redirect their gaze to the second target. In three experiments, we manipulated the emotional information of the first and second targets. We found that irrelevant emotional information of the first target impaired response inhibition compared to non-emotional information (geometric shapes) of the first target. When non-emotional information (geometric shape) came as the first target, irrelevant angry emotional faces as the second target interfered with both response inhibition and response adjustment compared to irrelevant happy and neutral faces. We explain these results with previous findings that processing faces with irrelevant angry facial expressions take up many attentional resources, leaving fewer resources available for ongoing activities such as response inhibition and response adjustment. (shrink)

Artificial intelligence research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, term in this article AI-Crime. AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young and inherently (...) interdisciplinary area—spanning socio-legal studies to formal science—there is little certainty of what an AIC future might look like. This article offers the first systematic, interdisciplinary literature analysis of the foreseeable threats of AIC, providing ethicists, policy-makers, and law enforcement organisations with a synthesis of the current problems, and a possible solution space. (shrink)

The gig economy is a phenomenon that is rapidly expanding, redefining the nature of work and contributing to a significant change in how contemporary economies are organised. Its expansion is not unproblematic. This article provides a clear and systematic analysis of the main ethical challenges caused by the gig economy. Following a brief overview of the gig economy, its scope and scale, we map the key ethical problems that it gives rise to, as they are discussed in the relevant literature. (...) We map them onto three categories: the new organisation of work (what is done), the new nature of work (how it is done), and the new status of workers (who does it). We then evaluate a recent initiative from the EU that seeks to address the challenges of the gig economy. The 2019 report of the European High-Level Expert Group on the Impact of the Digital Transformation on EU Labour Markets is a positive step in the right direction. However, we argue that ethical concerns relating to algorithmic systems as mechanisms of control, and the discrimination, exclusion and disconnectedness faced by gig workers require further deliberation and policy response. A brief conclusion completes the analysis. The appendix presents the methodology underpinning our literature review. (shrink)

Artificial Intelligence research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, term in this chapter AI-Crime. AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young and inherently (...) interdisciplinary area—spanning socio-legal studies to formal science—there is little certainty of what an AIC future might look like. This chapter offers the first systematic, interdisciplinary literature analysis of the foreseeable threats of AIC, providing ethicists, policy-makers, and law enforcement organisations with a synthesis of the current problems, and a possible solution space. (shrink)

Closed Loop medical devices such as Closed Loop Deep Brain Stimulation and Brain Computer Interface are some of the emerging neurotechnologies. New generations of implantable brain–computer interfaces have recently gained success in human clinical trials. These implants detect specific neuronal patterns and provide the subject with information to respond to these patterns. Further, Closed Loop brain devices give control to the subject so that he can respond and decide on a therapeutic goal. Although the implants have improved subjects’ quality of (...) life, their use has raised varied ethical concerns. The aim of this study is to provide an overview of the ethical implications specific to the therapeutic goals of closed loop brain implants. The authors analyze the related work qualitatively and quantitatively so as to help readers in understanding the various ethical implications of closed loop brain implants. (shrink)

Recent advances in the capability of digital information technologies—particularly due to advances in artificial intelligence —have invigorated the debate on the ethical issues surrounding their use. However, this debate has often been dominated by ‘Western’ ethical perspectives, values and interests, to the exclusion of broader ethical and socio-cultural perspectives. This imbalance carries the risk that digital technologies produce ethical harms and lack social acceptance, when the ethical norms and values designed into these technologies collide with those of the communities in (...) which they are delivered and deployed. This special issue takes a step towards broadening the approach of digital ethics, by bringing together a range of cultural, social and structural perspectives on the ethical issues relating to digital information technology. Importantly, it refreshes and reignites the field of Intercultural Digital Ethics for the age of AI and ubiquitous computing. (shrink)

Libertarian paternalism is a concept derived from cognitive psychology and behavioural science. It is behind policies that frame information in such a way as to encourage individuals to make choices which are in their best interests, while maintaining their freedom of choice. Clinicians may view their clinical consultations as far removed from the realms of cognitive psychology but on closer examination there are a number of striking similarities.

Organizations are increasingly looking for ways to reap the benefits of cognitive diversity for problem solving. A major unanswered question concerns the implications of cognitive diversity for longer-term outcomes such as team learning, with its broader effects on organizational learning and productivity. We study how cognitive style diversity in teams—or diversity in the way that team members encode, organize and process information—indirectly influences team learning through collective intelligence, or the general ability of a team to work together across a wide (...) array of tasks. Synthesizing several perspectives, we predict and find that cognitive style diversity has a curvilinear—inverted U-shaped—relationship with collective intelligence. Collective intelligence is further positively related to the rate at which teams learn, and is a mechanism guiding the indirect relationship between cognitive style diversity and team learning. We test the predictions in 98 teams using ten rounds of the minimum-effort tacit coordination game. Overall, this research advances our understanding of the implications of cognitive diversity for organizations and why some teams demonstrate high levels of team learning in dynamic situations while others do not. (shrink)

The world relies on authentic research that guides legislation, policy formulations, and governmental and corporate actions. Therefore, researchers globally should be aware of academic integrity and publication ethics. This research delved into plagiarism that severely undermines any scientific study. It explores the relationship between adverse attitudes (attitudes that favor plagiarism) and plagiaristic behavior. We probed deeper into the theories of planned behavior, reasoned action, and ethical theories of rational self-interest, cultural acceptance, and deontology to propose corrective measures as an intervention (...) to reduce adverse attitudes and plagiaristic behavior. Upon empirical testing of the said propositions through two studies (Study 1, n1 = 2609; Study 2, n2 = 2678), we ascertained a significant negative relationship between corrective measures and adverse attitudes and corrective measures and plagiaristic behavior. We also empirically examined the mediating effect of adverse attitudes on the relationship between corrective measures and plagiaristic behavior. The results confirm the mediation model, in which academics subjected to corrective actions reported reduced plagiaristic behavior through reduced adverse attitudes. The findings further the literature on plagiarism and provide crucial implications for managing plagiaristic behavior among academics. The study also provides specific corrective actions that educational administrators should initiate to ensure academic integrity. (shrink)

Vāda, the classical name for the act of discussion/debate in the Indian tradition, forms the basis of every conversation undertaken to reach correct knowledge. The paper explores the Indian tradition of Vāda and its subcategories with the intention of highlighting the all-encompassing and holistic nature of this Indian tool of cultural studies in both theory and praxis. It checks into its evolution through contemporary times, wherein it has lost its essence to accommodate the corrupted interests of modern individuals as well (...) as leaders and debaters. Through the analysis of various examples, the paper endeavours to establish Vāda as a comprehensive way to attain correct knowledge. Examples from day-to-day life as well as the historic-literary world help to explicitly comprehend these tools that have been used for establishing the nearest truth from ancient times in India. These tools are potent to all aspects of research across spatial-temporal limits as they are innate and immutable to all disciplines of knowledge and education. (shrink)

Broadly defined, government corruption is the abuse of public power for private gain. It can assume various forms, including bribery, embezzlement, cronyism, and electoral fraud. At root, however, government corruption is a problem of trust. Corrupt politicians abuse the powers entrusted to them by the electorate (the principal-agent problem). Politicians often resort to corruption out of a lack of trust that other politicians will abstain from it (the collective action problem). Corruption breeds greater mistrust in elected officials amongst the public. (...) The problem of trust is compounded where a lack of transparency and asymmetric information impede effective control over the exercise of public powers. (shrink)

This article addresses the question of how ‘Country of Origin Information’ reports—that is, research developed and used to support decision-making in the asylum process—can be published in an ethical manner. The article focuses on the risk that published COI reports could be misused and thereby harm the subjects of the reports and/or those involved in their development. It supports a situational approach to assessing data ethics when publishing COI reports, whereby COI service providers must weigh up the benefits and harms (...) of publication based, inter alia, on the foreseeability and probability of harm due to potential misuse of the research, the public good nature of the research, and the need to balance the rights and duties of the various actors in the asylum process, including asylum seekers themselves. Although this article focuses on the specific question of ‘how to publish COI reports in an ethical manner’, it also intends to promote further research on data ethics in the asylum process, particularly in relation to refugees, where more foundational issues should be considered. (shrink)

Working from home (WFH) is a new reality and norm in today’s work culture. COVID-induced lockdown introduced the concept of WFH for many people. Blurring home and workplace boundaries was a prominent cause of disorientation in people’s lives. Hence, WFH becomes a significant phenomenon to explore as it raises the fundamental question of body and space in shaping people’s experiences. To study this, the researchers designed a phenomenological inquiry and examined the lived phenomenon of WFH during the COVID lockdown. Borrowing (...) theoretical concepts from philosophers Martin Heidegger and Merleau-Ponty, they aimed to understand human experiences from an embodied perspective. They interviewed a few adults (age group 27–50) in three urban Indian cities during the first phase of the COVID-19 lockdown. The participants’ experiences were transcribed, and Interpretative Phenomenological Analysis (IPA) was conducted. The IPA themes highlighted their varied lived experiences and lifeworld, such as distractions in working from home, their changed routines, habits, and social interaction. The findings are discussed through phenomenological psychology concepts such as embodied cognition, body memory, extended self, shared empathy, intersubjectivity and pre-reflective bodily intelligence in coping. The study’s contribution is that it advances a methodological understanding by interpreting people’s experiences from a phenomenological view of being-in-the-world in which the individual is not an isolated entity but is in the world/placed in the world with other people and the environment. (shrink)

The article discusses the relationship between organizational culture and psychological capital through a systematic literature review. The exploratory research methodology is adopted to identify and study the existing gap in the available literature on the relationship between organizational culture and psychological capital from year 2000 to 2021. The articles from the ‘Scopus’ and ‘Web of Science’ databases were selected for the review. The literature review mentions a positive interplaying role between organizational culture and PsyCap that influences several factors including work (...) happiness, job performance, Organizational Citizenship Behaviour, burnout, innovation, etc. The article explores several antecedents and consequences of the two-way relationship between organizational culture and PsyCap. (shrink)

Business Ethics, the Environment &Responsibility, Volume 31, Issue 4, Page 1053-1101, October 2022.

This research updates and significantly extends Akaah and Riordon’s (J Market Res 26:112–120, 1989 ) evaluation of ethical perceptions of marketing research misconduct among marketing research professionals. In addition to examining changes in perceptions toward key marketing research practices over time, we assess professionals’ judgments on the ethicality, importance, and occurrence of a variety of new marketing research ethics situations in both online and offline contexts. In a second study, we assess ethical judgments of the public at large using a (...) representative sample of US consumers—key stakeholders ignored in prior research on unethical marketing research practices. Generally speaking, disapproval of unethical research conduct has grown across the board in the last 20 years for both managers and marketing researchers. The same misconduct elicits a stronger disapproval in the online environment compared to the offline environment. Compared to marketing researchers, managers tend to think that unethical research conduct occurs more frequently. Those who conduct marketing research or use its findings (i.e., marketing researchers and managers) are less tolerant of unethical research conduct than the general public. (shrink)

Deep neural networks (DNNs) have been playing a significant role in acoustic modeling. Convolutional neural networks (CNNs) are the advanced version of DNNs that achieve 4–12% relative gain in the word error rate (WER) over DNNs. Existence of spectral variations and local correlations in speech signal makes CNNs more capable of speech recognition. Recently, it has been demonstrated that bidirectional long short-term memory (BLSTM) produces higher recognition rate in acoustic modeling because they are adequate to reinforce higher-level representations of acoustic (...) data. Spatial and temporal properties of the speech signal are essential for high recognition rate, so the concept of combining two different networks came into mind. In this paper, a hybrid architecture of CNN-BLSTM is proposed to appropriately use these properties and to improve the continuous speech recognition task. Further, we explore different methods like weight sharing, the appropriate number of hidden units, and ideal pooling strategy for CNN to achieve a high recognition rate. Specifically, the focus is also on how many BLSTM layers are effective. This paper also attempts to overcome another shortcoming of CNN, i.e. speaker-adapted features, which are not possible to be directly modeled in CNN. Next, various non-linearities with or without dropout are analyzed for speech tasks. Experiments indicate that proposed hybrid architecture with speaker-adapted features and maxout non-linearity with dropout idea shows 5.8% and 10% relative decrease in WER over the CNN and DNN systems, respectively. (shrink)

Business leadership increasingly requires a master’s degree in business and graduate management admission test scores continue to be an important component of applications for admission to such programs. Given the ubiquitous use of GMAT scores as gatekeepers for business leadership, GMAT scores are likely to influence organizational ethical behavior through gender, cultural, and other biases in the GMAT. There is little prior literature in this area and we contribute by empirically documenting that GMAT scores are negatively related to the cultural (...) dimensions of masculinity and power distance and are positively related to math literacy, uncertainty avoidance, and individualism. We estimate that cultural factors may account for as much as an 80-point difference in cross-national mean GMAT scores which are also related negatively to local language literacy, national educational spending, wealth per capita, wealth inequality, and gender development. Most interestingly, we also find a significant negative association of GMAT scores with ethical orientation. These findings have important implications for business schools and corporate ethics and leadership. (shrink)

Ethical debates over the use of mental health knowledge and practice at the Guantánamo Bay detention facility have mostly revolved around military clinicians sharing detainee medical information with interrogators, falsifying death certificates in interrogations, and disagreements over whether the Central Intelligence Agency’s “enhanced interrogation techniques” violated bioethical principles to do no harm. However, debates over the use of magnetic resonance imaging in the mental health evaluations of detainees have received little attention. This paper provides the first known analysis of such (...) debates over MRI use in the case of Abd al-Rahim al- Nashiri. Through a close reading of open-source legal documents such as defense motions, prosecution motions, judge rulings, and al-Nashiri’s mental health evaluation, debates over MRI use become interpretive contests over the very meanings of mental illness and the extent to which MRI results can verify whether he was tortured in CIA custody. Such work can revitalize interest in the neuroethics of national security. (shrink)

Background Most studies on medical reasoning focus on contemporary allopathic practitioners. Here, the significance of diagnostic sense in Nizāmī ‘Arūzī’s Four Discourses (Chahār Maqāle), an influential text that circulated widely throughout the Islamic world, is explored. Methods After a brief introduction, key passages are translated on how doctors should cultivate analytical skills. Results Nizāmī ‘Arūzī cites three sources of diagnostic authority: (1) education in the texts of medical experts, (2) formal logic and (3) belief in the power of God. Conclusions (...) ‘Arūzī’s methods, though rooted in a religious faith that may seem foreign to contemporary doctors and educators, has much to recommend regarding its clarity of approach, its high ethical standards and expectations of doctors, and its commitment to best practices for the patient. Crosscultural studies of medical education and professionalism can offer valuable insights by demonstrating how doctors across history and geography have grappled with the common concerns of diagnosis and treatment. (shrink)

This paper implements the continuous Hindi Automatic Speech Recognition (ASR) system using the proposed integrated features vector with Recurrent Neural Network (RNN) based Language Modeling (LM). The proposed system also implements the speaker adaptation using Maximum-Likelihood Linear Regression (MLLR) and Constrained Maximum likelihood Linear Regression (C-MLLR). This system is discriminatively trained by Maximum Mutual Information (MMI) and Minimum Phone Error (MPE) techniques with 256 Gaussian mixture per Hidden Markov Model(HMM) state. The training of the baseline system has been done using (...) a phonetically rich Hindi dataset. The results show that discriminative training enhances the baseline system performance by up to 3%. Further improvement of ~7% has been recorded by applying RNN LM. The proposed Hindi ASR system shows significant performance improvement over other current state-of-the-art techniques. (shrink)

African philosophy in the twentieth century is largely the work of African intellectuals under the influence of philosophical traditions from the colonial countries. Among them are few names such as Amilcar Cabral, Franz Fanon, Kwame Nkrumah, and Julius Nyerere etc. This paper is an attempt to analyze the politicalphilosophy of Nkrumah, first President of Republic of Ghana in West Africa. The paper argues that from the African political and economic point of view Nkrumah advocated a socialist system created out of (...) the enculturation of African humanist values with the inherited European political culture and social traditions to liberate unite and integrate Ghana and rest of Africa. Following an interdisciplinary approach this paper assesses Nkrumah’s thought both as an individual, intellectual and as a politician. His book ‘Consciencism’ describes the more political than socio-economic approach to class contradictions in African society. In his ‘Handbook of Revolutionary Warfare’ he talked of three objectives i.e. nationalism, pan-Africanism and socialism. He offered the African liberationmovement a strategy of socialist revolution. Nkrumah who had earlier embraced Gandhian non-violence positive action later adopted the Fanonian lines of revolutionary violence recommending the use of universal method i.e. armed struggle to defeat colonialism.. Nkrumah played an important part in spreading the ideas of socialism in Africa. He had a holistic politico-cultural thought that was reflected in many of his speeches and works. Though critics in his thought have found profound contradictions or confusions but none can obscure the main achievements. Remembered as ‘the redeemer’ by the Africans, he provided the charisma they needed for a leading statesman against any form of imperialism. (shrink)

Scholars have mostly analyzed information from mental health practitioners, attorneys, and institutions to critique mental health practices in the War on Terror. These sources offer limited insights into the suffering of detainees. Detainee accounts provide novel information based on their experiences at Guantánamo. Mohamedou Ould Slahi’s Guantánamo Diary is the only text from a current detainee that provides a first-person account of his interrogations and interactions with health professionals. Despite being advertised as a diary, however, it has undergone redaction from (...) American government officials. This article examines Slahi’s account of his interrogations and representations of mental health at Guantánamo and considers its role within the narrative function of the nation. At stake is the right of detainees to narrate, scholars to critique medical practices in the War on Terror, and the nation’s attempts to control its narration. (shrink)

Macromolecular interactions play a central role in many biological processes. Protein‐protein interactions have mostly been studied by co‐immunoprecipitation, which cannot provide quantitative information on all possible molecular connections present in the complex. We will review a new approach that allows cellular proteins and biomolecular complexes to be studied in real‐time at the single‐molecule level. This technique is called single‐molecule pull‐down (SiMPull), because it integrates principles of conventional immunoprecipitation with the powerful single‐molecule fluorescence microscopy. SiMPull is used to count how many (...) of each protein is present in the physiological complexes found in cytosol and membranes. Concurrently, it serves as a single‐molecule biochemical tool to perform functional studies on the pulled‐down proteins. In this review, we will focus on the detailed methodology of SiMPull, its salient features and a wide range of biological applications in comparison with other biosensing tools. (shrink)

Millions of memes are created and shared every day on social media platforms. Memes are a great tool to spread humour. However, some people use it to target an individual or a group generating offensive content in a polite and sarcastic way. Lack of moderation of such memes spreads hatred and can lead to depression like psychological conditions. Many successful studies related to analysis of language such as sentiment analysis and analysis of images such as image classification have been performed. (...) However, most of these studies rely only upon either one of these components. As classifying meme is one problem which cannot be solved by relying upon only any one of these aspects, the present work identifies, addresses, and ensembles both the aspects for analyzing such data. In this research, we propose a solution to the problems in which the classification depends on more than one model. This paper proposes two different approaches to solve the problem of identifying hate memes. The first approach uses sentiment analysis based on image captioning and text written on the meme. The second approach is to combine features from different modalities. These approaches utilize a combination of glove, encoder-decoder, and OCR with Adamax optimizer deep learning algorithms. Facebook Challenge Hateful Meme Dataset is utilized which contains approximately 8500 meme images. Both the approaches are implemented on the live challenge competition by Facebook and predicted quite acceptable results. Both approaches are tested on the validation dataset, and results are found to be promising for both models. (shrink)

The purpose of cognitive models is to make predictive simulations of human behaviour, but this is often done at the aggregate level. Cranford, Gonzalez, Aggarwal, Cooney, Tambe, and Lebiere show that they can automatically customize a model to a particular individual on‐the‐fly, and use it to make specific predictions about their next actions, in the context of a particular cybersecurity game.

Ethical morality is one of the significant issues in self-driving cars. The paper provides a newer approach to solve the ethical decision problems in self-driving cars until there is no concrete ethical decision to all problems. This paper gives a two-way approach to solve a problem, with first being the mapping of problem to the solution already known or which has a fixed set of solutions and action priorities defined to a problem previously. Now, if no solution is found or (...) mapping is unsuccessful, then the second stage activates, where the solution from Deep Q-learning model is calculated. It estimates the best Q value and returns that solution or action which maximizes the reward at that instance. The reward function is designed with decreasing priorities and acts accordingly, where the users can change or define their priorities if needed. The case study and results show that the solution that is present in the paper will lead to solving ethical morality problems in self-driving cars up to a great extent. (shrink)

The objective of this study was to jointly analyze the importance of cognitive and financial factors in the accuracy of profit forecasting by analysts. Data from publicly traded Brazilian companies in 2019 were obtained. We used text analysis to assess the cognitive biases from the qualitative reports of analysts. Further, we analyzed the data using statistical regression learning methods and statistical classification learning methods, such as Multiple Linear Regression, k-dependence Bayesian, and Random Forest. The Bayesian inference and classification methods allow (...) an expansion of the research line, especially in the area of machine learning, which can benefit from the examples of factors addressed in this research. The results indicated that, among cognitive biases, optimism had a negative relationship with forecasting accuracy while anchoring bias had a positive relationship. Commonality, to a lesser extent, also had a positive relationship with the analyst’s accuracy. Among financial factors, the most important aspects in the accuracy of analysts were volatility, indebtedness, and profitability. Age of the company, fair value, American Depositary Receipts, performance, and loss were still important but on a smaller scale. The results of the RF models showed a greater explanatory power. This research sheds light on the cognitive as well as financial aspects that influence the analyst’s accuracy, jointly using text analysis and machine learning methods, capable of improving the explanatory power of predictive models, together with the use of training models followed by testing. (shrink)

This work is an initial step toward developing a cognitive theory of cyber deception. While widely studied, the psychology of deception has largely focused on physical cues of deception. Given that present‐day communication among humans is largely electronic, we focus on the cyber domain where physical cues are unavailable and for which there is less psychological research. To improve cyber defense, researchers have used signaling theory to extended algorithms developed for the optimal allocation of limited defense resources by using deceptive (...) signals to trick the human mind. However, the algorithms are designed to protect against adversaries that make perfectly rational decisions. In behavioral experiments using an abstract cybersecurity game (i.e., Insider Attack Game), we examined human decision‐making when paired against the defense algorithm. We developed an instance‐based learning (IBL) model of an attacker using the Adaptive Control of Thought‐Rational (ACT‐R) cognitive architecture to investigate how humans make decisions under deception in cyber‐attack scenarios. Our results show that the defense algorithm is more effective at reducing the probability of attack and protecting assets when using deceptive signaling, compared to no signaling, but is less effective than predicted against a perfectly rational adversary. Also, the IBL model replicates human attack decisions accurately. The IBL model shows how human decisions arise from experience, and how memory retrieval dynamics can give rise to cognitive biases, such as confirmation bias. The implications of these findings are discussed in the perspective of informing theories of deception and designing more effective signaling schemes that consider human bounded rationality. (shrink)