We study a controversial application of algorithmic profiling in the public sector, the Austrian AMAS system. AMAS was supposed to help caseworkers at the Public Employment Service (PES) Austria to allocate support measures to job seekers based on their predicted chance of (re-)integration into the labor market. Shortly after its release, AMAS was criticized for its apparent unequal treatment of job seekers based on gender and citizenship. We systematically investigate the AMAS model using a novel real-world (...) dataset of young job seekers from Vienna, which allows us to provide the first empirical evaluation of the AMAS model with a focus on fairness measures. We further apply bias mitigation strategies to study their effectiveness in our real-world setting. Our findings indicate that the prediction performance of the AMAS model is insufficient for use in practice, as more than 30% of job seekers would be misclassified in our use case. Further, our results confirm that the original model is biased with respect to gender as it tends to (incorrectly) assign women to the group with high chances of re-employment, which is not prioritized in the PES’ allocation of support measures. However, most bias mitigation strategies were able to improve fairness without compromising performance and thus may form an important building block in revising profiling schemes in the present context. (shrink)

ABSTRACT I argue that this examination and appreciation for the shift to abductive reasoning should be extended to the intersection of neuroscience and novel brain-computer interfaces too. This paper highlights the implications of applying abductive reasoning to personalized implantable neurotechnologies. Then, it explores whether abductive reasoning is sufficient to justify insurance coverage for devices absent widespread clinical trials, which are better applied to one-size-fits-all treatments. INTRODUCTION In contrast to the classic model of randomized-control trials, often with a large number of (...) subjects enrolled, precision medicine attempts to optimize therapeutic outcomes by focusing on the individual.[i] A recent publication highlights the strengths and weakness of both traditional evidence-based medicine and precision medicine.[ii] Plus, it outlines a tension in the shift from evidence-based medicine’s inductive reasoning style (the collection of data to postulate general theories) to precision medicine’s abductive reasoning style (the generation of an idea from the limited data available).[iii] The paper’s main example is the application of precision medicine for the treatment of cancer.[iv] I argue that this examination and appreciation for the shift to abductive reasoning should be extended to the intersection of neuroscience and novel brain-computer interfaces too. As the name suggests, brain-computer interfaces are a significant advancement in neurotechnology that directly connects someone’s brain to external or implanted devices.[v] Among the various kinds of brain-computer interfaces, adaptive deep brain stimulation devices require numerous personalized adjustments to their settings during the implantation and computation stages in order to provide adequate relief to patients with treatment-resistant disorders. What makes these devices unique is how adaptive deep brain stimulation integrates a sensory component to initiate the stimulation. While not commonly at the level of sophistication as self-supervising or generative large language models,[vi] they currently allow for a semi-autonomous form of neuromodulation. This paper highlights the implications of applying abductive reasoning to personalized implantable neurotechnologies. Then, it explores whether abductive reasoning is sufficient to justify insurance coverage for devices absent widespread clinical trials, which are better applied to one-size-fits-all treatments.[vii] ANALYSIS I. The State of Precision Medicine in Oncology and the Epistemological Shift While a thorough overview of precision medicine for the treatment of cancer is beyond the scope of this article, its practice can be roughly summarized as identifying clinically significant characteristics a patient possesses (e.g., genetic traits) to land on a specialized treatment option that, theoretically, should benefit the patient the most.[viii] However, in such a practice of stratification patients fall into smaller and smaller populations and the quality of evidence that can be applied to anyone outside these decreases in turn.[ix] As inductive logic helps to articulate, the greater the number of patients that respond to a particular therapy the higher the probability of its efficacy. By straying from this logical framework, precision medicine opens the treatment of cancer to more uncertainty about the validity of these approaches to the resulting disease subcategories.[x] Thus, while contemporary medical practices explicitly describe some treatments as “personalized”, they ought not be viewed as inherently better founded than other therapies.[xi] A relevant contemporary case of precision medicine out of Norway focuses on the care of a patient with cancer between the ventricles of the heart and esophagus, which had failed to respond to the standard regimen of therapies over four years.[xii] In a last-ditch effort, the patient elected to pay out-of-pocket for an experimental immunotherapy (nivolumab) at a private hospital. He experienced marked improvements and a reduction in the size of the tumor. Understandably, the patient tried to pursue further rounds of nivolumab at a public hospital. However, the hospital initially declined to pay for it given the “lack of evidence from randomised clinical trials for this drug relating to this [patient’s] condition.”[xiii] In rebuttal to this claim, the patient countered that he was actually similar to a subpopulation of patients who responded in “open‐label, single arm, phase 2 studies on another immune therapy drug” (pembrolizumab).[xiv] Given this interpretation of the prior studies and the patient’s response, further rounds of nivolumab were approved. Had the patient not had improvements in the tumor’s size following a round of nivolumab, then pembrolizumab’s prior empirical evidence in isolation would have been insufficient, inductively speaking, to justify his continued use of nivolumab.[xv] The case demonstrates a shift in reasoning from the traditional induction to abduction. The phenomenon of ‘cancer improvement’ is considered causally linked to nivolumab and its underlying physiological mechanisms.[xvi] However, “the weakness of abductions is that there may always be some other better, unknown explanation for an effect. The patient may for example belong to a special subgroup that spontaneously improves, or the change may be a placebo effect. This does not mean, however, that abductive inferences cannot be strong or reasonable, in the sense that they can make a conclusion probable.”[xvii] To demonstrate the limitations of relying on the abductive standard in isolation, commentators have pointed out that side effects in precision medicine are hard to rule out as being related to the initial intervention itself unless trends from a group of patients are taken into consideration.[xviii] As artificial intelligence (AI) assists the development of precision medicine for oncology, this uncertainty ought to be taken into consideration. The implementation of AI has been crucial to the development of precision medicine by providing a way to combine large patient datasets or a single patient with a large number of unique variables with machine learning to recommend matches based on statistics and probability of success upon which practitioners can base medical recommendations.[xix] The AI is usually not establishing a causal relationship[xx] – it is predicting. So, as AI bleeds into medical devices, like brain-computer interfaces, the same cautions about using abductive reasoning alone should be carried over. II. Responsive Neurostimulation, AI, and Personalized Medicine Like precision medicine in cancer treatment, computer-brain interface technology similarly focuses on the individual patient through personalized settings. In order to properly expose the intersection of AI, precision medicine, abductive reasoning, and implantable neurotechnologies, the descriptions of adaptive deep brain stimulation systems need to deepen.[xxi] As a broad summary of adaptive deep brain stimulation, to provide a patient with the therapeutic stimulation, a neural signal, typically referred to as a local field potential,[xxii] must first be detected and then interpreted by the device. The main adaptive deep brain stimulation device with premarket approval, the NeuroPace Responsive Neurostimulation system, is used to treat epilepsy by detecting and storing “programmer-defined phenomena.”[xxiii] Providers can optimize the detection settings of the device to align with the patient’s unique electrographic seizures as well as personalize the reacting stimulation’s parameters.[xxiv] The provider adjusts the technology based on trial and error. One day machine learning algorithms will be able to regularly aid this process in myriad ways, such as by identifying the specific stimulation settings a patient may respond to ahead of time based on their electrophysiological signatures.[xxv] Either way, with AI or programmers, adaptive neurostimulation technologies are individualized and therefore operate in line with precision medicine rather than standard treatments based on large clinical trials. Contemporary neurostimulation devices are not usually sophisticated enough to be prominent in AI discussions where the topics of neural networks, deep learning, generative models, and self-attention dominate the conversation. However, implantable high-density electrocorticography arrays (a much more sensitive version than adaptive deep brain stimulation systems use) have been used in combination with neural networks to help patients with neurologic deficits from a prior stroke “speak” through a virtual avatar.[xxvi] In some experimental situations, algorithms are optimizing stimulation parameters with increasing levels of independence.[xxvii] An example of neurostimulation that is analogous to the use of nivolumab in Norway surrounds a patient in the United States who was experiencing both treatment-resistant OCD and temporal lobe epilepsy.[xxviii]Given the refractory nature of her epilepsy, implantation of an adaptive deep brain stimulation system was indicated. As a form of experimental therapy, her treatment-resistant OCD was also indicated for the off-label use of an adaptive deep brain stimulation set-up. Another deep brain stimulation lead, other than the one implanted for epilepsy, was placed in the patient’s right nucleus accumbens and ventral pallidum region given the correlation these nuclei had with OCD symptoms in prior research. Following this, the patient underwent “1) ambulatory, patient-initiated magnet-swipe storage of data during moments of obsessive thoughts; (2) lab-based, naturalistic provocation of OCD-related distress (naturalistic provocation task); and (3) lab-based, VR [virtual reality] provocation of OCD-related distress (VR provocation task).”[xxix] Such signals were used to identify when to deliver the therapeutic stimulation in order to counter the OCD symptoms. Thankfully, following the procedure and calibration the patient exhibited marked improvements in their OCD symptoms and recently shared her results publicly.[xxx] In both cases, there is a similar level of abductive justification for the efficacy of the delivered therapy. In the case study in which the patient was treated with adaptive deep brain stimulation, they at least had their neural activity tested in various settings to determine the optimum parameters for treatment to avoid them being based on guesswork. Additionally, the adaptive deep brain stimulation lead was already placed before the calibration trials were conducted, meaning that the patient had already taken on the bulk of the procedural risk before the efficacy could be determined. Such an efficacy test could have been replicated in the first patient’s cancer treatment, had it been biopsied and tested against the remaining immunotherapies in vitro. Yet, in the case of cancer with few options, one previous dose of a drug that appeared to work on the patient may justify further doses. However, as the Norwegian case presents, corroboration with known responses to a similar drug (from a clinical trial) could be helpful to validate the treatment strategy. (It should be noted that both patients were resigned to these last resort options regardless of the efficacy of treatment.) There are some elements of inductive logic seen with adaptive deep brain stimulation research in general. For example, abductively the focus could be that patient X’s stimulation parameters are different from patient Y’s and patient Z’s. In contrast, when grouped as subjects who obtained personalized stimulation, patients X, Y, and Z demonstrate an inductive aspect to this approach’s safety and/or efficacy. The OCD case holds plenty of abductive characteristics in line with precision medicine’s approach to treating cancer and as more individuals try the method, there will be additional data. With the gradual integration of AI into brain-computer interfaces in the name of efficacy, this reliance on abduction will continue, if not grow, over time. Moving forward, if a responsive deep brain stimulation treatment is novel and individualized (like the dose of nivolumab) and there is some other suggestion of efficacy (like clinical similarities to other patients in the literature), then it may justify insurance coverage for the investigative intervention, absent other unrelated reasons to deny it. III. Ethical Implications and Next Steps While AI’s use in oncology and neurology is not yet as prominent as its use in other fields (e.g., radiology), it appears to be on the horizon for both.[xxxi] AI can be found in both the functioning of the neurotechnologies as well as the implementation of precision medicine. The increasing use of AI may serve to further individualize both oncologic and neurological therapies. Given these implications and the handful of publications cited in this article, it is important to have a nuanced evaluation of how these treatments, which heavily rely on abductive justification, ought to be managed. The just use an abductive approach may be difficult as AI infused precision medicine is further pursued. At baseline, such technology relies on a level of advanced technology literacy among the general public and could exclude populations who lack access to basic technological infrastructure or know-how from participation.[xxxii] Even among nations with adequate infrastructure, as more patients seek out implantable neurotechnologies, which require robust healthcare resources, the market will favor patient populations that can afford this complex care.[xxxiii] If patients already have the means to pay for an initial dose/use of a precision medicine product out of pocket, should insurance providers be required to cover subsequent treatments?[xxxiv] That is, if a first dose of a cancer drug or a deep brain stimulator over its initial battery life is successful, patients may feel justified in having the costs of further treatments covered. The Norwegian patient’s experience implies there is a precedent for the idea that some public insurance companies ought to cover successful cancer therapies, however, insurance companies may not all see themselves as obligated to cover neurotechnologies that rely on personalized settings or that are based on precision/abductive research more than on clinical trials. CONCLUSION The fact that the cases outlined above rely on abductive style of reasoning implies that there may not be as strong a justification for coverage by insurance, as they are both experimental and individualized, when compared to the more traditional large clinical trials in which groups have the same or a standardized protocol (settings/doses). If a study is examining the efficacy of a treatment with a large cohort of patients or with different experimental groups/phases, insurance companies may conclude that the resulting symptom improvements are more likely to be coming from the devices themselves. A preference for inductive justification may take priority when ruling in favor of funding someone’s continued use of an implantable neurostimulator. There are further nuances to this discussion surrounding the classifications of these interventions as research versus clinical care that warrant future exploration, since such a distinction is more of a scale[xxxv] than binary and could have significant impacts on the “right-to-try” approach to experimental therapies in the United States.[xxxvi] Namely, given the inherent limitations of conducting large cohort trials for deep brain stimulation interventions on patients with neuropsychiatric disorders, surgically innovative frameworks that blend abductive and inductive methodologies, like with sham stimulation phases, have traditionally been used.[xxxvii] Similarly, for adaptive brain-computer interface systems, if there are no large clinical trials and instead only publications that demonstrate that something similar worked for someone else, then, in addition to the evidence that the first treatment/dose worked for the patient in question, the balance of reasoning would be valid and arguably justify insurance coverage. As precision approaches to neurotechnology become more common, frameworks for evaluating efficacy will be crucial both for insurance coverage and for clinical decision making. ACKNOWLEDGEMENT This article was originally written as an assignment for Dr. Francis Shen’s “Bioethics & AI” course at Harvard’s Center for Bioethics. I would like to thank Dr. Shen for his comments as well as my colleagues in the Lázaro-Muñoz Lab for their feedback. - [i] Jonathan Kimmelman and Ian Tannock, “The Paradox of Precision Medicine,” Nature Reviews. Clinical Oncology 15, no. 6 (June 2018): 341–42, https://doi.org/10.1038/s41571-018-0016-0. [ii] Henrik Vogt and Bjørn Hofmann, “How Precision Medicine Changes Medical Epistemology: A Formative Case from Norway,” Journal of Evaluation in Clinical Practice 28, no. 6 (December 2022): 1205–12, https://doi.org/10.1111/jep.13649. [iii] David Barrett and Ahtisham Younas, “Induction, Deduction and Abduction,” Evidence-Based Nursing 27, no. 1 (January 1, 2024): 6–7, https://doi.org/10.1136/ebnurs-2023-103873. [iv] Vogt and Hofmann, “How Precision Medicine Changes Medical Epistemology,” 1208. [v] Wireko Andrew Awuah et al., “Bridging Minds and Machines: The Recent Advances of Brain-Computer Interfaces in Neurological and Neurosurgical Applications,” World Neurosurgery, May 22, 2024, S1878-8750(24)00867-2, https://doi.org/10.1016/j.wneu.2024.05.104. [vi] Mark Riedl, “A Very Gentle Introduction to Large Language Models without the Hype,” Medium (blog), May 25, 2023, https://mark-riedl.medium.com/a-very-gentle-introduction-to-large-language-models-without-the-hype-5 f67941fa59e. [vii] David E. Burdette and Barbara E. Swartz, “Chapter 4 - Responsive Neurostimulation,” in Neurostimulation for Epilepsy, ed. Vikram R. Rao (Academic Press, 2023), 97–132, https://doi.org/10.1016/B978-0-323-91702-5.00002-5. [viii] Kimmelman and Tannock, 2018. [ix] Kimmelman and Tannock, 2018. [x] Simon Lohse, “Mapping Uncertainty in Precision Medicine: A Systematic Scoping Review,” Journal of Evaluation in Clinical Practice 29, no. 3 (April 2023): 554–64, https://doi.org/10.1111/jep.13789. [xi] Kimmelman and Tannock, “The Paradox of Precision Medicine.” [xii] Vogt and Hofmann, 1206. [xiii] Vogt and Hofmann, 1206. [xiv] Vogt and Hofmann, 1206. [xv] Vogt and Hofmann, 1207. [xvi] Vogt and Hofmann, 1207. [xvii] Vogt and Hofmann, 1207. [xviii] Vogt and Hofmann, 1210. [xix] Mehar Sahu et al., “Chapter Three - Artificial Intelligence and Machine Learning in Precision Medicine: A Paradigm Shift in Big Data Analysis,” in Progress in Molecular Biology and Translational Science, ed. David B. Teplow, vol. 190, 1 vols., Precision Medicine (Academic Press, 2022), 57–100, https://doi.org/10.1016/bs.pmbts.2022.03.002. [xx] Stefan Feuerriegel et al., “Causal Machine Learning for Predicting Treatment Outcomes,” Nature Medicine 30, no. 4 (April 2024): 958–68, https://doi.org/10.1038/s41591-024-02902-1. [xxi] Sunderland Baker et al., “Ethical Considerations in Closed Loop Deep Brain Stimulation,” Deep Brain Stimulation 3 (October 1, 2023): 8–15, https://doi.org/10.1016/j.jdbs.2023.11.001. [xxii] David Haslacher et al., “AI for Brain-Computer Interfaces,” 2024, 7, https://doi.org/10.1016/bs.dnb.2024.02.003. [xxiii] Burdette and Swartz, “Chapter 4 - Responsive Neurostimulation,” 103–4; “Premarket Approval (PMA),” https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpma/pma.cfm?id=P100026. [xxiv] Burdette and Swartz, “Chapter 4 - Responsive Neurostimulation,” 104. [xxv] Burdette and Swartz, 126. [xxvi] Sean L. Metzger et al., “A High-Performance Neuroprosthesis for Speech Decoding and Avatar Control,” Nature 620, no. 7976 (August 2023): 1037–46, https://doi.org/10.1038/s41586-023-06443-4. [xxvii] Hao Fang and Yuxiao Yang, “Predictive Neuromodulation of Cingulo-Frontal Neural Dynamics in Major Depressive Disorder Using a Brain-Computer Interface System: A Simulation Study,” Frontiers in Computational Neuroscience 17 (March 6, 2023), https://doi.org/10.3389/fncom.2023.1119685; Mahsa Malekmohammadi et al., “Kinematic Adaptive Deep Brain Stimulation for Resting Tremor in Parkinson’s Disease,” Movement Disorders 31, no. 3 (2016): 426–28, https://doi.org/10.1002/mds.26482. [xxviii] Young-Hoon Nho et al., “Responsive Deep Brain Stimulation Guided by Ventral Striatal Electrophysiology of Obsession Durably Ameliorates Compulsion,” Neuron 0, no. 0 (October 20, 2023), https://doi.org/10.1016/j.neuron.2023.09.034. [xxix] Nho et al. [xxx] Nho et al.; Erik Robinson, “Brain Implant at OHSU Successfully Controls Both Seizures and OCD,” OHSU News, accessed March 3, 2024, https://news.ohsu.edu/2023/10/25/brain-implant-at-ohsu-successfully-controls-both-seizures-and-ocd. [xxxi] Awuah et al., “Bridging Minds and Machines”; Haslacher et al., “AI for Brain-Computer Interfaces.” [xxxii] Awuah et al., “Bridging Minds and Machines.” [xxxiii] Sara Green, Barbara Prainsack, and Maya Sabatello, “The Roots of (in)Equity in Precision Medicine: Gaps in the Discourse,” Personalized Medicine 21, no. 1 (January 2024): 5–9, https://doi.org/10.2217/pme-2023-0097. [xxxiv] Green, Prainsack, and Sabatello, 7. [xxxv] Robyn Bluhm and Kirstin Borgerson, “An Epistemic Argument for Research-Practice Integration in Medicine,” The Journal of Medicine and Philosophy: A Forum for Bioethics and Philosophy of Medicine 43, no. 4 (July 9, 2018): 469–84, https://doi.org/10.1093/jmp/jhy009. [xxxvi] Vijay Mahant, “‘Right-to-Try’ Experimental Drugs: An Overview,” Journal of Translational Medicine 18 (June 23, 2020): 253, https://doi.org/10.1186/s12967-020-02427-4. [xxxvii] Michael S. Okun et al., “Deep Brain Stimulation in the Internal Capsule and Nucleus Accumbens Region: Responses Observed during Active and Sham Programming,” Journal of Neurology, Neurosurgery & Psychiatry 78, no. 3 (March 1, 2007): 310–14, https://doi.org/10.1136/jnnp.2006.095315. (shrink)

The United Nations Global Compact (UNGC) was created in 2000 to leverage UN prestige and induce corporations to embrace 10 principles incorporating values of environmental sustainability, protection of human rights, fair treatment of workers, and elimination of bribery and corruption. We review and analyze the GC’s activities and impact in enhancing corporate social responsibility since inception. First, we propose an analytical framework which allows us to assess the qualities of the UNGC and its principles in the context of external (...) and internal elements that influence code effectiveness and implementation. Second, we analyze UNGC performance in encouraging companies to become signatory members and bring about demonstrable change in corporate CSR-sustainability activities. In its 10-year report, UNGC has proclaimed growth in both membership and program activity. However, all credible and publicly available data and documentation conclusively demonstrate that the UNGC has failed to induce its signatory companies to enhance their CSR efforts and integrate the 10 principles in their policies and operations. The result has been a loss of public trust and support of UNGC from important constituencies among civil society organizations, and those individuals and groups adversely impacted by corporate activities and resultant negative externalities. This diminished credibility has also made UNGC largely dependent on the corporate sector for its very survival. We conclude that this dependence has in turn impaired and would continue to hinder UNGC’s ability to fulfill its mission. Such an outcome raises serious questions as to the viability, usefulness, and continued existence of UNGC. (shrink)

Uncovering the world’s ethnic inequalities is hampered by a lack of ethnicity-annotated datasets. Name-ethnicity classifiers (NECs) can help, as they are able to infer people’s ethnicities from their names. However, since the latest generation of NECs rely on machine learning and artificial intelligence (AI), they may suffer from the same racist and sexist biases found in many AIs. Therefore, this paper offers an algorithmic fairness audit of three NECs. It finds that the UK-Census-trained EthnicityEstimator displays large accuracy biases with (...) regards to ethnicity, but relatively less among gender and age groups. In contrast, the Twitter-trained NamePrism and the Wikipedia-trained Ethnicolr are more balanced among ethnicity, but less among gender and age. We relate these biases to global power structures manifested in naming conventions and NECs’ input distribution of names. To improve on the uncovered biases, we program a novel NEC, N2E, using fairness-aware AI techniques. We make N2E freely available at www.name-to-ethnicity.com. (shrink)

In this article, we will take an in-depth look at the impact of artificial intelligence on the formation of working conditions in various fields of activity. By analyzing both general trends and specific examples, we will reveal how AI is helping to optimize workflows, change professional skills, and create new jobs. In addition, the article highlights the key benefits of using AI, including increased productivity and efficiency, automation of routine tasks, and improved workplace safety. We will also focus on the (...) challenges and potential risks associated with the use of artificial intelligence. The discussion will cover the ethical use of technology, the replacement of human labor by machines, the need to retrain employees, and the possibility of new forms of inequality in the workplace. The final part of the article offers reflections on the future of AI in the context of the labor market, including recommendations for adapting to these technological changes. Thus, we aim to provide a comprehensive view of the role of artificial intelligence in the modern world of work and its impact on the future of jobs and working conditions. The purpose of the article is to analyze the benefits of using artificial intelligence and algorithms to improve working conditions. On the other hand, the author identifies a number of challenges that states, businesses, and individuals may face in the event of AI implementation. At the same time, steps are proposed to reduce the negative consequences and prepare for the digitalization of jobs. (shrink)

In the rapidly evolving global economy, aligning labor market demands withskills needs development among adults is critical for sustainable economic growth andindividual career success. This alignment ensures that the workforce remains competitive,adaptable and capable of meeting industry requirements. A significant mismatchbetween labor market demands and available skills can lead to increased unemployment,underemployment, and diminished economic productivity. Addressing this gap necessitatesa comprehensive understanding of current and future labor market trends, coupledwith targeted educational and training programs.Adult (...) education and continuous professional development play pivotal rolesin this context, enabling workers to acquire new skills and upgrade existing ones inresponse to technological advancements and changing job roles. Collaboration amongpolicymakers, educational institutions and industry stakeholders is essential to createresponsive training programs that reflect the dynamic nature of the labor market. Moreover,effective skills development strategies can enhance job satisfaction, increase earningpotential and reduce socio-economic inequalities. By fostering a culture of lifelonglearning and adaptability, societies can better prepare their workforces for the challengesof the future, ensuring economic resilience and improved quality of life for individuals.This strategic approach ultimately benefits for both employers and employees, promotinga more inclusive and robust labor market. (shrink)

This paper analyses the ethical performance of foreign-investment enterprises operating in China in comparison to that of the indigenous state-owned enterprises, collectives and private enterprises. It uses both the deontological approach and the utilitarian approach in conceptualization, and applies quantitative and econometric techniques to ethical evaluations of empirical evidences. It shows that according to various ethical performance indicators, foreign-investment enterprises have fared well in comparison with local firms. This paper also tries to unravel the effect of a difference in business (...) culture and competitive market forces on ethical performance by comparing the behavior of foreign-investment enterprises with that of the indigenous state-owned enterprises and collectives on the one hand, and with that of the indigenous private enterprises on the other. (shrink)

Policy decisions during and after the New Deal tied the U.S. social contract to the employment contract, by conditioning eligibility and benefit levels for core welfare-state programs on work status and performance. The resulting system of social provision, however, embodied a set of assumptions about labor-market conditions that began to unravel with the structural economic shifts that began in the mid-1970s. Work was expected to provide open doors to employment, stable floors of security and stability over time, income (...) ladders promising adequate and rising earnings, and safety nets providing public and/or private protections against unforeseen or unavoidable hardships. Each of these assumptions was undermined by fundamental changes in the market, and this, in turn, has redefined patterns of social provision. As a result, core welfare-state programs have become less effective at meeting their own objectives of providing adequate social protections for rising numbers of working Americans. These trends preceded the recent recession and weak recovery, and cannot be reversed by the return of robust growth or pre-recession employment levels, in the absence of more fundamental change in the social contract. The roots of the current dilemma lie in the 1930s-40s, when politically mobilized employers fought alongside conservative policymakers to constrain the scope of the original system of social protections during and after the New Deal. In recent decades, they have battled to keep even this limited system from reaching those it was intended to assist, by blocking or limiting reform initiatives in areas such as employment policy, the minimum wage, health and pension insurance and modernization of the unemployment compensation system. (shrink)

Music is the carrier through which human beings express their emotions. It can clean up their hearts and seek emotional resonance. The combination of music and artificial intelligence, when music meets artificial intelligence, the mathematical logic part of data and algorithm replaces the image thinking, resulting in automatic music production. The basic principle of music creation is to use artificial intelligence technology to conduct in-depth training on a large number of songs, and then build a database. Then, within a certain (...) period of time, extract a segment from several songs, and then decompose it to form a new melody. The automatic music production is the collision of music and technology. With the flying of code and notes, it creates a different kind of beauty. Music culture is a new field of music application. With its refreshing audio-visual effect, it has made people have a new understanding of music and has become a hot topic in current mass cultural activities. The sound quality characteristics of music culture programs determine the characteristics of simple, fast and efficient design. However, the current audio and video design still stays in the traditional audio and video form design, with low design efficiency, long cycle, high cost and high requirements for designers. In view of the fact that the traditional audio and video design mode in China's music and cultural programs cannot meet the needs of performance programs at present, this paper proposes a design scheme of audio and visual effects of music and cultural programs with intelligent devices as the core, and develops a complete set of audio and visual effects aided design system on this basis. (shrink)

Institutions are increasingly employing algorithms to provide performance feedback to individuals by tracking productivity, conducting performance appraisals, and developing improvement plans, compared to traditional human managers. However, this shift has provoked considerable debate over the effectiveness and fairness of algorithmic feedback. This study investigates the effects of negative performance feedback (NPF) on the attitudes, cognition and behavior of medical researchers, comparing NPF from algorithms versus humans. Two scenario-based experimental studies were conducted with a total sample of 660 medical (...) researchers (algorithm group: N1 = 411; human group: N2 = 249). Study 1 analyzes the differences in scientific misconduct, moral disengagement, and algorithmic attitudes between the two sources of NPF. The findings reveal that NPF from algorithms shows higher levels of moral disengagement, scientific misconduct, and negative attitudes towards algorithms compared to NPF from humans. Study 2, grounded in trait activation theory, investigates how NPF from algorithms triggers individual’s egoism and algorithm aversion, potentially leading to moral disengagement and scientific misconduct. Results indicate that algorithm aversion triggers individuals’ egoism, and their interaction enhances moral disengagement, which in turn leads to increased scientific misconduct among researchers. This relationship is also moderated by algorithmic transparency. The study concludes that while algorithms can streamline performance evaluations, they pose significant risks to scientific misconduct of researchers if not properly designed. These findings extend our understanding of NPF by highlighting the emotional and cognitive challenges algorithms face in decision-making processes, while also underscoring the importance of balancing technological efficiency with moral considerations to promote a healthy research environment. Moreover, managerial implications include integrating human oversight in algorithmic NPF processes and enhancing transparency and fairness to mitigate negative impacts on medical researchers’ attitudes and behaviors. (shrink)

Language policies are increasingly acknowledged as being a necessary component of many decisions taken in the areas of the labor market, education, minority languages, mobility, and social inclusion of migrants. They can affect the democratic control of political organizations, and they can either entrench or reduce inequalities. These are the central topics of this book. Economists, philosophers, political scientists, and sociolinguists discuss – from an interdisciplinary perspective – the distributive socio-economic effects of language policies, their impact on (...) justice and inequality at the national or international level, as well as the connection between language choices and an inclusive access to public services. The range of social and economic issues raised by linguistic diversity in contemporary societies is large, and this requires new approaches to tackle them. This book provides new input to design better, more efficient, and fair language policies in order to manage linguistic diversity in different areas. Topics covered include: theoretical models of linguistic justice and linguistic disadvantage; the assessment of the socio-economic consequences of language policies; the evaluation of the costs, benefits, and degree of inclusion of language planning measures; the politics of migrants’ linguistic integration; as well as multilingualism and economic activities. These topics are discussed in different contexts, including the areas inhabited by linguistic minorities, cities receiving migrants, and supranational organizations. (shrink)

Active labor-market policies have developed significantly over the past two decades across Organization for Economic Cooperation and Development countries, with substantial cross-national differences in terms of both extent and overall orientation. The objective of this article is to account for cross-national variation in this policy field. It starts by reviewing existing scholarship concerning political, institutional, and ideational determinants of ALMPs. It then argues that ALMP is too broad a category to be used without further specification, and it (...) develops a typology of four different types of ALMPs: incentive reinforcement, employment assistance, occupation, and human capital investment. These are discussed and examined through ALMP expenditure profiles in selected countries. The article uses this typology to analyze ALMP trajectories in six Western European countries and shows that the role of this instrument changes dramatically over time. It concludes that there is little regularity in the political determinants of ALMPs. In contrast, it finds strong institutional and ideational effects, nested in the interaction between the changing economic context and existing labor-market policies. (shrink)

Whale optimization algorithm, known as a novel nature-inspired swarm optimization algorithm, demonstrates superiority in handling global continuous optimization problems. However, its performance deteriorates when applied to large-scale complex problems due to rapidly increasing execution time required for huge computational tasks. Based on interactions within the population, WOA is naturally amenable to parallelism, prompting an effective approach to mitigate the drawbacks of sequential WOA. In this paper, field programmable gate array is used as an accelerator, of which the high-level synthesis utilizes (...) open computing language as a general programming paradigm for heterogeneous System-on-Chip. With above platform, a novel parallel framework of WOA named PWOA is presented. The proposed framework comprises two feasible parallel models called partial parallel and all-FPGA parallel, respectively. Experiments are conducted by performing WOA on CPU and PWOA on OpenCL-based FPGA heterogeneous platform, to solve ten well-known benchmark functions. Meanwhile, other two classic algorithms including particle swarm optimization and competitive swarm optimizer are adopted for comparison. Numerical results show that the proposed approach achieves a promising computational performance coupled with efficient optimization on relatively large-scale complex problems. (shrink)

PurposeThe purpose of this paper is to argue that in spite of the widely optimistic held view on the effect of information and communication technologies (ICTs) in promoting the “knowledge society” in Europe and economic development elsewhere, evidence suggests that ICT's could be strengthening labour duality world wide.Design/methodology/approachThe paper addresses these issues by presenting a brief assessment of the “Washington Consensus” and the emergence of ICTs in terms of trade, growth and inequality in different regions of our planet. The paper (...) also describes the effects of globalisation and ICTs on European economies. Finally, the paper presents the key finding and raises some policy implications to exploit ICT potentialities to ensure welfare systems in advanced economies and development in emerging countries.FindingsThe lack of sufficient institutional mechanism of distribution in developing economies is not only making it more difficult for economic growth to translate into development but it is also favouring relocations of production, pressures to deregulate employment, control salaries and social expenditure in Europe. This feeds complex processes of social segmentation world wide. To meet this challenge Europe has no choice but to opt for the development of avant‐garde sectors. However, measures linked to the development of the knowledge society may not be sufficient to maintain our welfare states in the current context of globalisation. Europe must play a more internationally active role in the design of another model of globalisation that would encompass social policies at a global scale as one of its pillars.Originality/valueThere are very few studies of ICTs' role in the relationship between openness‐growth‐development‐inequality. What are ICTs responsible for? What are ICTs' effects on development and welfare state sustainability? (shrink)

This paper presents an intuitive explanation about why and how Rawlsian Theory of Justice (Rawls in A theory of justice, Harvard University Press, Harvard, 1971) provides the foundations to a solution for algorithmic bias. The contribution of the paper is to discuss and show why Rawlsian ideas in their original form (e.g. the veil of ignorance, original position, and allowing inequalities that serve the worst-off) are relevant to operationalize fairness for algorithmic decision making. The paper also explains how (...) this leads to a specific MinMaxfairness solution, which addresses the basic challenges of algorithmic justice. We combine substantive elements of Rawlsian perspective with an intuitive explanation in order to provide accessible and practical insights. The goal is to propose and motivate why and how the MinMaxfairness solution derived from Rawlsian principles overcomes some of the current challenges for algorithmic bias and highlight the benefits provided when compared to other approaches. The paper presents and discusses the solution by building a bridge between the qualitative theoretical aspects and the quantitative technical approach. (shrink)

With the increasing prevalence of Internet usage, Internet-Delivered Psychological Treatment (IDPT) has become a valuable tool to develop improved treatments of mental disorders. IDPT becomes complicated and labor intensive because of overlapping emotion in mental health. To create a usable learning application for IDPT requires diverse labeled datasets containing an adequate set of linguistic properties to extract word representations and segmentations of emotions. In medical applications, it is challenging to successfully refine such datasets since emotion-aware labeling is time (...) consuming. Other known issues include vocabulary sizes per class, data source, method of creation, and baseline for the human performance level. This paper focuses on the application of personalized mental health interventions using Natural Language Processing (NLP) and attention-based in-depth entropy active learning. The objective of this research is to increase the trainable instances using a semantic clustering mechanism. For this purpose, we propose a method based on synonym expansion by semantic vectors. Semantic vectors based on semantic information derived from the context in which it appears are clustered. The resulting similarity metrics help to select the subset of unlabeled text by using semantic information. The proposed method separates unlabeled text and includes it in the next active learning mechanism cycle. Our method updates model training by using the new training points. The cycle continues until it reaches an optimal solution, and it converts all the unlabeled text into the training set. Our in-depth experimental results show that the synonym expansion semantic vectors help enhance training accuracy while not harming the results. The bidirectional Long Short-Term Memory (LSTM) architecture with an attention mechanism achieved 0.85 Receiver Operating Characteristic (ROC curve) on the blind test set. The learned embedding is then used to visualize the activated word's contribution to each symptom and find the psychiatrist's qualitative agreement. Our method improves the detection rate of depression symptoms from online forum text using the unlabeled forum texts. (shrink)

Typically, fair machine learning research focuses on a single decision maker and assumes that the underlying population is stationary. However, many of the critical domains motivating this work are characterized by competitive marketplaces with many decision makers. Realistically, we might expect only a subset of them to adopt any non-compulsory fairness-conscious policy, a situation that political philosophers call partial compliance. This possibility raises important questions: how does partial compliance and the consequent strategic behavior of decision subjects affect the allocation outcomes? (...) If k% of employers were to voluntarily adopt a fairness-promoting intervention, should we expect k% progress (in aggregate) towards the benefits of universal adoption, or will the dynamics of partial compliance wash out the hoped-for benefits? How might adopting a global (versus local) perspective impact the conclusions of an auditor? In this paper, we propose a simple model of an employment market, leveraging simulation as a tool to explore the impact of both interaction effects and incentive effects on outcomes and auditing metrics. Our key findings are that at equilibrium: (1) partial compliance by k% of employers can result in far less than proportional (k%) progress towards the full compliance outcomes; (2) the gap is more severe when fair employers match global (vs local) statistics; (3) choices of local vs global statistics can paint dramatically different pictures of the performance vis-a-vis fairness desiderata of compliant versus non-compliant employers; (4) partial compliance based on local parity measures can induce extreme segregation. Finally, we discuss implications for auditors and insights concerning the design of regulatory frameworks. (shrink)

Conventional wisdom among comparative political economists maintains that the participation of employers in policymaking and policy implementation, fostered by corporatist arrangements, is crucial to the successful expansion of active labor market policy. This article introduces a transaction-oriented theory of corporatism, partisanship, and ALMP that challenges the dominant view. It argues that corporatist arrangements do not affect the overall scope of ALMP but facilitate particular types of ALMP programs, ones that require the joint participation of employers and the (...) state and involve a transfer of public resources to employers. Corporatist arrangements facilitating such programs—which center-right parties tend to prefer over those produced unilaterally by the state—also shift the focus of partisan conflict over ALMP from the level of public expenditure to the structure. Evidence for these claims is provided by time-series cross-sectional analyses of twenty-one OECD countries since the mid-1980s. (shrink)

Purpose. The purpose of the study is to define the negative impact of gender inequality on the global economy and public health. Theoretical basis. Unequal treatment of individuals based on gender discrimination has led to negative consequences in various areas of society. Gender inequality is very costly for the world due to the lack of representation of women in the labor market, gender income inequality situation, glass ceiling effect that have the negative impact on the world economy. (...) Outdated gender roles, which are inconsistent with the new reality and the idea of human progress, have a significant impact on life expectancy, health, mortality and disease, access to health care and medical care. Originality. The vector of the development of the human society changes its direction, which leads to a renewal of an individual status-role framework, the creation of the new systems of values, theories and ideologies that require a new field of opportunities and free human self-identification and gender-identification. Conclusions. The results show that gender inequality has a negative impact on economic growth and development, as well as on physical and mental health. Strictly fixed gender roles limit free human development. Everyone should have the right to determine her/his gender, her/his interests and behavior patterns, while having the right to personal respect and respect for their honor, convictions, and gender practices. (shrink)

In this paper we develop a general theory of algorithmic fairness. Drawing on Johnson King and Babic’s work on moral encroachment, on Gary Becker’s work on labor market discrimination, and on Strawson’s idea of resentment and indignation as responses to violations of the demand for goodwill toward oneself and others, we locate attitudes to fairness in an agent’s utility function. In particular, we first argue that fairness is a matter of a decision-maker’s relative concern for the plight (...) of people from different groups, rather than of the outcomes produced for different groups. We then show how an agent’s preferences, including in particular their attitudes to error, give rise to their decision thresholds. Tying these points together, we argue that the agent’s relative degrees of concern for different groups manifest in a difference in decision thresholds applied to these groups. (shrink)

Science is the basis for managing the affairs of life and human activities, and living without knowledge is a form of wandering and a kind of loss. Using scientific methods helps us understand the foundations of choice, decision-making, and adopting the right solutions when solutions abound and options are numerous. Operational research is considered the best that scientific development has provided because its methods depend on the application of scientific methods in solving complex issues and the optimal use of available (...) resources in various fields, private and governmental work in peace and war, in politics and economics, in planning and implementation, and in various aspects of life. Its basic essence is to use the data provided for the issue under study to build a mathematical model that is the optimal solution. It is the basis on which decision makers rely in managing institutions and companies, and when operations research methods meet with the neutrosophic teacher, we get ideal solutions that take into account all the circumstances and fluctuations that may occur in the work environment over time. One of the most important operations research methods is the linear programming method. Which prompted us to reformulate the linear models, the graphical method, and the simplex method, which are used to obtain the optimal solution for linear models using the concepts of neutrosophic science. In this research, and as a continuation of what we presented previously, we will reformulate the modified simplex algorithm that was presented to address the difficulty that we were facing when applying the direct simplex algorithm. It is the large number of calculations required to be performed in each step of the solution, which requires a lot of time and effort. (shrink)

Fairness, the notion that people deserve or have rights to certain resources or kinds of treatment, is a fundamental dimension of moral cognition. Drawing on recent evidence from economics, psychology, and neuroscience, we ask whether self-interest is always intuitive, requiring self-control to override with reasoning-based fairness concerns, or whether fairness itself can be intuitive. While we find strong support for rejecting the notion that self-interest is always intuitive, the literature has reached conflicting conclusions about the neurocognitive systems underpinning fairness. (...) We propose that this disagreement can largely be resolved in light of an extended Social Heuristics Hypothesis. Divergent findings may be attributed to the interpretation of behavioral effects of ego depletion or neurostimulation, reverse inference from brain activity to the underlying psychological process, and insensitivity to social context and inter-individual differences. To better dissect the neurobiological basis of fairness, we outline how future research should embrace cross-disciplinary methods that combine psychological manipulations with neuroimaging, and that can probe inter-individual, and cultural heterogeneities. (shrink)

This article concerns challenges arising from the development of economic globalization as the so-called “creator of a new world order“ and its tendency to deteriorate the foundation of a global order in terms of social justice, solidarity, and human dignity. As main point of referral functions, the report of the “Commission Stiglitz, Sen and Fitoussi cs“ on the Measurement of Economic Performance and Social Progress that refers to the European Commission's strategy of development, acknowledges the need for these values. On (...) behalf of this reflection, this article is based on the recent outcomes of the exploration of these social quality issues in a recent published book by the Foundation on Social Quality. The article argues that indicators are needed in order to understand the effects of societal changes in response to the current economic globalization, which increases inequality and the fragmentation of the labor market. (shrink)

The application of machine-learning technologies to medical practice promises to enhance the capabilities of healthcare professionals in the assessment, diagnosis, and treatment, of medical conditions. However, there is growing concern that algorithmic bias may perpetuate or exacerbate existing health inequalities. Hence, it matters that we make precise the different respects in which algorithmic bias can arise in medicine, and also make clear the normative relevance of these different kinds of algorithmic bias for broader questions about justice (...) and fairness in healthcare. In this paper, we provide the building blocks for an account of algorithmic bias and its normative relevance in medicine. (shrink)

The development of the social sciences needs to rely on precise methods. The nomological model of explanation adopted in the natural sciences is ill-suited for the social sciences. An algorithmic model of society can be a promising solution to existing problems. In its most general form, an algorithm is a generally understood prescription for what actions to perform and in what order to achieve the desired result. Any algorithm can be represented as a set of rules of the form (...) «If A, do D to get P». People are the bearers of this kind of rules that apply in different areas of their activities. The rules are subject to change based on personal and collective experience. There is a special mathematical discipline that studies the laws of evolution of such rules. This discipline is called genetic programming. Contrary to the threatening name, the algorithmic model does not imply the deprivation of a person’s right to free choice, but it needs this right as a necessary condition for the evolution of social algorithms. These algorithms allow us to give a non-causal, but law-like explanation of many well-known social phenomena, as well as to effectively model the future, which is critically important today. A retrospective look at the evolution of social algorithms shows that the current global crisis of human society is associated with the approach to the point of singularity in their evolution. This is due to the fact that there is no need for direct human participation in the implementation of social algorithms, which is reflected in a fundamental change in the sphere of employment and less need for further development of the sciences. (shrink)

This article uses a well-defined setting to suggest an optimistic view about the distributional effects of immigration. Section 2 provides a general picture of the native-immigrant differences in labour force participation, unemployment, and occupational and educational attainment, taking skill levels and years since immigration into account. Section 3 investigates the inequality impact of immigration by summarizing the potential labour market impacts and the wage and employment consequences. Section 4 deals with the potentially slow integration of immigrants into the (...) labour market of the host country, as well as with the role that self-selection and selection through politically set admission rules can play for the performance in the labour market. It also considers cultural or ethnic identity as an independent factor potentially affecting economic success and discusses the consequences for inequality. Section 5 concludes. (shrink)

In this paper we develop a general theory of algorithmic fairness. Drawing on Johnson King and Babic’s work on moral encroachment, on Gary Becker’s work on labor market discrimination, and on Strawson’s idea of resentment and indignation as responses to violations of the demand for goodwill toward oneself and others, we locate attitudes to fairness in an agent’s utility function. In particular, we first argue that fairness is a matter of a decision-maker’s relative concern for the plight (...) of people from different groups, rather than of the outcomes produced for different groups. We then show how an agent’s preferences, including in particular their attitudes to error, give rise to their decision thresholds. Tying these points together, we argue that the agent’s relative degrees of concern for different groups manifest in a difference in decision thresholds applied to these groups. (shrink)

The proposed work describes an approach for segmentation of activated sludge flocs from the microscopic images for monitoring wastewater treatment. The morphological features of flocs and filaments are related to the state of an activated sludge wastewater treatment plant and must be monitored for proper functioning. Hence, image processing and analysis could be a time-saving monitoring tool. To address this challenge, we propose a novel framework involving a multiphase edge detection algorithm based on information theory. The proposed framework (...) is evaluated and scrutinized critically considering the artifacts found in the photographs tested. To evaluate the segmentations, gold approximation of estimated truth images is created. In addition, the performance was subjectively evaluated for its potential for segmenting activated sludge images. Experimental results show that the proposed framework exhibits the good results and demonstrates its effectiveness. (shrink)

In this article we report the findings of a randomised control clinical trial that assessed the impact of a Philosophy for Children program and replicated a previous study conducted in Scotland by Topping and Trickey. A Cognitive Abilities Test was administered as a pretest and a posttest to randomly selected experimental groups and control groups. The students in the experimental group engaged in philosophy lessons in a setting of structured, collaborative inquiry in their language arts classes for one hour per (...) week for a number of weeks. The control group received the standard language arts curriculum in that one hour. The study found that the seventh grade students who had experienced the P4C program showed significant gains relative to those in the seventh grade control group at a high level of statistical significance, but the eighth grade students in the experimental group did not show such gains over the eighth grade control group. It was discovered that the seventh grade teachers started the program early in the school year and continued it for a period of 22 to 26 weeks, while the eighth grade teachers started much later and used the program for only 4 to 10 weeks. Our findings suggest that the P4C program must involve students in activities for a significant period of time before the program shows results, but that a meaningful impact on students’ cognitive abilities can be achieved in about 24 weeks of lessons, less than half the time evidenced by the study by Topping and Trickey. (shrink)

In almost all countries, the transition from a centrally planned economy to a market economy caused high unemployment. The governments attempted to ease the changeover to a market economy for the unemployed by introducing several passive and active labour market policies. This paper first points out which effects were to be expected of such policies from the perspective of Austrian Economics. These theoretical hypotheses are then tested empirically. It turns out that the hypotheses deducted from (...) Austrian Economics theory are impressively corroborated by the empirical evidence.Dans presque tous les pays, la transition d’une économie centralement planifiée vers une économie de marché ont provoqué un chômage élevé. Les gouvernements ont essayé d’adoucir la transition vers une économie de marché pour les chômeurs en introduisant plusieurs politiques passives et actives sur le marché du travail. Tout d’abord, cet article souligne quels étaient les effets attendus de telles politiques à la lumière de l’économie autrichienne. Ces hypothèses théoriques sont ensuite testées de manière empirique. Il en ressort que les hypothèses déduites de la théorie économique autrichienne sont corroborées de manière significative par les preuves empiriques. (shrink)

The article describes the evolution of problems in the Lithuanian labour law and labour law science since the re-establishment of independence in 1990. Three periods of evolution are presented: the Soviet period (lasted until 1990), the transitional period (1990- 2004) and the period of the Labour Code (2003 and onwards). During the Soviet period, the Code of Labour Laws regulated employment relationship in strict detail as the main employer was the state itself. Good reflections of that period can be pointed (...) out: active (but forced) collective bargaining, single tariff system that implemented equal treatment in the field of remuneration for work and fluent performance of enforcement of labour laws (legal clarity). During the transitional period, new labour laws were introduced and tuned-up with international labour standards (ILO), but in general there were no essential changes in practice. During all that period, the Lithuanian Labour Code was drafted and came in force in 2003. The period of the new Labour Code started together with the European integration and had to bring new trends of the European labour market into Lithuanian practice. The government and academics brought few initiatives for the liberalisation of labour laws but most of them were stuck in the stage of consulting with social partners (Tripartite Council). Nevertheless, 22 years after the collapse of command economy labour laws incompatible with free labour market still dominate. It is obvious that the Lithuanian Labour Code is outdated and needs general reconstruction. Scientific researches and the EU Council recommendations call for the introduction of flexibility, implementation of flexicurity aiming for full integration into the single European labour market. Some strict labour code rules are prevented from functioning in practice. The courts are forced to derogate from disproportionate and improper articles of the Labour Code. The author brings some of the existing problems of labour law into light and proposes their possible solutions. The existing crisis of labour law could be solved by drafting a new Labour Code with the help of academic researchers and by introducing it directly to the Parliament for adoption. (shrink)

While issues of efficacy and specificity are crucial for the future of neurofeedback training, there may be alternative designs and control analyses to circumvent the methodological and ethical problems associated with double-blind placebo studies. Surprisingly, most NF studies do not report the most immediate result of their NF training, i.e. whether or not children with ADHD gain control over their brain activity during the training sessions. For the investigation of specificity, however, it seems essential to analyze the learning and adaptation (...) processes that take place in the course of the training and to relate improvements in self-regulated brain activity across training sessions to behavioral, neuropsychological and electrophysiological outcomes. To this aim, a review of studies on neurofeedback training with ADHD patients, which include the analysis of learning across training sessions or relate training performance to outcome, is presented. Methods on how to evaluate and quantify learning of EEG regulation over time are discussed. “Non-learning” has been reported in a small number of ADHD-studies, but has not been a focus of general methodological discussion so far. For this reason, selected results from the brain-computer interface (BCI) research on the so-called “brain-computer illiteracy”, the inability to gain control over one’s brain activity, are also included. It is concluded that in the discussion on specificity, more attention should be devoted to the analysis of EEG regulation performance in the course of the training and its impact on clinical outcome. It is necessary to improve the knowledge on characteristic cross-session and within-session learning trajectories in ADHD and to provide the best conditions for learning. (shrink)

Algorithm is the core category and basic methods of the digital age, and advanced technologies such as big data, artificial intelligence, and blockchain all need to rely on various algorithm designs or take the algorithm as the underlying principle. However, due to the characteristics of algorithm design, application, and technology itself, there are also hidden worries such as algorithm black-box, algorithm discrimination, and difficulty in accountability in the operation process to varying degrees. This paper summarizes these problems into three aspects: (...) unexplainable, self-reinforcing and autonomous. Facing the opportunities and risks generated by the application of the algorithm in national governance, while actively promoting the development of algorithm technology to continuously promote the modernization process of national governance, it is also necessary to increase the governance of the algorithm. The practice has proved that enhancing the interpretability of algorithm, optimizing algorithm design, and adopting legal regulatory algorithm are the basic approaches to effective regulatory algorithm in the era of intelligent governance. (shrink)

This article focuses on the role of unions and their influence on economic inequality. Section 2 reviews the literature regarding the union effect on wages and wage inequality. Section 3 considers the separate contributions of union power, membership composition, bargaining coordination, and wage policy. Section 4 introduces the distinction between membership and coverage, while the following two sections discuss the impact of union power on earnings inequality when coverage is either exclusive or inclusive. Section 7 discusses the rationale for unions (...) aiming for wage compression while Section 8 estimates how the presence of trade unions has influenced the extent and dynamics of earnings inequality across advanced economies during the 1980s and 1990s. For this purpose indicators have been developed for trends in equality and union presence from different sources. Section 9 concludes. (shrink)

We analyse the development of Fair Trade in Italy by examining its principles, structure, performance, dilemmas and potential solutions and identifying its main distinctive features. These lead us to develop a specifically Italian model. Fair Trade in Italy is younger than its more established North European counterparts and more focussed on broad social justice issues in addition to its concern to include marginalized producers. This normative difference has given rise to a social-economy-dominated value chain, although it has generated much lower (...) per capita consumption of Fair Trade products. At the same time, we also observe a relatively higher specialization in handicraft products and educational activities as well as a strong capacity to attract voluntary labour and create social capital. We identify clear trade-offs between social goals and the economic performance of the Italian model: reduced economies of scale, a closer focus on non-economic-value-creating social activities and greater consideration of values such as consumption sobriety and environmental concerns which may conflict with economic performance. We propose solutions which may resolve these dilemmas without abandoning the initial ambition not only to achieve the promotion of market access for marginalized producers in the South, but also to pursue a broader concept of well-being in the North and the South. (shrink)

AI technology is capturing the African imaginations as a gateway to progress and prosperity. There is a growing interest in AI by different actors across the continent including scientists, researchers, humanitarian and aid organizations, academic institutions, tech start-ups, and media organizations. Several African states are looking to adopt AI technology to capture economic growth and development opportunities. On the other hand, African researchers highlight the gap in regulatory frameworks and policies that govern the development of AI in the continent. They (...) argue that this could lead to AI technology exacerbating problems of inequalities and injustice in the continent. However, most of the literature on AI ethics is biased toward Euro-American perspectives and lack the understanding of how AI development is apprehended in the Global South, and particularly Africa. Drawing on the case study of the first African Master’s in Machine Intelligence program, this paper argues for looking beyond the question of ethics in AI and examining AI governance issues through the analytical lens of the raciality of computing and the political economy of technoscience to understand AI development in Africa. By doing so, this paper seeks a different theorization for AI ethics from the South that is based on lived experiences of those in the margins and avoids the framings of technological futures that simplistically pathologize or celebrate Africa. (shrink)

Deep Brain Stimulation (DBS) is an effective treatment for advanced Parkinson’s disease. However, identifying stimulation parameters, such as contact and current amplitudes, is time-consuming based on trial and error. Directional leads add more stimulation options and render this process more challenging with a higher workload for neurologists and more discomfort for patients. In this study, a sweet spot-guided algorithm was developed that automatically suggested stimulation parameters. These suggestions were retrospectively compared to clinical monopolar reviews. A cohort of 24 Parkinson’s (...) disease patients underwent bilateral DBS implantation in the subthalamic nucleus at our center. First, the DBS’ leads were reconstructed with the open-source toolbox Lead-DBS. Second, a sweet spot for rigidity reduction was set as the desired stimulation target for programming. This sweet spot and estimations of the volume of tissue activated were used to suggest (i) the best lead level, (ii) the best contact, and (iii) the effect thresholds for full therapeutic effect for each contact. To assess these sweet spot-guided suggestions, the clinical monopolar reviews were considered as ground truth. In addition, the sweet spot-guided suggestions for best lead level and best contact were compared against reconstruction-guided suggestions, which considered the lead location with respect to the subthalamic nucleus. Finally, a graphical user interface was developed as an add-on to Lead-DBS and is publicly available. With the interface, suggestions for all contacts of a lead can be generated in a few seconds. The accuracy for suggesting the best out of four lead levels was 56%. These sweet spot-guided suggestions were not significantly better than reconstruction-guided suggestions (p = 0.3). The accuracy for suggesting the best out of eight contacts was 41%. These sweet spot-guided suggestions were significantly better than reconstruction-guided suggestions (p < 0.001). The sweet spot-guided suggestions of each contact’s effect threshold had a mean error of 1.2 mA. On an individual lead level, the suggestions can vary more with mean errors ranging from 0.3 to 4.8 mA. Further analysis is warranted to improve the sweet spot-guided suggestions and to account for more symptoms and stimulation-induced side effects. (shrink)

The authors attempt to speculatively reconstruct the concept of the “So­viet computer game”. They propose to consider gaming practices associ­ated with computers as a derivative of the accepted ideological guidelines that accompany the Soviet project of machine modernization. Within this framework, the concept of the Soviet computer game appears as an unre­alized historical alternative to the normative game design that has devel­oped in countries with market economies. Despite the industry — or the electronic entertainment market — not having (...) had the time to be properly established in the USSR, there were a number of discursive attitudes re­garding the game as such, and the gaming function of computing devices in particular. Even early Soviet pedagogical theories assumed that “playing like a Soviet” involves performing activities structurally similar to labor, where the player becomes part of production. Later, cybernetic discourse, through game theory, indicated the possibility of formalizing any prag­matic activity as a game model; with the advancement of programming, the pragmatics of digital gaming as a way of educating and solving utili­tarian tasks was developed. Based on the memoir archive of Soviet cyber­netics, and publications in the late-Soviet press, the authors demonstrate that the Soviet computer game was not seen an entertainment product, but a representative model for solving problems in an algorithmic form. Thus, the article is not about specific games that could be called Soviet, but about the logic that guided and set the tone for the interpretation of certain computer-game phenomena in the USSR. (shrink)

BackgroundComorbidity between diabetes mellitus and depression is highly prevalent. The risk of depression in a person with diabetes is approximately twice that of a person without this disease. Depression has a major impact on patient well-being and control of diabetes. However, despite the availability of effective and specific therapeutic interventions for the treatment of depression in people with diabetes, 50% of patients do not receive psychological treatment due to insufficient and difficult accessibility to psychological therapies in health systems. (...) The use of information and communication technologies has therefore been proposed as a useful tool for the delivery of psychological interventions, but it continues to be a field in which scientific evidence is recent and controversial. This systematic review aims to update the available information on the efficacy of psychological interventions delivered through ICTs to improve depressive symptomatology in patients with diabetes.MethodsA systematic review of the literature was performed following the PRISMA guidelines and using MEDLINE, Embase, PubMed, Web of Science, PsycINFO, Scopus, and Cochrane Library databases to search for randomized clinical trials of eHealth treatments for patients with diabetes and comorbid depression from 1995 through 2020. In addition, studies related to follow-up appointments were identified. Inclusion criteria were as follows: randomized clinical trials ; patients with type 1 and type 2 diabetes; adult population over 18 years of age; presence of depressive symptomatology assessed with standardized instruments; treatments for depression based on established psychotherapeutic techniques and principles; delivered through eHealth technologies. We did not limit severity of depressive symptomatology, delivery setting or comparison group. Two coauthors independently reviewed the publications identified for inclusion and extracted data from the included studies. A third reviewer was involved to discuss discrepancies found. The PEDro scale was used to assess the quality of the RCTs. No meta-analysis of the results was performed. The protocol used for this review is available in PROSPERO.ResultsThe initial search identified 427 relevant scientific publications. After removing duplicates and ineligible citations, a total of 201 articles were analyzed in full text. Ten articles met the criteria of this review and were included, obtaining very good scientific quality after evaluation with the PEDro scale. The main results show that the eHealth psychological intervention for depression in patients with diabetes showed beneficial effects both at the end of treatment and in the short and long term for the improvement of depressive symptomatology. The methodology used was very heterogeneous. However, all studies were based on cognitive-behavioral tools and used standardized assessment instruments to evaluate depressive symptomatology or diagnosis of MDD. Glycemic control was assessed by glycosylated hemoglobin, but no benefits were found in improving glycemic control. Only four studies included psychoeducational content on diabetes and depression, but none used tools to improve or enhance adherence to medical prescriptions or diabetes self-care.ConclusionsICT-based psychological interventions for the treatment of depression in people with diabetes appear to be effective in reducing depressive symptomatology but do not appear to provide significant results with regard to glycemic control. Nonetheless, the scientific evidence reported to date is still very limited and the methodology very diverse. In addition, no studies have implemented these systems in routine clinical practice, and no studies are available on the economic analysis of these interventions. Future research should focus on studying and including new tools to ensure improvements in diabetes outcomes and not only on psychological well-being in order to advance knowledge about these treatments. Economic evaluations should also be undertaken to analyze whether these treatment programs implemented using eHealth technologies are cost-effective. (shrink)

Drawing on constructionist theory, this study examines how the media portrayed five public reporting events initiated by the Fair Labor Association (FLA), considering whether the coverage encourages or discourages companies from undertaking a reporting initiative as part of their ethical management. Media coverage was limited but generally favorable across all five events. Coverage frequently included claims made by FLA spokespersons and provided basic facts about the organization and its activities. Extensive detail about labor violations found by monitors was (...) often included. Additional media coverage centered around themes of public reporting and transparency, an assessment of the FLA’s work, brand accountability and responsibility of corporations with regard to working conditions and labor standards, and specifics about the factory monitoring and partnering with factories and NGOs that is necessary to achieve change. Counter-claims brought question to the FLA’s efforts. Explanations about why the social condition exists were fairly limited, and thus, provided little insight into how the problems might be resolved. We discuss managerial implications regarding public reporting initiatives and media coverage, particularly regarding the countering effects of positive coverage and diminishing news stories. (shrink)

Wage inequality and land and labor insecurity are critical barriers to sustainable palm oil production among those employed in Indonesia’s small-farm sector. Palm oil contract farming, a pre-harvest agreement between palm oil farmers and transnational processors and traders, facilitates smallholder participation in global agro-commodities markets, improves smallholder livelihoods, and promotes local economic development in rural communities. But negative externalities in contract farming can emerge depending on whether corporate guarantors of contract-farm assets manage farmer assets equitably. This study explores how (...) contract farming agreements between smallholder farmers of palm oil and futures traders of palm stocks impact the long-term economic development of smallholder palm oil farming in Indonesia. We examined the relative impact of transnational palm oil corporations on smallholder assets in the Indonesian palm oil industry using annual financial data (2003–2019) from Indonesian commodities trading firms. Temporal trends indicated that oligopolistic market conditions were strongly associated with a growing comparative advantage in palm oil, the asymmetric accumulation of land resources by transnational firms, and excessive firm revenues from palm farmer activities. Our regression modelling results suggested that the comparative advantage in Indonesian palm oil was driven by state-oriented policies such that benefit palm traders but disadvantage smallholder farmers. And, through non-metric multidimensional scaling, we demonstrated that smallholder farmers were inefficiently used by firms to produce palm oil, but that smallholder assets were a significant driver to firm revenue growth. Notwithstanding the adverse consequences on palm farmers, these results indicate a set of unique effects of palm oil contract farming on land and labor security in Southeast Asia. The paper reasons that a system of inequitable contract farming is operating in the Indonesian palm oil industry, whereby smallholder palm oil farmers are trapped by transnational firms into socio-economic farming schemes of low oil yield and non-market activity, thus providing palm firms with lucrative non-market revenue streams. Large transnational trading firms are thereby implicated in the long-run commodification of smallholder land for marginal fruit production while exploiting a farmer’s non-market advantages through the manipulation of farmer assets. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Organ Transplant AllocationPat Milmoe McCarrick (bio)The introduction of the antibiotic, cyclosporin, which enhances the success rate of transplantation surgery, has resulted in the steady growth of organ transplantation since the mid-1980s. This growth increasingly focuses ethical interest on both the procurement and the allocation of human organs. Not everyone who might benefit from organ transplants can receive them since the number of patients in need of organs far exceeds (...) the number of organs available. Each year the waiting list for transplants increases by 20 percent, but the number of donated organs has remained stable for the past five years (Lawry 1994).Organ transplantation surgery performed on rock stars, sports heroes, politicians, and television celebrities brings questions about the fair allocation of scarce resources to the attention of everyone. Abigail Trafford, editor of Washington Post Health, wonders whether "new livers for hard livers" can be deserved when not enough organs are available for everyone who needs them. Writing about the dilemma of just allocation of organs, she calls famous recipients "poster patients" or "health care celebrities of medical catastrophe" (Trafford 1994). Personal responsibility—the viewpoint that "medical treatment should not be an entitlement program for profligate living"—is an emerging moral consideration according to Trafford. Deciding whose standards and values should apply to the allocation of organs raises many questions. Popular arguments for keeping the current criteria for allocation include: these patients are sick and therefore should be treated, regardless of the cause of their illness; former substance abusers should be able to benefit from their present abstention; physicians should treat anyone who is ill; and although many human illnesses may be caused by individual behavior, such behavior is not always used as a reason to deny care (Trafford 1995).Prior to 1984, when the government established regulations governing organ transplantation, organs routinely were given to the patients of the surgeons who excised them (Prottas 1994). In an effort to achieve a more equitable method of distribution, Congress passed the National Organ Transplant Act of 1984 (Pub. [End Page 365] L. No. 98-507, amended by Pub. L. No. 100607 and Pub. L. No. 101-616), which established a national Organ Procurement and Transplantation Network (OPTN) to improve the effectiveness of organ procurement, organ distribution, and transplant activities. The United Network for Organ Sharing (UNOS) received the federal government contract to be the OPTN.UNOS and its 66 regional organ procurement organizations (OPOs) around the nation have carried out the mandate since 1986. It requires hospitals that receive Medicare or Medicaid funds and perform transplants to belong to the network and to allocate organs according to network policies. UNOS maintains the national computer registry to match donor organs with individual recipients. In distributing organs, UNOS is required by law to use a fair and equitable system based on accepted medical criteria. UNOS regularly reevaluates its policies to ensure that organ donation and recipient selection meet criteria of efficiency and equity (UNOS Update 11 (8), 1995).At the end of June 1995, 278 transplant centers were in operation in the United States: almost all of them (247 centers) transplanted kidneys; 167 did hearts; 119, pancreases; 114, livers; 93, heart-lung; 88, lungs; 26, intestines; and only 19 centers performed pancreas islet cell transplants (UNOS Update 11 (8): 28, 1995). The number of patients waiting for organ transplants in July 1995 totalled 41,075: 29,274 were waiting for a kidney transplant; 4,937, liver; 3,298, heart; 1,816, lung; 1,223 kidney-pancreas; 240, pancreas; and 211, heart-lung (UNOS Update 11 (8): 40-41, 1995).OPOs are located in different geographic areas across the country, each with different organ needs, lengths of waiting lists, or with lists in areas with large older populations making it more difficult to find suitable donors. Black recipients often wait longer due to complex reasons including sensitization or rarer blood and antigen types (UNOS 11 (8): 31-32, 1995). When an organ becomes available, the OPO involved identifies a potential recipient from the UNOS list and offers it to the patient's surgeon. If no match can be made locally, the organ is next offered within a UNOS region, and finally, to... (shrink)

Labor market deregulation has been at the core of the changes in the political economy during the last decades. The pervasive neoliberal wisdom has depoliticized the nature and effects of this process, a bias that has also affected the scholarship, which often overlooks its power dimension. This article aims to explore the role of power in the labor market to offer some theoretical insights for empirical research and public debate. Departing from the worker–employer “contested exchange” (...) at the workplace, the article pivots on the concept of “decommodification” to grasp the institutional arrangements that shape this relationship at the institutional level of power. Furthermore, the article addresses the symbolic dimension of power and how epistemic reflexivity enables us to examine whether social research ideologically depicts or conceals the role of power in the study of labor relations, as illustrated by two subjects in vogue: the insiders–outsiders divide and the activation policy. The article concludes with a discussion of the normative implications of the preceding argument about freedom as nondomination for workers. (shrink)

Market economics can overreach and reduce all human activities to market-governed activities. More than a market-inspired explanation for human activities, it offers a normative account of how all goods and services should be distributed by private parties negotiating mutually agreeable terms. This paper argues that market values and practices are constrained by other fundamental values and practices. Liberal values are generally consistent with, though they are not reducible to, market values. Democratic and egalitarian values often (...) contrast with market values. The distribution of market benefits should accommodate those democratic and egalitarian values which constitute a polity's core commitments (and those core commitments need to be reasserted regularly). Indeed, market stability depends upon a general distribution of its benefits. Incentives to productive activity entail inequalities, but the terms of those inequalities are subject to review. Internal refinements to specific markets can reduce inequalities by promoting the fairness of market operations and by increasing the number of effective participants. (shrink)

Resources are typically discussed in economics as factors of production. This article proposes defining resources from the perspective of human needs, thereby dividing resources into two categories: material resources and information resources. The key distinction lies in whether they can be replicated, which determines if their marginal cost of supply is zero, and leads to their different distribution in society. For material resources, the main indicator is wealth, and the distribution of wealth follows a power law. This means that a (...) small minority of people control a large amount of wealth, leading to severe inequality issues. This led to Karl Marx's idea of abolishing private property, which ultimately failed. For information resources, the article suggests that reputation can serve as a main indicator for observation and proposes an algorithm for calculating reputation scores. The article points out that the distribution of reputation scores does not follow a power law, contrary to wealth distribution, and results in a multi-centered, star-like social structure. A star chart model is introduced to visualize this structure, illustrating the roles of creators, reflectors, and recipients in information dissemination. Thus, the social structure resulting from information activities has a relatively low level of inequality. Furthermore, the modern information infrastructure has lowered barriers to knowledge acquisition and reputation building, potentially mitigating wealth inequality by providing new income channels. It also addresses challenges in the digital age, such as cyberbullying and misinformation, proposing principles for effective governance of online spaces. (shrink)

Many of us assume that all the free editing and sorting of online content we ordinarily rely on is carried out by AI algorithms — not human persons. Yet in fact, that is often not the case. This is because human workers remain cheaper, quicker, and more reliable than AI for performing myriad tasks where the right answer turns on ineffable contextual criteria too subtle for algorithms to yet decode. The output of this work is then used for machine learning (...) purposes to generate algorithms constructed from large data sets containing thousands of correctly coded observations. The fact that ghost workers are treated as consumers distorts the basic logic of the employment relationship, effectively placing the worker-as-consumer in the worst of both worlds, in which they hold the legal rights of neither group. This puts them in a regulatory limbo position in which they have little or no protection, control, or guarantee of return on investment. This is because the platforms that facilitate ghost work have orchestrated a three-way virtual relationship that absolves all parties of responsibility, while placing nearly all the risks and opportunity costs squarely on the shoulders of the workers. As a result, we believe such a work arrangement as it stands, does not uphold basic standards of Rawlsian justice as fairness. (shrink)

Substance use disorders (SUDs) constitute a growing global health crisis, yet many limitations and challenges exist in SUD treatment research, including the lack of objective brain-based markers for tracking treatment outcomes. Electroencephalography (EEG) is a neurophysiological technique for measuring brain activity, and although much is known about EEG activity in acute and chronic substance use, knowledge regarding EEG in relation to abstinence and treatment outcomes is sparse. We performed a scoping review of longitudinal and pre-post treatment (...) EEG studies that explored putative changes in brain function associated with abstinence and/or treatment in individuals with SUD. Following PRISMA guidelines, we identified studies published between January 2000 and March 2022 from online databases. Search keywords included EEG, addictive substances (e.g., alcohol, cocaine, methamphetamine), and treatment related terms (e.g., abstinence, relapse). Selected studies used EEG at least at one time point as a predictor of abstinence or other treatment-related outcomes; or examined pre- vs. post-SUD intervention (brain stimulation, pharmacological, behavioral) EEG effects. Studies were also rated on the risk of bias and quality using validated instruments. Forty-four studies met the inclusion criteria. More consistent findings included lower oddball P3 and higher resting beta at baseline predicting negative outcomes, and abstinence-mediated longitudinal decrease in cue-elicited P3 amplitude and resting beta power. Other findings included abstinence or treatment-related changes in late positive potential (LPP) and N2 amplitudes, as well as in delta and theta power. Existing studies were heterogeneous and limited in terms of specific substances of interest, brief times for follow-ups, and inconsistent or sparse results. Encouragingly, in this limited but maturing literature, many studies demonstrated partial associations of EEG markers with abstinence, treatment outcomes, or pre-post treatment-effects. Studies were generally of good quality in terms of risk of bias. More EEG studies are warranted to better understand abstinence- or treatment-mediated neural changes or to predict SUD treatment outcomes. Future research can benefit from prospective large-sample cohorts and the use of standardized methods such as task batteries. EEG markers elucidating the temporal dynamics of changes in brain function related to abstinence and/or treatment may enable evidence-based planning for more effective and targeted treatments, potentially pre-empting relapse or minimizing negative lifespan effects of SUD. (shrink)

In the field of applied computer research, the problem of the reinforcement of existing inequalities through the processing of “big data” in neural networks is typically addressed via concepts of representation and fairness. These approaches, however, tend to overlook the limits of the liberal antidiscrimination discourse, which are well established in critical theory. In this paper, I address these limits and propose a different framework for understanding technologically amplified oppression departing from the notion of “mute compulsion” (Marx), a specifically modern (...) form of power based on the social abstraction of wage labor in market exchange. I begin with a reconstruction of the process of technological abstraction in automated pattern recognition, after which I summarize the conceptional shortcomings of representational fairness discourse. In contrast, I demonstrate how the social reproduction of exploitation is conceptualized in critical theory as being mediated through a process of social abstraction, defined as a social practice of reification that manifest in fetishization. To avoid economistic shortcomings, I contextualize the argument of social abstraction against the backdrop of social reproduction theory, which takes the juncture of various historical forms of oppression into account. I conclude by elaborating how technological abstraction corresponds to the problem of mute compulsion by replicating processes of social abstraction. (shrink)

Theories related to cognitive sciences, Human-in-the-loop Cyber-physical systems, data analysis for decision-making, and computational ethics make clear the need to create transdisciplinary learning, research, and application strategies to bring coherence to the paradigm of a truly human-oriented technology. Autonomous objects assume more responsibilities for individual and collective phenomena, they have gradually filtered into routines and require the incorporation of ethical practice into the professions related to the development, modeling, and design of algorithms. To make this possible, it is pertinent and (...) urgent to bring them closer to the problems and approaches of the humanities. Increasingly transdisciplinary research must be part of the construction of systems that provide developers and scientists with the necessary bases to understand the ethical debate and therefore their commitment to society. This article considers two theories as articulating axes: Blumenberg’s, coming from the field of philosophy, for whom the process of technification and especially the implementation of mathematical models in their algorithmic form leads to an emptying of meaning and therefore makes programmers who implement their functions to be alien to the concerns that gave them origin; Daston’s, belonging to the field of the history of science and according to which the division of labor in the processes of technification of the calculation implies a kind of subordination in which those who implement the inventions of a small group of privileged mathematicians ignore the procedures that put them into operation. Given these two theories, the black box models prevalent in AI development, and the urgency of establishing explanatory frameworks for the development of computational ethics, this article exposes the need to give a voice to the cultural history of consciousness for promoting the discussions around the implementation of mathematical algorithms. The paper takes as a reference the different points of view that have emerged around the study of technological ethics, its applicability, management, and design. It criticizes the current state of studies from a humanistic perspective and explains how the historical perspective allows promoting the training of software engineers, developers and creators so that they assume intuitions and moral values in the development of their work. Specifically, it aims to expose how cultural history, applied to the study of consciousness and its phenomena, makes those involved in this technological revolution aware of the effect that they, through their algorithms, have on society in general and on human beings in particular. (shrink)

Purpose. Based on the comparative analysis of the European and post-Soviet countries, the purpose of the article is to study one of the manifestations of gender discrimination, namely the problem of gender equality in the sphere of labor. It involves the consistent solution to the following tasks: a) to emphasize the basic principles of gender international and legal policy; b) to reflect the praxeological dimension of providing the equal social and economic opportunities for men and women at current level; (...) c) to emphasize the key criterion for ensuring the equality in socio-cultural sphere – equality in political life; d) to study the educational level of women and the possibility of self-realization in employment equal to men. Theoretical basis. The authors proceed from the standpoint that gender equality at the present stage has become a priority of legal policy and an important principle of the state of pro-European orientation. It is characterized in the legal plane, first of all, by the equality of the social roles of men and women, and the overcoming of the gender hierarchy of social ties, in which men are perceived as higher beings by their mental and physical abilities, and their activities are more significant and of priority in comparison with the activities of women. Originality. The authors have substantiated that in many economically developed countries the problem of providing a gender is still relevant, but most of the crisis problems in this area have found their legal regulation. The motivated position of the authors is that the level of education and professionalism of women cannot serve a reason for discrimination against women, which now exists in the economic and political sphere in the post-Soviet space. Conclusions. Gender stereotypes remain the priority in woman’s keeping family household, which creates significant inequalities of women and men at the labor market. Specialized regulatory acts in the field of gender declare the equality of men and women, while labor law defines a number of norms and guarantees that complicate the employment of women. In order to improve the situation we propose to implement a number of measures, such as, creation and financial support of the programs at the state level for supporting maternity, family and childhood; examination of all normative acts and concerning the issue of gender asymmetry, and especially the norms of labor law; introduction of state monitoring of employment and income of persons as to the complying with the principle of gender equality; introduction of quotas for women’s participation in political activities, in the work of the government and parliament, etc. (shrink)