This study assesses the student learning styles and academic performance in modular learning among Grade IV, V, and VI learners of Hindang Central School. This considered the learning styles and academic performance of the respondents in modular learning. A total of 252 learners from Hindang Central School participated as respondents in the evaluative method of research that consists of two parts questionnaires. This study used a modified survey questionnaire from the University of California at Merced, Student (...) Advising and Learning Center to gather the data of the respondents. As to the significance of learning styles and academic performances of the respondents in modular learning, Analysis of Variance (ANOVA) was used to analyze the significant differences. The study's findings indicated that auditory learning was the respondents' preferred method of learning. This learning style is best through speaking or listening. Moreover, auditory learners prevail dominantly amidst the health crisis faced. The respondents' academic achievement in the academic year 2020–2021 was also revealed to be Very Satisfactory. According to the Analysis of Variance (ANOVA), there was no apparent connection between learning preferences and academic achievement in the new typical education. Therefore, there was no relation or correlation between the two variables. (shrink)

The use of machine learning, or “artificial intelligence” (AI) in medicine is widespread and growing. In this paper, I focus on a specific proposed clinical application of AI: using models to predict incapacitated patients’ treatment preferences. Drawing on results from machine learning, I argue this proposal faces a special moral problem. Machine learning researchers owe us assurance on this front before experimental research can proceed. In my conclusion I connect this concern to broader issues in AI safety.

This study assesses the student learning styles and academic performance in modular learning among Grade IV, V, and VI learners of Hindang Central School. This considered the learning styles and academic performance of the respondents in modular learning. A total of 252 learners from Hindang Central School participated as respondents in the evaluative method of research that consists of two parts questionnaires. This study used a modified survey questionnaire from the University of California at Merced, Student (...) Advising and Learning Center to gather the data of the respondents. As to the significance of learning styles and academic performances of the respondents in modular learning, Analysis of Variance (ANOVA) was used to analyze the significant differences. The study's findings indicated that auditory learning was the respondents' preferred method of learning. This learning style is best through speaking or listening. Moreover, auditory learners prevail dominantly amidst the health crisis faced. The respondents' academic achievement in the academic year 2020–2021 was also revealed to be Very Satisfactory. According to the Analysis of Variance (ANOVA), there was no apparent connection between learning preferences and academic achievement in the new typical education. Therefore, there was no relation or correlation between the two variables. (shrink)

More philosophical effort is spent articulating evolutionary rationales for the development of belief-like capacities than for precursors of desires or preferences. Nobody, though, seriously expects naturally evolved minds to be disinterested epistemologists. We agree that world-representing states won’t pay their way without supporting capacities that prioritise from an organism’s available repertoire of activities in light of stored (and occurrent) information. Some concede that desire-like states would be one way of solving this problem. Taking preferences as my starting point instead of (...) belief-like states, I defend two conclusions. First, psychologically real preference states, which approximately token expected utilities, have a quite general evolutionary rationale. They are a solution to the problem of efficiently allocating capacities with incompatible uses. This argument is a version of the Environmental Complexity Thesis. Second, preferences can plausibly function and naturally evolve without belief-like states, even though the converse claim is incredible. Preferences, that is, can mediate between discriminations of occurrent states (‘internal’ or ‘external’) and the processes selecting activity without mediation by stored indicative representations. By tokening expected utilities of actions conditional on discriminated state, they can increase the rate at which the ‘right thing’ is done at appropriate times, and they can do this without the support of belief-like, world-representing states. Preferences, even incomplete and noisy sets of them, are a fuel for success that will tend to be favoured when environments are complex in ways that matter to an organism, and when the organisms have complex behavioural repertoires with heterogenous returns and costs. (shrink)

Inspired by the recent trends in education towards learner autonomy with their emphasis on the interests and desires of the students, and borrowing ideas from philosophy (particularly ethics), the present study is an attempt to investigate the discrepancy in the findings of the studies addressing error correction in L2 writing instruction, and suggest the (oft-neglected) students’ beliefs, interests and wants as what can point the way out of confusion. To this end, a questionnaire was developed and 56 advanced adult EFL (...) learners were asked to complete the questionnaire. The opinions of 20 EFL teachers were also collected using another questionnaire. Twenty-three of the students and 13 of the teachers were then interviewed in an attempt to collect explanations for their answers in the questionnaires. The results indicated that all the learners wanted the errors in their writings to be corrected. About 90 percent of them believed that all the errors in their writings should be corrected and only less than 10 percent of them agreed that there is no need to correct all the errors and that only “important” errors should be rectified. On the contrary, of the teachers who participated in the study, only 20 percent believed that all the errors in the students’ writings should be corrected. While most of the interviewed students attributed their preference of choice to feeling more confident and efficient in learning when they can recognize all the errors in their written assignments, most of the teachers believed that by correcting important errors (and not all errors), learners can get the most of their writings. Given the incongruity between teachers’ and (advanced) students’ beliefs over writing error correction, and considering advanced students as legitimate decision makers for their own learning, some suggestions are offered for EFL writing teachers. -/- . (shrink)

I explain and motivate the shutdown problem: the problem of creating artificial agents that (1) shut down when a shutdown button is pressed, (2) don’t try to prevent or cause the pressing of the shutdown button, and (3) otherwise pursue goals competently. I then propose a solution: train agents to have incomplete preferences. Specifically, I propose that we train agents to lack a preference between every pair of different-length trajectories. I suggest a way to train such agents using reinforcement (...) class='Hi'>learning: we give the agent lower reward for repeatedly choosing same-length trajectories. (shrink)

This chapter examines how social- scientific research on public preferences bears on the ethical question of how those resources should in fact be allocated, and explain how social-scientific researchers might find an understanding of work in ethics useful as they design mechanisms for data collection and analysis. I proceed by first distinguishing the methodologies of social science and ethics. I then provide an overview of different approaches to the ethics of allocating scarce medical interventions, including an approach—the complete lives system—which (...) I have previously defended, and a brief recap of social-scientific research on the allocation of scarce medical resources. Following these overviews, I examine different ways in which public preferences could matter to the ethics of allocation. Last, I suggest some ways in which social scientists could learn from ethics as they conduct research into public preferences regarding the allocation of scarce medical resources. (shrink)

The study aimed to determine if differentiated instruction effectively addresses learning gaps in mathematics. In particular, it explored how it can improve the student’s learning gaps concerning mathematical performance and confidence. The study employed a quasi-experimental design with 30 purposively-selected Grade 10 participants divided into differentiated (n = 15) and control groups (n = 15), ensuring the utmost ethical measures. The mean and standard deviation were used to describe the participants’ performance and confidence. Independent samples t-tests were used (...) to determine the significant differences in the performance and confidence between the two groups. In contrast, dependent samples t-tests were used to determine the significant differences in each group’s pre and posttest performance and confidence. Findings bared that the differentiated instruction successfully addressed students’ performance in mathematics even in a short period. It also increased the participants’ confidence when answering fundamental problems. Continuing differentiated instruction activities are recommended since it benefits students who struggle in mathematics, particularly in answering fundamental operations. Differentiated teaching activities in mathematics can boost academic achievement and engagement and prepare students for future success while fostering a positive and inclusive classroom culture that values individual learning needs and preferences. (shrink)

Except in extraordinary circumstances, patients' clinical care should reflect their preferences. Incapacitated patients cannot report their preferences. This is a problem. Extant solutions to the problem are inadequate: surrogates are unreliable, and advance directives are uncommon. In response, some authors have suggested developing algorithmic "patient preference predictors" (PPPs) to inform care for incapacitated patients. In a recent paper, Earp et al. propose a new twist on PPPs. Earp et al. suggest we personalize PPPs using modern machine learning (ML) techniques. (...) In this paper, I argue that, contrary to Earp et al.'s claim, personalized patient preference predictors are neither technically feasible nor ethically desirable. (shrink)

According to standard rational choice theory, as commonly used in political science and economics, an agent's fundamental preferences are exogenously fixed, and any preference change over decision options is due to Bayesian information learning. Although elegant and parsimonious, such a model fails to account for preference change driven by experiences or psychological changes distinct from information learning. We develop a model of non-informational preference change. Alternatives are modelled as points in some multidimensional space, only some of whose dimensions (...) play a role in shaping the agentís preferences. Any change in these "motivationally salient" dimensions can change the agent's preferences. How it does so is described by a new representation theorem. Our model not only captures a wide range of frequently observed phenomena, but also generalizes some standard representations of preferences in political science and economics. (shrink)

The educational process has been dramatically transformed by technology; this transformation has caused the emergence of central concepts, among which is distance learning. The latter has brought new opportunities to learn from; meanwhile, it has presented challenges that have impacted learning in many ways. Thus, the present study investigated the implementation of E-learning among EFL students at Moulay Ismail University to identify students' perceptions about this type of learning and consider the pros and cons to ensure (...) best practice solutions that endorse online learning quality. The study included 315 students at Moulay Ismail University in Morocco who completed an online questionnaire and used descriptive analysis because the data was presented in simple summaries that aimed to describe the basic features of the data and measures. The findings, both quantitative and qualitative, indicated that e-learning is still in its early stages. At the same time, students are not entirely prepared to supersede traditional learning with distance education due to some reasons, in particular, such as lack of university support in offering resources to learn online, lack of internet connection, malfunction of technological tools, etc. All in all, EFL students prefer blended learning because it allows them to combine a new technological experience with a traditional one. Meaning that e-learning should not be excluded entirely from the educational system, but it can be used only as a support to foster EFL students' academic achievements. (shrink)

This study explores the effectiveness of brain-based learning (BBL) as a pedagogical approach to address the challenges of poor conceptual understanding, which may have worsened due to the COVID-19 pandemic aftermath. In this meta- analysis, 14 studies qualified using the Publish or Perish software and the Preferred Reporting Items for Systematic Reviews and Meta-analyses. Statistical analysis conducted using Comprehensive Meta-Analysis (CMA) Version 4 software by Biostat, Inc. Based on the results, the overall effect size (ES = 3.135) indicates that (...) the use and integration of BBL principles and strategies have a significantly large and positive effect on student conceptual understanding. The moderator analysis revealed a significant difference between individual studies (p < .001); however, the overall results for academic level (p > .05) and discipline (p > .05) revealed no significant differences. Hence, each study included in this analysis may differ from one another due to the differences in various BBL strategies implemented; however, when grouped, they shared common effect sizes. With these findings, the researchers advocate the use of BBL principles and strategies to improve students' conceptual understanding at various levels in basic education, be it in English and STEM. Moreover, empirical studies focusing on a particular BBL variable, such as health and nutrition, are recommended for in-depth analysis and discussion. (shrink)

The present quasi-experimental study was undertaken to study students’ perceptions of the advantages and disadvantages of the LMS and the ‘real’ classroom. The data was collected using the online survey method (Google Form), which included questions related to students' perceptions of the effectiveness of both modes in enhancing knowledge, critical skills, and social competence. The study found that although the ratio of students who preferred ‘real’ classroom learning to learning through the LMS was higher, many students were also (...) comfortable with online learning. The present study concludes that a blended mode of learning, i.e., using digital learning tools with a more traditional classroom, can be a better option to meet the needs of both kinds of learners. (shrink)

In recent years there has been an explosion of interest in Artificial Intelligence (AI) both in health care and academic philosophy. This has been due mainly to the rise of effective machine learning and deep learning algorithms, together with increases in data collection and processing power, which have made rapid progress in many areas. However, use of this technology has brought with it philosophical issues and practical problems, in particular, epistemic and ethical. In this paper the authors, with (...) backgrounds in philosophy, maternity care practice and clinical research, draw upon and extend a recent framework for shared decision-making (SDM) that identified a duty of care to the client's knowledge as a necessary condition for SDM. This duty entails the responsibility to acknowledge and overcome epistemic defeaters. This framework is applied to the use of AI in maternity care, in particular, the use of machine learning and deep learning technology to attempt to enhance electronic fetal monitoring (EFM). In doing so, various sub-kinds of epistemic defeater, namely, transparent, opaque, underdetermined, and inherited defeaters are taxonomized and discussed. The authors argue that, although effective current or future AI-enhanced EFM may impose an epistemic obligation on the part of clinicians to rely on such systems' predictions or diagnoses as input to SDM, such obligations may be overridden by inherited defeaters, caused by a form of algorithmic bias. The existence of inherited defeaters implies that the duty of care to the client's knowledge extends to any situation in which a clinician (or anyone else) is involved in producing training data for a system that will be used in SDM. Any future AI must be capable of assessing women individually, taking into account a wide range of factors including women's preferences, to provide a holistic range of evidence for clinical decision-making. (shrink)

Experts in Artificial Intelligence (AI) development predict that advances in the dvelopment of intelligent systems and agents will reshape vital areas in our society. Nevertheless, if such an advance isn't done with prudence, it can result in negative outcomes for humanity. For this reason, several researchers in the area are trying to develop a robust, beneficial, and safe concept of artificial intelligence. Currently, several of the open problems in the field of AI research arise from the difficulty of avoiding unwanted (...) behaviors of intelligent agents, and at the same time specifying what we want such systems to do. It is of utmost importance that artificial intelligent agents have their values aligned with human values, given the fact that we cannot expect an AI to develop our moral preferences simply because of its intelligence, as discussed in the Orthogonality Thesis. Perhaps this difficulty comes from the way we are addressing the problem of expressing objectives, values, and ends, using representational cognitive methods. A solution to this problem would be the dynamic cognitive approach proposed by Dreyfus, whose phenomenological philosophy defends that the human experience of being-in-the-world cannot be represented by the symbolic or connectionist cognitive methods. A possible approach to this problem would be to use theoretical models such as SED (situated embodied dynamics) to address the values learning problem in AI. (shrink)

Effective stress management strategies correlate with improved academic performance in college students, yet inconsistent findings in existing research warrant further investigation. This study explored the intricate interplay between stress levels, coping strategies, and academic achievement in HyFlex learningenvironments. A stratified random sample of 111 students from five specializations within the Bachelor of Secondary Education program participated. Utilizing a descriptive-correlational design, data were collected through validated self-report questionnaires and a weighted general average. Subsequent descriptive statistics and bivariate correlation analysis revealed moderate (...) stress levels among participants who preferred task-oriented coping strategies. Interestingly, a significant positive association was observed between stress levels and academic achievement and emotion-oriented coping strategies, while a negative correlation emerged between stress and task-oriented coping strategies. Avoidance-oriented coping strategies, conversely, displayed a significant negative association with academic success. These findings underscore the crucial role of educational institutions in providing robust support mechanisms for stress management and cultivating a task-focused learning environment to optimize student well-being and academic performance within the HyFlex model. (shrink)

This study aimed to determine the experiences of male and female students on Flexible Learning (FL) during the COVID-19. A qualitative method using a phenomenological approach was used to ascertain the students' experiences, while written questionnaires were utilized to gather the information. The 24 students taking Development Communication and Public Administration were chosen based on set criteria. Both male and female flexible learning participants appreciated its benefits, including convenience and reduced academic stress. They both faced technology-related challenges and (...) suggested improvements. However, differences emerged in their experiences. Males found FL fun, emphasizing family time, while females highlighted skill development and concerns about teaching methods. Females also mentioned practical skill development not emphasized by males. These variations may stem from differing learning preferences and experiences. Variations in male and female experiences in Flexible Learning highlight the need for teachers to tailor instruction, offer mental health support, and incorporate skill development. Improved teacher training and clear guidelines are crucial, as are gender-inclusive program design and regular feedback mechanisms to create equitable and effective educational experiences. (shrink)

A qualitative phenomenological approach was used in this study to describe the lived experiences of Tagumpay National High School (TNHS) teachers on Online Learning Action Cell (LAC) session. LAC is a school-based professional development for teachers implemented by the Philippine Department of Education (DepEd). Due to teacher’s lack of participation on classroom LAC, a fully-online mode option is explored by offering TNHS teachers Online LAC session using Facebook as a Learning Management System (LMS). To capture the lived experience (...) of teachers, an in-depth interview with a purposive sample of one TNHS teacher is done in the process. The data gathered went through “Hycner’s Explicitation Process” (1999, in Groenewald, 2004) which includes bracketing, delineating, clustering, summarizing and extracting unique themes. Validity and Credibility were accomplished through an intercoder agreement between researchers, Facebook chat records, bracketing, and member checking. Results identified three themes in relation to teacher’s experience of Online LAC session including usefulness, barriers, and preference. Findings revealed the major role of TNHS teacher’s context on how Online LAC is utilized. Recommendations include administrator and expert teacher working with classroom teachers and the inclusion of teachers’ voices as input in the program design, implementation and evaluation stages of Online LAC to better address curriculum needs and facilitate the delivery of high-quality professional development for teachers’ professional growth. (shrink)

Purpose: Despite the prevalent use of the golden ratio in the environment design for autistic users, there is no experimental research that explains their desired space ratio. This study aims to find the desired ratio in the learning environment, like an occupational therapy room for autistic users, while considering effective variables on their choices. Methodology: Based on McAllister's (2012) study, a scale model inspired by a dollhouse has been chosen to work and play with autistic children directly and find (...) their desired space ratio. Meanwhile, the furniture configuration and the access type in the environment could also define the ratio for interviewees. Accordingly, the scale model was designed with six different scale rooms containing three ratios and two spatial access types represented by the furniture arrangement. 50 autistic children of different ages, genders, and disorders in the moderate and medium spectrum have been randomly sampled. Then, they were asked to choose their desired ratio by playing with the scale model and putting the doll in their preferred room. This study also included 50 non-autistic children as a control group with different genders and defined ages. Result: After interviewing both groups, the chi-square test with Cramer's V calculation analyzed the result to find the statistically significant correlation between control variables, among which two independent variables had a statistically significant correlation with the chosen ratio for all the interviewees. First, being autistic significantly impacted their desired ratio choice as autistic children went for a ratio of 2:5, and no autistic ones had a high tendency toward the golden ratio (1:1.6). The chi-square test also showed that the access type in the scale model was the effective variable for both groups when choosing their desired ratio. Conclusion: The access type of the room with its furniture configuration impacted how users perceived the room's ratio, as well as being autistic or non-autistic users. (shrink)

The development of conversational artificial intelligence (AI) has brought about new opportunities for improving the learning experience in education. ChatGPT, a large language model trained on a vast corpus of text, has the potential to revolutionize education by enhancing learning through personalized and interactive conversations. This paper explores the benefits of integrating ChatGPT in education in Thailand. The research strategy employed in this study was qualitative, utilizing in-depth interviews with eight key informants who were selected using purposive sampling. (...) The collected data was analyzed using content analysis and the software NVivo. The study's results indicated that ChatGPT can provide personalized learning experiences by adapting to individual student needs and preferences. Its ability to understand natural language and context can also facilitate more meaningful interactions between students and the system. Additionally, ChatGPT can assist with administrative tasks such as grading and feedback, allowing educators to focus on more personalized and meaningful interactions with students. Furthermore, ChatGPT can serve as a valuable tool for remote learning, providing students with the ability to access educational resources and support outside of traditional classroom settings. The paper also discusses potential ethical considerations in utilizing AI in education, such as data privacy and bias. Overall, this paper argues that the integration of ChatGPT in education has the potential to enhance the learning experience for students by providing personalized, interactive, and efficient support. (shrink)

Advancements in machine learning have fuelled the popularity of using AI decision algorithms in procedures such as bail hearings, medical diagnoses and recruitment. Academic articles, policy texts, and popularizing books alike warn that such algorithms tend to be opaque: they do not provide explanations for their outcomes. Building on a causal account of transparency and opacity as well as recent work on the value of causal explanation, I formulate a moral concern for opaque algorithms that is yet to receive (...) a systematic treatment in the literature: when such algorithms are used in life-changing decisions, they can obstruct us from effectively shaping our lives according to our goals and preferences, thus undermining our autonomy. I argue that this concern deserves closer attention as it furnishes the call for transparency in algorithmic decision-making with both new tools and new challenges. (shrink)

One notable component to look at in the teaching-learning process is the way the subject is taught because one way or another, students are greatly affected by it. Viewing students’ perspectives on the use of the different teaching methods, this study determined the frequency of use of these teaching methods and their level of satisfaction. Through a systematic investigation, the findings from a critical questionnaire administered to first-year BS Hospitality Management college students at Ifugao State University were analyzed and (...) summarized. The frequency of use of the indicated instructional strategies was shown to have a significant relationship with student satisfaction in this study. Furthermore, the data reveal a substantial difference in student satisfaction with instructional approaches utilized before and during the pandemic. Students, on the other hand, prefer the teaching techniques employed before the outbreak to those utilized during the pandemic. (shrink)

Teachers' pedagogical strategy in teaching reading comprehension cannot be neglected because when learners fail to comprehend text and give meaning to it, they experience difficulties understanding other subjects taught. This study, therefore, examined reading comprehension strategies adopted by teachers to enhance reading comprehension among primary school learners. This study adopted a qualitative research method with an interpret visit paradigm. Ten (10) teachers were purposively selected for the study one each from ten (10) primary schools. Data was collected the selected participants (...) using semi-structured interview. The researchers ensured the trustworthiness of the interview through disclosure and corroboration. The data collected were transcribed for the purpose of analysis using the atlasti software and the thematic data analysis technique. Findings indicate that some teachers did not understand the various strategies to optimise reading comprehension. Teachers also lacked knowledge of the different learners learning preferences to plan their reading comprehension lessons. Furthermore, the lack of appropriate reading material and differentiated reading exercises for slow learners were highlighted among the challenges that hampered reading comprehension. The study recommends capacity-building programmes to provide strategies for differentiated teaching, to learn to accommodate slow learners and to provide appropriate resources by the education department. (shrink)

The nature of learning processes as well as evolutionary considerations suggest that aesthetic judgement is of central importance in the formation of custom. Learning and extrapolation rely on evaluations of non-instrumental features like simplicity, analogy, straightforwardness, and clarity. Further, learning is particularly effective if it is driven by an active desire to uncover new regularities, rather than merely gathering information in a passive way.From an evolutionary perspective, learning has evolved as an adaptation to fast and transitory (...) environmental changes which cannot be effectively traced by the slow and long-term evolutionary processes which take place on the genetic level. The evolutionary raison d’être of learning is to enable the individual to incessantly search for upcoming new regularities, and to act appropriately on them. As learning depends on aesthetic judgement, the evolutionary selection for learning implies an evolutionary molding of an aesthetic sense, and a preference for patterns and patterned action which ultimately leads to the formation of custom and social learning. The paper presents, thus, an evolutionary underpinning for the behavioral tendencies underlying my theory of custom. (shrink)

The ongoing explosion of interest in artificial intelligence is fueled in part by recently developed techniques in machine learning. Those techniques allow automated systems to process huge amounts of data, utilizing mathematical methods that depart from traditional statistical approaches, and resulting in impressive advancements in our ability to make predictions and uncover correlations across a host of interesting domains. But as is now widely discussed, the way that those systems arrive at their outputs is often opaque, even to the (...) experts who design and deploy them. Is it morally problematic to make use of opaque automated methods when making high-stakes decisions, like whether to issue a loan to an applicant, or whether to approve a parole request? Many scholars answer in the affirmative. However, there is no widely accepted explanation for why transparent systems are morally preferable to opaque systems. We argue that the use of automated decision-making systems sometimes violates duties of consideration that are owed by decision-makers to decision-subjects, duties that are both epistemic and practical in character. Violations of that kind generate a weighty consideration against the use of opaque decision systems. In the course of defending our approach, we show that it is able to address three major challenges sometimes leveled against attempts to defend the moral import of transparency in automated decision-making. (shrink)

Given the explanatory stalemate between ‘embedded’ (EMB) and ‘extended’ (EXT) cognition, various authors have proposed normative and moral arguments in favour of EXT. According to what we call the “extended cognition moral narrative” (EXT-MN) (Cassinadri, 2022), we should embrace EXT and dismiss EMB, because the former leads to morally preferable consequences with respect to the latter. In this article we argue that two arguments following the EXT moral narrative are flawed. In Sect. 2.1 and 2.2, we present respectively King (2016) (...) and Vold’s (2018) ‘argument from assessment of capacities’ (AAC) and Clowes (2013), Farina and Lavazza’s (2022a) ‘cognitive diminishment argument’ (CDA). The AAC states that we should embrace EXT over EMB since the former is better at attributing cognitive credit to individuals with learning disabilities who use assistive tools to complete their learning tasks, thus avoiding their marginalisation. The CDA states that EMB implies a morally undesirable picture of the agent in terms of cognitive diminishment. In Sect. 3, we clarify and criticise the underlying assumptions of the AAC and CDA: the “cognitive credit assumption”, the “marginalisation assumption” and, more generally, an ableist conception of disabled agency. In Sect. 3.1, we discuss the role of moto-perceptual skills and metacognitive credit involved in complex cases of tool-use, to demonstrate that the EXT-MN is uninformative in addressing these cases. To conclude, in Sect. 4 we argue that AAC and CDA fail to present EXT as descriptively and normatively superior to EMB. (shrink)

Semua orang memiliki kemampuan untuk belajar tetapi tidak semua orang memiliki keterampilan dalam belajar. Untuk menjadi terampil dalam belajar maka seseorang memerlukan prinsip Preferentisme agar ia dapat melakukan praktik belajar secara merdeka sesuai dengan preferensi belajarnya sendiri yang didasarkan pada Sense of Liking. Anda dapat mempelajari apa saja, kapan saja, dan di mana saja untuk memperoleh pengetahuan dan keterampilan yang anda butuhkan dengan tujuan akhir menjadi individu yang terampil dalam belajar. Buku ini diawali dengan penjelasan filosofis-teologis tentang alasan mengapa manusia (...) harus belajar. Selain itu, buku ini juga memberikan pemahaman secara teoretis dan praktis tetang bagaimana semestinya anda belajar dalam kemerdekaan dan merdeka dalam belajar berdasarkan pandangan Preferentisme. (shrink)

Nonindexical Context-Dependence and the Interpretation as Abduction Approach Inclusive nonindexical context-dependence occurs when the preferred interpretation of an utterance implies its lexically-derived meaning. It is argued that the corresponding processes of free or lexically mandated enrichment can be modeled as abductive inference. A form of abduction is implemented in Simple Type Theory on the basis of a notion of plausibility, which is in turn regarded a preference relation over possible worlds. Since a preordering of doxastic alternatives taken for itself only (...) amounts to a relatively vacuous ad hoc model, it needs to be combined with a rational way of learning from new evidence. Lexicographic upgrade is implemented as an example of how an agent might revise his plausibility ordering in light of new evidence. Various examples are given how this apparatus may be used to model the contextual resolution of context-dependent or semantically incomplete utterances. The described form of abduction is limited and merely serves as a proof of concept, but the idea in general has good potential as one among many ways to build a bridge between semantics and pragmatics since inclusive context-dependence is ubiquitous. (shrink)

Why learn about libertarianism? Because politics causes or exacerbates the very problems that it purports to solve, or it misperceives voluntary behaviour and free markets as problems. Liberty is always preferable: its maximal practical observance entailing self-ownership, private property, and consensual interactions. And libertarianism will be the ideological framework of the future of humankind.

Future-biased individuals systematically prefer positively valenced events to be in the future (positive future-bias) and negatively valenced events to be in the past (negative future-bias). The most extreme form of future-bias is absolute future-bias, whereby we completely discount the value of past events when forming our preferences. Various authors have thought that we are absolutely future-biased (Sullivan (2018:58); Parfit (1984:173) and that future-bias (absolute or otherwise) is at least rationally permissible (Prior (1959), Hare (2007; 2008), Kauppinen (2018), Heathwood (2008)). The (...) permissibility of future-bias is often held to be grounded in the structure of the temporal dimension. In this paper I consider several proposals for grounding the permissibility of such preferences and evaluate these in the light of the preferences we would have, and judge that we should have, in various time-travel scenarios. I argue that what we learn by considering these scenarios is that these preferences really have nothing to do with temporal structure. So if something grounds their permissibility, it is not temporal structure. (shrink)

Background: Besides regulatory learning skills, learning also requires students to relate to their social context and negotiate it as they transition and adjust to medical training. As such, there is a need to consider and explore the role of social and cultural aspects in student learning, particularly in problem-based learning, where the learning paradigm differs from what most students have previously experienced. In this article, we report on the findings of a study exploring first-year medical (...) students’ experiences during the first semester of an undergraduate problem-based learning medical program at an African medical school. Method: We employed a qualitative case study approach using in-depth interviews with 23 first-year medical students. Participants ranged in age from 18 to 25 years. All students were bi/multilingual (some spoke three to five languages), with English as the learning language. We conducted an inductive thematic analysis to systematically identify and analyze patterns in the data using the Braun and Clarke framework. Results: Before medical school, students worked hard to compete for admission to medical school, were primarily taught using a teacher-centered approach, and preferred working alone. At the beginning of medical school, students found it challenging to understand the problem-based learning process, the role of the case, speaking and working effectively in a group, managing a heavy workload, and taking increased responsibility for their learning. By the end of the first semester, most students were handling the workload better, were more comfortable with their peers and facilitators, and appreciated the value of the problem-based learning approach. Conclusions: Our study highlights the importance of interrogating contextual sociocultural factors that could cause tension when implementing problem-based learning in non-western medical schools. Adjustment to problem-based learning requires a conceptual and pedagogic shift towards learner-centered practice, particularly concerning self direction, the role of the case, and collaborative learning. As such, there is a need to develop and implement research informed learning development programs that enable students to reflect on their sociocultural beliefs and practices, and enhance their regulatory learning competence to optimize meaningful and early engagement with the problem based learning process. (shrink)

Universities seeking to provide modern education face a constant need to update their courses. This study was conducted to collect and analyze empirical data to help philosophy course designers consider the views of Ukrainian students about effective ways to learn this subject. A survey was conducted among 40 humanities students and 34 social science students to determine participants’ views on a number of key issues related to the organization of the learning process in the Philosophy course. Most of the (...) students surveyed said that of the types of skills and knowledge that can be acquired during the course, they will find critical thinking skills and the skills needed to build and argue their own positions on ethical, social and worldview issues most valuable in their future professional activities. The majority of respondents named traditional lectures and discussions of lecture videos as their preferred forms of learning philosophy. Their preferred forms of assessment of students’ knowledge and skills in philosophy were essays, as well as reports and participation in the discussion during practical lessons. The study also identified three significant differences in the responses of the surveyed humanities and social science students. First, socio-scientific students valued the opportunity to develop their communication skills in the framework of the Philosophy course significantly more than humanities students. Second, humanities students included thought experiments among the most desirable ways of learning philosophy, unlike social science students, who included case studies. Third, in contrast to humanities students, social science students considered quizzes to be one of the best forms of assessment for the course. In addition to the above, this study also compared the data on the opinions of social sciences and humanities students with the results of the previous survey of 60 STEM students about their thoughts on the course. The comparative analysis revealed five common features and two significant differences in the responses of students from these three fields of knowledge. The common belief among surveyed students in all three groups is that learning philosophy can provide them with the skills and knowledge they will need in their professional activities after graduation from university. Moreover, they prefer skills to knowledge. In all three groups of respondents, a large number of students named critical thinking and argumentation skills as the ultimate achievements in the learning of philosophy. Another finding was that surveyed students from all three groups do not give priority to learning the concepts of modern philosophers over learning the ideas of ancient philosophers. In addition, respondents from all three fields showed the least interest in those forms of knowledge and skills that are difficult to use outside of highly specialized philosophical activities. As for the differences, the study showed that STEM students are significantly less likely to believe that they will need the historico-philosophical components of the Philosophy course in their further professional activities than students in the humanities and social sciences. They are also more interested in developing communicative skills in the process of learning philosophy than the surveyed humanities students. (shrink)

The potential for Large Language Models (LLMs) to attain technological singularity—the point at which artificial intelligence (AI) surpasses human intellect and autonomously improves itself—is a critical concern in AI research. This paper explores the feasibility of current LLMs achieving singularity by examining the philosophical and practical requirements for such a development. We begin with a historical overview of AI and intelligence amplification, tracing the evolution of LLMs from their origins to state-of-the-art models. We then proposes a theoretical framework to assess (...) whether existing LLM technologies could satisfy the conditions for singularity, with a focus on Recursive Self-Improvement (RSI) and autonomous code generation. We integrate key component technologies, such as Reinforcement Learning from Human Feedback (RLHF) and Direct Preference Optimization (DPO), into our analysis, illustrating how these could enable LLMs to independently enhance their reasoning and problem-solving capabilities. By mapping out a potential singularity model lifecycle and examining the dynamics of exponential growth models, we elucidate the conditions under which LLMs might self-replicate and rapidly escalate their intelligence. We conclude with a discussion of the ethical and safety implications of such developments, underscoring the need for responsible and controlled advancement in AI research to mitigate existential risks. Our work aims to contribute to the ongoing dialogue on the future of AI and the critical importance of proactive measures to ensure its beneficial development. (shrink)

Abstract: Online book review platforms generate vast user data, making accurate rating prediction crucial for personalized recommendations. This research explores neural networks as simple models for predicting book ratings without complex algorithms. Our novel approach uses neural networks to predict ratings solely from user-book interactions, eliminating manual feature engineering. The model processes data, learns patterns, and predicts ratings. We discuss data preprocessing, neural network design, and training techniques. Real-world data experiments show the model's effectiveness, surpassing traditional methods. This research can (...) enhance user experience, book catalog organization, and aid publishers, simplifying recommendation processes and providing tailored suggestions based on user preferences. (shrink)

Schools worldwide have started opening doors to welcome back students who, for almost two years, have been stuck studying at home. This study looks at the standpoint of Filipino students on going back to regular face-to-face schooling. There were 2,274 students of different tiers of education (high school, collegiate, graduate) from different major island groups of the Philippines (Luzon, Visayas, Mindanao) who participated in the study. The study used a mixed-method of descriptive statistics to present the quantitative data gathered and (...) thematic analysis of qualitative responses from the subjects. The majority of all the respondents favored going back to the physical classroom, and little only favored staying using the distance mode. In the qualitative analysis, the recurring reasons of the students varied from personal, economic, and fear of getting the virus. It was concluded that Filipino students want to go back to schooling. Moreover, a sizeable amount preferred hybrid while a small number preferred to stay in online or distance mode. Educational institutions should always observe the covid 19 protocol when students go back. (shrink)

As a teacher in Singapore, I regularly encounter a classroom full of quiet students, reluctant to participate in class, to engage with the teacher when questioned, or even to volunteer for any project or initiative. Many teachers here are quick to conclude that Singapore students are passive or conformists. This observation is, in fact, not unique to students in Singapore, but also to the broader Asian region. Scholars like Cortazzi and Jin (1996) attributed such behaviour to the specific cultural values, (...) such as the importance of deference to the authority of a teacher, as reasons for such passivity and reticence. Liu and Littlewood (1997), on the other hand, argue that people from certain cultures prefer not to speak up so as to avoid entering into situations of uncertainty. I have found that as a teacher busily pre-occupied with preparing for classes, it is easy to forget how students perceive their learning experience, and I have been quite inclined to agree with the observations above. Fortunately, I have had the opportunity to be both a post-graduate student and a teacher. And this privileged position allows me to question some of my own assumptions as a teacher, thereby gaining deeper insights into the underlying reasons for the lack of participation here in Singapore. There is a lot more going on in the minds of Singapore students. Here, I would like to offer a new perspective on this matter. (shrink)

Since the beginning of the 21st century, technologies like neural networks, deep learning and “artificial intelligence” (AI) have gradually entered the artistic realm. We witness the development of systems that aim to assess, evaluate and appreciate artifacts according to artistic and aesthetic criteria or by observing people’s preferences. In addition to that, AI is now used to generate new synthetic artifacts. When a machine paints a Rembrandt, composes a Bach sonata, or completes a Beethoven symphony, we say that this (...) is neither original nor real art, but simply the complex imitation and reproduction of existing products of human culture. We face the old question concerning the nature of creativity: what kind of recombination of ideas, unusual analogies, and conceptual connections are considered the mark of originality? Can AI produce artworks? Could machines reach a point at which we consider them genuinely creative? We also need to investigate the challenges posed by AI-art to the notion of authoriality: Who is the author of an artificially generated artifact? An artificial system could be considered just an artist’s and a programmer’s tool. However, we are also fascinated by the idea of autonomous artificial creativity in the aesthetic domain, as a manifestation of highly intelligent behavior. This paper will try to define some key questions around what could it mean to consider a machine creative or even equipped with artistic intentionality. (shrink)

This inaugural lecture, delivered on 17 November 2021 at the University of Neuchâtel, addresses the question: Are material objects analyzable into more basic constituents and, if so, what are they? It might appear that this question is more appropriately settled by empirical means as utilized in the natural sciences. For example, we learn from physics and chemistry that water is composed of H2O-molecules and that hydrogen and oxygen atoms themselves are composed of smaller parts, such as protons, which are in (...) turn composed of yet smaller parts, such as quarks, and so on. While the question at the center of this lecture might thus appear to fall more appropriately into the empirical domain of natural science, I argue that metaphysics in fact has an important role to play in determining how best to answer the question before us. More concretely, I propose that the Aristotelian doctrine of hylomorphism, when appropriately interpreted, provides the best metaphysical answer to the question of whether and how material objects are analyzable into more basic constituents. Hylomorphism holds that those entities to which this doctrine applies are, in some sense, compounds of matter (“hylē”) and form (“morphē” or “eidos”). Thus, the title of this lecture, “Form, Matter, Substance”, refers to the claim that lies at the center of the doctrine of hylomorphism, as applied to the domain of material objects, namely that sensible substances are the result of combining matter and form in the right sort of way; or, for short, “form + matter = substance”. I begin in Section II by providing some historical background which brings out Aristotle’s motivations for proposing the doctrine of hylomorphism in the context of his analysis of change. Section III turns to some of the main features of the contemporary hylomorphic theory I have defended especially in Koslicki (2008) and Koslicki (2018). Section IV discusses some challenging questions concerning artifacts which arise for both hylomorphic and other approaches to the metaphysics of concrete particular objects. Section V concludes by summarizing why, as contemporary metaphysicians, we should prefer a hylomorphic theory over its competitors as an analysis of concrete particular objects that is compatible with our current scientific understanding of the world. (shrink)

On Hume’s account of motivation, beliefs and desires are very different kinds of propositional attitudes. Beliefs are cognitive attitudes, desires emotive ones. An agent’s belief in a proposition captures the weight he or she assigns to this proposition in his or her cognitive representation of the world. An agent’s desire for a proposition captures the degree to which he or she prefers its truth, motivating him or her to act accordingly. Although beliefs and desires are sometimes entangled, they play very (...) different roles in rational agency. In two classic papers (Lewis 1988, 1996), David Lewis discusses several challenges to this Humean picture, but ultimately rejects them. We think that his discussion of a central anti-Humean alternative – the desire-as-belief thesis – is in need of refinnement. On this thesis, the desire for proposition p is given by the belief that p is desirable. Lewis claims that ‘[e]xcept in trivial cases, [this thesis] collapses into contradiction’(Lewis 1996, p. 308). The problem, he argues, is that the thesis is inconsistent with the purportedly plausible requirement that one’s desire for a proposition should not change upon learning that the proposition is true; call this the invariance requirement. In this paper, we revisit Lewis’s argument. We show that, if one carefully distinguishes between non-evaluative and evaluative propositions, the desire-asbelief thesis can be rendered consistent with the invariance requirement. Lewis’s conclusion holds only under certain conditions: the desire-as-belief thesis conflicts with the invariance requirement if and only if there are certain correlations between non-evaluative and evaluative propositions. But when there are such correlations, we suggest, the invariance requirement loses its plausibility. Thus Lewis’s argument against the desire-as-belief thesis appears to be valid only in cases in which it is unsound. (shrink)

Following Freud’s analysis of the fragile line between the uncanny double and its comic redoubling, I identify the doubling of the double found in critical moments of Hegelian dialectic as producing a kind of comic effect. It almost goes without saying that two provides greater pleasure than one, the loneliest number. Many also find two to be preferable to three, the tired trope of dialectic as a teleological waltz. Two seems to offer lightness, relieving one from her loneliness and lacking (...) the complications of a third who comes in between. And yet, we learn through Marx and Freud that the double (even the double of tragedy and farce) borders on something closer to horror than comedy. -/- In the following, I would like to explore why four is funnier than two in my staging of dialectic as the doubling of the double or, to borrow a movie title from Laurel and Hardy, “Twice Two” (Roach et al. 1933a). I will begin by exploring the formulations of the double in the form of a pair of opposites and in the form of a pair of twins. The literary tropes of the double as the odd couple, on one side, and the twins, on the other, appear to serve very different narrative functions, which incite different kinds of affective responses from the audience. However, the form of the opposed double sometimes conceals the realization that the empty or fragmented content of the first is only reduplicated in the second. The “straight man” of the odd couple cannot see himself in his counterpart “the comic.” The redoubling of the double, however, forces not only the audience, but the original double on stage to confront what was already present, but unrealized, from the beginning. To illustrate this redoubling of the double within the opening of Hegel’s Science of Logic, I consider two short films by Laurel and Hardy in which the comic duo redoubles itself. The formula (2 x 2) produces a comic excess through the dialectical redoubling of there uncanny double. (shrink)

For several years, scholars have (for good reason) been largely preoccupied with worries about the use of artificial intelligence and machine learning (AI/ML) tools to make decisions about us. Only recently has significant attention turned to a potentially more alarming problem: the use of AI/ML to influence our decision-making. The contexts in which we make decisions—what behavioral economists call our choice architectures—are increasingly technologically-laden. Which is to say: algorithms increasingly determine, in a wide variety of contexts, both the sets (...) of options we choose from and the way those options are framed. Moreover, artificial intelligence and machine learning (AI/ML) makes it possible for those options and their framings—the choice architectures—to be tailored to the individual chooser. They are constructed based on information collected about our individual preferences, interests, aspirations, and vulnerabilities, with the goal of influencing our decisions. At the same time, because we are habituated to these technologies we pay them little notice. They are, as philosophers of technology put it, transparent to us—effectively invisible. I argue that this invisible layer of technological mediation, which structures and influences our decision-making, renders us deeply susceptible to manipulation. Absent a guarantee that these technologies are not being used to manipulate and exploit, individuals will have little reason to trust them. (shrink)

This research assesses the factors influencing students' decision-making when choosing a university. The study proposes eight factors, such as parental or guardian influence, high school teacher recommendations, graduate quality, colleague recommendations, location, school fees, learning environment, and university reputation, on students' university choices. A quantitative approach was employed, utilizing both secondary and primary data. A total of 330 students were sampled for this study. The data were analyzed using SPSS, employing descriptive statistics for data summarization and inferential statistics for (...) analysis. Descriptive tools such as frequency analysis were used to examine the distribution of responses, while regression analysis was conducted to test the predictive power of the factors. The findings of this study indicate that factors such as parental or guardian influence, high school teacher recommendations, graduate quality, colleague recommendations, location, school fees, learning environment, and university reputation are all significant considerations in students' decision-making process when choosing a university. These factors play an influential role in shaping students' preferences and choices. The results show that these factors significantly impact students' university choices. The study contributes to the existing literature by providing empirical evidence on the importance of these factors in the decision-making process. Understanding the influence of these factors can assist universities in developing targeted strategies to attract and meet the needs of prospective students. By recognizing the significance of parental involvement, fostering positive relationships with high school teachers, showcasing successful graduates, promoting positive word-of-mouth recommendations, providing a conducive learning environment, and building a solid reputation, universities can enhance their appeal and effectively compete in the higher education market. Further research in this area can explore additional factors and delve deeper into the mechanisms influencing students' decision-making when choosing a university. (shrink)

The thesis deals with the concept of truth and the paradoxes of truth. Philosophical theories usually consider the concept of truth from a wider perspective. They are concerned with questions such as - Is there any connection between the truth and the world? And, if there is - What is the nature of the connection? Contrary to these theories, this analysis is of a logical nature. It deals with the internal semantic structure of language, the mutual semantic connection of sentences, (...) above all the connection of sentences that speak about the truth of other sentences and sentences whose truth they speak about. Truth paradoxes show that there is a problem in our basic understanding of the language meaning and they are a test for any proposed solution. It is important to make a distinction between the normative and analytical aspect of the solution. The former tries to ensure that paradoxes will not emerge. The latter tries to explain paradoxes. Of course, the practical aspect of the solution is also important. It tries to ensure a good framework for logical foundations of knowledge, for related problems in Artificial Intelligence and for the analysis of the natural language. Tarski’s analysis emphasized the T-scheme as the basic intuitive principle for the concept of truth, but it also showed its inconsistency with the classical logic. Tarski’s solution is to preserve the classical logic and to restrict the scheme: we can talk about the truth of sentences of a language only inside another essentially richer metalanguage. This solution is in harmony with the idea of reflexivity of thinking and it has become very fertile for mathematics and science in general. But it has normative nature | truth paradoxes are avoided in a way that in such frame we cannot even express paradoxical sentences. It is also too restrictive because, for the same reason we cannot express a situation in which there is a circular reference of some sentences to other sentences, no matter how common and harmless such a situation may be. Kripke showed that there is no natural restriction to the T-scheme and we have to accept it. But then we must also accept the riskiness of sentences | the possibility that under some circumstances a sentence does not have the classical truth value but it is undetermined. This leads to languages with three-valued semantics. Kripke did not give any definite model, but he gave a theoretical frame for investigations of various models | each fixed point in each three-valued semantics can be a model for the concept of truth. The solutions also have normative nature | we can express the paradoxical sentences, but we escape a contradiction by declaring them undetermined. Such a solution could become an analytical solution only if we provide the analysis that would show in a substantial way that it is the solution that models the concept of truth. Kripke took some steps in the direction of finding an analytical solution. He preferred the strong Kleene three-valued semantics for which he wrote it was "appropriate" but did not explain why it was appropriate. One reason for such a choice is probably that Kripke finds paradoxical sentences meaningful. This eliminates the weak Kleene three valued semantics which corresponds to the idea that paradoxical sentences are meaningless, and thus indeterminate. Another reason could be that the strong Kleene three valued semantics has the so-called investigative interpretation. According to this interpretation, this semantics corresponds to the classical determination of truth, whereby all sentences that do not have an already determined value are temporarily considered indeterminate. When we determine the truth value of these sentences, then we can also determine the truth value of the sentences that are composed of them. Kripke supplemented this investigative interpretation with an intuition about learning the concept of truth. That intuition deals with how we can teach someone who is a competent user of an initial language (without the predicate of truth T) to use sentences that contain the predicate T. That person knows which sentences of the initial language are true and which are not. We give her the rule to assign the T attribute to the former and deny that attribute to the latter. In that way, some new sentences that contain the predicate of truth, and which were indeterminate until then, become determinate. So the person gets a new set of true and false sentences with which he continues the procedure. This intuition leads directly to the smallest fixed point of strong Kleene semantics as an analytically acceptable model for the logical notion of truth. However, since this process is usually saturated only on some transfinite ordinal, this intuition, by climbing on ordinals, increasingly becomes a metaphor. This thesis is an attempt to give an analytical solution to truth paradoxes. It gives an analysis of why and how some sentences lack the classical truth value. The starting point is basic intuition according to which paradoxical sentences are meaningful (because we understand what they are talking about well, moreover we use it for determining their truth values), but they witness the failure of the classical procedure of determining their truth value in some "extreme" circumstances. Paradoxes emerge because the classical procedure of the truth value determination does not always give a classically supposed (and expected) answer. The analysis shows that such an assumption is an unjustified generalization from common situations to all situations. We can accept the classical procedure of the truth value determination and consequently the internal semantic structure of the language, but we must reject the universality of the exterior assumption of a successful ending of the procedure. The consciousness of this transforms paradoxes to normal situations inherent to the classical procedure. Some sentences, although meaningful, when we evaluate them according to the classical truth conditions, the classical conditions do not assign them a unique value. We can assign to them the third value, \undetermined", as a sign of definitive failure of the classical procedure. An analysis of the propagation of the failure in the structure of sentences gives exactly the strong Kleene three-valued semantics, not as an investigative procedure, as it occurs in Kripke, but as the classical truth determination procedure accompanied by the propagation of its own failure. An analysis of the circularities in the determination of the classical truth value gives the criterion of when the classical procedure succeeds and when it fails, when the sentences will have the classical truth value and when they will not. It turns out that the truth values of sentences thus obtained give exactly the largest intrinsic fixed point of the strong Kleene three-valued semantics. In that way, the argumentation is given for that choice among all fixed points of all monotone three-valued semantics for the model of the logical concept of truth. An immediate mathematical description of the fixed point is given, too. It has also been shown how this language can be semantically completed to the classical language which in many respects appears a natural completion of the process of thinking about the truth values of the sentences of a given language. Thus the final model is a language that has one interpretation and two systems of sentence truth evaluation, primary and final evaluation. The language through the symbol T speaks of its primary truth valuation, which is precisely the largest intrinsic fixed point of the strong Kleene three valued semantics. Its final truth valuation is the semantic completion of the first in such a way that all sentences that are not true in the primary valuation are false in the final valuation. (shrink)

Epistemic Authority is a mature work of a leading epistemologist and philosopher of religion. It is a work primarily in epistemology with applications to religious epistemology. There are obvious applications of the notion of epistemic authority to philosophy of religion. For, on the face of it, the notion of some kind of ”epistemic authority’ may serve as a conceptual anchor for our understanding of faith. Indeed, there is ample historical precedent for this. Faith, says Locke, is ”the assent to any (...) proposition... upon the credit of the proposer, as coming from God, in some extraordinary way of communication’. 1 In later Lockeans, ”credit’ is often rendered ”authority’, and the terms were used synonymously at the time of his writing. 2 One of the beauties of Locke’s view is its reductionism, that is, it’s parsimony, which is a species of elegance and therefore beauty. Zagzebski’s notion is more high-octane than Locke’s. In this essay I will do four things. In Section 1 I will describe two kinds or notions of authority or at least two usages of the word ”authority’. In Section 2 I will describe Zagzebski’s use of one of these notions, the non-Lockean one, to ground the reasonableness of religious belief. In Section 3 I will give four arguments against her view. In section 4 I will reply to her critique of Locke. The upshot, in my view, is that though we learn much from Epistemic Authority, a more Lockean approach to the nature of faith is still preferable. (shrink)

We demonstrate how Darwinian evolution enhances decision-making via experiential learning and game-theoretical strategies. To an external observer, the resultant moderate intra-individual variability is indistinguishable from free will. We conclude that this evolutionary outcome is the simplest explanation for decision-making, thus being preferable according to Occam's razor, and implying that free will is an illusion. Furthermore, we argue that the perception of free will exists due to evolutionary benefits.

Nel 1956, in piena guerra fredda, una conferenza di scienziati al Dartmouth College negli Stati Uniti annunciò il lancio di un audace progetto scientifico, l’Intelligenza Artificiale (I.A.). Dopo l’iniziale fallimento degli sforzi della “Hard AI” di produrre un’intelligenza simile a quella umana, alla fine del XX secolo è emerso il movimento della “Soft AI”. Invece di essere orientato a imitare il comportamento umano in relazione a compiti specifici, ha preferito cercare modi alternativi di eseguire i compiti basati sulle particolari funzioni (...) e strutture della macchina. Il fattore decisivo è stata la combinazione della tecnologia di apprendimento automatico con le comunicazioni digitali online, l’incontro tra l’IA e Internet. Le applicazioni dell’IA “soft” sono quelle che vediamo nel mondo dei dispositivi automatici “intelligenti” che informano la nostra vita sociale digitale. Nel seguente articolo mi concentrerò su una particolare applicazione dell’IA per le discussioni online con utenti umani, ChatGPT, per mostrare le implicazioni della tecnologia digitale online nelle modalità storico-sociali dell’esistenza umana. ChatGPT è un’applicazione che combina l’IA con Internet, le possibilità della corrispondenza tra macchine e le potenzialità della tele-comunicazione umana. Il mio approccio si concentra sulle implicazioni fenomenologiche e storico-sociali della proliferazione della tecnologia AI per quanto riguarda la coscienza e la socialità umana. -/- Abstract (english) -/- In 1956, amidst the Cold War, a conference of scientists at Dartmouth College in the United States announced the launch of a bold, scientific project, Artificial Intelligence (A.I.). After the initial failure of “Hard AI” efforts to produce a human-like intelligence, the “Soft AI” movement emerged in the late 20th century. Instead of being oriented towards imitating human behaviour concerning specific tasks, it preferred to seek alternative ways of performing tasks based on the particular functions and structures of the machine. The decisive factor was the combination of Machine Learning technology with Digital Online Communications, the meeting between AI and the Internet. The applications of “Soft” AI are those we see in the world of “smart”, “intelligent” automatic devices that inform our digital social life. In the following article, I will focus on a particular application of AI for online discussions with human users, ChatGPT, in order to show the implications of online digital technology in the social-historical modalities of human existence. ChatGPT is an application that combines AI with the Internet, the possibilities of Machine correspondence with the potentialities of human telecommunications. My approach focuses on the phenomenological and social-historical implications of the proliferation of AI technology as regards human consciousness and sociality. (shrink)

One of the main lines of research in algorithmic fairness involves individual fairness (IF) methods. Individual fairness is motivated by an intuitive principle, similar treatment, which requires that similar individuals be treated similarly. IF offers a precise account of this principle using distance metrics to evaluate the similarity of individuals. Proponents of individual fairness have argued that it gives the correct definition of algorithmic fairness, and that it should therefore be preferred to other methods for determining fairness. I argue that (...) individual fairness cannot serve as a definition of fairness. Moreover, IF methods should not be given priority over other fairness methods, nor used in isolation from them. To support these conclusions, I describe four in-principle problems for individual fairness as a definition and as a method for ensuring fairness: (1) counterexamples show that similar treatment (and therefore IF) are insufficient to guarantee fairness; (2) IF methods for learning similarity metrics are at risk of encoding human implicit bias; (3) IF requires prior moral judgments, limiting its usefulness as a guide for fairness and undermining its claim to define fairness; and (4) the incommensurability of relevant moral values makes similarity metrics impossible for many tasks. In light of these limitations, I suggest that individual fairness cannot be a definition of fairness, and instead should be seen as one tool among several for ameliorating algorithmic bias. (shrink)

Abstract: This research delves into the utilization of Artificial Neural Networks (ANNs) as a powerful tool for predicting the overall ratings of books by leveraging a diverse set of attributes. To achieve this, we employ a comprehensive dataset sourced from Goodreads, enabling us to thoroughly examine the intricate connections between the different attributes of books and the ratings they receive from readers. In our investigation, we meticulously scrutinize how attributes such as genre, author, page count, publication year, and reader reviews (...) influence a book's overall rating. Through rigorous analysis and experimentation, we construct an advanced ANN model tailored for predictive analysis in the realm of book ratings. The outcomes of our study reveal the remarkable potential of ANNs in this domain. The ANN model exhibits an impressive level of accuracy when it comes to forecasting book ratings, underlining the efficacy and promise of artificial neural networks in enhancing our understanding and prediction of book evaluations. This research opens up new avenues for leveraging machine learning techniques to gain deeper insights into the dynamics of book ratings and reader preferences. (shrink)

With the current international competition among global companies, Business English as a Lingua Franca (BEFL) has become a necessity. As for one, Boardwalk Direct Selling Company recognizes the adoption of the BEFL concept within the organization to equip its workforce with adequate English language skills at par with global standards. This study aims to assess the organization’s current English proficiency and the readiness of its employees to embrace BEFL. This also presents the major English language skills areas that need improvement (...) through training intervention. A stratified sampling method is utilized to extract data via an online survey. Respondents are strategically chosen to represent different strata such as organizational departments or groups, job levels, tenure, and age. A convenient size of 34 respondents participated in this study. Generally, respondents acknowledge the importance of the English language skill set in their job functions and as criteria for their career growth. Half of the sampling population affirms their English language proficiency. However, the study reveals that Boardwalk employees are willing to subject themselves to improving their English skills, most particularly in speaking and writing aspects. Given their willingness, the employees recommend that the company strengthen its BEFL trainings across the organization. Moreover, with the current setup of mostly working from home due to COVID restrictions, majority of the employees prefer online learning. (shrink)

Evolutionary psychologists often try to “bring together” biology and psychology by making predictions about what specific psychological mechanisms exist from theories about what patterns of behaviour would have been adaptive in the EEA for humans. This paper shows that one of the deepest methodological generalities in evolutionary biology—that proximate explanations and ultimate explanations stand in a many-to-many relation—entails that this inferential strategy is unsound. Ultimate explanations almost never entail the truth of any particular proximate hypothesis. But of course it does (...) not follow that there are no other ways of “bringing together” biology and psychology. Accordingly, this paper explores one other strategy for doing just that, the pursuit of a very specific kind of consilience. However, I argue that inferences reflecting the pursuit of this kind of consilience with the best available theories in contemporary evolutionary biology indicate that psychologists should have a preference for explanations of adaptive behavior in humans that refer to learning and other similarly malleable psychological mechanisms—and not modules or instincts or any other kind of relatively innate and relatively non-malleable psychological mechanism. (shrink)