Unless and until our society recognizes cyber bullying for what it is, the suffering of thousands of silent victims will continue.” ~ Anna Maria Chavez. There had been series of research on cyber bullying which are unable to provide reliable solution to cyber bullying. In this research work, we were able to provide a permanent solution to this by developing a model capable of detecting and intercepting bullying incoming and outgoing messages with 92% accuracy. We also developed a chatbot automation (...) messaging system to test our model leading to the development of Artificial Intelligence powered anti-cyber bullying system using machine learning algorithm of Multinomial Naïve Bayes (MNB) and optimized linear Support Vector Machine(SVM). Our model is able to detect and intercept bullying outgoing and incoming bullying messages and take immediate action. (shrink)

Text classification is one of the most important task in natural language processing, In this research, we carried out several experimental research on three (3) of the most popular Text classification NLP classifier in Convolutional Neural Network (CNN), Multinomial Naive Bayes (MNB), and Support Vector Machine (SVN). In the presence of enough training data, Deep Learning CNN work best in all parameters for evaluation with 77% accuracy, followed by SVM with accuracy of 76%, and multinomial Bayes (...) with least performance of 69% accuracy. CNN has the best performance in the presence of large enough training dataset because of the presence of filter/ kernels which help to indentify patterns in text data regardless of their position in the sentence. We repeated the training again with just one-third of our data, at this point SVM comes with the best performance, the performance of CNN noticeably drops but still better than Multinomial Naive Bayes, the reason why SVM works best when we reduce the training data was because of its ability to look for a hyper-plane that creates a boundary between different classes of data so as to properly classify them, so we believed that getting the hyper-plane was more efficient when we reduce the dataset, hence reason for the good performance. Multinomial Naive Bayes have the least performance which we attributed to its assumption of independency between the features which sometimes does not hold true. We concluded that availability of data should be an important factor when choosing classifier for Natural Language Processing Text Classification task. CNN should be use in the presence of enough dataset, and SVM should be use when data is not enough. Multinomial Naive Bayes must not be trusted with state of the art NLP task due to its assumption of independency between the features . (shrink)

Text classification is one of the most important task in natural language processing, In this research, we carried out several experimental research on three (3) of the most popular Text classification NLP classifier in Convolutional Neural Network (CNN), Multinomial Naive Bayes (MNB), and Support Vector Machine (SVN). In the presence of enough training data, Deep Learning CNN work best in all parameters for evaluation with 77% accuracy, followed by SVM with accuracy of 76%, and multinomial Bayes (...) with least performance of 69% accuracy. CNN has the best performance in the presence of large enough training dataset because of the presence of filter/ kernels which help to indentify patterns in text data regardless of their position in the sentence. -/- We repeated the training again with just one-third of our data, at this point SVM comes with the best performance, the performance of CNN noticeably drops but still better than Multinomial Naive Bayes, the reason why SVM works best when we reduce the training data was because of its ability to look for a hyper-plane that creates a boundary between different classes of data so as to properly classify them, so we believed that getting the hyper-plane was more efficient when we reduce the dataset, hence reason for the good performance. Multinomial Naive Bayes have the least performance which we attributed to its assumption of independency between the features which sometimes does not hold true. We concluded that availability of data should be an important factor when choosing classifier for Natural Language Processing Text Classification task. CNN should be use in the presence of enough dataset, and SVM should be use when data is not enough. Multinomial Naive Bayes must not be trusted with state of the art NLP task due to its assumption of independency between the features. (shrink)

Bayesian classifiers perform well when each of the features is completely independent of the other which is not always valid in real world applications. The aim of this study is to implement and compare the performances of each variant of the Bayesian classifier (Multinomial, Bernoulli, and Gaussian) on anomaly detection in network intrusion, and to investigate whether there is any association between each variant’s assumption and their performance. Our investigation showed that each variant of the Bayesian algorithm blindly follows (...) its assumption regardless of feature property, and that the assumption is the single most important factor that influences their accuracy. Experimental results show that Bernoulli has accuracy of 69.9% test (71% train), Multinomial has accuracy of 31.2% test (31.2% train), while Gaussian has an accuracy of 81.69% test (82.84% train). Going deeper, we investigated and found that each Naïve Bayes variants performances and accuracy is largely due to each classifier assumption, Gaussian classifier performed best on anomaly detection due to its assumption that features follow normal distributions which are continuous, while multinomial classifier have a dismal performance as it simply assumes discreet and multinomial distribution. (shrink)

In this paper, we investigated multiple machine learning classifiers which are, Multinomial Naive Bayes, Support Vector Machine, Decision Tree, K Nearest Neighbors, and Random Forest in a text classification problem. The data we used contains real and fake job posts. We cleaned and pre-processed our data, then we applied TF-IDF for feature extraction. After we implemented the classifiers, we trained and evaluated them. Evaluation metrics used are precision, recall, f-measure, and accuracy. For each classifier, results were summarized and (...) compared with others. (shrink)

The college hopes that every semester students are able to pay tuition properly and smoothly. The hope is that the institution will be able to maintain monthly cash flow so that its operational and maintenance costs can be met. Therefore, this study was conducted to predict and fulfill the institution's cash-in from the method of paying tuition fees either by cash, installments, or sometimes late payments every semester. In predicting the method of paying tuition fees, using student profile data (name, (...) name, study program) and achievement index every semester for 5 semesters passed and the method of payment (cash, installments, and late--cash or installments). Using the Naive Bayes (NB) method, Support Vector Machine (SVM), and Deep Learning, this study aims to forecast tuition costs. The Classification Prediction Model with Naive Bayes, SVM, and Deep Learning produces Confusion Matrix Performance NB with an Accuracy of 91.49%, Confusion Matrix Performance SVM with an Accuracy of 85.11%, and Confusion Matrix Performance Deep Learning with an Accuracy of 89.36%, according to the research findings. (shrink)

Phishing is one of the most effective ways in which cybercriminals get sensitive details such as credentials for online banking, digital wallets, state secrets, and many more from potential victims. They do this by spamming users with malicious URLs with the sole purpose of tricking them into divulging sensitive information which is later used for various cybercrimes. In this research, we did a comprehensive review of current state-of-the-art machine learning and deep learning phishing detection techniques to expose their vulnerabilities and (...) future research direction. For better analysis and observation, we split machine learning techniques into Bayesian, non-Bayesian, and deep learning. We reviewed the most recent advances in Bayesian and non-Bayesian-based classifiers before exploiting their cor- responding weaknesses to indicate future research direction. While exploiting weaknesses in both Bayesian and non-Bayesian classifiers, we also compared each performance with a deep learning classifier. For a proper review of deep learning-based classifiers, we looked at Recurrent Neural Networks (RNN), Convolutional Neural Networks (CNN), and Long Short Term Memory Networks (LSTMs). We did an empirical analysis to evaluate the performance of each classifier along with many of the proposed state-of-the-art anti-phishing techniques to identify future research directions, we also made a series of proposals on how the performance of the under-performing algorithm can improved in addition to a two-stage prediction model. (shrink)

Chronic kidney disease (CKD) is a global health problem with high morbidity and mortality rate, and it induces other diseases. There are no obvious incidental effects during the starting periods of CKD, patients routinely disregard to see the sickness. Early disclosure of CKD enables patients to seek helpful treatment to improve the development of this disease. AI models can effectively assist clinical with achieving this objective on account of their fast and exact affirmation execution. In this appraisal, proposed a Logistic (...) relapse framework for diagnosing CKD. Proposed calculation like NAIVE BAYES , DECISION TREE , KSTAR , LOGISITIC , AND SVM and look at these calculation and get the most noteworthy precision .AI store, which has an enormous number of missing qualities. Missing characteristics are for the most part found, taking everything into account, clinical conditions since patients might miss a couple of assessments for various reasons. By separating the misjudgements delivered by the set up models and proposed a fused model that unites determined backslide and sporadic woods by using perceptron. (shrink)

The availability of large digital archives of historical newspaper content has transformed the historical sciences. However, the scale of these archives can limit the direct application of advanced text processing methods. Even if it is computationally feasible to apply sophisticated language processing to an entire digital archive, if the material of interest is a small fraction of the archive, the results are unlikely to be useful. Methods for generating smaller specialized corpora from large archives are required to solve this problem. (...) This article presents such a method for historical newspaper archives digitized using the METS/ALTO XML standard (Veridian Software, n.d.). The method is an ‘iterative bootstrapping’ approach in which candidate corpora are evaluated using text mining techniques, items are manually labelled, and Naïve Bayes text classifiers are trained and applied in order to produce new candidate corpora. The method is illustrated by a case study that investigates philosophical content, broadly construed, in pre-1900 English-language New Zealand newspapers. Extensive code is provided in Supplementary Materials. (shrink)

Abstract—Breast cancer is considered the second most common cancer in women compared to all other cancers. It is fatal in less than half of all cases and is the main cause of mortality in women. It accounts for 16% of all cancer mortalities worldwide. Early diagnosis of breast cancer increases the chance of recovery. Data mining techniques can be utilized in the early diagnosis of breast cancer. In this paper, an academic experimental breast cancer dataset is used to perform a (...) data mining practical experiment using the Waikato Environment for Knowledge Analysis (WEKA) tool. The WEKA Java application represents a rich resource for conducting performance metrics during the execution of experiments. Pre-processing and feature extraction are used to optimize the data. The classification process used in this study was summarized through thirteen experiments. Additionally, 10 experiments using various different classification algorithms were conducted. The introduced algorithms were: Naïve Bayes, Logistic Regression, Lazy IBK (Instance-Bases learning with parameter K), Lazy Kstar, Lazy Locally Weighted Learner, Rules ZeroR, Decision Stump, Decision Trees J48, Random Forest and Random Trees. The process of producing a predictive model was automated with the use of classification accuracy. Further, several experiments on classification of Wisconsin Diagnostic Breast Cancer and Wisconsin Breast Cancer, were conducted to compare the success rates of the different methods. Results conclude that Lazy IBK classifier k-NN can achieve 98% accuracy among other classifiers. The main advantages of the study were the compactness of using 13 different data mining models and 10 different performance measurements, and plotting figures of classifications errors. (shrink)

Lately in the past couple of years, there are an increasing in the normal rate of playing computer games or video games compared to the E-learning content that are introduced for the safety of our children, and the impact of the video game addictiveness that ranges from (Musculoskeletal issues, Vision problems and Obesity). Furthermore, this paper introduce an intelligent tutoring system for both parent and their children for enhancement the experience of gaming and tell us about the health problems and (...) how we can solve them, with an easy user interface that way can our children be happy and excited about the information and their health. (shrink)

Plagiarism detection is the process of finding similarities on electronic based documents. Recently, this process is highly required because of the large number of available documents on the internet and the ability to copy and paste the text of relevant documents with simply Control+C and Control+V commands. The proposed solution is to investigate and develop an easy, fast, and multi-language support plagiarism detector with the easy of one click to detect the document plagiarism. This process will be done with the (...) support of intelligent system that can learn, change and adapt to the input document and make a cross-fast search for the content on the local repository and the online repository and link the content of the file with the matching content everywhere found. Furthermore, the supported document type that we will use is word, text and in some cases, the pdf files –where is the text can be extracting from them- and this made possible by using the DLL file from Word application that Microsoft provided on OS. The using of DLL will let us to not constrain on how to get the text from files; and will help us to apply the file on our Delphi project and walk throw our methodology and read the file word by word to grantee the best working scenarios for the calculation. In the result, this process will help in the uprising the documents quality and enhance the writer experience related to his work and will save the copyrights for the official writer of the documents by providing a new alternative tool for plagiarism detection problem for easy and fast use to the concerned Institutions for free. (shrink)

Abstract: The integration of Artificial Intelligence (AI) into leadership practices is rapidly transforming organizational dynamics and decision-making processes. This paper explores the ways in which AI enhances leadership effectiveness by providing data- driven insights, optimizing decision-making, and automating routine tasks. Additionally, it examines the challenges leaders face when adopting AI, including ethical considerations, potential biases in AI systems, and the need for upskilling. By analyzing current applications of AI in leadership and discussing future trends, this study aims to offer a (...) comprehensive overview of the opportunities AI presents for effective leadership, as well as the strategies required to address its associated challenges. (shrink)

The proposed paper presents an argument in favor of a Rawlsian approach to ethics for Internet technology companies (den Hoven & Rooksby, 2008; Hoffman, 2017). Ethics statements from such companies are analyzed and shown to be utilitarian and teleological in nature, and therefore in opposition to Rawls’ theories of justice and fairness. The statements are also shown to have traits in common with Confucian virtue ethics (Ames, 2011; Nylan, 2008).

Lately in the past couple of years, there are an increasing in the normal rate of playing computer games or video games compared to the E-learning content that are introduced for the safety of our children, and the impact of the video game addictiveness that ranges from (Musculoskeletal issues, Vision problems and Obesity). Furthermore, this paper introduce an intelligent tutoring system for both parent and their children for enhancement the experience of gaming and tell us about the health problems and (...) how we can solve them, with an easy user interface that way can our children be happy and excited about the information and their health. (shrink)

Nghiên cứu này được thực hiện nhằm đánh giá thực trạng hành vi và mức độ tiếp cận giáo dục về vấn đề rác thải nhựa của học sinh trung học phổ thông ở khu vực Miền Trung. Kết quả khảo sát trên 2183 học sinh thuộc 10 tỉnh thành ở Miền Trung trong khoảng thời gian từ tháng 9 tới tháng 12 năm 2022 cho thấy: mặc dù, nhận thức của học sinh về vấn đề rác thải nhựa tương (...) đối cao song kiến thức và hành vi đối với vấn đề rác thải nhựa vẫn còn nhiều hạn chế; công tác giáo dục về rác thải nhựa hiện nay trong các trường học chủ yếu ở mức thỉnh thoảng thực hiện và hiệu quả chưa thật sự cao như kì vọng; hành vi đối với vấn đề rác thải nhựa của học sinh có sự khác biệt liên quan tới giới tính; khối lớp và giữa các địa bàn nghiên cứu. Kết quả nghiên cứu là cơ sở để đề xuất các biện pháp giáo dục phù hợp cho học sinh trung học phổ thông tại các tỉnh Miền Trung. [This study evaluates the current status of behavior and level of access to education on the issue of plastic waste among high school students in Central Vietnam. Survey results on 2,183 students from 10 provinces and cities in the Central region from September to December 2022 show that although students' awareness of the plastic waste issue is relatively high, but their knowledge and behavior towards plastic waste still has many limitations; current education about plastic waste in schools is mainly done occasionally, and the effectiveness is lower than expected; students' behavior towards plastic waste has gender-related differences; grade levels and between research areas. The research results are the basis for proposing appropriate educational measures for high school students in Central Vietnam.]. (shrink)

Today’s everyone normal life can include a normal rate of playing computer games or video games; but what about an excessive or compulsive use of video games that impact on our life? Our kids, who usually spend a lot of time in playing video games will likely have a trouble in paying attention to their school lessons. In this paper, we introduce an expert system to help users in getting the correct diagnosis of the health problem of video game addictions (...) that range from (Musculoskeletal issues, Vision problems and Obesity). Moreover, this expert system provides information about the problem and tell us how we can solve it. SL5 Object expert system language was used to design and implement the expert system. (shrink)

Naïve Realists think that the ordinary mind-independent objects that we perceive are constitutive of the character of experience. Some understand this in terms of the idea that experience is diaphanous: that the conscious character of a perceptual experience is entirely constituted by its objects. My main goal here is to argue that Naïve Realists should reject this, but I’ll also highlight some suggestions as to how Naïve Realism might be developed in a non-diaphanous direction.

Perceptual experience has representational content. My argument for this claim is an inference to the best explanation. The explanandum is cognitive penetration. In cognitive penetration, perceptual experiences are either causally influenced, or else are partially constituted, by mental states that are representational, including: mental imagery, beliefs, concepts and memories. If perceptual experiences have representational content, then there is a background condition for cognitive penetration that renders the phenomenon prima facie intelligible. Naïve realist or purely relational accounts of perception leave (...) cognitive penetration less well-explained, even when formulated with so-called ‘standpoints’ or ‘third relata.’. (shrink)

Visual experiences seem to exhibit phenomenological particularity: when you look at some object, it – that particular object – looks some way to you. But experiences exhibit generality too: when you look at a distinct but qualitatively identical object, things seem the same to you as they did in seeing the first object. Naïve realist accounts of visual experience have often been thought to have a problem with each of these observations. It has been claimed that naïve realist (...) views cannot account for the generality of visual experiences, and that the naïve realist explanation of particularity has unacceptable implications for self- knowledge: the knowledge we have of the character of our own experiences. We argue in this paper that neither claim is correct: naïve realism can explain the generality of experiences, and the naïve realist explanation of particularity raises no problems for our self-knowledge. (shrink)

Unconscious perceptions have recently become a focal point in the debate for and against naive realism. In this paper I defend the naive realist side. More specifically, I use an idea of Martin’s to develop a new version of naive realism—neuro-computational naive realism. I argue that neuro-computational naive realism offers a uniform treatment of both conscious and unconscious perceptions. I also argue that it accommodates the possibility of phenomenally different conscious perceptions of the same items, and that it can answer (...) a further challenge to naive realism raised by Berger and Nanay. (shrink)

Different authors offer subtly different characterizations of naïve realism. We disentangle the main ones and argue that illusions provide the best proving ground for naïve realism and its main rival, representationalism. According to naïve realism, illusions never involve per- ceptual error. We assess two leading attempts to explain apparent perceptual error away, from William Fish and Bill Brewer, and conclude that they fail. Another lead- ing attempt is assessed in a companion paper, which also sketches an alternative (...) representational account. (shrink)

It has been claimed that naïve realism predicts phenomenological similarities where there are none and, thereby, mischaracterises the phenomenal character of perceptual experience. If true, this undercuts a key motivation for the view. Here, we defend naïve realism against this charge, proposing that such arguments fail (three times over). In so doing, we highlight a more general problem with critiques of naïve realism that target the purported phenomenological predictions of the view. The problem is: naïve realism, (...) broadly construed, doesn’t make phenomenological predictions of the required sort. So, as a result, opponents must resign themselves to attacking specific incarnations of naïve realism, or approach matters quite differently. (shrink)

Relationalism maintains that perceptual experience involves, as part of its nature, a distinctive kind of conscious perceptual relation between a subject of experience and an object of experience. Together with the claim that perceptual experience is presentational, relationalism is widely believed to be a core aspect of the naive realist outlook on perception. This is a mistake. I argue that naive realism about perception can be upheld without a commitment to relationalism.

Early twentieth-century philosophers of perception presented their naïve realist views of perceptual experience in anti-Kantian terms. For they took naïve realism about perceptual experience to be incompatible with Kant’s claims about the way the understanding is necessarily involved in perceptual consciousness. This essay seeks to situate a naïve realist account of visual experience within a recognisably Kantian framework by arguing that a naïve realist account of visual experience is compatible with the claim that the understanding is (...) necessarily involved in the perceptual experience of those rational beings with discursive intellects. The resultant view is middle way between recent conceptualist and non-conceptualist interpretations of Kant, holding that the understanding is necessarily involved in the kind of perceptual consciousness that we, as rational beings, enjoy whilst allowing that the relations of apprehension which constitute perceptual consciousness are independent of acts of the understanding. (shrink)

In a recent paper, Berger and Nanay consider, and reject, three ways of addressing the phenomenon of unconscious perception within a naïve realist framework. Since these three approaches seem to exhaust the options open to naïve realists, and since there is said to be excellent evidence that perception of the same fundamental kind can occur, both consciously and unconsciously, this is seen to present a problem for the view. We take this opportunity to show that all three approaches (...) considered remain perfectly plausible ways of addressing unconscious perception within a naïve realist framework. So far from undermining the credibility of naïve realism, Berger and Nanay simply draw our attention to an important question to be considered by naïve realists in future work. Namely, which of the approaches considered is most likely to provide an accurate account of unconscious perception in each of its purported incarnations? (shrink)

This paper sets out a novel response to the ‘screening off problem’ for naïve realism. The aim is to resist the claim (which many naïve realists accept) that the kind of experience involved in hallucinating also occurs during perception, by arguing that there are causal constraints that must be met if an hallucinatory experience is to occur that are never met in perceptual cases. Notably, given this response, it turns out that, contra current orthodoxy, naïve realists need (...) not adopt any particular view about the psychological nature of hallucinatory experience to handle the screening off problem. Consequently, room opens up for naïve realists to endorse whatever theory of hallucinatory experience seems to best capture the distinctive nature of such episodes. (shrink)

This paper defends the idea that phenomenological approaches to self-consciousness can enrich the current analytic philosophy of perception, by showing how phenomenological discussions of minimal self-consciousness can enhance our understanding of the phenomenology of conscious perceptual experiences. As a case study, I investigate the nature of the relationship between naïve realism, a contemporary Anglophone theory of perception, and experiential minimalism (or, the ‘minimal self’ view), a pre-reflective model of self-consciousness originated in the Phenomenological tradition. I argue that naïve (...) realism is not only compatible with, but can be supplemented with experiential minimalism in a novel way. The suggestion is that there are reasons to combine naïve realism and experiential minimalism. My focus here will be on drawing a connection between the notion of minimal self and two core theoretical commitments of naïve realism, relationalism and transparency. (shrink)

It seems possible to see a star that no longer exists. Yet it also seems right to say that what no longer exists cannot be seen. We therefore face a puzzle, the traditional answer to which involves abandoning naïve realism in favour of a sense datum view. In this article, however, I offer a novel exploration of the puzzle within a naïve realist framework. As will emerge, the best option for naïve realists is to embrace an eternalist (...) view of time, and claim that in the relevant case, one sees a still existent star‐stage located somewhere in the distant past. (shrink)

Recently, it has been objected that naïve realism is inconsistent with an empirically well-supported claim that mental states of the same fundamental kind as ordinary conscious seeing can occur unconsciously (SFK). The main aim of this paper is to establish the following conditional claim: if SFK turns out to be true, the naïve realist can and should accommodate it into her theory. Regarding the antecedent of this conditional, I suggest that empirical evidence renders SFK plausible but not obvious. (...) For it is possible that what is currently advocated as unconscious perception of the stimulus is in fact momentaneous perceptual awareness (or residual perceptual awareness) of the stimulus making the subject prone to judge in some way rather than another, or to act in some way rather than another. As to the apodosis, I show that neither the core of naïve realism nor any of its main motivations is undermined if SFK is assumed. On the contrary, certain incentives for endorsing naïve realism become more tempting on this assumption. Since the main motivations for naïve realism retain force under SFK, intentionalism is neither compulsory nor the best available explanation of unconscious perception. (shrink)

In a companion paper (Byrne and Green 2023) we disentangled the main characterizations of naïve realism and argued that illusions provide the best proving ground for naïve realism and its main rival, representationalism. According to naïve realism, illusions never involve perceptual error. We assessed two leading attempts to explain apparent perceptual error away, from William Fish and Bill Brewer, and concluded that they fail. This paper considers another prominent attempt, from Craig French and Ian Phillips, and also (...) sketches the case for representationalism. (shrink)

It is well-known that naïve realism has difficulty accommodating perceptual error. Recent discussion of the issue has focused on whether the naïve realist can accommodate hallucination by adopting disjunctivism. However, illusions are more difficult for the naïve realist to explain precisely because the disjunctivist solution is not available. I discuss what I take to be the two most plausible accounts of illusion available to the naïve realist. The first claims that illusions are cases in which you (...) are prevented from perceiving properties you would ordinarily perceive and subsequently form a mistaken judgment about the perceived object. The second appeals to an unusual look or appearance that the perceived object instantiates. I argue that neither account is satisfactory and that, consequently, naïve realism ought to be rejected. (shrink)

Naïve realism, often overlooked among philosophical theories of perception, has in recent years attracted a surge of interest. Broadly speaking, the central commitment of naïve realism is that mind-independent objects are essential to the fundamental analysis of perceptual experience. Since the claims of naïve realism concern the essential metaphysical structure of conscious perception, its truth or falsity is of central importance to a wide range of topics, including the explanation of semantic reference and representational content, the nature (...) of phenomenal consciousness, and the basis of perceptual justification and knowledge. One of the greatest difficulties surrounding discussions of naïve realism, however, has been lack of clarity concerning exactly what affirming or denying it entails. In particular, it is sometimes unclear how naïve realism is related to the claim that perceptual experience is in some sense direct or unmediated, and also to what extent the view is compatible with another widely discussed thesis in the philosophy of perception, the claim that perceptual experiences are states with representational content. In this essay, I discuss how recent work on these issues helps to clarify both the central commitments of naïve realism, as well as its relation to representationalist theories of perception. Along the way, I will attempt to shed light on the different ways in which each approach tries to address the various theoretical challenges facing a philosophical theory of perception, and also to assess the prospects for views that attempts to combine features of each approach. (shrink)

How can we have a sense of the presence of ordinary three-dimensional objects (e.g., an apple on my desk, a partially occluded cat behind a picket fence) when we are only presented with some parts of objects perceived from a particular egocentric viewpoint (e.g., the facing side of the apple, the unoccluded parts of the cat)? This paper presents and defends a novel answer to this question by incorporating insights from two prominent contemporary theories of perception, naïve realism and (...) sensorimotor theory. Naïve realism is the view that perception is fundamentally a matter of obtaining a relation of ‘acquaintance’ with some mind-independent entities (e.g., objects, properties, events). Sensorimotor theory holds that perception involves implicit practical understanding or ‘anticipation’ of the covariance between movements and sensory changes. I argue that perceptual presence is best accounted for in terms of the combination of our direct ‘acquaintance’ with some parts of perceived objects and sensorimotor ‘anticipations’ of how the objects would look different depending on some movements and actions. (shrink)

Naive realists hold that experience is to be understood in terms of an intimate perceptual relation between a subject and aspects of the world, relative to a certain standpoint. Those aspects of the world themselves shape the contours of consciousness. But blurriness is an aspect of some of our experiences that does not seem to come from the world. I argue that this constitutes a significant challenge to some forms of naive realism. But I also argue that there is a (...) robust form of naive realism which is unfazed by the blurriness of some of our experiences, even when that blurriness is understood as a subjective modification of consciousness. (shrink)

Nontransitive responses to the validity Curry paradox face a dilemma that was recently formulated by Barrio, Rosenblatt and Tajer. It seems that, in the nontransitive logic ST enriched with a validity predicate, either you cannot prove that all derivable metarules preserve validity, or you can prove that instances of Cut that are not admissible in the logic preserve validity. I respond on behalf of the nontransitive approach. The paper argues, first, that we should reject the detachment principle for naive validity. (...) Secondly, I show how to add a validity predicate to ST while avoiding the dilemma. (shrink)

Much of the discussion of Naive Realism about veridical experience has focused on a consequence of adopting it—namely, disjunctivism about perceptual experience. However, the motivations for being a Naive Realist in the first place have received relatively little attention in the literature. In this paper, I will elaborate and defend the claim that Naive Realism provides the best account of the phenomenal character of veridical experience.

I begin by describing what I call simple naïve realism. Then I describe relevant empirical results. Next, I develop two new empirical arguments against simple naive realism. Then I briefly look at two new, more complex forms of naïve realism: one due to Keith Allen and the other due to Heather Logue and Ori Beck. I argue that they are not satisfactory retreats for naive realists. The right course is to reject naive realism altogether. My stalking horse is (...) contemporary naive realism but there is a larger, positive lesson: new empirical results support a brain-based theory of sensory consciousness. (shrink)

It’s generally thought that we naively or pre-theoretically represent the future to be open. While philosophers have modelled future openness in different ways, it’s unclear which, if any, captures our naïve sense that the future is open. In this paper we focus on just one way the future might count as being open: by being nomically open, and empirically investigate whether our naïve representation of the future as open is partly constituted by representing the future as nomically open. (...) We also investigate the connection between our naïve representation of the future as open, and our representation of time. One of the purported advantages of the growing block theory of time is that it captures our naive sense that the future is open, and the past closed. We investigate whether there is an explanatory connection between people representing the future to be nomically open and representing our world to be a growing block and reflect on the implications of our findings for theorising about future openness and temporal ontology. (shrink)

About a British Academy collection of papers on Bayes' famous theorem.

This paper elaborates on an argument in my book *Perception*. It has two parts. In the first part, I argue against what I call "basic" naive realism, on the grounds that it fails to accommodate what I call "internal dependence" and it requires an empirically implausible theory of sensible properties. Then I turn Craig French and Ian Phillips’ modified naïve realism as set out in their recent paper "Austerity and Illusion". It accommodates internal dependence. But it may retain the (...) empirically implausible theory of sensible properties. And it faces other empirical problems. Representationalism about experiences avoids those problems and is to be preferred. (shrink)

Naïve realism (also called ‘relationalism’ or ‘object view’) is becoming increasingly popular, but the specific outline of its commitments remains often underspecified by proponents and misunderstood by critics. Naïve realism is associated with two claims, both concerning genuine, veridical perceptual experience (where this excludes hallucinations). Constitutive Claim (CC): The phenomenal character of perception is (partly) constituted by the mind-independent objects in one’s surrounding and their properties. Relational Claim (RC): Perception is a relation to mind-independent objects in the environment (...) and their properties. Some philosophers use the two claims interchangeably while talking about naïve realism, while others use only one or the other, although they do not explicitly discuss if the other claim is also a core commitment of naïve realism, or if naïve realism can be held without the other claim. This raises the question of how RC and CC relate to one another, together with the most pressing question of what each claim ultimately commits one to. After discussing the shortcomings of alternative interpretations, I argue that naïve realism should be understood as committed to, first and foremost, RC. This should be understood as a claim about the phenomenal character of perception, rather than about its nature, structure or essence (whatever that means). CC, on the other hand, should be understood as a corollary of RC. This doesn’t only offer a better characterisation of how naïve realists understand phenomenal character: it also helps us understand how we can simultaneously claim that the object of perception is a constitutive element of perception, while also allowing for it to play a causal role in determining perception. (shrink)

Beall and Murzi :143–165, 2013) introduce an object-linguistic predicate for naïve validity, governed by intuitive principles that are inconsistent with the classical structural rules. As a consequence, they suggest that revisionary approaches to semantic paradox must be substructural. In response to Beall and Murzi, Field :1–19, 2017) has argued that naïve validity principles do not admit of a coherent reading and that, for this reason, a non-classical solution to the semantic paradoxes need not be substructural. The aim of (...) this paper is to respond to Field’s objections and to point to a coherent notion of validity which underwrites a coherent reading of Beall and Murzi’s principles: grounded validity. The notion, first introduced by Nicolai and Rossi, is a generalisation of Kripke’s notion of grounded truth, and yields an irreflexive logic. While we do not advocate the adoption of a substructural logic, we take the notion of naïve validity to be a legitimate semantic notion that points to genuine expressive limitations of fully structural revisionary approaches. (shrink)

Hành vi bầy đàn là hiện tượng khi các cá nhân, trong các quyết định tài chính hoặc đầu tư, hành động theo số đông, bất chấp thông tin cá nhân hoặc phân tích riêng biệt của họ. Lý thuyết mindsponge có thể cung cấp cách tiếp cận hữu ích để khắc phục hiệu ứng bầy đàn trong đầu tư chứng khoán, thông qua việc giúp nhà đầu tư quản lý và xử lý thông tin một cách hiệu quả hơn.

The naive theory of properties states that for every condition there is a property instantiated by exactly the things which satisfy that condition. The naive theory of properties is inconsistent in classical logic, but there are many ways to obtain consistent naive theories of properties in nonclassical logics. The naive theory of classes adds to the naive theory of properties an extensionality rule or axiom, which states roughly that if two classes have exactly the same members, they are identical. In (...) this paper we examine the prospects for obtaining a satisfactory naive theory of classes. We start from a result by Ross Brady, which demonstrates the consistency of something resembling a naive theory of classes. We generalize Brady’s result somewhat and extend it to a recent system developed by Andrew Bacon. All of the theories we prove consistent contain an extensionality rule or axiom. But we argue that given the background logics, the relevant extensionality principles are too weak. For example, in some of these theories, there are universal classes which are not declared coextensive. We elucidate some very modest demands on extensionality, designed to rule out this kind of pathology. But we close by proving that even these modest demands cannot be jointly satisfied. In light of this new impossibility result, the prospects for a naive theory of classes are bleak. (shrink)

The project of a 'naive physics' has been the subject of attention in recent years above all in the artificial intelligence field, in connection with work on common-sense reasoning, perceptual representation and robotics. The idea of a theory of the common-sense world is however much older than this, having its roots not least in the work of phenomenologists and Gestalt psychologists such as K hler, Husserl, Schapp and Gibson. This paper seeks to show how contemporary naive physicists can profit from (...) a knowledge of these historical roots of their discipline, which are shown to imply above alla critique of the set-theory-based models of reality typically presupposed by contemporary work in common-sense ontology [1]. (shrink)

Despite their popularity, relatively scant attention has been paid to the upshot of Bayesian and predictive processing models of cognition for views of overall cognitive architecture. Many of these models are hierarchical ; they posit generative models at multiple distinct "levels," whose job is to predict the consequences of sensory input at lower levels. I articulate one possible position that could be implied by these models, namely, that there is a continuous hierarchy of perception, cognition, and action control comprising levels (...) of generative models. I argue that this view is not entailed by a general Bayesian/predictive processing outlook. Bayesian approaches are compatible with distinct formats of mental representation. Focusing on Bayesian approaches to motor control, I argue that the junctures between different types of mental representation are places where the transitivity of hierarchical prediction may be broken, and I consider the upshot of this conclusion for broader discussions of cognitive architecture. (shrink)

The viability of a naïve realist theory of memory was a lively debate for philosophers of mind in the first half of the twentieth century. More recently, though, naïve realism has been largely abandoned as a non-starter in the memory literature, with representationalism being the standard view held by philosophers of memory. But rather than being carefully argued, the dismissal of naïve realism is an assumption that sits at the back of much recent theorizing in the philosophy (...) of memory. In this paper, we identify three reasons why philosophers of memory have felt compelled to outright reject naïve realism. We argue that none of those reasons are successful. Thus, far from being a non-starter, we argue that naïve realism is a theoretical perspective that needs to be given serious consideration in current philosophy of memory debates. (shrink)