Hasil untuk "Philosophy. Psychology. Religion"

Tanya Klowden, Terence Tao

Artificial intelligence (AI) is the name popularly given to a broad spectrum of computer tools designed to perform increasingly complex cognitive tasks, including many that used to solely be the province of humans. As these tools become exponentially sophisticated and pervasive, the justifications for their rapid development and integration into society are frequently called into question, particularly as they consume finite resources and pose existential risks to the livelihoods of those skilled individuals they appear to replace. In this paper, we consider the rapidly evolving impact of AI to the traditional questions of philosophy with an emphasis on its application in mathematics and on the broader real-world outcomes of its more general use. We assert that artificial intelligence is a natural evolution of human tools developed throughout history to facilitate the creation, organization, and dissemination of ideas, and argue that it is paramount that the development and application of AI remain fundamentally human-centered. With an eye toward innovating solutions to meet human needs, enhancing the human quality of life and expanding the capacity for human thought and understanding, we propose a pathway to integrating AI into our most challenging and intellectually rigorous fields to the benefit of all humankind.

Yutao Yang, Junsong Li, Qianjun Pan et al.

Existing methods for AI psychological counselors predominantly rely on supervised fine-tuning using static dialogue datasets. However, this contrasts with human experts, who continuously refine their proficiency through clinical practice and accumulated experience. To bridge this gap, we propose an Experience-Driven Lifelong Learning Agent (\texttt{PsychAgent}) for psychological counseling. First, we establish a Memory-Augmented Planning Engine tailored for longitudinal multi-session interactions, which ensures therapeutic continuity through persistent memory and strategic planning. Second, to support self-evolution, we design a Skill Evolution Engine that extracts new practice-grounded skills from historical counseling trajectories. Finally, we introduce a Reinforced Internalization Engine that integrates the evolved skills into the model via rejection fine-tuning, aiming to improve performance across diverse scenarios. Comparative analysis shows that our approach achieves higher scores than strong general LLMs (e.g., GPT-5.4, Gemini-3) and domain-specific baselines across all reported evaluation dimensions. These results suggest that lifelong learning can improve the consistency and overall quality of multi-session counseling responses.

Kailash Gopal Darmasubramanian, Akash Pareek, Arindam Khan et al.

Optimizing the timing and frequency of ads is a central problem in digital advertising, with significant economic consequences. Existing scheduling policies rely on simple heuristics, such as uniform spacing and frequency caps, that overlook long-term user interest. However, it is well-known that users' long-term interest and engagement result from the interplay of several psychological effects (Curmei, Haupt, Recht, Hadfield-Menell, ACM CRS, 2022). In this work, we model change in user interest upon showing ads based on three key psychological principles: mere exposure, hedonic adaptation, and operant conditioning. The first two effects are modeled using a concave function of user interest with repeated exposure, while the third effect is modeled using a temporal decay function, which explains the decline in user interest due to overexposure. Under our psychological behavior model, we ask the following question: Given a continuous time interval $T$, how many ads should be shown, and at what times, to maximize the user interest towards the ads? Towards answering this question, we first show that, if the number of displayed ads is fixed, then the optimal ad-schedule only depends on the operant conditioning function. Our main result is a quasi-linear time algorithm that outputs a near-optimal ad-schedule, i.e., the difference in the performance of our schedule and the optimal schedule is exponentially small. Our algorithm leads to significant insights about optimal ad placement and shows that simple heuristics such as uniform spacing are sub-optimal under many natural settings. The optimal number of ads to display, which also depends on the mere exposure and hedonistic adaptation functions, can be found through a simple linear search given the above algorithm. We further support our findings with experimental results, demonstrating that our strategy outperforms various baselines.

Kaustubh Shivshankar Shejole, Pushpak Bhattacharyya

Stereotypes are known to have very harmful effects, making their detection critically important. However, current research predominantly focuses on detecting and evaluating stereotypical biases, thereby leaving the study of stereotypes in its early stages. Our study revealed that many works have failed to clearly distinguish between stereotypes and stereotypical biases, which has significantly slowed progress in advancing research in this area. Stereotype and Anti-stereotype detection is a problem that requires social knowledge; hence, it is one of the most difficult areas in Responsible AI. This work investigates this task, where we propose a five-tuple definition and provide precise terminologies disentangling stereotypes, anti-stereotypes, stereotypical bias, and general bias. We provide a conceptual framework grounded in social psychology for reliable detection. We identify key shortcomings in existing benchmarks for this task of stereotype and anti-stereotype detection. To address these gaps, we developed StereoDetect, a well curated, definition-aligned benchmark dataset designed for this task. We show that sub-10B language models and GPT-4o frequently misclassify anti-stereotypes and fail to recognize neutral overgeneralizations. We demonstrate StereoDetect's effectiveness through multiple qualitative and quantitative comparisons with existing benchmarks and models fine-tuned on them. The dataset and code is available at https://github.com/KaustubhShejole/StereoDetect.

Kylie L. Anglin, Stephanie Milan, Brittney Hernandez et al.

Due to their architecture and vast pre-training data, large language models (LLMs) demonstrate strong text classification performance. However, LLM output - here, the category assigned to a text - depends heavily on the wording of the prompt. While literature on prompt engineering is expanding, few studies focus on classification tasks, and even fewer address domains like psychology, where constructs have precise, theory-driven definitions that may not be well represented in pre-training data. We present an empirical framework for optimizing LLM performance for identifying constructs in texts via prompt engineering. We experimentally evaluate five prompting strategies --codebook-guided empirical prompt selection, automatic prompt engineering, persona prompting, chain-of-thought reasoning, and explanatory prompting - with zero-shot and few-shot classification. We find that persona, chain-of-thought, and explanations do not fully address performance loss accompanying a badly worded prompt. Instead, the most influential features of a prompt are the construct definition, task framing, and, to a lesser extent, the examples provided. Across three constructs and two models, the classifications most aligned with expert judgments resulted from a few-shot prompt combining codebook-guided empirical prompt selection with automatic prompt engineering. Based on our findings, we recommend that researchers generate and evaluate as many prompt variants as feasible, whether human-crafted, automatically generated, or ideally both, and select prompts and examples based on empirical performance in a training dataset, validating the final approach in a holdout set. This procedure offers a practical, systematic, and theory-driven method for optimizing LLM prompts in settings where alignment with expert judgment is critical.

Yupei Li, Shuaijie Shao, Manuel Milling et al.

Depression is a growing concern gaining attention in both public discourse and AI research. While deep neural networks (DNNs) have been used for recognition, they still lack real-world effectiveness. Large language models (LLMs) show strong potential but require domain-specific fine-tuning and struggle with non-textual cues. Since depression is often expressed through vocal tone and behaviour rather than explicit text, relying on language alone is insufficient. Diagnostic accuracy also suffers without incorporating psychological expertise. To address these limitations, we present, to the best of our knowledge, the first application of LLMs to multimodal depression detection using the DAIC-WOZ dataset. We extract the audio features using the pre-trained model Wav2Vec, and mapped it to text-based LLMs for further processing. We also propose a novel strategy for incorporating psychological knowledge into LLMs to enhance diagnostic performance, specifically using a question and answer set to grant authorised knowledge to LLMs. Our approach yields a notable improvement in both Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) compared to a base score proposed by the related original paper. The codes are available at https://github.com/myxp-lyp/Depression-detection.git

Dave Vliegenthart, Nadine Sajo

Psychologists are paying increasing attention to a distinction between two ways of thinking. Cognitive psychologists discern between non-reflective “intuitive” and critical reflective “analytic” thinking. Cultural psychologists discern between context-focused “holistic” and object-focused “analytic” thinking. Both find the former strongly correlated with religious beliefs and Asian cultures, the latter with secular beliefs and Euro-American cultures. Yet, recent studies convincingly suggest: first, that analytic thinking does not just relate to secular beliefs but also to alternative beliefs that straddle the boundaries between secular and religious worldviews; second, that critical reflective thinking includes both the holistic context-focus of Asian religions and the analytic object-focus of European philosophies and sciences. This article supports these recent studies in the psychology of religion based on recent studies from the history and sociology of religion and a discourse analysis of interviews with members of a small-scale twenty-first-century spiritual group, as an example. We show that people who identify as spiritual in a metamodern context use both holistic and analytic thinking in creating alternative worldviews, which dialectically reconcile beliefs that many within modern western cultures would consider contradictory. We conclude that this both/and logic challenges theories and stereotypes about “secular versus religious” and “eastern versus western” thinking.

Xiaofan Mu, Merna Bibars, Salman Seyedi et al.

The aging society urgently requires scalable methods to monitor cognitive decline and identify social and psychological factors indicative of dementia risk in older adults. Our machine learning (ML) models captured facial, acoustic, linguistic, and cardiovascular features from 39 older adults with normal cognition or Mild Cognitive Impairment (MCI), derived from remote video conversations and quantified their cognitive status, social isolation, neuroticism, and psychological well-being. Our model could distinguish Clinical Dementia Rating Scale (CDR) of 0.5 (vs. 0) with 0.77 area under the receiver operating characteristic curve (AUC), social isolation with 0.74 AUC, social satisfaction with 0.75 AUC, psychological well-being with 0.72 AUC, and negative affect with 0.74 AUC. Our feature importance analysis showed that speech and language patterns were useful for quantifying cognitive impairment, whereas facial expressions and cardiovascular patterns were useful for quantifying social and psychological well-being. Our bias analysis showed that the best-performing models for quantifying psychological well-being and cognitive states in older adults exhibited significant biases concerning their age, sex, disease condition, and education levels. Our comprehensive analysis shows the feasibility of monitoring the cognitive and psychological health of older adults, as well as the need for collecting largescale interview datasets of older adults to benefit from the latest advances in deep learning technologies to develop generalizable models across older adults with diverse demographic backgrounds and disease conditions.

Muskan Garg, MSVPJ Sathvik, Amrit Chadha et al.

The social NLP research community witness a recent surge in the computational advancements of mental health analysis to build responsible AI models for a complex interplay between language use and self-perception. Such responsible AI models aid in quantifying the psychological concepts from user-penned texts on social media. On thinking beyond the low-level (classification) task, we advance the existing binary classification dataset, towards a higher-level task of reliability analysis through the lens of explanations, posing it as one of the safety measures. We annotate the LoST dataset to capture nuanced textual cues that suggest the presence of low self-esteem in the posts of Reddit users. We further state that the NLP models developed for determining the presence of low self-esteem, focus more on three types of textual cues: (i) Trigger: words that triggers mental disturbance, (ii) LoST indicators: text indicators emphasizing low self-esteem, and (iii) Consequences: words describing the consequences of mental disturbance. We implement existing classifiers to examine the attention mechanism in pre-trained language models (PLMs) for a domain-specific psychology-grounded task. Our findings suggest the need of shifting the focus of PLMs from Trigger and Consequences to a more comprehensive explanation, emphasizing LoST indicators while determining low self-esteem in Reddit posts.

O. Soloviov, O. Litvinova

Behaviorist psychology, following analytical philosophy, which was formed on the unquestioning belief in the ability of classical physical determinism to explain even the nature of mental phenomena, sometimes declared the mental to be an artifact of the physical activity of the brain, sometimes reduced it to the physical as such. Sometimes psychologists and philosophers simply stated the fundamentally incomprehensible nature of the mental – like the Kantian «thing in itself». But psychology, since it became aware of itself, has not forgotten to investigate, describe and interpret mental phenomena and processes. However, even in our times, enlightened by respectable theories, the «spirit» of secrecy and incomprehensibility of the ontological foundations of the mental is still present in psychology. And this clearly does not contribute to raising the status of psychology as a well-conceptually formed science, despite the undeniable ontological scale of the object of its research – the psyche. So, here, in order to discover these ontological foundations of the psychic, we have considered the psychic against the background of two fundamental factors. One of them is the physical world surrounding living beings (including humans), to which the psychic should adapt them. The second is the properties of neural networks of the brain (also, by the way, physically functioning), the activity of which is directly related to the realization of the mental itself. This enables us not only to determine the issue of the ontological nature of the mental, i.e., the way and specificity of its existence and functioning, but also to identify the main mechanism of the procedurality of the mental during information processing. The quintessence of this mechanism is that it occurs thanks to two key aspects of the mental information process in the brain. This is, first of all, the ability of living beings with a sufficiently highly organized brain to subjectively assess the biological (and later in evolution and social) value of objects and phenomena in their physical environment. And secondly, it is the subjective selection of information stored in the brain for the purpose of integration of accumulated experience, which is functionally related to the ability to subjectively evaluate. This mechanism allows such living beings to respond to probable, new external stimuli with their behavioral novelty (creative activity). Therefore, mental proceduralism should become unthinkable without taking into account the factors of subjective evaluation and freedom of choice. And freedom of choice is, first of all, a mental aspect of processing information, and as a result, and precisely because it is a valuable phenomenon, it is also a social value – whether in the form of freedom of religion, or political freedoms, or freedom of speech , or something else like this.

Muhsin Muhsin, Ahmad Muadin

Educational institutions have recently experienced a period of growth which is full of competition, especially the Islamic-based education level which must be fully innovative and better, always updating the right information, making breakthroughs full of strategic innovation and mobilizing skills and commitment among all madrasahs. In fulfilling its mission as an educational level, MI/MTS/MA should be managed as well as possible so as to achieve the vision and mission that has been set. The purpose of this study is to describe the vision of education from the perspective of Islam, psychology, philosophy and sociology. In this study, the vision of education can be seen from several perspectives that are able to interpret the humanistic vision of education, that is, to humanize humans because recently there has been a lot of education that is still wrong in understanding and implementing the vision of education. The research method used is a qualitative approach with descriptive analysis methods based on literature searches or literature searches. Literature review is an activity related to collecting data on library materials, reading and storing research materials, and analyzing them. The results of the study show that insight into the vision of education based on religion, philosophy, psychology and sociology is the eternal essence of efforts to develop human thinking abilities to develop the perfection of human dignity and worth as God's creatures on earth.

Daeun Lee, Harjinder Singh Lallie, Nadine Michaelides

Despite the rapid rise in social engineering attacks, not all employees are as compliant with information security policies (ISPs) to the extent that organisations expect them to be. ISP non-compliance is caused by a variety of psychological motivation. This study investigates the effect of psychological contract breach (PCB) of employees on ISP compliance intention (ICI) by dividing them into intrinsic and extrinsic motivation using the theory of planned behaviour (TPB) and the general deterrence theory (GDT). Data analysis from UK employees (\textit{n=206}) showed that the higher the PCB, the lower the ICI. The study also found that PCBs significantly reduced intrinsic motivation (attitude and perceived fairness) for ICI, whereas PCBs did not moderate the relationship between extrinsic motivation (sanction severity and sanctions certainty) and ICI. As a result, this study successfully addresses the risks of PCBs in the field of IS security and proposes effective solutions for employees with high PCBs.

Chen-Wei Yu, Yun-Shiuan Chuang, Alexandros N. Lotsos et al.

Latent semantic similarity (LSS) is a measure of the similarity of information exchanges in a conversation. Challenging the assumption that higher LSS bears more positive psychological meaning, we propose that this association might depend on the type of conversation people have. On the one hand, the share-mind perspective would predict that higher LSS should be associated with more positive emotional experiences across the board. The broaden-and-build theory, on the other hand, would predict that higher LSS should be inversely associated with more positive emotional experiences specifically in pleasant conversations. Linear mixed modeling based on conversations among 50 long-term married couples supported the latter prediction. That is, partners experienced greater positive emotions when their overall information exchanges were more dissimilar in pleasant (but not conflict) conversations. This work highlights the importance of context in understanding the emotional correlates of LSS and exemplifies how modern natural language processing tools can be used to evaluate competing theory-driven hypotheses in social psychology.

Klaas Landsman, Kirti Singh

We re-examine the old question to what extent mathematics may be compared with a game. Mainly inspired by Hilbert and Wittgenstein, our answer is that mathematics is something like a rhododendron of language games, where the rules are inferential. The pure side of mathematics is essentially formalist, where we propose that truth is not carried by theorems corresponding to whatever independent reality and arrived at through proof, but is defined by correctness of rule-following (and as such is objective given these rules). Goedel's theorems, which are often seen as a threat to formalist philosophies of mathematics, actually strengthen our concept of truth. The applied side of mathematics arises from two practices: first, the dual nature of axiomatization as taking from heuristic practices like physics and informal mathematics whilst giving proofs and logical analysis; and second, the ability of using the inferential role of theorems to make surrogative inferences about natural phenomena. Our framework is pluralist, combining various (non-referential) philosophies of mathematics.

Daria Chernova, Artem Novozhilov, Natalia Slioussar et al.

Although all healthy adults have advanced syntactic processing abilities in their native language, psycholinguistic studies report extensive variation among them. However, very few tests were developed to assess this variation, presumably, because when adult native speakers focus on syntactic processing, not being distracted by other tasks, they usually reach ceiling performance. We developed a Sentence Comprehension Test for the Russian language aimed to fill this gap. The test captures variation among participants and does not show ceiling effects. The Sentence Comprehension Test includes 60 unambiguous grammatically complex sentences and 40 control sentences that are of the same length, but are syntactically simpler. Every sentence is accompanied by a comprehension question targeting potential syntactic processing problems and interpretation errors associated with them. Grammatically complex sentences were selected on the basis of the previous literature and then tested in a pilot study. As a result, six constructions that trigger the largest number of errors were identified. For these constructions, we also analyzed which ones are associated with the longest word-by-word reading times, question answering times and the highest error rates. These differences point to different sources of syntactic processing difficulties and can be relied upon in subsequent studies. We conducted two experiments to validate the final version of the test. Getting similar results in two independent experiments, as well as in two presentation modes (reading and listening modes are compared in Experiment 2) confirms its reliability. In Experiment 1, we also showed that the results of the test correlate with the scores in the verbal working memory span test.

Jiawei Wang, Ruiyang Zhou, Fengying Wei

This paper considers a single-population model with age structure and psychological effects in a polluted environment. We divide the single population into two stages of larval and adult structure. The model uses Logistic input, and the larvae are converted into adult bodies by constant ratio. We only consider adulthood. The role of psychological effects makes the contact between adult and environmental toxins a functional form, while the contact between larvae and environmental toxins is linear. For the deterministic model embodied as a nonlinear time-varying system, we discuss the asymptotic stability of the system by Lyapunov one-time approximation theory, and give a sufficient condition for stability to be established. Considering that the contact rate between biological and environmental toxins in nature is not always constant, we make the contact rate interfere with white noise, and then modify the contact rate into a stochastic process, thus establishing a corresponding random single-population model. According to Itô formula and Lyapunov in the function method, we first prove the existence of globally unique positive solutions for stochastic models under arbitrary initial conditions, and then give sufficient conditions for weak average long-term survival and random long-term survival for single populations in the expected sense.

Yoichi Yamazaki, Masayuki Ishii, Takahiro Ito et al.

To achieve continuous frail care in the daily lives of the elderly, we propose AHOBO, a frail care robot for the elderly at home. Two types of support systems by AHOBO were implemented to support the elderly in both physical health and psychological aspects. For physical health frailty care, we focused on blood pressure and developed a support system for blood pressure measurement with AHOBO. For psychological frailty care, we implemented reminiscent coloring with the AHOBO as a recreational activity with the robot. The usability of the system was evaluated based on the assumption of continuous use in daily life. For the support system in blood pressure measurement, we performed a qualitative evaluation using a questionnaire for 16 subjects, including elderly people under blood pressure measurement by the system. The results confirmed that the proposed robot does not affect the blood pressure readings and is acceptable in terms of ease of use based on subjective evaluation. For the reminiscent coloring interaction, a subjective evaluation was conducted on two elderly people under the verbal fluency task, and it has been confirmed that the interaction can be used continuously in daily life. The widespread use of the proposed robot as an interface for AI that supports daily life will lead to a society in which AI robots support people from the cradle to the grave.

Marie Mazerolle, Amy M. Smith, McKinzey Torrance et al.

Numerous studies have documented the detrimental impact of age-based stereotype threat (ABST) on older adults' cognitive performance and especially on veridical memory. However, far fewer studies have investigated the impact of ABST on older adults' memory distortion. Here, we review the subset of research examining memory distortion and provide evidence for the role of stereotype threat as a powerful socio-emotional factor that impacts age-related susceptibility to memory distortion. In this review we define memory distortion as errors in memory that are associated with gist-based errors or source misattributions. Whereas, some of the reviewed experiments support the conclusion that ABST should be considered in the context of age-related differences in memory distortion, others reported little or no impact of stereotype threat. These discrepancies suggest that the role of ABST, and socio-emotional processes generally, in age-related changes in memory distortion are less clear. In this review, we argue that ABST does play an important role in age-related changes in memory distortion. We present evidence suggesting that discrepancies in the reviewed literature may be reconciled when evaluated in the context of the leading theories about stereotype threat: the Executive Resource Depletion hypothesis and the Regulatory Focus theory. We also discuss how differences in methodology and participant characteristics can account for a priori contradictory results in the literature. Finally, we propose some recommendations for researchers and practitioners when assessing memory in older adults.

Syafira Nur Sabilla

Stress pengasuhan yang tinggi sering terjadi pada orangtua dengan anak berkebutuhan khusus salah satunya pada anak Gangguan Pemusatan Perhatian dan Hiperaktivitas (GPPH). Padahal peran orangtua dalam kehidupan anak GPPH justru lebih penting. Oleh karena itu stress pengasuhan harus segera diatasi salah satunya adalah dengan menerapkan mindful parenting. Tujuan dari penelitian ini adalah untuk memberikan paparan secara jelas berupa tinjauan sistematis mengenai mindful parenting sebagai faktor protektif pada stress pengasuhan orangtua dengan anak GPPH dalam rangka optimalisasi peran dan dukungan keluarga dalam Pendidikan anak. Terdapat enam studi yang digunakan, dimana keenam studi tersebut merupakan jurnal terbitan 10 tahun terakhir, hasil peer review dengan tema yang sama, dan berbahasa Inggris atau Indonesia. Database yang digunakan dari ScienceDirect, Springer Link, Frontier Psychology, ProQuest, PsycARTICLES, dan Google Scholar. Hasil dari tinjauan sistematis ini menyimpulkan bahwa mindful parenting efektif untuk mengurangi stress pengasuhan dan meningkatkan kualitas hubungan orangtua dan anak dengan GPPH. Ini menegaskan bahwa penting bagi orangtua untuk menjaga hubungan dengan anak dan mengoptimalkan perannya dalam mendidik atau memenuhi kebutuhan anak akan pendidikan yang layak. Kata Kunci: Gangguan Pemusatan Perhatian dan Hiperaktivitas (GPPH), mindful parenting, tinjauan sistematis Mindful Parenting in Parents of Children with Attention Deficit Hyperactivity Disorder (ADHD): A Systematic Review Abstract High parenting stress often occurs in parents of children with special needs such as Attention Deficit Hyperactivity Disorder (ADHD). Whereas the involvement of parents in the life of children with ADHD is much more important. Thus the stress should rightly be prevented, by applying mindful parenting. The aim of this research is to give a clear explanation in the form of systematic review about mindful parenting as a protective factor in handling parenting stress on parents of children with ADHD. It aims eventually to optimize the role of parents and family support for children’s education. It surveys six studies in English and Indonesian published in the last 10 years, peer reviewed under the same theme. The databases used are from ScienceDirect, Springer Link, Frontier Psychology, ProQuest, PsycARTICLES, and Google Scholar. The research concludes that mindful parenting is effective at reducing parenting stress and improving the quality of parent-child relationships in the case of ADHD children. It also emphasizes that it is important for parents to maintain relationships with children and optimize their role in educating or fulfilling children’s needs for proper education. Keywords: Attention Deficit Hyperactivity Disorder (ADHD), mindful parenting, systematic review

Shamionov R.M.

Objectives. The study the commitment to social activity and its various forms in relation to the risk propensity characteristics of students with different types of subject regulation of behavior. Background. The problem of social activity of students as a sphere of their socialization and establishing connections with various social groups and society as a whole is analyzes. One of its most important components is the question of the subject regulation of social activity. It is assumed that depending on the type of subject regulation (Autonomous or Dependent), students prefer various forms of social activity, implement socially-oriented activity, and show the specifics of risk-taking. Study design. The paper analyzes the level indicators of adherence to different forms of social activity of students, depending on the type of their subject regulation; a typological analysis of risk propensity and uncertainty experiences in students with Autonomous and dependent types of subject regulation; the hypothesis of direct and indirect effects of autonomy on General and socially-oriented activity using structural modeling. Participants. The study involved 297 full-time students (36% men), average age M=21; SD=2.74. Measurements. The scale for the assessment of various forms of social activity, feelings of uncertainty with a dimension of from 1 to 5, the method of evaluating component and composite index of socio-oriented activity (R.M. Shamionov, M.V. Grigorieva), a questionnaire of autonomy-dependence (G.S. Prygin), a questionnaire of tendency to extreme and risky behavior (M. Zuckerman). Results. Students with an Autonomous type of subject regulation are more committed to leisure, socio-political, and civic activity, while students with a dependent type are more committed to protest activity. Socially-oriented activity is more attractive to students with an Autonomous type of subject regulation. Students with an Autonomous type of regulation are characterized by higher indicators of non-adaptive striving for difficulties, with a Dependent type-indicators of searching for new impressions and experiencing uncertainty. The continuous indicator of (Autonomous) subject regulation has a direct impact on variations in socially-oriented activity, and indicators of risk propensity are moderators of a direct causal relationship, respectively, of autonomy to socially-oriented activity and age to the overall activity of students. Conclusions. Students with Autonomous and Dependent types of subject regulation are characterized by specificity in their commitment to various forms of activity and their attitude to risk. The causal relationship of subject regulation on variations of socially-oriented activity is established.