Yair Neuman

AI for Understanding Subtext in Film and Drama offers a novel, rigorous, and deeply reflective approach to one of the most elusive problems in aesthetics and interpretation: how meaning emerges when it is not explicitly stated. Drawing on film and drama case studies – from Pulp Fiction and Bergman to Pinter and Mamet – Prof. Yair Neuman develops a structured methodology for uncovering subtext through a disciplined tri-alogue between the human reader, the text, and artificial intelligence. The book introduces third-mind hermeneutics: a theoretically grounded, pedagogically applicable framework that uses large language models as tools for attentive observation rather than mechanical explanation. The result is a work that enriches aesthetic experience, sharpens interpretive skill, and extends the analysis of subtext beyond art to everyday human interaction. The book will be of strong interest to researchers and advanced students, scholars in human–AI interaction and AI for the humanities, and educators teaching interpretation, subtext, and critical reading. It is suitable for graduate-level courses, advanced undergraduate seminars, and interdisciplinary programs that bridge the humanities, social sciences, and AI studies.

AI for Understanding Subtext in Film and Drama offers a novel, rigorous, and deeply reflective approach to one of the most elusive problems in aesthetics and interpretation: how meaning emerges when it is not explicitly stated. Drawing on film and drama case studies – from Pulp Fiction and Bergman to Pinter and Mamet – Prof. Yair Neuman develops a structured methodology for uncovering subtext through a disciplined tri-alogue between the human reader, the text, and artificial intelligence. The book introduces third-mind hermeneutics: a theoretically grounded, pedagogically applicable framework that uses large language models as tools for attentive observation rather than mechanical explanation. The result is a work that enriches aesthetic experience, sharpens interpretive skill, and extends the analysis of subtext beyond art to everyday human interaction. The book will be of strong interest to researchers and advanced students, scholars in human–AI interaction and AI for the humanities, and educators teaching interpretation, subtext, and critical reading. It is suitable for graduate-level courses, advanced undergraduate seminars, and interdisciplinary programs that bridge the humanities, social sciences, and AI studies.

Artificial intelligence (AI) and specifically large language models (LLMs) revolutionize our lives with new technologies appearing at an unprecedented rate. These technologies can potentially change how we understand human conversations, from the dialogues of married couples to diplomatic conversations.This book explains how to use LLMs to analyze human conversations and how better LLMs can be developed by incorporating a deep theoretical understanding.Drawing on case studies from Pulp Fiction to diplomatic meetings, the book provides detailed, approachable, and theoretically grounded explanations of how LLMs can help us understand conversations.

Artificial intelligence (AI) and specifically large language models (LLMs) revolutionize our lives with new technologies appearing at an unprecedented rate. These technologies can potentially change how we understand human conversations, from the dialogues of married couples to diplomatic conversations.This book explains how to use LLMs to analyze human conversations and how better LLMs can be developed by incorporating a deep theoretical understanding.Drawing on case studies from Pulp Fiction to diplomatic meetings, the book provides detailed, approachable, and theoretically grounded explanations of how LLMs can help us understand conversations.

Context is necessary for understanding human behavior. However, so far, the concept of context has mostly been treated in a way that lacks any clear relevance for using, developing and engineering intelligent systems. In this book, the author explains the importance of context for understanding human behavior, presents a theory of context, and shows how AI, specifically Large Language Models such as GPT, can support our understanding of context when analyzing human behavior as expressed in texts ranging from conversations to short stories. Drawing on years of R&D and academic publications in top rated journals, the author provides the reader with a simple and deep understanding of context and its modeling for specific challenges, from identifying social norm violations to understanding conversations going awry and stories by great authors. The book may interest a wide variety of readers seeking to incorporate AI into their understanding of human behavior.

Mindmatics invites readers into a captivating exploration where the boundaries between mind and mathematics dissolve. Professor Neuman delves into the profound connections between cognitive processes and mathematical expression in this groundbreaking work. From how children grasp abstract concepts to symmetry's role in art and mathematics, this book uncovers the hidden structures that shape our understanding of the world. With insightful discussions on the relationship between poetry and mathematics and the essential role of the unconscious in fostering mathematical imagination, Mindmatics offers a unique perspective on the interplay of thought, creativity, and logic. This book is a must-read for anyone curious about the deeper links between the human mind and the mathematical universe.

Searching for a needle in a haystack is an important task in several contexts of data analysis and decision-making. Examples include identifying the insider threat within an organization, the prediction of failure in industrial production, or pinpointing the unique signature of a solo perpetrator, such as a school shooter or a lone wolf terrorist. It is a challenge different from that of identifying a rare event (e.g., a tsunami) or detecting anomalies because the "needle" is not easily distinguished from the haystack. This challenging context is imbued with particular difficulties, from the lack of sufficient data to train a machine learning model through the identification of the relevant features and up to the painful price of false alarms, which might cause us to question the relevance of machine learning solutions even if they perform well according to common performance criteria. In this book, Prof. Neuman approaches the problem of finding the needle by specifically focusing on the human factor, from solo perpetrators to insider threats. Providing for the first time a deep, critical, multidimensional, and methodological analysis of the challenge, the book offers data scientists and decision makers a deep scientific foundational approach combined with a pragmatic practical approach that may guide them in searching for a needle in a haystack.

This concise volume offers an accessible introduction to state-of-the-art artificial intelligence (AI) language models, providing a platform for their use in textual interpretation across the humanities and social sciences.The book outlines the affordances of new technologies for textual analysis, which has historically employed established approaches within the humanities. Neuman, Danesi, and Vilenchik argue that these different forms of analysis are indeed complementary, demonstrating the ways in which AI-based perspectives echo similar theoretical and methodological currents in traditional approaches while also offering new directions for research. The volume showcases examples from a wide range of texts, including novels, television shows, and films to illustrate the ways in which the latest AI technologies can be used for "dialoguing" with textual characters and examining textual meaning coherence. Illuminating the potential of AI language models to both enhance and extend research on the interpretation of texts, this book will appeal to scholars interested in cognitive approaches to the humanities in such fields as literary studies, discourse analysis, media studies, film studies, psychology, and artificial intelligence.

Crowds are misleading, both in their simplicity and in their complexity. On the one hand, they behave according to expected trends; on the other, they present sudden shifts and frantic, unexpected behavior. Therefore, “betting against the crowd,” whether in politics, sports, or finance, requires a deep understanding of the crowd’s dynamics. In this book, Prof. Neuman addresses this challenge by delving into the complexity of crowds. The book involves foundational issues and novel ideas, such as why crowds behave unexpectedly, why betting against the crowd is possible only in short time frames, why is it important to be attentive to suspicious signs that are indicative of the crowd’s behavior, and why the long tail of fatalities in armed conflicts leaves us surprised by blitz attacks of violent mobs. The book combines scientific knowledge, experiments, and accessible, often humorous, exposition. It can be read by anyone with a basic science education who seeks to understand crowds and how one can act within and against them.

This concise volume offers an accessible introduction to state-of-the-art artificial intelligence (AI) language models, providing a platform for their use in textual interpretation across the humanities and social sciences.The book outlines the affordances of new technologies for textual analysis, which has historically employed established approaches within the humanities. Neuman, Danesi, and Vilenchik argue that these different forms of analysis are indeed complementary, demonstrating the ways in which AI-based perspectives echo similar theoretical and methodological currents in traditional approaches while also offering new directions for research. The volume showcases examples from a wide range of texts, including novels, television shows, and films to illustrate the ways in which the latest AI technologies can be used for "dialoguing" with textual characters and examining textual meaning coherence. Illuminating the potential of AI language models to both enhance and extend research on the interpretation of texts, this book will appeal to scholars interested in cognitive approaches to the humanities in such fields as literary studies, discourse analysis, media studies, film studies, psychology, and artificial intelligence.

Searching for a needle in a haystack is an important task in several contexts of data analysis and decision-making. Examples include identifying the insider threat within an organization, the prediction of failure in industrial production, or pinpointing the unique signature of a solo perpetrator, such as a school shooter or a lone wolf terrorist. It is a challenge different from that of identifying a rare event (e.g., a tsunami) or detecting anomalies because the "needle" is not easily distinguished from the haystack. This challenging context is imbued with particular difficulties, from the lack of sufficient data to train a machine learning model through the identification of the relevant features and up to the painful price of false alarms, which might cause us to question the relevance of machine learning solutions even if they perform well according to common performance criteria. In this book, Prof. Neuman approaches the problem of finding the needle by specifically focusing on the human factor, from solo perpetrators to insider threats. Providing for the first time a deep, critical, multidimensional, and methodological analysis of the challenge, the book offers data scientists and decision makers a deep scientific foundational approach combined with a pragmatic practical approach that may guide them in searching for a needle in a haystack.

Most of us are intuitively familiar with small social systems, such as families and soccer teams. Surprisingly, though, most of us are unaware of how complex these systems are or of the fact that they have a unique character distinguishing them from both populations and individuals. The current manuscript, which emerged from high-level scientific publications on the subject, aims to bridge this gap in our understanding of small social systems. The book aims to explain, illustrate, and model the unique and fascinating nature of small (social) systems by relying on deep scientific foundations and by using examples from sport, movies, music, and the martial arts. To support its friendly exposition of challenging scientific ideas, the book also discusses entertaining questions such as (1) why inviting your mother-in-law to dinner might be a challenging event, for reasons you have never considered; (2) why soccer teams should be messy in order to win; (3) why Nazis are deeply wrong in their understanding of the importance of entropy; and (4) why “panda fighters” failed in the UFC (Ultimate Fighting Championship)."How Small Systems Work is a welcome book, which sheds light on a branch of mathematics overlooked by scholars: how networks store information. Focusing on small systems, the book asks fundamental questions, providing the tools (and the examples) for answering them –with fun. Neuman analyses, with plenty of humor, the dynamics of a family of cats, the pleasure of listening to jazz, and the science behind football championships, while uncovering hidden gems in the history of cinema”Dr. Mario Alemi, author of “The Amazing Journey of Reason: from DNA to Artificial Intelligence”

Most of us are intuitively familiar with small social systems, such as families and soccer teams. Surprisingly, though, most of us are unaware of how complex these systems are or of the fact that they have a unique character distinguishing them from both populations and individuals. The current manuscript, which emerged from high-level scientific publications on the subject, aims to bridge this gap in our understanding of small social systems. The book aims to explain, illustrate, and model the unique and fascinating nature of small (social) systems by relying on deep scientific foundations and by using examples from sport, movies, music, and the martial arts. To support its friendly exposition of challenging scientific ideas, the book also discusses entertaining questions such as (1) why inviting your mother-in-law to dinner might be a challenging event, for reasons you have never considered; (2) why soccer teams should be messy in order to win; (3) why Nazis are deeply wrong in their understanding of the importance of entropy; and (4) why “panda fighters” failed in the UFC (Ultimate Fighting Championship)."How Small Systems Work is a welcome book, which sheds light on a branch of mathematics overlooked by scholars: how networks store information. Focusing on small systems, the book asks fundamental questions, providing the tools (and the examples) for answering them –with fun. Neuman analyses, with plenty of humor, the dynamics of a family of cats, the pleasure of listening to jazz, and the science behind football championships, while uncovering hidden gems in the history of cinema”Dr. Mario Alemi, author of “The Amazing Journey of Reason: from DNA to Artificial Intelligence”

This book uncovers mathematical structures underlying natural intelligence and applies category theory as a modeling language for understanding human cognition, giving readers new insights into the nature of human thought. In this context, the book explores various topics and questions, such as the human representation of the number system, why our counting ability is different from that which is evident among non-human organisms, and why the idea of zero is so difficult to grasp.The book is organized into three parts: the first introduces the general reason for studying general structures underlying the human mind; the second part introduces category theory as a modeling language and use it for exposing the deep and fascinating structures underlying human cognition; and the third applies the general principles and ideas of the first two parts to reaching a better understanding of challenging aspects of the human mind such as our understanding of thenumber system, the metaphorical nature of our thinking and the logic of our unconscious dynamics.

The emergence of intelligent technologies, sophisticated natural language processing methodologies and huge textual repositories, invites a new approach for the challenge of automatically identifying personality dimensions through the analysis of textual data. This short book aims to (1) introduce the challenge of computational personality analysis, (2) present a unique approach to personality analysis and (3) illustrate this approach through case studies and worked-out examples.This book is of special relevance to psychologists, especially those interested in the new insights offered by new computational and data-intensive tools, and to computational social scientists interested in human personality and language processing.

This book uncovers mathematical structures underlying natural intelligence and applies category theory as a modeling language for understanding human cognition, giving readers new insights into the nature of human thought. In this context, the book explores various topics and questions, such as the human representation of the number system, why our counting ability is different from that which is evident among non-human organisms, and why the idea of zero is so difficult to grasp.The book is organized into three parts: the first introduces the general reason for studying general structures underlying the human mind; the second part introduces category theory as a modeling language and use it for exposing the deep and fascinating structures underlying human cognition; and the third applies the general principles and ideas of the first two parts to reaching a better understanding of challenging aspects of the human mind such as our understanding of thenumber system, the metaphorical nature of our thinking and the logic of our unconscious dynamics.

What if you found yourself working for an intelligence agency and suddenly your understanding of other human beings had become a matter of life or death? Yair Neuman draws us into a unique thought experiment, using portraits from some of Shakespeare’s most stirring works to illustrate how our psychological understanding of human nature can be significantly enriched through literature. Provocative and engaging, Shakespeare for the Intelligence Agent: Toward Understanding Real Personalities invites you to a challenging, enjoyable, and in many cases humorous reading of human personality through Shakespeare’s plays.

What if you found yourself working for an intelligence agency and suddenly your understanding of other human beings had become a matter of life or death? Yair Neuman draws us into a unique thought experiment, using portraits from some of Shakespeare’s most stirring works to illustrate how our psychological understanding of human nature can be significantly enriched through literature. Provocative and engaging, Shakespeare for the Intelligence Agent: Toward Understanding Real Personalities invites you to a challenging, enjoyable, and in many cases humorous reading of human personality through Shakespeare’s plays.

The emergence of intelligent technologies, sophisticated natural language processing methodologies and huge textual repositories, invites a new approach for the challenge of automatically identifying personality dimensions through the analysis of textual data. This short book aims to (1) introduce the challenge of computational personality analysis, (2) present a unique approach to personality analysis and (3) illustrate this approach through case studies and worked-out examples.This book is of special relevance to psychologists, especially those interested in the new insights offered by new computational and data-intensive tools, and to computational social scientists interested in human personality and language processing.

Human psychology is deeply rooted in the culture in which people live. Introduction to Computational Cultural Psychology introduces a revolutionary approach for studying cultural psychology. Drawing on novel computational tools and in-depth case studies, Professor Yair Neuman offers thought-provoking answers to questions such as: how are thought and language deeply related? How can computers help us to understand different cultures? How can computers assist military intelligence in identifying vengeful intentions? And how is our concept of 'love' rooted in our basic embodied experience? Written by a leading interdisciplinary researcher this book is a 'tour-de-force' which will be of interest to a variety of researchers, students and practitioners in psychology as well as an interdisciplinary audience with an interest in the intricate web weaved between the human psyche and its cultural context.