How To Measure Mind

Get to grips with the debate around the historical epistemological origins of psychometric assessment Written by leading experts Explores modern and historical aspects Full of illustrations A thoughtful look at the history of psychological assessment While there have been significant developments in the technical aspects of assessing mental functioning, there is still much to be debated about the motivations and meanings of measuring the mind. How can mental faculties be objectified and what influence does subjectivity have on the object being measured and the mind measuring it? What are the consequences of quantifying complex and interdependent functions and scaling these measurements for psychometric instruments? The contributors of this edited volume explore these questions by adopting a historical and epistemological approach to consider how psychometric assessment was born and developed within the affirmation of psychology as an empirical science. Chapters explore the birth of the scientific approach, as well as different assessment methods of cognitive abilities and personality traits, and the development of new technologies that support psychological evaluation and its applications in educational and rehabilitative fields. This book is of interest to researchers of human behavior as well as practicing psychologists and psychiatrists who want to deepen their understanding of the historical and epistemological roots of psychological assessment.

Are psychometric tests valid for a new reality of artificial intelligence systems, technology-enhanced humans, and hybrids yet to come? Are the Turing Test, the ubiquitous CAPTCHAs, and the various animal cognition tests the best alternatives? In this fascinating and provocative book, José Hernández-Orallo formulates major scientific questions, integrates the most significant research developments, and offers a vision of the universal evaluation of cognition. By replacing the dominant anthropocentric stance with a universal perspective where living organisms are considered as a special case, long-standing questions in the evaluation of behavior can be addressed in a wider landscape. Can we derive task difficulty intrinsically? Is a universal g factor - a common general component for all abilities - theoretically possible? Using algorithmic information theory as a foundation, the book elaborates on the evaluation of perceptual, developmental, social, verbal and collective features and critically analyzes what the future of intelligence might look like.

Is it possible to measure psychological attributes like intelligence, personality and attitudes and if so, how does that work? What does the term 'measurement' mean in a psychological context? This fascinating and timely book discusses these questions and investigates the possible answers that can be given in response.

In this provocative yet practical guidebook Steve Morlidge demonstrates why the approach and methods of performance reporting that all information professionals have been taught fails, and what we need to do differently to help us make sense of the dynamic, complex and data rich world in which we now live and work. Reporting on performance should not be treated as worthy but dull, requiring no more than routine comparisons of actual against targets. This traditional approach is based on the false premise organisations can be managed as if they were a simple mechanical system operating in a predictable environment. And the methods associated with it, such as variance analyses and data tables that are used to measure and communicate performance, are completely inadequate. Instead, Morlidge argues performance reporting should be reconceived as an act of perception conducted on behalf of the organisation, helping to make sense of the sensory inputs (data) that it has at its disposal. And to do so effectively performance reporters need to learn from and exploit the strengths of our own brains, compensate for its weaknesses and communicate in a way that makes it easy for their audience’s brains to assimilate. Drawing on the latest insights from cognitive science in this book you will learn: • how to bring a dynamic perspective into performance reporting • how to deploy a set of simple tools to help speared the signal from the noise inherent in large data sets and to make sound inferences • how to set goals intelligently • about the grammar of data visualization and how use it to design powerful and simple reports In this way information professionals are uniquely charged with the responsibility for creating the shared consciousness that is a prerequisite for organisations to effectively respond and adapt to their environments.

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The Measure of Mind provides a sustained critique of a widely held representationalist view of propositional attitudes and their role in the production of thought and behaviour. On this view, having a propositional attitude is a matter of having an explicit representation that plays a particular causal/computational role in the production of thought and behaviour. Robert J. Matthews argues that this view does not enjoy the theoretical or the empirical support that proponents claim for it; moreover, the view misconstrues the role of propositional attitude attributions in cognitive scientific theorizing. The Measure of Mind goes on to develop an alternative measurement-theoretic account of propositional attitudes and the sentences by which we attribute them. On this account, the sentences by which we attribute propositional attitudes function semantically like the sentences by which we attribute a quantity of some physical magnitude (e.g., having a mass of 80 kilos). That is, in much the same way that we specify a quantity of some physical magnitude by means of its numerical representative on a measurement scale, we specify propositional attitude of a given type by means of its representative in a linguistically-defined measurement space. Propositional attitudes turn out to be causally efficacious aptitudes for thought and behaviour, not semantically evaluable mental particulars of some sort. Matthews' measurement-theoretic account provides a more plausible view of the explanatorily relevant properties of propositional attitudes, the semantics of propositional attitude attributions, and the role of such attributions in computational cognitive scientific theorizing.