Cybernetic Psychology and Mental Health

A Circular Logic Of Control Beyond The Individual

Timothy J. Beck

• Publisher: Routledge
• Year: 2020
• ISBN:
  9781000080346
• Edition: 1
• Topic: Psychology
• Subtopic: History & Theory in Psychology
• Index: Psychology

This book explores the cultural importance of cybernetic technologies and their relationship to human experience through a critical theoretical lens.

Bringing several often-marginalized histories of cybernetics, psychology, and mental health into dialogue with one another, Beck questions common assumptions about human life such as that our minds operate as information processing machines and our neurons communicate with one another. Rather than suggest that such ideas are either right or wrong, however, this book analyzes how and why we have come to frame questions about ourselves in these ways, as if our brains were our own personal computers. Here, the rationality underlying information theories in psychology is followed to its logical conclusion, only to find it circles back to where it began: engineered methods of human control. After tracing a series of recent developments in this vein across fields related to mental health, Beck highlights emerging psychosocial alternatives by incorporating recent work of scholars and activists who have already begun creating collective support networks in radical ways. Their work overlaps fruitfully with ideas from those, including Gilbert Simondon and Fernand Deligny, who foresaw many of the current problems with how information theories have been coupled with psychology and mental health care.

This book is fascinating reading for advanced undergraduate and postgraduate students across psychology, mental health programs, and digital media studies, and academics and researchers with a theoretical interest in the philosophy of technology. It's also an interesting resource for professionals with a practical interest in organizing care services under the data-driven imperatives of contemporary capitalism.

1
Towards a technical history of thinking about human thought

Introduction

Information about what others might be thinking has become an increasingly valuable commodity within contemporary capitalist societies. Private companies employ market research strategies in ever more inventive forms, hoping to discover what we want, desire, or think we need. Psychologists and other mental health professionals are continually reviewing information about individuals in the forms of notes, assessments, and research studies to more effectively intervene on their thoughts and behaviors. And what are social media platforms other than corporatized, digital ledgers of personal thoughts, opinions, and reactions, which we add to every time we logon? The sheer breadth of these concerted efforts to probe more deeply into the nature of human experience points to something beyond a mere amplification of prior attempts to establish greater scientific certainty about the world. They express qualitatively new obsessions with accumulating information about information, whereby assumptions about “mental health” are reconfigured through channels of social communication that are themselves able to be tracked and communicated about. While concerns related to surveillance and privacy are of course important here, a more general set of questions relate to how datasets collected on humans are “fed back” into the mechanisms by which we understand ourselves in relation to what we perceive to be the world. This renders mediation a fundamental principle in such societies, as perception in general becomes increasingly dependent on networks of information technologies (e.g., an internet of things) and the users who subtend them.

And yet, there are unavoidable limits to thinking about thinking—underscoring conceptual, practical, and ethical questions about how data collected about human life can to be interpreted and used. Such limits have traditionally been framed through a notion of access to information, referring specifically to who has been granted access and to what extent. In a purely phenomenological sense, for instance, we cannot directly access others’ thoughts in the same way we do objects in the world. This is also true, in a slightly different sense, for our own thoughts. Philosophers have described such issues in terms of first-person vs. third-person perspectives, the hard problem of consciousness (Chalmers, 1997), or the “problem of other minds” (Leudar & Costall, 2004). With social organizations today relying on personal/behavioral data more than ever before, however, information about what others could be thinking has become valuable for reasons outside of academia. Under the totalizing conditions of global capitalism, such data cannot possibly be collected and mobilized in ways that can be made accessible to everyone equally. In economies where the demand for networked data rivals that of material goods and services, overlaps across market research, biological sciences, and diagnostic assessment yield value primarily for individual entities with the technical capital required to access and analyze said data.

This book explores how conventional problems regarding who has access to what kind of information have been reconfigured, broadly, for new social purposes that cut across issues related to mental health, governance, and technology. At the basis of each of these social arenas are new demands to map the ways certain populations of individuals think, behave, and/or feel. New network approaches to psychopathology, for instance, are being used to organize growing banks of mental health data into computational models, transforming diagnoses from pre-defined categories to evolving constellations of biological, psychological, and social traits (see McNally, 2016; Jones et al., 2017). Despite all the talk lately about data-ethics across industries and sciences generally (Kostakis & Bauwens, 2014; Ekbia & Nardi, 2017), very few mental health professionals or clinical researchers have questioned how the collection of such data might have consequences for service users moving forward. This has broad social relevance not only because of the way policies and funding are so intimately tied to scientific research—although this is an important point also addressed below. Even more relevant to what has been discussed so far, however, this signals how mental health professionals have begun turning to the same technologies that are already being used to surveil individuals around the world and, by extension, organize data collected on them into ever more comprehensive information infrastructures (Halpern, 2015; Mayer-Schönberger & Ramge, 2018).

These examples illustrate how datasets about human thoughts and behavior are not simply collected for their own sake; today they are often mobilized to intervene on behavior across diverse domains of social life (Zuboff, 2019). This has consequences well beyond the goals for which psychological data collection practices were initially developed. Whenever concepts like the individual, mind, or culture are used to surveil and intervene on social behaviors, for instance, their meanings tend to taken-for-granted and, in most cases, tailored to conform to the overarching social purposes of institutions employing these methods. This is reminiscent to how the privileged position traditionally afforded to the concept of humanity, on the one hand, and the boundaries between human bodies and machines, on the other, have been challenged by recent movements like posthumanism and transhumanism (see Ferrando, 2014), with new theoretical frameworks proposed that are better equipped to engage with global problems unique to the 21st century. Critical analyses of how ideas in psychology are inextricable from social values are thus useful not because they chart absolute boundaries beyond which thought is impossible, or even because they reveal essential qualities about human nature. Rather, by marking the conceptual mechanisms underpinning current modes of society, life itself can be reimagined in forms that would otherwise be unthinkable given the most popular socioeconomic values.

More specifically, critical histories of psychological practices, particularly those associated with the term “mental health,” provide robust case studies for thinking through the ethics of emerging techno-governance models and how subjectivities are produced through information networks, as such. This is evident in the way research on humans, most notably in neuroscience, depends increasingly on innovations in digital technology, as well as how technical metaphors are applied so liberally to explain poorly understood areas of human life. This is likewise important in terms of reflecting more generally on how the margins between humans and machines, as well as individuals and groups, are steadily redefined through information processing tropes so that data about “mental health” can be more easily integrated into transdisciplinary research programs. Here, it is necessary to account for how what would have been considered purely academic concerns in earlier generations are actively incorporated into the decision-making processes of transnational companies and governments around the world. Theories about human psychology and mental health are thus unavoidably structured through conditions of contemporary capitalism, where ethics is often but a subsidiary of overarching goals like risk-assessment and financial growth. With emerging network technologies being employed by mental health professionals, researchers, and service-user activist communities alike, there has never been a more important time to interrogate how data and information about “mental health” is collected, stored, and interpreted, and reflect critically on who benefits from its mobilization, as such.

Technology as a medium for thinking about human thought

From Aristotle’s notion of the mind as the navigator of a ship to the hydraulic model of the psyche proposed by Sigmund Freud, there is no shortage of metaphors throughout Western history that link technology to human thought. Rather than attempt to determine which of these are the most useful today, this book explores the social affordances technical metaphor provides within particular places and times. There is one technical framework that stands out as especially central to the history psychology in general: Rene Descartes’ mechanistic theory of science (see Schultz & Shultz, 2015). What is arguably one of the first myths of psychological auto-individuation emerging from scientific research, Descartes’ dualism famously separated the mind and body into two, completely different realms of reality. Human bodies were said to operate according to natural laws of the physical universe, and it was the task of scientists to uncover the logical mechanisms underlying human action. This is also the domain where animal behavior resides. Data collected on bodies through experimental studies were expected to conform to such laws and, when they did not, it was typically an indication of error on the part of either the scientist or the tool used for measurement.

Human minds in Descartes’ framework, by contrast, were granted privileged access to God—at least to the extent their thoughts remained rational. Following his model to its logical conclusion, individual minds can only learn about the world outside of itself through a reliance on God, as the chief programmer of the physical world. This is how Descartes was able to wed science, ideologically, with religion—as scientists were said to have special insight into the mind of God. What makes Descartes’ philosophy even more relevant to the concerns of this book, however, is the way he linked God to mathematics, subordinating both mental and physical processes, albeit in different ways, to the same ideal mathematical structure. Here, divine principles and mathematical principles were fused into uniform, universal laws of nature. And in this way, human minds were uniquely positioned to comprehend the extended universe of which their bodies operated as physical parts.

This, in turn, formed the foundation of Descartes’ representational theory of knowledge, whereby the truth value of any idea an individual might have is determined solely by its capacity to mediate between the most essential parts of an object, or body, affording a predictable degree of control over its organization. Gilbert Simondon (2013) underscores how this was a core aspect of Descartes’ epistemology of mind. With:

Cartesian mechanism, the fundamental operation of the simple machine is analogous to the functioning of logical thought capable of being rigorous and productive… [where] the transfer of forces goes from link to link, so that if each link is welded well and there are no gaps in the enchainment, the last link is fixed to the anchoring point in a more mediated but also more rigorous way than the first. (p. 2)

In this way, the analytic nature of modern knowledge, as formalized by Cartesian geometry, links the organization of life axiomatically to the conditions of thought, such that “if [living beings] were not machines ontologically, they would have to be so at least analogically in order to be objects of science” (p. 3). Simondon furthermore describes Cartesian mechanism, in this sense, as a particular cognitive schema—a schema of intelligibility—by which a certain form of technical thought made it possible for scientists to represent human thinking with “no gaps in the enchainment.” In other words, with no scientific method available to access human thought directly, scientists have traditionally been able to learn about mental processes only by comparing them to something already situated within the realm of scientific knowledge—e.g., technology?

Well before artificial intelligence (AI) became a popular conversational trope, it was common for psychiatrists and psychologists to construe individual persons in terms of mechanistic systems composed of functional relations. Making sense of human beings through technical metaphor has such a long history in Western thought that it is almost impossible to talk about conceptual innovations in psy-disciplines (i.e., psychology, psychiatry, and psychotherapy) without considering contemporaneous ones in technology (Leary, 1994). Comparisons have been made, for instance, between Freud’s theory of the psyche and the steam engine (Carveth, 1984), but he was perhaps fonder of the “mystic writing pad” as a model for memory traces and the unconscious (see Freud, 1925). The influence of electrical engineering on the thinking of Skinner and other behaviorists was clear with the broadly construed switchboard model they used to map organism–environment relations mechanistically as stimulus- response circuits (Edwards, 2000). And of course, applications of digital computing metaphors to the human brain, and by extension, the mind, has made possible all sorts of systems diagrams of human thought and action across social domains as diverse as medicine, education, and war (see Boden, 2008).

To date, clinical researchers interested in mental health have engaged, at best, indirectly with ethical issues related to computer–human interface. The focus tends to remain exclusively at the level of the individual, where there might be expressed interest, for instance, with effects of social media use on mental health, or with how human cognitive capacities can be enhanced through technical devices. As alluded to above, the most innovative research in this domain incorporates ideas that developed out of former cybernetic programs, which now range from social network theories to neural networking. And yet, there are many noteworthy examples of psychiatrists and psychologists across the 20th century who were concerned primarily with systems and how individuals operate within them. As I outline below, several enduring figures, in fact, laid the theoretical foundations for trends currently cutting across data-driven industries, information sciences, and mental health care. By theorizing about networks of cause and effect beyond the scope of individual persons, historical figures like Sigmund Freud and B.F. Skinner provide prescient insights regarding current impulses to decode individual behavior as a function of their environment.

As Keller and Longino (1996) suggest, moreover, understanding the role of the individual in relation to the environment is important for reasons beyond the important contribution of standpoint theory, moving into a critique of “the supposed universality of scientific norms” (p. 3). Going further, they explain how concepts like dualism, consciousness, and the individual are each shaped uniquely by the historical constraints placed on science at any given moment, which includes the tools scientists have at their disposal. Haraway (1996) describes, for instance, how the even concept of:

The “eyes” made available in modern technological sciences shatter any idea of passive vision; these prosthetic devices show us that all eyes, including our own organic ones, are active perceptual systems, building in translations and specific ways of seeing, that is, ways about life. (Haraway, 1996, p. 254)

In these ways, the tools used to collect and analyze data condition not only what we are able to measure but also how we ask questions about and, even, perceive what the data is supposed to represent. Exploring scientific research from the perspective of the “researcher as person,” as Osbeck (2018) suggests, emphasizes that science-based activities are unavoidably structured by a range of personal and social values that cannot be entirely isolated and controlled for through the scientific method alone.

These overlaps across the practical and theoretical dimensions of science are especially relevant today given the increasingly data-driven nature of most professional pursuits. Organizations ranging from colleges to banks rely on data about individual behavior to make decisions about how their finances and resources should be managed, rendering digital technology essential to their underlying institutional infrastructures. Similar developments can be seen in academic research programs as well. Research in nearly every discipline relies on computers to store and evaluate data in ways that mediate relations between humans and the world. Here, aspects of human thought that would otherwise remain unobservable can be represented (hence visualized) in new, ever-more elaborate forms. The most widely funded studies on humans are, for instance, typically in neuroscience, where conceptual innovation relies on ever more creative applications of computers to elicit new neurological data, which are then fed into the development of new neural maps. And in mental health contexts, new computational models of mental disorders have been positioned as viable alternatives to conventional diagnostic taxonomies like the Diagnostic and Statistical Manual for Mental Disorders, or the DSM (see McNally, 2016). Data collected about individuals’ mental, social, and biological lives are being plugged into network modeling programs that map constellations of traits in ways that can continually be updated as more data is collected on service users (see Jones et al., 2017). In these ways, Cartesian mechanism has become refined in ever more practical forms through the models of “mental health” we use to think about each other and ourselves. This can be seen even in cases where Descartes’ mind-body dualism has ostensibly been transcended through materialist explanations for human behavior, like contemporary neuroscience, for instance (see Damasio, 2005). And yet, his mechanistic approach to science continues to condition how human knowledge is wedded to both technical artifice and empirical data.

The cybernetic foundation of current methods of psychosocial control

Many of the most popularly discussed issues related to machine–human interface can be traced directly to the cybernetics research programs of the mid-20th century. During this period, concepts like communication, information, feedback, and recursion—analogues of ideas psychologists had been theorizing about for decades—were redefined by academics, industry professionals, and psychiatrists collaborating across disciplinary lines (see Pias, 2016). Methods and concepts spanning the fields linguistics, biology, and engineering were brought together under the assumption that physical processes underlying organic systems can (and should) be...

Table of contents

• Cover
• Half Title
• Series Page
• Title Page
• Copyright Page
• Table of Contents
• Preface
• Acknowledgements
• Introduction
• 1 Towards a technical history of thinking about human thought
• 2 Cybernetic narratives beyond The Individual
• 3 Three (psycho)logical myths of auto-individuation (pseudo-AI)
• 4 Deinstitutionalization, biopolitics, and network maps of “mental disorder”
• 5 Disorder without borders
• 6 The network as a mode of being
• References
• Index