Emergent Democracy

Version 3.2. Originally published on blog and wiki and then as a chapter in the book, Extreme Democracy. This version edited by Jon Lebkowsky.This essay argues that a new form of democracy — an “Emergent Democracy” — will develop as a result of the use of Internet communication tools and platforms such as blogs. The essay explores a variety of tools available and explores the history of democracy, modern experiments with democracy and how these tools might support democracy. The essay also explores concerns as these new tools emerge. These issues include concerns such as privacy and the societally negative use of these tools by corporations, totalitarian regimes and terrorists

The Practice of Change

PhD dissertation submitted to Keio University Graduate School of Media & GovernanceOver the last century civilization has systematically supported a market based approach to developing technical, financial, social and legal tools that focus on efficiency, growth and productivity. In this manner we have achieved considerable progress on some of the most pressing humanitarian challenges, such as eradicating infectious diseases and making life easier and more convenient. However, we have often put our tools and methods to use with little regard to their systemic or long-term effects, and have thereby created a set of new, interconnected, and more complex problems. Our new problems require new approaches: new understanding, solution design and intervention. Yet we continue to try to solve these new problems with the same tools that caused them. Therefore in my dissertation I ask: How can we understand and effectively intervene in interconnected complex adaptive systems? In particular, my thesis presents through theory and practice the following contributions to addressing these problems: 1. A post-Internet framework for understanding and intervening in complex adaptive systems. Drawing on systems dynamics, evolutionary dynamics and theory of change based on causal networks, I describe a way to understand and suggest ways to intervene in complex systems. I argue that an anti-disciplinary approach and paradigm shifts are required to achieve the outcomes we desire. 2. Learnings from the creation and management of post-Internet organizations that can be applied to designing and deploying interventions. I propose an architecture of layers of interoperability to unbundle complex, inflexible, and monolithic systems and increase competition, cooperation, generativity, and flexibility. I argue that the Internet is the best example of this architecture and that the Internet has provided an opportunity to deploy this architecture in other domains. I demonstrate how the Internet has has made the world more complex but through lowering the cost of communication and collaboration has enabled new forms of organization and production. This has changed the nature of our interventions. 3. How and why we must change the values of society from one based on the measurement of financial value to flourishing and robustness. The paradigm determines what we measure and generates the values and the goals of a system. Measuring value financially has created a competitive market-based system that has provided many societal benefits but has produced complex problems not solvable through competitive market-based solutions. In order to address these challenges, we must shift the paradigm across our systems to focus on a more complex measure of flourishing and robustness. In order to transcend our current economic paradigm, the transformation will require a movement that includes arts and culture to transform strongly held beliefs. I propose a framework of values based on the pursuit of flourishing and a method for transforming ourselves. Reflecting on my work experience, I examine my successes and failures in the form of learnings and insights. I discuss what questions are outstanding and conclude with a call to action with a theory of change; we need to bring about a fundamental normative shift in society through communities, away from the pursuit of growth for growth’s sake and towards a sustainable sensibility of flourishing that can draw on both the historical examples and the sensibilities of some modern indigenous cultures, as well as new values emerging from theoretical and practical progress in science

The Aesthetics of the Internet – Context as a Medium

The Internet connects computers, people, sensors, vehicles, telephones, and just about anything together in a global network which is fast and cheap. This interconnectedness is the context. Context represents the way and the timing in which nodes are connected together. If content were the noun part of information, then context would be the verb part

Interventions over Predictions: Reframing the Ethical Debate for Actuarial Risk Assessment

Actuarial risk assessments might be unduly perceived as a neutral way to counteract implicit bias and increase the fairness of decisions made at almost every juncture of the criminal justice system, from pretrial release to sentencing, parole and probation. In recent times these assessments have come under increased scrutiny, as critics claim that the statistical techniques underlying them might reproduce existing patterns of discrimination and historical biases that are reflected in the data.Much of this debate is centered around competing notions of fairness and predictive accuracy, resting on the contested use of variables that act as “proxies” for characteristics legally protected against discrimination, such as race and gender. We argue that a core ethical debate surrounding the use of regression in risk assessments is not simply one of bias or accuracy. Rather, it’s one of purpose. If machine learning is operationalized merely in the service of predicting individual future crime, then it becomes difficult to break cycles of criminalization that are driven by the iatrogenic effects of the criminal justice system itself. We posit that machine learning should not be used for prediction, but rather to surface covariates that are fed into a causal model for understanding the social, structural and psychological drivers of crime. We propose an alternative application of machine learning and causal inference away from predicting risk scores to risk mitigation