Introduction To Algorithmic Government

The world is changing at a fast pace, so is the Government and Governance style. Humans are bound to go for Algorithmic strategies rather than manual or electronic ones in different domains. This book introduces the Algorithmic Government or Government by Algorithm, which refers to authorizing machines in the Public Sector for automated decision-making based on Artificial Intelligence, Data Science, and other technologies. It is an emerging concept introduced globally and will be considered revolutionary in the future. The book covers concepts, applications, progress status, and potential use-cases of Algorithmic Government. This book serves as introductory material for the readers from technology, public policy, administration, and management fields.

The book provides various EdgeAI concepts related to its architecture, key performance indicators, and enabling technologies after introducing algorithmic government, large-scale decision-making, and computing issues in the cloud and fog. With advancements in technology, artificial intelligence has permeated our personal lives and the fields of economy, socio-culture, and politics. The integration of artificial intelligence (AI) into decision-making for public services is changing how governments operate worldwide. This book discusses how algorithms help the government in various ways, including virtual assistants for busy civil servants, automated public services, and algorithmic decision-making processes. In such cases, the implementation of algorithms will occur on a massive scale and possibly affect the lives of entire communities. The cloud-centric architecture of artificial intelligence brings out challenges of latency, overhead communication, and significant privacy risks. Due to the sheer volume of data generated by IoT devices, the data analysis must be performed at the forefront of the network. This introduces the need for edge computing in algorithmic government. EdgeAI, the confluence of edge computing and AI, is the primary focus of this book. It also discusses how one can incorporate these concepts in algorithmic government through conceptual framework and decision points. Finally, the research work emphasizes some design challenges in edge computing from applications viewpoint. This book will be helpful for data engineers, data scientists, cloud engineers, data management experts, public policymakers, administrators, research scholars and academicians.

This is an open access title available under the terms of a CC BY-NC-ND 4.0 International licence. It is free to read at Oxford Scholarship Online and offered as a free PDF download from OUP and selected open access locations. Are algorithms ruling the world today? Is artificial intelligence making life-and-death decisions? Are social media companies able to manipulate elections? As we are confronted with public and academic anxieties about unprecedented changes, this book offers a different analytical prism through which these transformations can be explored. Claudia Aradau and Tobias Blanke develop conceptual and methodological tools to understand how algorithmic operations shape the government of self and other. They explore the emergence of algorithmic reason through rationalities, materializations, and interventions, and trace how algorithmic rationalities of decomposition, recomposition, and partitioning are materialized in the construction of dangerous others, the power of platforms, and the production of economic value. The book provides a global trandisciplinary perspective on algorithmic operations, drawing on qualitative and digital methods to investigate controversies ranging from mass surveillance and the Cambridge Analytica scandal in the UK to predictive policing in the US, and from the use of facial recognition in China and drone targeting in Pakistan to the regulation of hate speech in Germany.

We live in an algorithmic society. Algorithms have become the main mediator through which power is enacted in our society. This book brings together three academic fields – Public Administration, Criminal Justice and Urban Governance – into a single conceptual framework, and offers a broad cultural-political analysis, addressing critical and ethical issues of algorithms. Governments are increasingly turning towards algorithms to predict criminality, deliver public services, allocate resources, and calculate recidivism rates. Mind-boggling amounts of data regarding our daily actions are analysed to make decisions that manage, control, and nudge our behaviour in everyday life. The contributions in this book offer a broad analysis of the mechanisms and social implications of algorithmic governance. Reporting from the cutting edge of scientific research, the result is illuminating and useful for understanding the relations between algorithms and power.Topics covered include: Algorithmic governmentality Transparency and accountability Fairness in criminal justice and predictive policing Principles of good digital administration Artificial Intelligence (AI) in the smart city This book is essential reading for students and scholars of Sociology, Criminology, Public Administration, Political Sciences, and Cultural Theory interested in the integration of algorithms into the governance of society.

Governments around the world use machine learning in automated decision-making systems for a broad range of functions. However, algorithmic bias in machine learning can result in automated decisions that produce disparate impact and may compromise Charter guarantees of substantive equality. This book seeks to answer the question: what standards should be applied to machine learning to mitigate disparate impact in government use of automated decision-making? The regulatory landscape for automated decision-making, in Canada and across the world, is far from settled. Legislative and policy models are emerging, and the role of standards is evolving to support regulatory objectives. While acknowledging the contributions of leading standards development organizations, the authors argue that the rationale for standards must come from the law and that implementing such standards would help to reduce future complaints by, and would proactively enable human rights protections for, those subject to automated decision-making. The book presents a proposed standards framework for automated decision-making and provides recommendations for its implementation in the context of the government of Canada’s Directive on Automated Decision-Making. As such, this book can assist public agencies around the world in developing and deploying automated decision-making systems equitably as well as being of interest to businesses that utilize automated decision-making processes.

Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with data and analytics using reproducible methods in R. Each of the eight chapters provides a detailed case study, showing readers: how to develop exploratory indicators; understand ‘spatial process’ and develop spatial analytics; how to develop ‘useful’ predictive analytics; how to convey these outputs to non-technical decision-makers through the medium of data visualization; and why, ultimately, data science and ‘Planning’ are one and the same. A graduate-level introduction to data science, this book will appeal to researchers and data scientists at the intersection of data analytics and public policy, as well as readers who wish to understand how algorithms will affect the future of government.

A concise but informative overview of AI ethics and policy. Artificial intelligence, or AI for short, has generated a staggering amount of hype in the past several years. Is it the game-changer it's been cracked up to be? If so, how is it changing the game? How is it likely to affect us as customers, tenants, aspiring home-owners, students, educators, patients, clients, prison inmates, members of ethnic and sexual minorities, voters in liberal democracies? This book offers a concise overview of moral, political, legal and economic implications of AI. It covers the basics of AI's latest permutation, machine learning, and considers issues including transparency, bias, liability, privacy, and regulation.

This book presents new trends to optimize e-Government in various contexts. It aims to highlight new methods and approaches that unveil the potential of data for public services. The book also illustrates how public services can be mathematically modeled with many case studies. Then, algorithms are proposed to optimize their functioning and to better contribute to the general interest, such as education, health care, safety, security, or culture. The book also focuses on protecting citizens' personal data and obtaining their explicit consent. The book is suitable for students and academics aiming to build up their background on the usage of data and algorithms through various techniques, including artificial intelligence. The book is used as a reference book for teaching a graduate course on e-Government, Process Modeling, or Artificial Intelligence. Besides its use in academia, this book is used by civil servants of every domain and citizens who aim to understand the ongoing modernization of public services.