The Cambridge Handbook of the Law of Algorithms

The Cambridge Handbook of the Law of Algorithms
Author: Woodrow Barfield
Publisher: Cambridge University Press
Total Pages: 1327
Release: 2020-11-05
Genre: Law
ISBN: 1108663184

Algorithms are a fundamental building block of artificial intelligence - and, increasingly, society - but our legal institutions have largely failed to recognize or respond to this reality. The Cambridge Handbook of the Law of Algorithms, which features contributions from US, EU, and Asian legal scholars, discusses the specific challenges algorithms pose not only to current law, but also - as algorithms replace people as decision makers - to the foundations of society itself. The work includes wide coverage of the law as it relates to algorithms, with chapters analyzing how human biases have crept into algorithmic decision-making about who receives housing or credit, the length of sentences for defendants convicted of crimes, and many other decisions that impact constitutionally protected groups. Other issues covered in the work include the impact of algorithms on the law of free speech, intellectual property, and commercial and human rights law.

Algorithms and Law

Algorithms and Law
Author: Martin Ebers
Publisher: Cambridge University Press
Total Pages: 321
Release: 2020-07-23
Genre: Computers
ISBN: 1108424821

Exploring issues from big-data to robotics, this volume is the first to comprehensively examine the regulatory implications of AI technology.

The Cambridge Handbook of Policing in the United States

The Cambridge Handbook of Policing in the United States
Author: Tamara Rice Lave
Publisher: Cambridge University Press
Total Pages: 615
Release: 2019-07-04
Genre: Law
ISBN: 1108420559

A comprehensive collection on police and policing, written by experts in political theory, sociology, criminology, economics, law, public health, and critical theory.

Just Algorithms

Just Algorithms
Author: Christopher Slobogin
Publisher: Cambridge University Press
Total Pages: 183
Release: 2021-07-29
Genre: Law
ISBN: 1108996809

Statistically-derived algorithms, adopted by many jurisdictions in an effort to identify the risk of reoffending posed by criminal defendants, have been lambasted as racist, de-humanizing, and antithetical to the foundational tenets of criminal justice. Just Algorithms argues that these attacks are misguided and that, properly regulated, risk assessment tools can be a crucial means of safely and humanely dismantling our massive jail and prison complex. The book explains how risk algorithms work, the types of legal questions they should answer, and the criteria for judging whether they do so in a way that minimizes bias and respects human dignity. It also shows how risk assessment instruments can provide leverage for curtailing draconian prison sentences and the plea-bargaining system that produces them. The ultimate goal of Christopher Slobogin's insightful analysis is to develop the principles that should govern, in both the pretrial and sentencing settings, the criminal justice system's consideration of risk.

Oxford Handbook of Ethics of AI

Oxford Handbook of Ethics of AI
Author: Markus D. Dubber
Publisher: Oxford University Press
Total Pages: 1000
Release: 2020-06-30
Genre: Law
ISBN: 0190067411

This volume tackles a quickly-evolving field of inquiry, mapping the existing discourse as part of a general attempt to place current developments in historical context; at the same time, breaking new ground in taking on novel subjects and pursuing fresh approaches. The term "A.I." is used to refer to a broad range of phenomena, from machine learning and data mining to artificial general intelligence. The recent advent of more sophisticated AI systems, which function with partial or full autonomy and are capable of tasks which require learning and 'intelligence', presents difficult ethical questions, and has drawn concerns from many quarters about individual and societal welfare, democratic decision-making, moral agency, and the prevention of harm. This work ranges from explorations of normative constraints on specific applications of machine learning algorithms today-in everyday medical practice, for instance-to reflections on the (potential) status of AI as a form of consciousness with attendant rights and duties and, more generally still, on the conceptual terms and frameworks necessarily to understand tasks requiring intelligence, whether "human" or "A.I."

The Ethical Algorithm

The Ethical Algorithm
Author: Michael Kearns
Publisher:
Total Pages: 229
Release: 2020
Genre: Business & Economics
ISBN: 0190948205

Algorithms have made our lives more efficient and entertaining--but not without a significant cost. Can we design a better future, one in which societial gains brought about by technology are balanced with the rights of citizens? The Ethical Algorithm offers a set of principled solutions based on the emerging and exciting science of socially aware algorithm design.

Algorithms for Decision Making

Algorithms for Decision Making
Author: Mykel J. Kochenderfer
Publisher: MIT Press
Total Pages: 701
Release: 2022-08-16
Genre: Computers
ISBN: 0262047012

A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them. Automated decision-making systems or decision-support systems—used in applications that range from aircraft collision avoidance to breast cancer screening—must be designed to account for various sources of uncertainty while carefully balancing multiple objectives. This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them. The book first addresses the problem of reasoning about uncertainty and objectives in simple decisions at a single point in time, and then turns to sequential decision problems in stochastic environments where the outcomes of our actions are uncertain. It goes on to address model uncertainty, when we do not start with a known model and must learn how to act through interaction with the environment; state uncertainty, in which we do not know the current state of the environment due to imperfect perceptual information; and decision contexts involving multiple agents. The book focuses primarily on planning and reinforcement learning, although some of the techniques presented draw on elements of supervised learning and optimization. Algorithms are implemented in the Julia programming language. Figures, examples, and exercises convey the intuition behind the various approaches presented.

The Cambridge Handbook of Applied Perception Research

The Cambridge Handbook of Applied Perception Research
Author: Robert R. Hoffman
Publisher: Cambridge University Press
Total Pages: 1468
Release: 2015-01-26
Genre: Psychology
ISBN: 1139993534

The Cambridge Handbook of Applied Perception Research covers core areas of research in perception with an emphasis on its application to real-world environments. Topics include multisensory processing of information, time perception, sustained attention, and signal detection, as well as pedagogical issues surrounding the training of applied perception researchers. In addition to familiar topics, such as perceptual learning, the Handbook focuses on emerging areas of importance, such as human-robot coordination, haptic interfaces, and issues facing societies in the twenty-first century (such as terrorism and threat detection, medical errors, and the broader implications of automation). Organized into sections representing major areas of theoretical and practical importance for the application of perception psychology to human performance and the design and operation of human-technology interdependence, it also addresses the challenges to basic research, including the problem of quantifying information, defining cognitive resources, and theoretical advances in the nature of attention and perceptual processes.

Algorithmic Regulation

Algorithmic Regulation
Author: Karen Yeung
Publisher: Oxford University Press
Total Pages: 346
Release: 2019-09-12
Genre: Law
ISBN: 0192575449

As the power and sophistication of of 'big data' and predictive analytics has continued to expand, so too has policy and public concern about the use of algorithms in contemporary life. This is hardly surprising given our increasing reliance on algorithms in daily life, touching policy sectors from healthcare, transport, finance, consumer retail, manufacturing education, and employment through to public service provision and the operation of the criminal justice system. This has prompted concerns about the need and importance of holding algorithmic power to account, yet it is far from clear that existing legal and other oversight mechanisms are up to the task. This collection of essays, edited by two leading regulatory governance scholars, offers a critical exploration of 'algorithmic regulation', understood both as a means for co-ordinating and regulating social action and decision-making, as well as the need for institutional mechanisms through which the power of algorithms and algorithmic systems might themselves be regulated. It offers a unique perspective that is likely to become a significant reference point for the ever-growing debates about the power of algorithms in daily life in the worlds of research, policy and practice. The range of contributors are drawn from a broad range of disciplinary perspectives including law, public administration, applied philosophy, data science and artificial intelligence. Taken together, they highlight the rise of algorithmic power, the potential benefits and risks associated with this power, the way in which Sheila Jasanoff's long-standing claim that 'technology is politics' has been thrown into sharp relief by the speed and scale at which algorithmic systems are proliferating, and the urgent need for wider public debate and engagement of their underlying values and value trade-offs, the way in which they affect individual and collective decision-making and action, and effective and legitimate mechanisms by and through which algorithmic power is held to account.