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"Ryberg, Jesper"
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Retributivism and the (Lack of) Justification of Proportionality
The principle of proportionality has gained widespread adherence in the modern retributively-dominated era of penal theory. It has often been held that, if one subscribes to a retributivist theory, then one is also committed to proportionality in punishment (or at least to proportionately-determined upper punishment constraints). In the present article, this assumption is challenged. It is shown that the inference from the fact that one offender has committed a more serious crime than another offender, to the conclusion that this offender should be punished more severely than the other, presupposes the satisfaction of two conditions: The Necessity Requirement and the Sufficiency Requirement. It is argued that modern expressionist accounts of retributivism fail to satisfy these requirements. Moreover, it is suggested that the satisfaction of these requirements constitutes a challenge for other retributivist theories. In so far as this is the case, the inference from retributivism to proportionality will be blocked.
Journal Article
Punishment and ethics : new perspectives
This collection of original contributions by philosophers working in the ethics of punishment presents the reader with new perspectives on various interesting and relevant topics including: punishment and discrimination, punishment and forgiveness, punishment and rehabilitation, punishment and public opinion, punishment and restitution, punishment and tortur, e punishment and dignity /from the publisher's website.
Book
Risk-Based Sentencing and Predictive Accuracy
The use of risk assessment tools has come to play an increasingly important role in sentencing decisions in many jurisdictions. A key issue in the theoretical discussion of risk assessment concerns the predictive accuracy of such tools. For instance, it has been underlined that most risk assessment instruments have poor to moderate accuracy in most applications. However, the relation between, on the one hand, judgements of the predictive accuracy of a risk assessment tool and, on the other, conclusions concerning the justified use of such an instrument in sentencing practice, is often very unclear. The purpose of this paper is to examine this relation. More precisely, it is argued that the relation between predictive accuracy and the question as to whether a new risk assessment tool should be introduced in sentencing practice is highly complicated. For instance, there may be cases in which a new risk assessment tool is more accurate than those currently in use, but should nevertheless not be introduced; and conversely, where a new tool is less accurate, but where its introduction instead of current tools would be morally preferable.
Journal Article
Minding Rights: Mapping Ethical and Legal Foundations of ‘Neurorights’
The rise of neurotechnologies, especially in combination with artificial intelligence (AI)-based methods for brain data analytics, has given rise to concerns around the protection of mental privacy, mental integrity and cognitive liberty – often framed as “neurorights” in ethical, legal, and policy discussions. Several states are now looking at including neurorights into their constitutional legal frameworks, and international institutions and organizations, such as UNESCO and the Council of Europe, are taking an active interest in developing international policy and governance guidelines on this issue. However, in many discussions of neurorights the philosophical assumptions, ethical frames of reference and legal interpretation are either not made explicit or conflict with each other. The aim of this multidisciplinary work is to provide conceptual, ethical, and legal foundations that allow for facilitating a common minimalist conceptual understanding of mental privacy, mental integrity, and cognitive liberty to facilitate scholarly, legal, and policy discussions.
Journal Article
Criminal Justice and Artificial Intelligence: How Should we Assess the Performance of Sentencing Algorithms?
Artificial intelligence is increasingly permeating many types of high-stake societal decision-making such as the work at the criminal courts. Various types of algorithmic tools have already been introduced into sentencing. This article concerns the use of algorithms designed to deliver sentence recommendations. More precisely, it is considered how one should determine whether one type of sentencing algorithm (e.g., a model based on machine learning) would be ethically preferable to another type of sentencing algorithm (e.g., a model based on old-fashioned programming). Whether the implementation of sentencing algorithms is ethically desirable obviously depends upon various questions. For instance, some of the traditional issues that have received considerable attention are algorithmic biases and lack of transparency. However, the purpose of this article is to direct attention to a further challenge that has not yet been considered in the discussion of sentencing algorithms. That is, even if is assumed that the traditional challenges concerning biases, transparency, and cost-efficiency have all been solved or proven insubstantial, there will be a further serious challenge associated with the comparison of sentencing algorithms; namely, that we do not yet possess an ethically plausible and applicable criterion for assessing how well sentencing algorithms are performing.
Journal Article
Sentencing Disparity and Artificial Intelligence
The idea of using artificial intelligence as a support system in the sentencing process has attracted increasing attention. For instance, it has been suggested that machine learning algorithms may help in curbing problems concerning inter-judge sentencing disparity. The purpose of the present article is to examine the merits of this possibility. It is argued that, insofar as the unfairness of sentencing disparity is held to reflect a retributivist view of proportionality, it is not necessarily the case that increasing inter-judge uniformity in sentencing is desirable. More generally, it is shown that the idea of introducing machine learning algorithms, that produce sentencing predictions on the ground of a dataset that is built of previous sentencing decisions, faces serious problems if there exists a discrepancy between actual sentencing practice and the sentences that are ideally desirable.
Journal Article
Neuroscience, Mind Reading and Mental Privacy
Many theorists have expressed the view that current or future applications of neurotechnology may prompt serious ethical problems in terms of privacy. This article concerns the question as to whether involuntary neurotechnological mind reading can plausibly be held to violate a person’s moral right to mental privacy. It is argued that it is difficult to specify what a violation of a right to mental privacy amounts to in a way that is consistent with the fact that we usually regard natural mind reading as morally unproblematic.
Journal Article
Neuroethics and Brain Privacy: Setting the Stage
Despite the fact that ethics as an overall field of research has over the last couple of decades experienced the emergence of a large number of more specialized sub-disciplines, there is little doubt that neuroethics—understood roughly as the study of ethical issues arising from what we can do to the brain and what we know about it—constitutes one of the most significant ‘stories of success’.
Journal Article