• Corpus ID: 217366408

Algorithms in the Criminal Justice System: Assessing the Use of Risk Assessments in Sentencing

  title={Algorithms in the Criminal Justice System: Assessing the Use of Risk Assessments in Sentencing},
  author={D{\'a}niel Kehl and Samuel Kessler},

Artificial Intelligence-Powered Criminal Sentencing in Malaysia: A conflict with the rule of law

Artificial Intelligence (AI) promises to heighten human decision-making, including in court. AI sentencing would be better at detecting, organizing, and calibrating all of the variables correlated to

The Impact of Artificial Intelligence on the Right to a Fair Trial: Towards a Robot Judge?

Abstract This paper seeks to examine the potential influences AI may have on the right to a fair trial when it is used in the courtroom. Essentially, AI systems can assume two roles in the courtroom.

Machine learning in criminal justice : a philosophical enquiry

Forecasting in criminal justice can be dated back to at least the 1920s, while the machine-learning version of it is a fairly recent development. This thesis focuses on the specific case of the

Engendering assemblages: the constitution of digital health data as an epistemic consumption object

ABSTRACT This article uncovers the ideational work implied in the formation of a new assemblage dedicated to the constitution of ‘digital health’ as a productive field of social action. We analyze

Easy to Decide, Hard to Agree: Reducing Disagreements Between Saliency Methods

It is demonstrated that rank correlation is not a good for evaluating agreement and argued that Pearson is a better suited alternative, and it is shown that regularization techniques that increase faithfulness of attention explanations also increase agreement between saliency methods.

An Efficient HPU Resource Virtualization Framework for Human-Machine Computing Systems

An efficient HPU resource virtualization framework for HMC systems is proposed which aims to establish the mapping between each real HPU (rHPU) and its virtual HPUs (vHPUs) and the results show that the solution can make remarkable effectiveness.

On the Role of Negative Precedent in Legal Outcome Prediction

Every legal case sets a precedent by developing the law in one of the following two ways. It either expands its scope, in which case it sets positive precedent, or it narrows it down, in which case

The Right to be an Exception in Data-Driven Decision-Making

Data-driven assessments estimate a target—such as the likelihood an individual will recidivate or commit welfare fraud—by pattern matching against historical data. There are, however, limitations to

Scientific Thinking About Legal Truth

In the criminal process, the fact finders assess the validity of impressions reported by witnesses based on their perceptions and determine what has happened in reality. However, these impressions

Maximizing team synergy in AI-related interdisciplinary groups: an interdisciplinary-by-design iterative methodology

In this paper, we propose a methodology to maximize the benefits of interdisciplinary cooperation in AI research groups. Firstly, we build the case for the importance of interdisciplinarity in



Estimating Gender Disparities in Federal Criminal Cases

This paper assesses and decomposes gender disparities in federal criminal cases. It finds large unexplained gaps favoring women throughout the sentence length distribution, conditional on arrest

See also Carissa Byrne Hessick, Race and Gender as Explicit Sentencing Factors, 14

  • J. Gender Race & Just
  • 2000

United States v. Maples, 501 F.2d

    which the court later suggested required an "exceedingly persuasive justification

    • 1976