Read the following passage regarding the debate over algorithmic accountability in criminal justice:
The integration of algorithmic risk assessments into criminal sentencing has provoked a multifaceted debate among legal scholars. Proponents, such as conservative jurist Eleanor Vance, argue that algorithms, by adhering strictly to empirical data, eliminate the subconscious biases that have long plagued human judges, thereby serving as an objective baseline for sentencing. Conversely, critical race theorists contend that these systems are fundamentally flawed because they are trained on historical arrest data that reflects generations of over-policing in minority communities. According to this group, algorithms merely launder human prejudice under the guise of mathematical neutrality. Attempting to chart a middle course, legal philosopher David Chen posits that the primary issue is not the use of algorithms per se, but rather their proprietary nature; Chen insists that algorithmic accountability can only be achieved if the source code is subject to open-source peer review by independent auditors. Meanwhile, the author of this passage maintains that all these perspectives overlook the core constitutional issue: delegating sentencing power to a machine, regardless of its accuracy or transparency, inherently violates a defendant's right to individualized due process.
Based on the passage, match each of the following theoretical positions or claims to the specific scholar, group, or perspective to which the passage attributes it.
- Algorithms provide an impartial standard that mitigates the influence of human prejudice.Eleanor Vance
- The fundamental problem with algorithmic sentencing lies in the opacity of privately owned software.David Chen
- The reliance on historical data in risk assessment tools perpetuates and obscures systemic discrimination.Critical race theorists
- The mechanical determination of sentences inherently infringes upon legal rights to personalized adjudication.The author of the passage