information designPareto frontierAlgorithms are widely used to guide high-stakes decisions, from medical recommen- dations to loan approvals. Designers are increasingly optimizing not only forLiang, AnnieLu, JayMu, XiaoshengSocial Science Electronic Publishing...
Such regions give rise to confusion matrices that are defined by greater degrees of freedom, potentially making it possible to address complicated trade-offs between accuracy, fairness, etc., as well as to accommodate predictions subject to politi- cal or social constraints. Providing this ...
Keywords and search terms included “organ allocation scores”, “continuous distribution”, “predict* AND organ allocation”, “fairness AND organ allocation”, “allocation policy equity”, “liver allocation AND MELD”, “Lung Allocation Score”, “Heart Tier System”, “donor heart allocation”...
In The Ethical Algorithm, two University of Pennsylvania professors explain how social values such as fairness and privacy can be designed into machines.
The machine learning community has become alert to the ways that predictive algorithms can inadvertently introduce unfairness in decision-making. Herein, we discuss how concepts of algorithmic fairness might apply in healthcare, where predictive algorith
The queuing mechanism inherent to order books, based on the first-in-first-out principle to structure transactions, was thought to foster more efficiency, fairness and equality compared to prior, “human”, infrastructures. On the other hand, it also enabled new forms of harmful practices such ...
Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies BMJ, 368 (2020), p. m689 CrossrefView in ScopusGoogle Scholar 3 J Wiens, S Saria, M Sendak, et al. Do no harm: a roadmap for responsible machine learning for hea...
Most ML techniques still focus on traditional objectives of maximising accuracy and performance with respect to the known value of \(Y\). Merely adding constraints to this optimisation in the form of technical metrics creates tensions between fairness and accuracy. This is often referred to as the...
fairness, accountability, and explainability. Shin (2021c) additionally showed that, after a chatbot gave recommendations to participants, perceived algorithmic trust had a positive effect on both the performance rating of algorithmic accuracy and the perceived quality of personalization. Experimental researc...
We have chosen to focus our theorizing around accuracy, however, because we are interested in determinants of procedural fairness in various organizational contexts, where group identity may be either strong or weak. With that said, it is likely that, in contexts implicating people’s livelihood (...