2012. "Justice as Fairness in Planning Policy Making." International Planning Studies 17 (2): 147-162.McKay, S, M Murray and S Macintyre (2012), "Justice as Fairness in Planning Policy-Making", International Planning Studies, 17(2), pages 147-162....
Whenalgorithmsare now incorporated into a decision-making process, using predictions for decisions can simultaneously lead to consequences in multiple contexts. For example, applying the same algorithmic rationale across different domains might lead to outcome homogenization, which reinforces structural injusti...
In healthcare, the development and deployment of insufficiently fair systems of artificial intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models stratified across subpopulations have revealed inequalities in how patients are diagnosed, treated and billed. In this Perspec...
Does not indicate that best possible price has been received or paid, as the case may be; instead a fairness opinion indicates that the price is in a range of values indicated by the analyses, or above or below the range, as the case may be ...
We increasingly depend on a variety of data-driven algorithmic systems to assist us in many aspects of life. Search engines and recommender systems among o
'Fairness Constraint' refers to a set of restrictions specified in automated model checkers like SMV and SVE, which are assumed to hold throughout the model to ensure fairness in the system behavior, such as ensuring that each run must be infinite or granting resources infinitely often based on...
policy in a repetitive scheduling environment. Recall that in our example given in Section 2.3, the global total completion time was maximized under an optimal fair schedule. The natural question to ask is: what is the worst ratio between the optimal global policy and the optimal fair policy?
Research on fairness in machine learning (ML) has been largely focusing on individual and group fairness. With the adoption of ML-based technologies as ass
Attention to administrative process is of key importance in reconciling competing interests in environmental policy‐making and implementation. Acute wilderness preservation/logging conflict in recent years in British Columbia, Canada, has led the government to attach a political priority to the development...
Long-term fairness is an important factor of consideration in designing and deploying learning-based decision systems in high-stake decision-making contexts. Recent work has proposed the use of Markov Decision Processes (MDPs) to formulate decision-making with long-term fairness requirements in ...