… the role of training data in equitable algorithm design. A reasonable default is to train algorithms
on data that are representative of the population to which the algorithms will be applied (…

… many meaningful interventions toward equitable algorithmic systems are non-technical.
Where many efforts consider the design and development of a specific algorithm or system, our …

… Machine learning algorithms increasingly affect both our online … with a general overview of
algorithmic fairness, and then … of what it means for an algorithm to be fair. Unfortunately, as we …

… It is also important to keep in mind that an equitable algorithm must be derived from a …
inclusive design principles, algorithm auditing process and cross-functional work teams. Algorithm …

… for a More Equitable Co-Design Process We recognize that utilizing the traditional co-design …
Using an age-appropriate mental model of algorithmic decision-making as our guide, our …

… analysis and a deeper understanding of algorithms. The numerical examples throughout …
used as part of a course on communication network design or on modeling and optimization …

… algorithmic systems that lead to inequitable consequences and instead support the design
of algorithmic … and cultivate, what I call, affirmative algorithmic futures. To that end, this paper …

… The goal of this work is to design a dynamic fee schedule for the marketplace that is
equitable and profitable to all traders while being profitable to the marketplace at the same time (…

… This paper reviews algorithmic or artificial intelligence (AI) … fiction, speculative and liberatory
design. It discusses the causes of … Design thinking for a more equitable future must include a …

… leaders involved in algorithm design, development… algorithm to improve and advance
equitable outcomes or is the primary goal to maximize profit?). Additionally, if a particular algorithm …