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Sep 25, 2020 · First, it presents a variety of marketing examples in which algorithmic bias may occur. The examples are organized around the 4 P's of marketing - promotion, price, place and product-characterizing the marketing decision that generates the bias and highlighting the consequences of such a bias.
The authors provide a tool for revamping the decision process at the boundaries between functions and describe how Target, Nordstrom, and other large companies have identified important decisions...
Oct 21, 2019 · The key to addressing these disparities is to look at the small, daily decisions that are made in your workplace, and to ensure that those decisions are equitable. If your company is like most ...
Marketing guide published by the IAB AI Standards Working Group in March 2021. What follows are the key participants in the bias detection and mitigation process, and an understanding of their roles and responsibilities.
May 1, 2022 · Algorithmic design bias consisting of data, model, or method bias will be significantly more likely to influence marketing strategies in executing ML-based marketing decisions, such as segmentation, targeting and positioning.
Oct 1, 2023 · Recognizes eight different machine learning biases, including social bias, measurement bias, representation bias, label bias, algorithmic bias, evaluation bias, deployment bias, and feedback bias as well as offers a number of mitigation methods in order to handle ML biases in the marketing context.
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What is anchoring bias? Anchoring bias, or anchor bias, describes how we tend to rely too heavily on the first piece of information we get. When we are making a decision, our first reference point often acts as an “anchor.”
