Ethical Considerations When Deploying AI Processes
You must consider the issues of bias and outcome validity — otherwise, practical vulnerabilities lurk in the deep.
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You must consider the issues of bias and outcome validity — otherwise, practical vulnerabilities lurk in the deep.
If any profession values the significance of one’s choice of words, it is the legal profession. We know that slight nuances in the meanings of words can result in a deluge of complications. Words have power. The use of male dominated language has historically been accepted, normalised and expected, with the result that most people are completely oblivious or indifferent to the fact that contracts contain gendered language. It is generally the default position when the gender is unknown. For instance, references to the ‘chairman’ might not even be perceived to be male.&n...
What impact has enforced isolation and social distancing had on how physical experiences are designed? We take a look as part of The Drum’s Deep Dive into The New Customer Experience Economy.
This article introduces algorithmic bias in machine learning (ML) based marketing models. Although the dramatic growth of algorithmic decision making continues to gain momentum in marketing, research in this stream is still inadequate despite the devastating, asymmetric and oppressive impacts of algorithmic bias on various customer groups. To fill this void, this study presents a framework identifying the sources of algorithmic bias in marketing, drawing on the microfoundations of dynamic capability. Using a systematic literature review and in-depth interviews of ML professionals, the findings...
BT's Nicola Millard and CWIT's Liana Tomescu talk about the impact creativity and the arts can have on inspiring the next generation of STEM.