Alexa, in you, I trust! Fairness and Interpretability Issues in E-commerce Search through Smart Speakers
Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh, Animesh, Mukherjee, Krishna P. Gummadi

TL;DR
This study examines fairness and interpretability issues in voice-assisted e-commerce search, revealing discrepancies between user understanding, product relevance, and user preferences, raising concerns about trustworthiness of voice assistants like Alexa.
Contribution
It provides empirical evidence on fairness and interpretability challenges in voice-based e-commerce search, highlighting user perception gaps and relevance mismatches.
Findings
81% users interpret 'top result' differently from Alexa
68% of Alexa's chosen products are less relevant than top desktop results
73% of users prefer desktop top results over Alexa's choices
Abstract
In traditional (desktop) e-commerce search, a customer issues a specific query and the system returns a ranked list of products in order of relevance to the query. An increasingly popular alternative in e-commerce search is to issue a voice-query to a smart speaker (e.g., Amazon Echo) powered by a voice assistant (VA, e.g., Alexa). In this situation, the VA usually spells out the details of only one product, an explanation citing the reason for its selection, and a default action of adding the product to the customer's cart. This reduced autonomy of the customer in the choice of a product during voice-search makes it necessary for a VA to be far more responsible and trustworthy in its explanation and default action. In this paper, we ask whether the explanation presented for a product selection by the Alexa VA installed on an Amazon Echo device is consistent with human understanding…
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Taxonomy
TopicsEthics and Social Impacts of AI · Mobile Crowdsensing and Crowdsourcing · Explainable Artificial Intelligence (XAI)
