Unlocking the Black Box of Wearable Intelligence: Ethical Considerations and Social Impact

Abstract

Computational intelligence is making its way into a variety of popular consumer products, including wearable physiological monitors such as activity trackers and sleep trackers. Such products are very convenient for the user, but this convenience is the result of a trade-off that has ethical implications, since in almost all cases it denies the user access to their own raw data underlying the easy-to-understand analyses that the products generate for them. One problem with this is that the user is not made aware of the uncertainty of the conclusions or analyses drawn from the data; another is that it is difficult for the user to reuse his or her data in other contexts, such as to combine data from multiple sources. Even if the user did have full control of the data, this would only solve part of the problem, because most people do not have the special skills required to analyze such data. This overall problem could be solved through collaboration between the data owner and a data analysis expert, though this again introduces further problems, notably that of preserving the data owner's privacy. In this paper we analyze the aforementioned issues pertaining to the ethics of wearable intelligence, propose possible approaches to handling them, and discuss the potential social impact of the technology if the issues can be successfully overcome.

Assessing the Accuracy of Popular Commercial Technologies That Measure Resting Heart Rate and Heart Rate Variability

“…These algorithms are rarely disseminated to consumers or tested by independent researchers (De Arriba-Pérez et al, 2016 ). The result is a black box effect for both parties, leaving everyone, except for the manufacturers, unaware as to how the physiological metrics are processed (Tuovinen and Smeaton, 2019 ).…”

A Domain Ontology and Software Platform for Collaborative Personal Data Analytics

“…Trading personal data for access to services is one example of how individuals can benefit from their own personal data, but it is not the only option. With the rising popularity of self-tracking products, an increasing number of people have access to a steadily accumulating database of physiological data about themselves, and this data is potentially valuable to them, although there are problems arising from uncertainties concerning the accuracy of the data and limitations concerning the ability of the people to control it [18].…”

Remote Collaborative Knowledge Discovery for Better Understanding of Self-tracking Data

“…These products enable a user to measure and log phenomena that are relevant to their health and wellbeing, such as physical activity and sleep. Even relatively inexpensive wearable products generate a diverse range of outputs and present them in an engaging and user-friendly way, so it is not surprising that such self-tracking products are gaining popularity, even though there are issues concerning their accuracy and the ability of the users to control their own data [1].…”