Damn the users, full speed ahead!
https://www.sciencedirect.com/science/article/pii/S0167404821000511
A First Look into Users’ Perceptions of Facial Recognition in the Physical World
Facial recognition (FR) technology is being adopted in both private and public spheres for a wide range of reasons, from ensuring physical safety to providing personalized shopping experiences. It is not clear yet, though, how users perceive this emerging technology in terms of usefulness, risks, and comfort. We begin to address these questions in this paper. In particular, we conducted a vignette-based study with 314 participants on Amazon Mechanical Turk to investigate their perceptions of facial recognition in the physical world, based on thirty-five scenarios across eight different contexts of FR use. We found that users do not have a binary answer towards FR adoption. Rather, their perceptions are grounded in the specific contexts in which FR will be applied. The participants considered a broad range of factors, including control over facial data, the utility of FR, the trustworthiness of organizations using FR, and the location and surroundings of FR use to place the corresponding privacy risks in context. They weighed the privacy risks with the usability, security, and economic gain of FR use as they reported their perceptions. Participants also noted the reasons and rationals behind their perceptions of facial recognition, which let us conduct an in-depth analysis of their perceived benefits, concerns, and comfort with using this technology in various scenarios. Through this first systematic look into users’ perceptions of facial recognition in the physical world, we shed light on the tension between FR adoption and users’ concerns. Taken together, our findings have broad implications that advance the Privacy and Security community’s understanding of FR through the lens of users, where we presented guidelines for future research in these directions.
Questions come before answers, mostly.
https://www.jstor.org/stable/pdf/resrep28766.pdf
Questions about Facial Recognition
Concern over the misuse of facial recognition technology is one of the latest fears over technological change that have included Frankenfish, mass surveillance, chip implants, and artificial intelligence (AI). As with these earlier examples, there is both confusion and exaggeration over potential risks. This is exacerbated by the lack of adequate privacy protections in the United States and the rapid pace of technological change, which can create a sense of uncertainty about risk. Broader social and political concerns over race and policing also shape the debate on facial recognition.
We reviewed the most salient of these concerns for accuracy and for their implications for policymaking, and came to several conclusions. Our first conclusion is that to reduce concerns about facial recognition, Congress needs to pass effective privacy legislation to govern digital technologies. Facial recognition requires access to personally identifiable information (PII). The United States already has extensive rules governing law enforcement access to data and collection of evidence. These need to be extended and, in some instances, modified for new technologies such as facial recognition. But rules for facial recognition do not need to wait for national privacy legislation, since guidelines can be based on existing legal authorities.
A second conclusion is that improvements in facial recognition technology, especially in how algorithms are developed and trained, will continue to reduce the risks of error and bias. Like all new technologies, continued improvement reduces risk, and concerns based on how facial recognition technology worked even a few years ago are now out of date. To help improve public understanding of facial recognition, we have reviewed the following questions to address some of the leading concerns.
For the “We can, therefore we must” crowd.
http://www.scrd.eu/index.php/scrd/article/view/94
Private information in public spaces: Facial recognition in the times of smart urban governance
… This paper aims to discuss the new dilemmas that arrive with the growth of surveillance technologies applied to urban centers and the increasing participation of the private sector in the processing of data whose origin lies within public services.
Using AI.
Building AI Leadership Brain Trust: Why Is Data Analytics Literacy Key To AI Competency Development?
This blog is a continuation of the Building AI Leadership Brain Trust Blog Series which targets board directors and CEO’s to accelerate their duty of care to develop stronger skills and competencies in AI in order to ensure their AI programs achieve sustaining results.
In this blog series, I have identified forty skill domains in an AI Leadership Brain Trust Framework to guide board directors and CEO’s to ensure they can develop and accelerate their investments in successful AI initiatives. You can see the full roster of the forty leadership Brain Trust skills in my first blog.
In other words, read more SciFi!
https://bmcmedethics.biomedcentral.com/articles/10.1186/s12910-021-00586-7
Frankenstein; or, the modern Prometheus: a classic novel to stimulate the analysis of complex contemporary issues in biomedical sciences
Advances in biomedicine can substantially change human life. However, progress is not always followed by ethical reflection on its consequences or scientists’ responsibility for their creations. The humanities can help health sciences students learn to critically analyse these issues; in particular, literature can aid discussions about ethical principles in biomedical research. Mary Shelley’s Frankenstein; or, the modern Prometheus (1818) is an example of a classic novel presenting complex scenarios that could be used to stimulate discussion.
Two professions/age groups/skillsets, divided by a common language.
https://dilbert.com/strip/2021-02-28
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