Child Data Citizen by Veronica Barassi

Author:Veronica Barassi
Language: eng
Format: epub
Publisher: MIT Press

That companies can gather all these different forms of data implies not only that they have the potential to harness highly contextual data from children but also to integrate this data with biometric information. The privacy implications of technologies that can integrate context and biometrics are immense.

CHILDREN’S HOME LIFE DATA: BETWEEN BIOMETRICS AND CONTEXT

One of the critical questions that I kept asking myself when I was trying to navigate the data policy of Amazon Household was whether home hub companies were able to map all this home life data to voice prints and therefore build unique ID profiles of children. A voice print, like a face scan or fingerprint, is a uniquely identifiable piece of data. Once that data is linked to an individual it can be used to infer many things about them, and these inferences can follow children across a lifetime (Barassi and Scanlon 2019).

So far there is evidence that companies are developing technologies to infer sensitive information about users on the basis of their voice data. As mentioned, Amazon was recently issued a patent (Jin and Wang 2018) for “Voice-Based Determination of Physical and Emotional Characteristics of Users,” which will enable the company to infer from voice patterns such as sniffles, crying, and other abnormal changes whether the user is sick or has an emotional issue, and then use that data for targeted ads. The question at heart for children’s privacy is whether a company like Amazon can effectively recognize children through their voice prints, infer sensitive data about them, and use this data to profile them. Unfortunately, we do not have an answer to this because privacy policies and regulations do not address the problem of aggregated profiles or biometric data.

Yet what is becoming increasingly clearer is that through the aggregation of adult and children’s profiles and the collection of household, family, and situational data, home hubs can gather and harness highly contextual data of children. The following examples are particularly illustrative (although a bit dated) of the ways in which developers are thinking about context:

In 2015, Wulfeck one of the developers of the AI toy Hello Barbie mentioned in an interview on the New York Times that: “[Hello Barbie] should always know that you have two moms and that your grandma died, so don’t bring that up, and that your favorite color is blue, and that you want to be a veterinarian when you grow up.” (Wulfeck, ToyTalk in Vlahos 2015)

In 2016 also, Zuckerberg wrote about the importance of context in his post on home automation. “Understanding context is important for any AI. For example, when I tell it to turn the AC up in “my office,” that means something completely different from when Priscilla tells it the exact same thing. That one caused some issues! Or, for example, when you ask it to make the lights dimmer or to play a song without specifying a room, it needs to know where you are or it might end up blasting music in Max’s room when we really need her to take a nap.

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