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APIs: a Human Social Interface

Jay Cousin’s conceptualises Personal APIs as Social APIs. Put simply, a Social API is a means of creating an interface of yourself for organisations and groups. In his blog, his conceived Social API is a list of common responses to selected topics (like a FAQ), detailing his preferences for email length to comfort food. Cousin’s reasons that this presentation was conceived around the idea that humans have an interface problem. “I find this notion of Human as software interesting, I would like to make my own behavioural code open source, which could also make memetic and behavioural replication easier.”

The conception of a Social API as open source behavioural code suggests that the aggregation of personal data could assist in social interactions with the individual. In Naveen’s commentary on his own API, he conceives his project as a virtual me. The virtual me is defined by all published quantifiable data publicly available. The aggregation of data from multiple platforms would produce the quantified self. So, if the human is defined as software then the quantified self is an API for social and personal usage.

The applications of a Social API is easy to dismiss. Take for example Jehiah Czebotar’s 6 year-running annual report which details e.g. his coffee and travel habits. Its presentation, while beautiful, doesn’t inform much about Czebotar beyond his questionable habit of drinking coffee. In fact, the data’s limitations brought Czebotar to the defence of comments questioning his priorities of work over family, where Czebotar stated this report did not cover his personal life. Czebotar’s quantified self is arguable a misrepresentation of his self. But Czebotar argues that the representation “is a way to learn about my year (not directly to change my actions)”.

Like Czebotar, Stephen Wolfram describes the act of quantifying oneself is “an effort at ‘self awareness’”. However, Wolfram’s commentary on his own extensive data collection highlights the potential for finding nuance and stories from the anomalies in data. “Some of it will focus on large-scale trends, some of it on identifying specific events or anomalies, and some of it on extracting “stories” from personal data.” In regards to Czebotar’s data, an anomaly in his data that showed a dramatic shift in coffee preference was due to an office move.

Commentary lends to the potential benefits of experts, in research or health fields, examining personal data to provide another layer of commentary. “As personal analytics develops, it’s going to give us a whole new dimension to experiencing our lives”. This sort of tracking leads to human life archiving, I suppose a more elaborate and detailed data capturing that isn’t necessary for a simple Personal API. But the quantification of data can lead to the ability of discoverability. For example: Cousin’s ponders over the potential for dating sites;  access to doctors or insurance companies; and Brian Proffitts suggests, the management of online communication could be prioritised on relationships. These are all practical applications of a Social API.

My interest is in the extraction of stories from anomalies within personal data, as it connects me to my exploration of narrative practice within the education institution.  I was informed recently that informal opportunities for feedback at UOW far outweigh formal opportunities. Feedback is sent through set up streams 360 – 840 times a year, versus 200,000 informal conversations through student service team members (this figures discounts other potential informal interactions). Imagine if every student had a Social API that was setup within a service-orientated architecture, where Student Central microservices were carried out by chat bots (or elevated to real personnel if needed). All informal interactions, anonymous unless a Student gave access to their API, would be stored and analysed. The discoverability of health, mental health, study habits, etc. could be explored and used to assist in engaging with a student. Anomalies in data could signal redflags that indicate faculty should engage in a narrative with affected students.

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