CoC—Ch. 5, 168-184

Defending the freedom of the self

“to be oneself in the other.”

Can we freely use the spaces where we experience the world with others?

The Illusion of Autonomy through Self-Measurement

Data relations are being proposed as new ways to come to find out about oneself.

“Know thyself” to this device

Self tracking, goal setting, storing accomplishment data about oneself on remote servers, sharing on social media, discover the locations of self and others: enhance our experiences by collecting data about them.

Philosophical challenges to self-quantification

Who’s doing the self reflection? The individual or the data analyst in the feedback loop?

At what point do you lose the ability to self regulate?
At what point do we depend on the evaluations of others when we establish our self-evaluations?
	while it is the case that sense of self is developed in cooperation with others – – those others are supposed to be people that we know, people that we live with, people who are intimate to us. The “comparison sense of self” is developed in cooperation with one’s family and peers not with data analysts and machine learning. In fact, not even with the X number of “followers” or “friends” that we have on social media.

The personal data appropriation spectrum.

A lot of the verbiage that is used to justify data collection for social scientific research covers over actual practices and fails to account for mistakes, errors, bias, or intentional misuse. Nevertheless we have to recognize that broad data collection can sometimes be helpful with regard to human processes such as health management or traffic patterning.

Nevertheless, many data collection procedures related to health are extremely disconcerting. Passing along one's genetic code/identity markers just to amuse oneself is probably inadvisable. While there may be instances when learning about one’s DNA is crucial – – for example in cases when genetic patterns indicate the presence or likelihood of malformation or disease or when parentage is at issue – – in other instances, such as simply trying to find out what kind of heritage is in one’s family line, DNA testing is commercialized and unnecessary.

In Education:
In a 2014 report, Pearson Education employs the metaphor of a “digital ocean” to capture this new approach, which can record every “fleeting experience” of individuals for monitoring, processing, and evaluation. The costs of continuous surveillance are not even acknowledged here as a risk.

Pearson is BU’s primary partner in online education.
Let’s read the executive summary from this paper. 
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Impacts of the Digital Ocean on Education
Kristen E. DiCerbo & John T. Behrens
February 2014

Executive Summary

The devices and digital environments with which we interact are designed to record and store experiences, thereby creating a slowly rising ocean of digital data. We can imagine schools and individual learners using this “digital ocean” to inform decisions about learning. As learners learn, they are able to collect information about their activities and get feedback about what they know and can do. Learning can occur in formal and informal contexts, and data can be drawn from both. In the digital ocean, we would expect to see data from all types of activities and contexts used to create persistent learner profiles, which could then be used to recommend future activity.

Our new ability to record, store and process information from learners in numerous non-testing situations suggests a paradigm shift in assessment to include the following:

• focus on a broad range of attributes versus measuring narrowly defined knowledge and skills
• assessment from in vivo naturalistic tasks vs. via pre-made tests
• integration of data over activity and time as opposed to over singular events
• detailed tracking of context outside of testing situations
• dissolution of current distinctions such as “informal” vs. “formal” learning
• collection and permanence of learner profile data to make ongoing, intelligent recommendations.

The data of the digital ocean is not simply more data as we knew it in the pre-digital era. Several aspects of data generation, storage, transfer and use make the new data qualitatively different from that of the past. It is ubiquitous (coming from all manner of activity) and persistent, and it reflects social connection. However, the data itself is only a starting point that is necessary, but not sufficient to transform education - or any activity. Data is only a representation or symbol of what happens in the world.

In most contexts, the goal of data collection and analysis is to provide insight and inform decisions. In classrooms, the fundamental decision of the learning process is what the learner should do next. In the paper, we break this decision into a series of steps, beginning with an activity. Learner interactions with activities generate data that can be analysed for patterns. Such data lead to updates of the learner’s profile maintained by the teacher, parent, computer or learner themselves, which in turn informs subsequent decisions or recommendations. Performance in individual activities can often provide immediate feedback (“you forgot to carry the eight”) based on local pattern recognition, while performance over several activities can lead to profile updates, which can facilitate inferences about general performance (“you are good at multiplication”). Profiles can be used within an activity system (class, computer programme, etc.) or across systems, if persistence and process connection is planned. The shift toward the digital ocean opens up new possibilities for conceptualisation and action in the above process, particularly in the following ways.

Interaction
With technological advances, it is now possible for computers to score a much wider range of responses. This allows for the subsequent expansion of the types of activities that can be used to characterise the knowledge, skills, and attributes of learners and, hence, the forms of assessment we can allow.

Data
Technology provides us with the space to expand our thinking about evidence, which, here, is what we can collect from interactions between learners and learning material. Digital systems allow us to capture stream or trace data from learners’ interactions, which will expand our ability to understand learners’ processes when solving problems, not just their final products.

Pattern Seeking
Human and computer analysis of these new data types can uncover new patterns that may provide evidence about learning.

Immediate Feedback
Once information is gathered about an activity or ‘work product,’ and an interpretation is assigned to it, that information can be used to provide immediate feedback to learners and/or their teachers about their performance on that specific activity.

Learner Profiles
Having more data also helps us build better models of learners’ knowledge, skills, and attributes. The data helps us “tune” these models, ensuring that the relationships between what we observe from learners and the inferences we draw about their proficiencies are accurate
and valid.

Activity Recommendation
Data ultimately enables us to take a learner’s profile of knowledge, skills, and attributes and determine the best subsequent activity for that learner’s effort to meet a particular goal (for example, learning, motivation, or assessment).

While the digital ocean requires changes to technological systems and to some of our statistical and data analysis procedures, perhaps the biggest change required is a change in thinking. Categories of thinking and acting have often been based on the limits and artifacts of the pre-digital era. As we move forward in the age of the digital ocean, we must step back and consider not only new, specific technologies, but also new relationships to existing categories. Specifically, we will need to move:

From items in isolation to activity in context. Rather than thinking of a multitude of individual, isolated items, the digital ocean encourages us to think about integrated activity. From this perspective, rather than posing questions, activities request action.
• From assessment isolation to educational unification. The costs of collecting, analysing, and making inferences from data decrease with technological advances. This means that more learners and educators should be able to make use of standardised deployments of systems in everyday use. Such systems employ statistical and data-based tools to provide feedback on performance and understanding of themes relevant to classroom teaching and learning. The historic separation between learning and informal inference for classroom concerns can be left behind.
• From individual paradigm to social paradigm. As technology facilitates movement toward collecting information from more natural interactions, the social nature of everyday lives will become apparent in the data collected. While this will present technical challenges to assessment, it will also allow for more authentic experience
and a closer relationship between assessment tasks and life outside the classroom.

Many aspects of the story presented here are aspirational, and some are cautionary. However, many are based on existing experiences of educators and learners around the world, who, as digital natives, are moving forward in their embrace of digital technologies and who, in a few more years, will be unaware of any shift having taken place at all. For those of us who have emerged from the pre-digital era, the challenge is to move beyond the understanding of new technology as a new means to acquire old ends and to re-invent our conceptualisations to take advantage of a digital-first, data-first world.

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The links between continuous surveillance and the education of children are so deeply naturalized here that the panoptic notion of teachers using continuous real-time monitoring is presented as neither chilling nor threatening. On the contrary, it is a selling point, giving teachers “a full bird’s eye view of the entire classroom” (Impero Education), which enables them to “immediately intervene in a highly personalized way” (Blackboard). Data collection is imagined to “create a virtuous circle of real-time data that solves issues relating to student learners lacking necessary skills.”

what happens when the data is used in other ways? Sold into the data marketplace, aggregated with other information about the student, etc.

Legal battles for the self’s minimal integrity.

Our authors recognize that the term privacy is now highly problematic.
they do not want to abandon the term but they recognize that traditional senses of the term are passé. The problem of course is that our legal regime focuses on the term as it was once defined.

The historical legacy of privacy protection

Although the right to be left alone has been established in US law that privacy right has been left unprotected against incursions by new media corporations via almost unlimited amounts of data collection.

Even protections implied by the Constitution no longer stretch across commercialized  data collection activities. 

Reinvention of privacy law?

Examples in the EU and in the state of California suggest that revisions of law can challenge current corporate practices. However United States lawmakers are unwilling to adopt those practices.

It is not the case that massive data collection cannot be controlled it is the case that neither leaders more people appear to want to invoke controls. This is the state of being an American – – it is not the state of being human. People all over the globe resistant various ways while we insist the resistance is futile.

And of course regardless of what governments overseas want, American capitalism and commercialism wreaks havoc in their systems as well as in ours. Our new media companies are willing to pay tens of millions of dollars in fines rather than fully modify their data collection practices in companies overseas.

Privacy and the new contradictions of capitalism

Data collection and the new media environment has simply outstripped the ability of law to control or constrain it. Further, 

“practices of data colonialism are potentially eroding the very notion of the rational, reflexive, law-respecting human subject on which the legitimacy of law itself depends.”

Stands between Americans and Fascism or totalitarianism is a very thin line. One can easily bring to mind forces in our society that would like to be able to wield unlimited power. in previous heroes that power was either unavailable or was checked by normal political processes. It's possible today that circumstances could develop it would find neither traditional constraints nor everyday politics getting in the way of totalitarianism in this country.

Toward a larger vision

None of the ideals desired in today’s societies—their democratic status, their freedom, their health, or otherwise—make any sense without reference to an autonomous self in the minimal sense defended in this chapter.

Moving decisively away from individualistic notions of autonomy, freedom, and privacy, we can argue that the datafied social governance and incursions into the self’s minimal integrity discussed in part II of the book together constitute an environment that is toxic for human life.