Author Archives: Achim Koh

surveillance tools

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Hi, I am still thinking of a good way to frame the questions for the coming week, but wanted to lay a few points out in the meantime.

First, a quick recap of the Edge Tools event. For convenience I interpret the term as applications of digital methodologies (data mining, storytelling, etc) to social sciences research and beyond, in “an increasingly complex and connected world” characterized by big data. The topics addressed included:

  • monitoring social media data for marketing
  • applying multiple data sources and flexible human organization to military operations
  • locating potential national security threats by data mining children’s stories, collected using a mobile survey platform
  • analyzing diverse forms of information ranging from social media to humanitarian information in order to track the activities of military forces in Syria
  • crowdfunding a successful game through data analysis of successful precedents and storytelling

That all speakers talked about either military or marketing purposes speak to the general orientation of this event. Not surprising since the military and the economic sector have an important role in the history of computation, to say the least. Underlying all of these examples is the current technological landscape where the world becomes data, both because everything seems to be represented as data and tools are developed to be able to deal with the data. What flows alongside this current is the belief that this change offers the potential for a more profound, direct and wider understanding and/or interaction with the world.

Which is exactly what surveillance is about. The extensive communications monitoring by the NSA is an attempt to better handle the soaring amount of information, much as search engines allow one to navigate the web. Bilton describes how the availability of data and tools for gathering it is a given nowadays, quoting Wizner’s claim that “tracking technologies have outpaced democratic controls.” In addition to technical possibility, the industrial structure also facilitates surveillance. Wu’s article provides historic examples of the cooperation between the government and corporate monopolies, which was also repeated in the NSA case. Both articles point to the idea that the current situation is making it very easy to monitor people, be it the technological development or the industrial structure. And as Grimmelman lays out using examples of Google search, the design, use and regulation of a system, by companies, users and governments, are not neutral; all activities have political implications. When the design of the systems we use move more and more towards keeping our data on someone else’s hard drive (the cloud), there is yet another tradeoff between convenience of use and risk of surveillance.

(Please help improve this post)

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Wikipedia’s three core content policies (NPOV, V, NOR) demonstrate what type of knowledge platform this is; an aggregator of existing knowledge. (Reagle) By consequence, this leads to the question of how to deal with existing bias feeding into the knowledge base, as portrayed by the readings ((Hill), (American Women Novelists)) and well pointed out by Sakina. Is not neutrality an obstacle to intervention when the playing field is unlevel, for example?

But to be fair, these norms which govern the collective process of Wikipedia are what distinguishes it from different types of collaboration like, say, Anonymous. (Collaborative Futures) What this specific kind of collaboration is is also captured in DGG’s comment that “just as we are not a place for original scholarship, or original fiction, we are not a place of original participatory art” on the discussion page regarding David Horvitz’s attempt to have his page deleted. I imagine these are codes which developed in the collective effort to maintain the stance of a democratic platform, and I should say it has done a good job at keeping that position on the internet, which is, you know, the internet. Scrolling through the CfD discussion on American Woman Novelists, however irritated I may be by some of what is written there, I am also amazed at the fact that there actually is a discussion which led to somewhere.

While achieving productive discussion on the internet is not something which happens exclusively in Wikipedia, I feel safe in saying it is neither something which happens in most big platforms for gathering people. What contributes to making Wikipedia a different platform than others; the big and small efforts from many people, the platform’s technical implementation, the visions which are promoted in and outside the community, broader social contexts? While the answer will be something similar to all of the above, one thing I am curious about is how the practice in Wikipedia differs from language to language.

Also, the assumption of “good faith” resonates with the democratic vision of collaboration between modern individuals, or Western liberal subjects—a term we examined through Haraway, and which kanarinka also points at. Among the many possible ways to think about this, I would like to ask what it means to assume good faith, with regards to automated processes of knowledge making. This also could mean a lot of things, but what I am picturing is the following. Even now there are many bots which are active in Wikipedia, though I imagine most are limited to trivial tasks, and for good reasons. However, as computer science fields like natural language processing keep growing and terms like automated journalism are moving from speculation to real things, I find it not too hard to imagine a piece of software which could do wikipedia edits in a more author-like way. Wikipedia policies like Verifiability and No Original Research help in making the editing process more standardized, which would also help in automating it. But what happens once bot-edits become as reliable as human-made edits in terms of accuracy? Do the bots pass the WikiTuring test and become part of the community? Can a script prove its not having Conflict of Interest? Or, in a less dramatic and more likely picture, editors might want to employ those scripts (just as the bots which are now active) to contribute more to the knowledge aggregation process which is Wikipedia. I wonder if and how the community’s social norms will change under such circumstances.

[citation needed]

Technology, Privacy, and the Future of Education @NYU Steinhardt

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I was able to attend the second half of this event and I thought I might share some points made by the panels.

Natasha Singer, Reporter, The New York Times; Fellow, Data & Society

4K+(?) apps are in use in K-12 education. Three cases of apps she investigated:

  • Reward/penalty system (ClassDojo)
    • The reward / penalties can be arbitrary
  • Attendance app which I forgot the name
    • This app provides an interface to the teacher, who can swipe the names in the class roster to the left (absent) or to the right (tardy; the teacher can input how late the student was). The system will then send a text to the parent.
    • The particular school which uses this app is using it alongside other measures to increase attendance such as mentorship, so it’s not like it’s out of the blue. Still, the question stands of what it means to take out of the equation direct communication to the student (as far as the app is concerned); also, the data points (app usage, attendance, graduation rate) do not show the students’ irritation
  • The third app provides students with micro-scholarships—from 10+ USD to 1000+ USD—which can be obtained by various achievements such as getting an A (or B) in a course, doing some sports or other activities, taking AP courses, etc. If I understood correctly, the app does not actually give money away but rather serves as a calculator which translates a student’s achievement into how much money that achievement might be worth in terms of scholarship.
    • One of the students who gave positive feedback said that the app is nice because it does not try to know anything about their parent’s information.
    • What is the implication of encouraging students through such a direct promise of monetary reward?

Brett Frischmann, Professor, Cardozo Law School

  • Is working on a book on what it means to be human in this technological change (w/ Sellinger)
  • The story of mandatory Fitbit for undergraduate students
    • Criticism ranged from the creepiness of surveillance to privacy issues like the lack of consent. Advocacy was also present, especially the one which noted that this is just an extension of what the school has always been doing (tracking students’ physical status)
    • Looking at this issue as a matter of consent or opt-out (which the school technically did provide), or that the argument that this is not different from the records students were providing to the school for many years, show the limits of the current paradigm.
    • Because it diverts the attention from important issues such as self-reflection, judgement and human involvement – all being dismissed in automatic collection (student’s active decision, autonomy, is not trivial) – students become passive objects in data collection.
    • Surveillance creep works both ways: gradual increase of the surveilling activity, and also of the surveilled people being accustomed to it)
    • It’s not just universities, elementary school programs are being funded

Mitchell Stevens, Associate Professor of Education and Director of Data Policy in the Office of the Vice Provost for Teaching and Learning, Stanford University

  • The mid-20th century U.S. has built something which became the best higher education system in the world during 25 years or so. Although federal support was crucial in the establishment of research universities, these institutions were also given enough independence to effectively act as non-profit organizations, and assume agency from the “national interest”, although the latter was a big reasoning for providing federal support in the first place.
  • However, recent years are seeing a renegotiation of this cold war era-based relationship towards increased influence of private capital, partly in the form of digital education. In short, business and higher ed are becoming increasingly intimate.
  • This is in a way a continuation of what rich people like Ford, Carnegie and Mellon did in the past: achieving a huge success in their industry by using scientific management and applying the same method in education—something the Gates are doing, for instance.
  • However, as the status of universities as non-profit has been in decline along with the federal system providing capital, the relationship between the government, educational institutions and businesses are changing; governance is yet to be determined.

Elana Zeide, Research Fellow, New York University; Affiliate, Data & Society

  • Importance of local context in setting rules
  • There has been rising attention towards student privacy
  • Typical use of notion ‘privacy’ in lawmaking and parents organization, for example, focus more on the access/disclosure of data, than the usage of it. But the latter is becoming more and more important.
  • Also, in the age of big data, conventional expressions such as limiting something to “educational purposes” do not mean the same thing anymore
    • Ex) think face recognition- not being tagged is not the same level of privacy as before

Q&A, Comments

  • The ubiquity of evaluation and data collection has a substantial impact in people’s behavior; students can become more conforming to the majority’s norm, without even noticing it. Knowing more may not be for the best.
  • The tools may seem neutral, but in practice they incorporate power relations. Also, many tools now equal businesses
  • Formative assessment, summative assessment, credentialing used to be separate things. Now not only is the separation blurred, but also the evaluation is managed by third party for-profits
  • Are there studies on the effect of such classroom technologies on brain development?
  • The “science” of teaching. Pedagogy itself becoming an engineering of the classroom— Need to define what success is in education
  • Automation bias, or the tendency to act as the machine tells people to
  • Education as citizen-making (which according to Stevens is what the U.S. had systemized during the 20C) vs worker-raising
  • The right to be off (disconnected)

👋

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So happy to meet you all (again for most of you)! This is my hands-on semester where all of my courses involve getting my hands dirty with some type of tech/code stuff, and I already feel emotionally safer knowing that I will be around you folks while I suffer.

I have two things in mind right now. Subject-wise, my main interest is the history of internet and its relation with the shaping of contemporary society, and how to look at various dimensions including but not limited to education/knowledge production, gender, governmental policies, disasters, etc. while navigating both in the U.S. and South Korean context.

The other thing I am pondering about is the increasingly popular field of machine learning, and my relation with that field. While I do sense industrial hype being built around it, the increasing access to the computational methods seems to offer some educational benefit and I would be happy to think about and work on ways to harness it in humanities research. I’ll try to elaborate on this in another post.