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Autocomplete Final
- 1. KYLE RENTSCHLER PATRICK DAVISON Values Embodied in Info and Communications Technology - Spring 2011
- 4. TAB COMPLETION -> AUTOCOMPLETION
- 13. 1. NATURALIZATION - 2. CLOSED ALGORITHM
- 25. WHY?
- 26. CAN’T ANALYZE IN THE FUTURE WITHOUT A DATABASE NOW
- 27. PUTTING IT ONLINE MAKES IT ACCESSIBLE TO OTHERS
- 28. MIGHT BE THE ONLY WAY TO GLEAN THE CLOSED ALGORITHM
- 29. ACCESSIBILITY
- 30. FLEXIBILITY
- 31. VISIBILITY
- 32. RELEVANT SOCIAL GROUPS Scholars, The Public, Developers, Journalists, Educators, Marketers
- 33. SCHOLARS
- 34. THE PUBLIC
- 35. DEVELOPERS
- 37. human welfare, ownership/property, privacy, freedom from bias, universal usability, trust, autonomy, informed consent, accountability, courtesy, identity, calmness, environmental sustainability
- 38. human welfare, ownership/property, privacy, freedom from bias, universal usability, trust, autonomy, informed consent, accountability, courtesy, identity, calmness, environmental sustainability
- 39. human welfare, ownership/property, privacy, freedom from bias, universal usability, trust, autonomy, informed consent, accountability, courtesy, identity, calmness, environmental sustainability...reflection?
Editor's Notes
- Hello.\n
- P: So - the world in general is not COMPLETELY ignorant about the vagueries of autocomplete...consider: moderately popular website and now book: Whoogles...\n
- K: Like Patrick, some of us (accusatory glance at Luke) might be familiar with the censorship of sexy words in autocomplete.  Indeed, the autocomplete implemented in the search bars of many popular websites seems to refuse autocompleting words that are sexually lewd or offensive.  Here, it is worth mentioning that censorship of any given word or phrase has side-effects other than perpetuating questionable ideologies. For example, though we don’t expect many users to need autocomplete to search for Nixon’s nickname or large, long-billed, blue-footed birds, there is an obvious tension in the unintended censorship of homonyms. These sort of seemingly inconsequential side-effects of censorship are worth mentioning insofar as they help expose how small changes in autocomplete have the potential to alter our perception of cyberspace and change our browsing experience.\n
- P: Historically, autocompletion can be most closely linked to “tab-completion” which allows users typing in command line interfaces to have their computer finish commands after having typed only a few letters, and then hitting tab. However, the specific flavor of auto-complete that we are interested in investigating is that which resides in internet connected search bars. \n
- P: The differences between a tab completion and auto-completion are significant. We’d like to highlight three different ways:\n
- P: First, when you’re completing a command, you’re always completing something known. When you’re constructing a search query, it’s often the case that the ideal query is unknown.\n
- P: Second, the process by which tab-completion works is pretty transparent, compared to autocompletions which are often run by proprietary commercial software.\n
- P: Third, while tab-completion is local and personal, auto-completion is networked, aggregated, and public.\n
- K: One goal of our project is to unveil autocorrect as a technology that has become normalized.  Throughout this project, we talked a lot about normalization... so much so that conversing about normalization actually became a normalized experience.  At some point, though, we recognized that autocorrect is only one entry in a massive array of web tech that people engage with in a particularly uncritical way.\n
- K: Search Results (google vs bing)\n
- K: Twitter trends (bieber vs wikileaks)\n
- K: Facebook Friends (random vs intimacy)]\n
- K: There is a two-part danger indicated by these examples. The first is that of normalization - in all three of these cases we can see users questioning the underlying algorithmic determination of their experiences, but then, how many more are NOT pursuing this same questioning? Secondly, the act of questioning on the part of these users makes it clear that really, because the algorithms in question are proprietary and unadvertised that really only educated speculation is possible, rather than true transparency.\n
- P: So, for the purposes of our particular project, we’ve limited our investigation of autocomplete to Amazon.com For two reasons: 1. we believe that the explicit commercial nature of the site is bound to have “value” rich implications, and 2. since it’s perceived ostensibly as a store (and not a search engine) it’s been subjected to far less critical scrutiny than something like Google.\n
- P: With a little bit of code, we’re able to piggyback on the slightly unorthodox manner in which Amazon delivers their own search auto-complete suggestions from one machine to another. \n
- P: So we simply “enter” each letter of the alphabet, and then document the 10 suggestions that come back from amazon.\n
- P: Then we’re able to correlate that data in order to get stats for everything that’s been suggested. So we know how long something has been in the “top ten.”\n\n\n
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- KYLE DOES THIS\n
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- P: In addition to essentially shoving snapshots of Amazon’s past into a digital mattress, the script also has a tiny front end that allows both us (and theoretically other users) to search for information and generate different types of visualizations. (mentionworking with Hock he’s a good guy)\n
- K: So why do this you might be wondering?\n
- K: First, there is a value in databasing the past for future research.  If the present is never properly logged, it won’t be accessible to anybody in the future who might use this information for projects or analyses of their own.\n
- K: There is also value in the online database in that it allows for a broad audience to access it.  Again, this audience might do something with it, or just engage with it in a hopefully reflective manner.\n
- K: Because the algorithm that dictates the behavior of Amazon autocorrect is locked behind closed doors, we have to rely on inference to get closer and closer to discovering the algorithm.  Having a database of this size allows for us to more accurately glean that algorithm by providing an accessible but large quantity of information.\n
- P: As we’ve said before, we want our database to be accessible to the general public, and visualizing data which might otherwise seem complex and crazy makes it infinitely more accessible.\n
- P: By affording a wide variety of options in the representation of the data, we hope to embed our database with flexibility.  In other words, we borrowed from reflective design, and decided we wanted to make a database that was just as customizable as Amazon’s autocorrect isn’t.??\n
- P: And as a final point, visibility as a whole often lends itself to easier comparisons.  By being able to understand the information from a particular visual viewpoint, the data becomes more easy to digest. ??\n
- K: So, WHO cares?  Well, we hope lots of people... but especially these people...scholars, public, developers, journalists, educators, and marketers.  But of these six relevant social groups, we find three to be the most relevant-scholars, the public, and developers.\n
- P: As far as scholars go, one potential “audience” for this type of work would be other contemporary researchers. Others may have far more ideas as to what analytics can be run on this type of data, but they can’t go back in time to start the archive in the past - so it pays to begin grabbing this info before all possible applications are theorized. As such, the idea of putting a more API-like interface on the front end, so that programming savvy people could leverage the data being grabbed, is an attractive prospect, and one that can scale up as the project continues.\n
- K: Given the mild popularity of things like “Whoogles” and “Seriously, Google?” it’s plausible to believe that certain types of auto-complete archives (perhaps not JUST amazon) might be leveraged to produce oddball comedic content. This kind of link-bait could theoretically lead everyday internet users to a space where the naturalization of auto-completion could be debunked, but there are obviously no guarantees.\n
- P: Aside from alterations to our own script, database, or visualizations, there are numerous possibilities for adding features to actual instances of auto-completion in order to combat the naturalization that is currently in place. Obviously, some measure of publication on the actual nature of the algorithms at the heart of auto-complete would be ideal, but even given that, other small changes might be positive as well.\n\n
-  P: talk about this\n
- K: Taking from Friedman et al, we think it’s crucial to understand which social values are most relevant to our project.  Friedman proposes 13 human values with ethical import-human welfare, ownership/property, privacy, freedom from bias, universal     usability, trust, autonomy, informed consent, accountability, courtesy, identity, calmness,  and environmental sustainability.  \n
- K: While most are relevant to our project, the core values we tried to focus on are freedom from bias, autonomy, and informed consent.  This idea of informed consent hints at what we consider the central value of our project...\n
- K: Borrowing from reflective design, we consider reflection to be a value in itself, especially when considering technologies such as autocomplete, which have quickly and often uncritically garnered widespread usage in our day-to-day lives.  In reflecting on reflection as a value, we realized that it has the unique potential to support other values, such as human welfare, privacy, freedom from bias, autonomy, and identity.  Basically, reflection might very well be our drive, goal, and methodology.\n In fact, we consider this value of “reflection” and reflective design in itself to have conceptually under-girded all our efforts, from the construction of the scraper tool and database to our overarching analysis of autocorrect.  \n
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