Week 15: Number, Big Data, and the Brave New World

Big Data is a big concept.  That may be a bit trite, but after reading this week's articles, I did my usual supporting research from my usual starting point:  Ted.com.  Because those people really seem to know what they're talking about.  I found many videos about big data, but the one that gave me the best perspective was this one titled, "What do we do with all this big data?" by Susan Etlinger.

http://www.ted.com/talks/susan_etlinger_what_do_we_do_with_all_this_big_data

I really needed her level set.  Big Data is overwhelming.  Yes, there's a lot of information out there. Yes, it's amazing that we suddenly have access to it all. Yes, there are 100 Big Data jobs for every single applicant.  Yes, zettabyte is a real word.  Yes, we create the same amount of data every ten minutes in 2015 that were created in history up to the year 2003.  Yes, we're awesome.  So what?

What do we do with all this information?  Why is it useful?  The article titled, "The Promise of Big Data" by the Harvard T.H. Chan School of Public Health showed an extreme usefulness to Big Data.  Who WOULD'T like to prevent TB patients from dying when access to Big Data might reveal a cure?  Contrarily, The Consumerist article about SAT test prep price differences due to poorly programmed Big Data pointed to an extreme negative.  After all, I DO live in an affluent Dallas suburb with three children who have taken or will take the SAT.  I don't like that I may have paid more for one of their SAT prep courses.

The benefits of Big Data from an genomic and/or medical perspective are pretty clear.  But is that how the majority of Big Data are being used?  Or is Big Data primarily being sold and culled with the end result of my privacy being compromised?  The later seems to be the case.  The uber-paranoid article, "The hypocrisy of the Internet journalist' seems to prove my theory (a weird, ego-centric  article, by the way).

But I come back to Susan Etlinger, a strong proponent of Big Data.  But she's very clear that Big Data, consisting of images, text, video, and audio files, require context to be useful.  As we've studied throughout the semester, data itself, let alone how it's collected and its collection framework, is entirely up to interpretation and, conversely, misinterpretation.  A 2014 article by Nicole Fallon on Big Data in Business News Daily states, "technology does the tedious work of pulling the data apart and categorizing it, so humans can spend time truly deriving insights and taking action." 

Etlinger mentions an "accident truth" in a misquote by Ronald Reagan during the 1988 Republican National Convention.  He stated that "facts are stupid things."  He meant to quote John Adams, "Facts are stubborn things."  Well, facts ARE stupid; as Ms. Etlinger states, "Data doesn't create meaning; we do."

All that being said, Big Data is helpful in developing cures for diseases and understanding societal behaviors and trends (there's good and bad in that).  And Big Data is certainly inevitable.  So how do we tame it?  Regarding the usefulness of Big Data, Etlinger is a proponent of, "post hoc ergo proctor hoc."  Meaning, "just because something happens after something else has happened does not mean that second thing had anything to do with the first thing" (Huffington Post article definition).  We need to collect data while honoring people's privacy and giving consumers an "opt in" option.  We need to speak clearly about our hypotheses and conclusions.  And, importantly, we need to "show our math" when drawing conclusions.  These steps will help increase participation and hence, the amount of data, as well as expose any fundamental framework and process flaws.  Like with high school Algebra, showing our data work will reveal where we may have broken down.

In an interview with Science Node, Etlinger explained further:

"The key, ultimately, is context– and, without getting too metaphysical, what constitutes context is contextual. Ultimately I think it comes down to clarifying the desired research question, and making it as specific as possible:

• Is there a link between X and Y?
• Can we detect whether it is correlative or causal?
• What is the likely impact of X on Y population?
• With what confidence level are we able to determine this?"

But how do we ensure that everyone culling Big Data is using the same set of principles?  We can't, really.

Week 15 - April 19

How Numbers on Facebook Change Behavior

After reading this article I installed the extension onto my computer to see how I would feel while using it. Since the article was written, Facebook has changed their “Liking” system so the plug-in works slightly differently but basically the same. I find that I base my “liking” off what the numbers say. However, instead of liking a post because so many others did, I find that I will like a post if not many others have so I can boost the poster’s like count. I find that I will also compare my posts, specifically on Instagram. If one photo got more likes than another, I want to know why. Was it the hashtags I used? Was my caption too long? Was it because I made the image black and white? Was it because I made the image too saturated? Was it because the image was too dark? WHY DON’T PEOPLE LIKE ME?!? Dramatic, I know. But that’s how social media works. If don’t like your post, do they like you in real life. Facebook and Instagram can lead to an existential crisis.

How Social Bias Creeps Into Web Technology

“Computers aren’t magically less biased than people[…]” This is an interesting statement seeing how people (for now) have to program computers. Even in the future, a person will create the base program the computer will learn and probably teach itself from. As long as people have a hand in computer programming the computer will always have shadows of biases.

It’s also interesting that these computer systems seem to make things easier but at a closer look, they fall short in so many areas. It’s unfortunate that the computer messes up tagging people by labeling them horribly incorrect. I wouldn’t say that the tags mentioned in the article are “insensitive” but rather ill-informed and highly unfortunate (under the assumption the programmer was attempting to be as unbiased as possible). A computer (unlike people) doesn’t use context clues or situational data to help make the deacon when labeling people or things. It can only use past binary data. People can look at a photo of several people at a party and know not to label one an “ape” because they understand the image on a deeper level than the computer does.

Week 15:To Data or Not to Data

Well, it's only taken me 16 weeks to figure it out, but I finally realize this class is really the study of good vs. evil, right vs. wrong. 

This collection left me mad as heck with readings 1, 3, 4, 5 and 6. But no worries: it was pretty much all wiped off the table with the second article. I'll cover the depressing stuff first.

Starting with The Atlantic's Facebook/numbers article: I've always known in the back of my mind that Facebook was using numbers and buttons to influence my behavior. I'm not too proud--or smart enough--to deny that the likes don't matter to me. I enjoy the validation. I want  to see who cares about my posts. And now with the emoticons "reaction" buttons, well, bring it on, Facebook. But it's still shocking to read the article, to see all the facts about Facebook's outright intrusion on my life right before my eyes. We're being played. I feel like the numbers and likes are just a great big psychological experiment. And one day somebody (Zuckerberg, maybe?) is going to say, "Just kidding!"

The WSJ article about social bias in data was upsetting. I hadn't heard about the photo tagging disaster on Flickr. I'm back to the argument I've made all along: why are we trusting technology, software with tasks that technology and software really don't need to be managing? What in the world is the importance of the tags, really? It's one thing to want to add those for your (the user) own way-finding and memory-saving purposes. It's a whole other ball game to have software do it and make this kind of appalling error. It's embarrassing and altogether unnecessary. But here's the thing that's so hard to swallow: maybe it's our own bias that's really to blame?!? There goes my argument for letting the human manage his tagging himself. It's an ugly circle. 

It was the same thought I had when reading about test prep companies charging based on geography, resulting in race-based price gouging. The people are failable, here, clearly. And it's because they're trusting the software implicitly, it appears. 

The "Hypocrisy of the Internet Journalist" was one of the most dystopian pieces of...collegiate reading...ever. I felt defeated and demoralized and scandalized. But what am I going to do about it? What's the author's goal here? "You're screwed, but I don't have any answers for you (evil laugh). Have a good life though!"

In "Metrics have a powerful influence on journalists' morale," I thought: wow, conflict of interest. I'm now meant to worry about journalists getting high traffic to their stories to feel good? When and where will we stop feeding the need to validate our existence at every turn, with praise and encouraging words? 

Reading "The Promise of Big Data," I felt hopeful all over again. On the one hand, obviously, I'm worrying about All The Data and how it's being used to predict my next trip to the bathroom. Next thing I know, I'm thinking, oh, this is great! All The Data might save us all. It's incredibly confusing. Good vs. evil, right vs. wrong, I tell you. 

Group Discussion: Media Literacy

Several of you mentioned the importance of teaching the younger generation media literacy. If you were designing an outline for such a course, what are specific topics that you would cover?

Well, there's a lot of potential ground to cover here. As students, we receive lots of media literacy instruction in snippets within various courses. I'll attempt to narrow down to a few generalized topics.

1) Learn the system
Develop a general process to analyze media. Students don't need to learn coding, but a lesson on how to research media is valuable. It's like being taught the Dewey Decimal system and old library card catalogues. It's a basis for how to find information you seek. Survey each class to find the current most popular social media service. Then assign students the task of learning as much as they can about how it works. For example, if the class mostly uses Twitter students would look beyond hashtags and tweets and into Twitter's construction. Once a person truly understands a system, they can maximize it's the system's potential benefits or manipulate it.

2) Verify web sources
As an undergrad, one of my professors would invite a guest speaker every semester to lecture one class time. The guest speaker was from the library and taught the class methods of determining the legitimacy of websites. It started with simple things like paying attention to the url extension (.com, .org, .gov), where to look for the last page update, spotting native ads and so forth into more complicated methods like finding secondary sources. After lecturing, the librarian would run the class through a some of exercises. We'd look at a series of webpages and rate their legitimacy using the tools we just learned.
This was presented as a basic introduction, but I'm sure it could be expanded into a full semester course.

3) Learn the jargon
The article about faking cultural literacy talked about how people pretended to know more than they did. Every industry has its own set of jargon and customs. And people fake their knowledge just like they do in social situations. Learning the jargon of digital media will help increase literacy, like learning a foreign language includes cultural studies. Once a language literacy is established, one can root out the essentials of any new media by understanding the words used.
During medic training, we were encouraged to learn the latin roots of words. That way, when encountering something new, we'd at least be in the right ballpark for what the new topic was. For ex: Hemo = Blood, Pneumo = Air. Throrax = Middle section of body. So if I saw the word "hemopneumothorax" for the first time and had no context, I'd at least know that the word had something to do with both blood and air in the middle of a person's body.
The same process can be applied to media studies.

4) Data Collection/Profiling
We've all had multiple lectures about how much data is collected on us, but it's hard to imagine it in any truly meaningful way based solely on a lecture. I suggest breaking the students up into groups where the members don't really know each other. Then, their assignment is to "cyberstalk" another group member, collect as much data as they can, create a profile then present the results to the class. The presentation will included how accurate the profile is and what tools they used to collect data and organize it meaningfully. I think this type of project would really drive home concepts surrounding big data collection by personalizing the topic.

5) Consequences of online sharing
It's no secret that some employers and organizations look to social media before making a hiring decision or granting membership. All personal information we voluntarily disclose online may come back to help or harm us. Examples abound for the creation of case studies. Assign students to research an incident where social sharing affected an individuals life. The more local the assignment can be the better. Try to avoid letting someone report about Anthony Weiner's weiner pics. Urge the class to find local examples so the topic is more relevant. Also, not all consequences of social sharing are negative. Sometimes it's a good thing, like finding a great job because a random manager liked your pictures on Instagram or you tweet well.

The running theme here is that each topic requires students to increase media literacy by using digital tools outside their normal habits and gaining some knowledge about "How?" and "Why?" as opposed to just "What?"

Group Discussion: Minimizing Overload

Best practices for minimizing overload?

I don't believe there's any single set of practices to minimize overload. At best, there's situational dependent tips. Before employing a method, a person experiencing overload should deduce what's causing the overload. For example, I don't feel overloaded by email, but I don't work or live in a setting where that's an issue. Therefore, email management wouldn't help me much. this list of suggestions are based solely on my experience.

1) The "Zen" Day
In the past, I would check into a hotel about once a month to isolate myself from the world for a weekend. No calls, no social media, no internet. Baring that, I would take solitary day/overnight trips to places like state parks and new towns. Unplugging was my way of dealing with overload. I live alone now, so I don't need these kinds of trips as frequently.
It's really about taking some personal time, even for a short period. I look at it like charging a battery. There's only so much energy available to accomplish tasks. Once the energy is depleted, it's time to recharge. The key here is realizing that while charging, it's not possible to engage in any other tasks. Once complete, the battery can be used at full strength again.

2) Schedule Face-To-Face time
Make a habit of spending time in the company of others. These days, that often involves a pre-scheduled event. Plan a dinner party, meet for coffee, play a sport, walk nature trails, etc. The point is to regularly experience a sense of community that is only accessible within the physical presence of others. To reap the full benefit of these interactions, remove as many digital distractors as possible. Silence phones, turn off the TV, no net surfing during the event.

3) Turn off notifications.
I don't spend excessive amounts of time online, yet I still receive lots of interruptions from push notifications. Turn off the alerts. Try to redefine CMC and digital media as tools at your disposal, don't accept that you are at their disposal. Take back control. By turning off notifications, you decide when to acknowledge them. They'll still be there, even Snapchat until you open it.
I think of the constant alerts coming from my phone and computer as "micro-interruptions." In this sense their kind of like the concept of "micro-aggressions," unconscious aggression from mechanical objects and software. The difference is we self impose these on ourselves instead of experience them from others.

4) Remove the clutter
The therapeutic value throughly cleaning your home can't be underestimated. This extends into your digital life as well. It's hard to be production when physically and mentally surrounded by disorganization. Clean out what ever you don't need. Be it old papers or apps running in the background.

5) Try new things
Avoid behavioral ruts. Break up monotony with new experiences. Do something unexpected. Test your limits and abilities. If you sit at a computer all the time, do something physical outdoors. If you're a bookworm, go see a play. If you only watch movies and listen to music, try reading a book. The point is that breaking up routines gives your brain and body a new stimulus to contend with which often is a good thing.

There's more suggestions out there. Find what works for you and dispense with the rest.

Week 15 Reading Response

As week 15's reading assignment represents not only the final course reading block, but the last group of assigned readings for me as a student, I'll attempt brevity.

Hhmmm... I hope I labeled every post...

"How numbers on Facebook change behavior" reminded me of the Bergen Facebook Addiction Scale I discovered in 2012. Here's a link to a 2015 article on the same topic:

http://www.medicalnewstoday.com/articles/245251.php

Personally, I experience a loathe-hate relationship with Facebook. I understand FB's value as a tool, but also view it as an unnecessary distraction. Typically, I don't log in until my Yahoo! inbox fills up with FB notifications and then I'm on long enough click the alerts off and log off. My pattern of use resulted in shock that people took metrics to heart and disgust (different article) that metrics would be posted in plain view. I suppose nothing should shock me anymore, but self-worth based on a number of likes? Really?
I don't have much to say on this one, but it seems to fit within patterns of any other addiction.

"The Promise of Big Data," presents a nice change of pace to the normal evils of big data collection. Wow. As a medical professional, and one who's been in tuberculosis prone regions, I enjoyed this reading. Approaching problems from new angles often yields unexpected results as described in the
TB and genetic analyses. Bravo to the scientists willing to break convention, but they're a minority. I hope the next generation of scientists really do embrace this method of data crunching, as the article suggests. Unfortunately, current research practices will require major overhauls for that to happen. Crowdsourcing analysis isn't a new idea. In the early days of public internet access (I think I was in high school), groups employed this approach from day one. I remember installing S.E.T.I.'s (Search for Extraterrestrial Life) screen saver on my family's computer. Computer techs at the community college installed the program in all the campus labs. The screen saver was actually a program that analyzed small pieces of radio telescope data searching for ET.

http://setiathome.ssl.berkeley.edu/

S.E.T.I.'s screensaver has advanced a bit in the past 20 years, but hasn't found any aliens yet. It's a big galaxy though, and maybe just a matter of time. My LG phone has many times the computing power of Apollo 11's systems after all. The point is, while Big Data helped advance some medical studies, we should't get too excited just yet. There's still the problems of programing algorithms, enlisting participants and choosing which data sets to tackle. Despite those issues, there's reason for optimism if not excitement.

"Pitfalls of Big Data" was disturbing in it's outline of discrimination. But was anyone really surprised? We're all targets for money-grubbing companies, and have been for so long that it's really a cliché. I'm sure the Princeton Review will win any law suits brought against them, or settle out of court. Of course automated pricing schemes are biased. Humans inherently harbor bias, even unconsciously, and that bias seeps into the projects. Who writes the programs? People. Who's biased? People. Who's under pressure to produce programs quickly? People.
I'm sure if someone were able to slow down the process, the price algorithm would have become a tad less discriminatory. But combining inherent discrimination with speed driven product only serves to promote these types of events.

Full disclosure about the WSJ article concerning social bias on the internet: I laughed. A lot. I agree that tagging African Americans as primates is NOT funny. It's the ridiculous results of poor programming that amuses me. Granted, my sense of humor leans dark.
Remember "Tay?" Microsoft built a chatbot for Twitter, then pulled it offline a day later because of how users twisted the program.

http://www.theverge.com/2016/3/24/11297050/tay-microsoft-chatbot-racist

Automated social bias on the internet is indicative of a much larger problem. When rushing to release a new digital application  combines with inherent human bias and poor design input, offensive things happen. there's a systemic cultural ignorance at the heart of the bias. We need to overcome that. In this case it only caused emotional turmoil, not economic loss like Princeton Review's SAT prep or some other disaster. The lowest price was still over $6000 and in Dallas? I used a SAT vocabulary prep book given out free of charge. The print quality makes me think it only cost a few cents and thousands of trees to produce. If Dallas paid that much, I hate to think about the financial burden on Asian communities. There's still a silver lining. As socially unacceptable events like this go public, designers learn more about what criteria to examine. As the learning curve increases, social bias will hopefully decrease. The challenges presented by PR nightmares raise awareness and the determination to improve society.

On a personal note, I don't have an abundance of sympathy for veterans disqualified for jobs because software didn't understand their skills. I am empathetic because I share in this issue. The software isn't the problem. Think of military-ese as a foreign language, and imagine the job prospects of an employee submitting resumes in languages other than English in the U.S. It is a problem, but I wouldn't apply for a job in Mexico without a resume written in Spanish. The Army is trying to address this problem, at least since 2011 (when I transferred from active duty to the reserve). One of the out-processing steps requires soldiers to attend resume and job seeking classes. Instructors outline the the wording of military jobs into civilian language. There's also a lot of internet resources to help, like this one:
http://www.military.com/veteran-jobs/skills-translator/

By the way, Federal employment resumes are an entirely different story. There's a unique language required when applying for federal positions. I was given a book on the subject. Basically, the feds use computers to scan resumes before hiring managers even see potential employees.

I guess what I'm saying is there's an element of personal responsibility in the equation too. Some things, like offensive photo tagging, is out of the individual's control. But tailoring a resume for the specific job is most definitely within the scope of personal action.

"The Hypocrisy of the Internet Journalist" creeped me out. Less so the article, but rather while reading it my home networked printer suddenly turned on and performed some mysterious task. Nothing printed out (I would have included it in this post), but that's almost worse. Why would a powered down printer suddenly come to life with no explanation for itself?
As a Ghostery user, I'm aware of the data mining attacks resulting from simply opening a webpage. I applaud Norton for sticking to principles as best as she could, and understand why principles sometimes take a back burner to cash desperation. Hell, I've had jobs I've quit over similar issues, or never even applied for. I've had others where the desire for food money outweighed moral outrage.
I'm sure any journalist taking the time to list corporate spyware embedded in articles would find unemployment quickly. I'm glad Norton wrote this piece. There's plenty of stories reporting methods of data collection, but personal accounts resonate more with audiences. Society needs more attention grabbing stories like this one in order to act before something truly dreadful happens.

"Metrics have powerful influence on journalists' morale" finds me... not amused. Why the hell would anyone install a signboard displaying metrics in a newsroom? It's not like reporters have anything else to worry about like shrinking job opportunities, low pay for hard work, investor oversight, libel lawsuits or government prosecution. If people don't understand what the numbers mean, or the stats are poorly collected, what could does a sign board do? Of course it lowers morale. Maybe managerial staff should try interpreting the data first, or teaching employees how to do so.

Week 14: Lori's Response

This week I decided to just do my reading response a little differently than I have been doing. I couldn't help but read this week's readings through the lens of Chris' presentation argument last week that this concern about how we are exposed to too much information is something we shouldn't actually be too worried about. Because when you really think about it, how would be benefit from having less information available.

I remember in my AP World History class a boy arguing that communism wasn't actually such a bad thing when you thought about how much easier it could be to make decisions when there are less options available. On one level, this makes sense, but in reality, holistically speaking, who would definitively trade variety for convenience. How much blander would the world be?

None of the authors argue that we need less information, but it feels like it's the unspoken solution when what they're waxing poetic about the difficulty of life in our current state of information availability.

The biggest problem with which I agree from "Faking Cultural Literacy" is that it is far too easy for people to like and share articles without having read them themselves but still contributing to, even somewhat shaping, the public discourse. I think this happens all too often, not just with civilians, but also with news centers thinking publishing articles that will know will attract and incense readers and inadvertently shape how the layman sees the world and current events. It's very dangerous.

But, overall, I think that the fears underlying most of these articles is drawn out of proportion. The type of person that's described in the "Faking Cultural Literacy" article that would be found at a "cocktail party" does not represent the every man. I also think that this author assumes that everyone has this desire to be "in the know" and on top of the viral hits. It's kind of immature.

I think my favorite article this week was “7 things you need to stop doing to be more productive” because I think it displays the type of forward thinking that might become the mainstream in the future. It's the type of lessons that I honestly think students in public school would benefit form having in a required class. 

I think digital literacy as a whole is a field of study that is really important and worth studying, because being able to sift through all the bile in our growing abundance of information is something people of all ages should be able to do. Kids today I think are able to learn from an early age, so I'm not so concerned with them. I'm more concerned with how our elders will be able to adapt and stay afloat. Because as advanced as things seem now, I'm sure things might look just as different when I'm elderly.

I think all this commotion about information overload can be solved with less worry about the negatives and more focus on the strategies (literacies) that enable the best adapted to thrive.