The iPod Shuffle as a Database/Algorithm

The distinction between databases and algorithms in the digital world is often very defined — when we look at the music industry for example, we’re pretty much used to the first in its entirety. That wasn’t always the case.

I remember my first iPod Shuffle. The ability to listen to my music, on the go, and on my own device was an idea that mesmerized me. But I got a little greedy. I loved the iPod Shuffle, but its capabilities as a database were limited. I could load the songs I wanted, but those songs came up in a random order; I couldn’t listen to that “one song” unless I shuffled through the rest.

Photo courtesy of MacWorld

Fast forward almost 10 years, and we pretty much have everything we could ask for in terms of a music database. Now, for a relatively low monthly price, once can stream all the music desired from a giant online database — Spotify is an example. Again though, the power of this database seems to underwhelm after some time, and subsequently, we desire algorithms again.

We rely on the shuffle button to pick songs for us; the thing that used to be a burden is now an every day function that’s come to be desired. Not just that, but the music industry has created algorithms (like Pandora) that select new songs for us based on what we’ve listened to in the past. We no longer desire music as solely a giant collection of songs in which we have autonomy over what we hear; now, we want algorithms to make selections for us.

It’s odd to see this movement from a simple algorithm to a database and back to algorithms. Back when I had an iPod Shuffle, all I ever wanted was to choose my own song on the device; now, that’s something I take for granted.

Let bots be bots and humans be humans

Upon searching Twitter for popular bots, I found an interesting one with the handle: @DearAssistant. Ask the bot any question, and the algorithm that drives the bot will respond to you with an answer.

But wait. Don’t we already have something for that? Last time I checked, it was easier to get information with a quick google search than it was to use a Twitter bot for answers. Heck, I could just ask Siri some of these questions, and she should be able to get back to me within a few seconds.

Yet, this was a popular account (at least until it stopped tweeting in 2016), and the bot accumulated more than 4,700 followers. Clearly, the simple interaction with bots like these is what drives their popularity and existence. It’s not always the bot’s usefulness; I’m sure the user in the above example knew what day it was but still wanted to see the bot’s answer.

In this sense, How to Think About Bots hits it on the head with the idea of “botness.” The way a bot is “not convincingly human” is amusing to us.  If a human was asked “current time in London?”, I highly doubt he or she would respond down to the second like the bot did. That preciseness ( what makes a bot, well, a bot) is what drives us to adore these creations.

Look at this same user’s response to another question.

I remember a service called “Cha Cha” that you used to be able to text for answers to any question you may have. It was completely free for awhile, so long as you didn’t reply to any of “Cha Cha’s” promotional messages.

This service differed from today’s Twitter bots like “Dear Assistant” in that humans were the ones replying to our messages. Is it any fun to ask a human the time of day? Not really. But is it fun to ask some random human “Where’s Waldo?” or “Who is Grant Labedz?” Definitely.

That’s what the service became for me and my friends. It was intriguing to see what kind of witty, intellectual, creative responses these humans could come up with on the other end of the line. Some would actually have fun with it too and feed us with surprising responses that made us laugh.

In a sense, we expect different things from humans and bots. Bots are exciting because they’re bots. They fulfill their functions in a “bot-like” manner, and to us, that’s cool enough. From humans, we expect more. We want creativity, wit, and sometimes more than just information when asking a question.

Meet “Ken M”

“Ken M,” possibly the “world’s greatest Internet troll,” has gained online popularity through one simple action: commenting. That’s right; the screen name “Ken M” can apparently be seen throughout the Internet, leaving “hot takes” and “dumb comments” across some of the Internet’s more popular posts, articles, and videos. And believe it or not, this guy’s gained a following. People actually keep up with this guy to see him troll the digital world.

“Ken M” is the perfect example of a troll thriving off anonymity. He himself notes that his followers don’t want to see his real face. Saying that it’d almost ruin the fun of his online persona, “Ken M” remains anonymous to keep this humorous character in the imagination of his fans and his victims.

What’s interesting is that “Ken M” doesn’t seem to be your typical “Internet Troll.” Instead, he tends to go around cyberspace planting low-hanging fruit for other users to swipe at. He knows he’s putting out stupid comments, but that’s the point. Others want to shut down what he has to say; they probably think he doesn’t know he’s an idiot, but that’s the reason he’s so popular.

Another thing I noticed with “Ken M,” and this is something I’ve seen with trolls across the Internet, is the obvious misspelling of simple words. In one of the trolling examples mentioned in the video above, “Ken M” spells “dinasaurs” incorrectly, and it seems way too obvious to be a typo. This guy sounds like an intelligent dude who knows how to manipulate others and gain fame online. Did he really accidentally misspell the word “dinosaur?”

Probably not. My guess is guys like “Ken M” will misspell simple words in hope that others will comment to fix their mistakes. I’ve seen this online with Twitter trolls. Some accounts will misspell every other word; they want to play the part of the fool so you correct them and engage with them. Misspelling words is like the hook; some people can’t help but engage, and then they’re stuck. “Ken M” is an interesting example of a troll: not necessarily hateful, but very good at getting people to react and interact with his content.

Is Digital Blackface the fault of GIF databases like GIPHY?

Here’s an interesting question: to what extent is digital blackface — the frequent embodiment of black culture through the use of online GIFs — the fault of GIF databases like GIPHY? If we’re being honest, the average person who, say, wants to tweet a reaction GIF is not going to take the time to make his or her own.  The process can be somewhat cumbersome, and it takes time and effort to make your own GIF. Instead, search bases like GIPHY allow someone to filter through a variety of GIFs with a key search word. Typing in “reaction” on GIPHY brings up interesting results.

5 of the first 12 search results to the keyword “reaction” on GIPHY brings about GIFs featuring black people. On a further note, one of Twitter’s main categories (“Dance”) under popular GIFs displays quite a few instances of black people dancing as suggested GIFs. In this case, the user doesn’t even have to search for these GIFS; they’re displayed right there as suggestions.

The prominent use of black people in “reaction” GIFs and “dance” GIFs on Twitter seem to be an issue, but this development begs the question as to how much of it is the user’s fault? If we’re presented with a library of GIFs from the keyword “reaction,” and a large portion of those GIFs are of black people, doesn’t it seem more likely that we’ll ultimately choose one of those “black people GIFs” to formulate the reaction that we want? It seems that these popular platforms like GIPHY are more to blame, as they’re the ones that are ultimately linking GIFs of black people with stereotyping search terms. In order to address this issue, it’s probably worth looking at how these databases choose to display these GIFs; we need to look at why GIFs of black people come up more frequently when we’re looking for reaction GIFs.

Lab Report #3 — Animated GIFs

Sports GIF Example

Sports GIF Counter-Example

This counter-example takes what looks like a traditional sports highlight GIF and spins it on its head. In the main GIF, we see a player celebrate after scoring a touchdown. He spikes the ball; he’s excited. All the attention is on him, and effectively, the GIF serves to reiterate the celebration of a team succeeding. Take the counter-example though, and you’ll see that the GIF doesn’t focus on the highlight or celebration at all. We see the ball go in the hoop, but then the camera zooms in on a player on the opposing team’s bench. The player lets his head down in disgust; clearly his team is not playing well, and the opponent making yet another shot causes him to react in this manner. While on the surface this GIF looks like a sports highlight GIF, it acts more like a reaction GIF, as the focus is on the opposing player’s reaction to the made shot rather than the highlight itself. In a sense, this is a way for Illinois Basketball fans to showcase their disgust: the reaction of one of their players mimicking exactly what the fans see as they watch the game. It’s more of a lowlight sports GIF than a highlight sports GIF even though a shot is being made.

Cinemagraph GIF Example

Cinemagraph GIF Counter-Example

Here we can see how this counter-GIF is a clear attempt at parodying a typical cinematographic GIF. The first GIF is still and focuses on an aspect of nature — nothing moves except the water, and we as viewers are supposed to be mesmerized, looking closer and closer at the ripples of the stream. While the counter-example is not a still frame, it has a lot of the same qualities as the GIF above it — with a twist. We’re supposed to be relaxed looking at nature and casually following a car as it makes its way behind a tree. In fact, this classic Youtube video “Scary Car” causes us to look closer and closer for the car as it’s about to appear from behind the tree. We’re relaxed, we’re interested, and we might find ourselves moving our heads a bit closer to the screen in order to follow the car more closely. And then, this zombie-like creature pops out and scares us in order to throw off the whole dynamic of the relaxing features of nature. This counter-GIF sets up like a cinemagraph GIF, but the purpose is to “troll” the viewer at the end of the loop rather than to allow for creative and intuitive viewing.

Reaction GIF Example

Reaction GIF Counter-Example

This counter-example GIF to a typical reaction GIF serves as a counter-example because, well, there is no reaction. Yes, most reaction GIFs are over-the-top to egregiously display emotion in the form of excitement, grief, etc. The reaction GIF example above is a more subtle reaction, but it still effectively displays a reaction: slow and subtle realization leading to a pleased and content smile. This Youtube video turned into a GIF of a man not reacting at all to a roller coaster ride flips the idea of a “reaction GIF” on its head. In a sense, this GIF doesn’t make sense because there is no reaction. At the same time though, we can see how this GIF could be effective in certain contexts to display the lack of a reaction. Imagine this GIF with the caption “My face when someone thinks they’re better than me.” It works. The reaction is no reaction. This GIF shows the emotion of being unfazed without displaying any emotion at all. This counter-example shows the idea that reaction GIFs don’t necessarily have to display emotion to depict the way someone feels.

“The Single Biggest Thing We’re Going to Build as a Species”

In an article in the Atlantic, Gary Cook, a senior IT analyst at Greenpeace, is quoted saying that “the Internet is the single biggest thing we’re going to build as a species.” Surprising or not, that single biggest thing that we’re currently building may be an environmental hazard. Shockingly, the article cites that an hour of streaming online can use more energy than a refrigerator in a year. Maybe it’s time to log off Netflix.

But what about one of the biggest “things” we as humans have already created? When you think of enormous manmade objects, you think of skyscrapers, trucks, etc. You might not think of the Great Pacific Garbage Patch, a manmade, floating pile of junk in the Pacific Ocean. The patch of plastic and other debris is estimated to be twice the size of Texas.

In a way, the Internet can kind of be seen as a, well, giant floating patch of debris. As we consume and consume online, we use more energy and exhaust more resources. While some of these can be renewable, it’s still incredible just how much energy daily functions on our phone require. And the bigger it seems to get, the more that is required. More lights, more power, and more energy is needed to keep these big data centers running.

The effects of Internet use on the environment might not be as obvious as a giant floating pile of trash in the ocean, but the concepts are strikingly similar. We as humans, as we build things bigger and bigger, also generate more waste. The more we consume, the bigger the impact we leave on the environment. So maybe we need a different approach when considering the “single biggest thing we’re going to build as a species.”

Is it time to stop “blaming” technology for our relationship issues?

In Perpetual Contact : Mobile Communication, Private Talk, Public Performancethe authors bring up an interesting idea revolving around the “absent presence” that technology instills upon us. The authors mention the idea that the Internet may be resulting in a large-scale devaluation of the depths of our relationship. More specifically, this reading links increased technology usage with higher divorce rates and young adults getting married later and later every year.

This seems like somewhat of a cop out; it’s easy to blame our relationship problems with the growing age of Internet use and time spent online. But just because there is correlation doesn’t necessarily mean there’s causation. A video from BrainCraft actually suggests the opposite idea.

This video presents some interesting statistics and ideas. A study suggests that increased social media use among couples actually resulted in greater intimacy among those with attachment anxiety. While we may expect “jealous” individuals to be more anxious when their partners use social media, the opposite actually tends to be true. Essentially, those with attachment anxiety use their phone in order to seek more attachment from their partner, and studies have suggested that that does lead to more intimacy. The video also sites a statistic that 74% of married couples saw either no impact or a positive impact in regards to technology usage and their relationships.

The video also suggests another idea: phone use and social media engagement lets us tell and relive our stories with our significant others. In a sense, we’re reminded of the times spent with our lovers when we see these memories in digital form, and we can all attest to those in relationships actively displaying their love on social media platforms through Instagram pictures, Facebook memories, and other forms of digital affection.

A woman in this video sums up this idea nicely. She says the Internet and social media are “tools that enable your behavior. It’s not the Internet; it’s you.” This is an interesting thought, and it makes sense: a phone can not ruin your relationship, but you can as a result of your behavior. If you let social media impact your relationship in a positive and healthy way, there should be no reason to remove phone usage from your love life at all.

Is Neuromancer warning us about AI’s deceptive abilities?

It’s no secret that Neuromancer deeply explores the concept of Artificial Intelligence. We see the AI named “Neuromancer” attempt to trick Case into staying with Linda Lee on a beach — the AI’s ineffective last line of defense. But what if that last line of defense had been effective? What if the AI was so smart, that it made an irresistible offer to Case, having the power to own him?

Interestingly enough, there’s emerging evidence that AI is becoming better than us at tricking humans. A writer for Forbes decided to do an experiment with an AI twitter bot: who could be more effective at getting users to click on malicious links: the bot or the writer? Surprising or not, the AI won 275-49. How? It was much more creative in the way it displayed deceptive content. (DON’T CLICK ON THE TWITTER LINK BELOW)

Here’s a look at the Forbes writer’s attempt at getting users to click. The writer uses hashtags, tries to entice with an urging message, and even responds with multiple accounts in order to make the post look more legitimate. Not bad. But the AI? It was way more creative. The bot sent out a variety of tweets, making them more diverse, including GIFs and other forms of media, and even sending them out in different languages. The Forbes writer could not keep up with the creativity of the Artificial Intelligence. That’s kind of freaky.

Neuromancer leaves us hanging, somewhat, as we learn that Wintermute and Neuromancer have combined to create one big personality; they now apparently make up the entire matrix. We don’t know exactly what this is supposed to mean or what it might entail, but we do know that it sounds pretty damn powerful. Neuromancer certainly explores the idea of AI ruling the world. Case literally asks “You God?” It’s a chilling thought, and the scariest part is that we’re beginning to see AI act deceptive and cunning, even more so than humans in some cases.