No more trolls?

No, not those trolls

I'm sure we're all had our experiences with trolls on the internet. People posting in comment sections of websites just to start fights or to get a rise out of other people. "The goal for the Web troll is to get the victim riled up as a joke. But usually the troll is the only one laughing" (HowStuffWorks). They generally take away from the fact that the internet is supposed to be an educational or entertaining place. There is some good news, however! There is an algorithm in the works that could get rid of these trolls forever! In the past, websites have used moderators or the removal of anonymity to try to combat trolls, but this new algorithm is much more promising. 

The algorithm can do something amazing that these moderators couldn't: detect trolls before they get banned or make exceedingly controversial posts. Using a sample of millions of posts and users, researchers at Stanford and Cornell were able to compile a list of common attributes of trolls including things like poor grammar, more profanity, and more posts when compared to the average user. Using this list, they created an algorithm that could predict when a user would be banned from a website for trolling with 80% accuracy. 

Although 80% accuracy is fairly high, it still isn't high enough to implement the algorithm. Also, the studies are only research and not yet available to the public. This algorithm, while still useful, would not eradicate the need for human moderators. It would simply save time by suggesting possible internet trolls to the human moderators. The algorithm won't be in use in the immediate future, but will likely be popularized for websites later. Though it might seem like a very small area of research, trolls affect many people, and I think it's cool that there is such extensive research being done into the topic. 

https://s-media-cache-ak0.pinimg.com/736x/4b/8e/53/4b8e5333fea465fae3f3163d7cdf78fd.jpg

http://computer.howstuffworks.com/algorithm-spot-trolls-on-internet3.htm

http://wpmu.mah.se/nmict151group2/2015/03/13/new-media-activism-and-racist-internet-trolls/

Are you a robot?

I'm sure everyone reading this blog post has encountered a CAPTCHA test before to make sure the person using the website is a human. CAPTCHA stands for Completely Automated Public Turing Test to Tell Computers and Humans Apart. It is derived from the Turing Test, a test to determine whether or not a computer can think like a human can. The CAPTCHAs are created by a computer, but are unable to be deciphered by a computer (haha, ironic) to prevent people from creating programs to cheat the system.

The most common CAPTCHA test is a a set of distorted letters. The user would then need to type the letters they see into a box. If they match the distorted letters presented, then the computer carries on with the intended actions, like creating an account for a website or buying tickets. Although the distorted letters are the most common type of CAPTCHA, there is usually also an option for an audio CAPTCHA. 

Why might these kinds of tests be useful? A common use is in online polls. In 1999, before CAPTCHAs were popularized, a website ran a poll to determine which computer science program at certain schools was better. Students at MIT and Carnegie Mellon coded programs to continuously vote for their schools. Because there was no CAPTCHA to prevent these bots from doing so, there was an endless amount of votes. Another common use, as I mentioned before, is in online ticket sales. This prevents ticket scalpers from creating bots to buy mass amounts of tickets and sell them at a higher rate. CAPTCHAs are incredibly useful and basically essential in the online world!

It is important for computers to randomly create these tests, because if every user was presented the same CAPTCHA, it would be incredibly easy to code a program and simply input the predetermined answer. To combat this, many programs will simply generate a random string of letters and numbers. It then takes this string and distorts it in some way, like stretching the letters. This makes it difficult for computers to interpret the message.

This system works well for now, but creating indecipherable CAPTCHA tests is becoming much harder. Computer programs are being created to decrypt the audio messages as well as the less complex visual ones. The bright side here is that every time a computer can figure out a CAPTCHA test, we are getting closer and closer to artificial intelligence. This is cool, but a little scary in terms of security, in my opinion. What do you think??

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https://encrypted-tbn1.gstatic.com/images?q=tbn:ANd9GcTYPyWcklqg3edeqNizl62fAAynSzaiV4TFjT-5_9ZW_WmvaBFs3Q
http://www.captcha.net/images/recaptcha-example.gif
http://computer.howstuffworks.com/captcha5.htm

Dreaming computers? Google Deep Dream

I recently found out about this weird computer program created by Google called Deep Dream. It is an automatic image editing program that locates patterns in images and superimposes them onto the image to show the user. It's hard to explain what the images look like, so it's good to try it for yourself. Here's a picture that I edited using the service.

What started as a picture of me jumping at my summer job, turned into a trippy representation of the same picture. It's really fun to mess around with different pictures and settings! But what exactly does it do, and how does it work?

It uses a very complex kind of searching called "image recognition". Image recognition is very difficult for computers to do accurately because they are so hard coded to do searches from words. That's why this program is so cool!

As I've talked about in previous blogs, this program uses an artificial neural network (ANN), similar to the one used in IBM Watson, that can learn things as more information is presented to it. Google trained this program using tons of images and repetition to learn what certain objects look like and recreate versions of these objects without further input. For example, after the program is fed many pictures of bikes, it will learn what a bike typically looks like, and can create its own image of a bike on command. This is the kind of technology that was applied to Deep Dream.

Groups of artificial neurons work together to identify different aspects of an image, such as borders and colors, and using this information, try to find other objects, like a bike, that may have the same or similar borders and colors. So when I uploaded the picture of myself jumping, it saw wrinkles in my shirt and colors that created a pattern similar to that of a dog. The neurons overemphasize every aspect of the image, looping through the same process of identifying patterns and accentuating those patterns several times, until a final image is produced. You can even manually upload the same image to the system several times and see what it produces. Here are a few more examples of my own pictures and some that I found on the internet:

The same picture as before, but put through the system about 5 times.

Here's an image before, and after it was put through the system 10 times.

Although this specific program is intended mostly for recreational purposes for the public, the general idea can be applied to technology and programming as a whole. Nobody is telling the computer what to find in these images; the computers have been trained to locate and show what it sees. Some people think that this is a huge step towards artificial intelligence because the computer is creating something on its own that isn't necessarily there. I think this quote sums it up well:

• "It's hard to know exactly what is in control of Deep Dream's output. No one is specifically guiding the software to complete preprogrammed tasks. It's taking some rather vague instructions (find details and accentuate them, over and over again) and completing the jobs without overt human guidance. The resulting images are a representation of that work. Perhaps those representations are machine-created artwork. Maybe it's a manifestation of digital dreams, born of silicon and circuitry. And maybe it's the beginning of a kind of artificial intelligence that will make our computers less reliant on people" (Chandler).

What do you guys think? Also, here's the link to try it out for yourself! There's also a gallery of cool images that people have made through the program. 

https://deepdreamgenerator.com

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http://computer.howstuffworks.com/google-deep-dream3.htm

https://en.wikipedia.org/wiki/DeepDream

Computers to aid in early detection of communication disorders

Speech and language disorders require early detection in children in order to provide effective treatment, but with the current methods of detection, many disorders go undiagnosed until it's too late. New technology in the works, however, can diagnose these disorders much earlier. A computer program being developed at MIT can listen to the speech of children, analyze it, and identify early patterns of speech and language disorders. Although the work is not finished yet, the possible results would be extremely helpful.

The system works by teaching the computer to assess large amounts of data and screening for patterns. It then takes these patterns and compares it to patterns shown by people with communication disorders. The technology here needs to be able to listen to the child and recognize their voice, and also analyze the pattens shown. Specifically, the computer listens to the pauses in speech.

I like to compare this machine's ability to scan large amounts of information to IBM Watson and how it is also being used in the medical field for cancer patients. In addition, it uses "machine learning" which is also present in IBM Watson. This is the ability of a computer to "learn without being explicitly programmed" (Wikipedia).

Although there are still some bugs in the system and problems that need to be sorted out and accounted for, this technology is wildly promising. Detecting communication disorders early is crucial in allowing for academic success later in life. Hopefully this technology is perfected soon, because it would be so beneficial for future generations!
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https://en.wikipedia.org/wiki/Machine_learning
http://news.mit.edu/2016/automated-screening-childhood-communication-disorders-0922
https://www.southernct.edu/academics/schools/health/academic-programs/communicationdisorders/centerforcommunicationdisorders/

SPOOKY

It's Halloween!! In honor of this spooky holiday, I'm writing an article about how motion detection technology can be used to make automated haunted houses. Currently, for good haunted houses, you need actors that will jump out at you as you pass by. With motion detection and robotics, there could be (spooky) jump scares without the need for human actors. But how does motion detection work? Let's find out!
A basic form of motion detection is called a "radar-based motion detector". This device sends and receives ultrasonic sound waves. If the waves that are received are different than the waves that were sent out, motion has been detected. A more advanced kind of motion detector is called a "passive infared (PIR)" motion detector. When a human walks in front of the sensor, it detects a sharp increase in infared energy.

That's great and all, but how does it relate to computer science? When browsing the web for information about motion detection and haunted houses, I found an example of a short piece of code you could use to activate your special effects! Everything needs to be digital, so codes and programs are needed to take the information from the motion detectors and create some special effects. The haunted house would also use robots in place of the human actors to scare the customers. The signals from the motion detectors would be sent to the robots, which are coded to do a specific action, like jump out into the room. Sounds and lighting would also work similarly, and would require the use of computer science and coding in order to work properly. Another kind of technology being used in haunted houses is virtual reality and augmented reality. People would wear the virtual reality goggles as they walk through a physical house. So in the near future, all haunted houses may be completely run by technology and computing. Spooky!
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http://www.aforgenet.com/framework/samples/computer_vision.html
http://www.bizjournals.com/orlando/blog/2016/08/universal-orlandos-halloween-horror-nights-to.html
https://en.wikipedia.org/wiki/Motion_detector
https://www.youtube.com/watch?v=WWum0VRc6MI