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      "title": "The Future of Fake News",
      "body": "I think we can all agree that fake news is a problem. However the time we are in now may be the last time we can be sure that any videos/images and audio are not completely fictional. Recently with the rise of Machine Learning algorithms there have been many studies into generating totally unique audio and visual media. At the moment they are still very limited and experimental but with large corporations like [Google and Facebook](https://www.techworld.com/picture-gallery/data/tech-giants-investing-in-artificial-intelligence-3629737/) pouring money into AI research they could make the process more efficient and the product of a better quality. \n\nOne of the [studies](https://arxiv.org/pdf/1612.03242v1.pdf) comes from a partnership between Rutgers University, the University of North Carolina at Charlotte, Lehigh University, and the Chinese University of Hong Kong. In this paper they demonstrate how the researchers made a neural network called StackGAN that was able to create images from a descriptive line of text. Since I would not be able to explain it myself here is how they describe it works. “*The Stage-I GAN sketches the primitive shape and basic colors of the object based on the given text description, yielding Stage-I low resolution images.  The Stage-II GAN takes Stage-I results and text descriptions as inputs,  and  generates  high  resolution  images  with  photo-realistic  details. The Stage-II GAN is able to rectify defects and add compelling details with the refinement process*”.  So from this process, the team is able to produce pictures from just text, here is what it looks like.  \n\n\n![deeplearning](https://cdn-images-1.medium.com/max/800/1*sIphVx4tqaXJxtnZNt3JWA.png)\n\nImage [Source](https://medium.com/@Moscow25/gans-will-change-the-world-7ed6ae8515ca)\n\nBut not only images are being artificially made through machine learning. In [this](https://grail.cs.washington.edu/projects/AudioToObama/) paper the University of Washington’s GRAIL lab creates a machine learning algorithm that can manipulate a target video to lip sync inputted audio different from the original video. They show this off by changing the speech of Obama from the source video to a different speech while also lip syncing the audio. Another example of this is a research project by the [Niessner Lab](http://www.niessnerlab.org/papers/2016/1facetoface/thies2016face.pdf) called “Face2Face: Real-time Face Capture and Reenactment of RGB Videos”. In this project the authors created a neural network that could change video of a target actor using a source video in real time. \nhttps://youtu.be/ohmajJTcpNk\nAn example of Face2Face's program in work\n\nFinally there are several tech companies that are creating programs that can upon being trained on an amount of data, can reproduce a target actor’s voice with just text input. One of the companies creating this software is Adobe; its tool called [VoCo](https://thenextweb.com/apps/2016/11/04/adobes-upcoming-audio-tool-lets-you-synthesize-speech-in-anyones-voice/) will be able to reproduce someone’s voice with just 20 minutes of audio data from that actor. The other company is called [lyrebird](https://lyrebird.ai/custom-voice), it says that it can do the same with just one minute of audio data. Either way, this voice, video, and picture manipulation software could defiantly be useful for applications like video games and movies however these programs could be used unethically to create “fake news”.\n \n<h1>Solutions</h1>\n\nOne possible solution for this future problem could be to create a machine learning algorithm that can detect these deep fakes and one lab has already [done](http://niessnerlab.org/projects/roessler2018faceforensics.html) that. However this could just exacerbate the problem because someone could just use the data from the deep fake detector algorithm and train their neural net to fool that algorithm, making that deep fake generator even more realistic and difficult to falsify. This is how [generative adversarial networks](https://en.wikipedia.org/wiki/Generative_adversarial_network) (GAN’s) work. \nAnother solution could be the blockchain.  Because the main benefits of a blockchain are that it mathematically verifies data and cannot be changed without a significant amount of work. Possibly, a video app on your phone could be linked with a blockchain and when you record a video a token could be added to the video’s data that could verify its authenticity using the blockchain. \nHopefully by the time this becomes a real problem we will have a solution like this. If anyone has any other ideas about solutions to this problem or wants to point out any errors I have made in this post please put them in the comments, I would love to read them.",
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      "title": "Self-Driving Cars, the Good, the Bad, and the Ugly.",
      "body": "![sdc.jpg](https://steemitimages.com/DQmVbchK4UBE3t6MrBuHnPfoGkqDknEFYVJBy1LB4haTURr/sdc.jpg)\n[Image Source](https://futurism.com/uber-launching-its-self-driving-cars-this-month/)\n\nI’m sure we have all seen self-driving cars in sci-fi movies, books, and video games. There are many companies that are developing and testing their own self-driving car technologies such as Google, Uber, Tesla, GM, Ford, BMW, and Apple. Most of these companies are saying that they want to have their cars ready by around 2020 with Uber already testing their car in Pittsburgh with a select few volunteers according to Business Insider writer [Danielle Muoio.](http://www.businessinsider.com/companies-making-driverless-cars-by-2020-2016-10)\n\n<h1>The Good</h1>\nWhat are the Benefits of Self Driving Cars? Well, for one, there is the environmental benefit. As reported by Time writer [Justin Worland](http://time.com/4476614/self-driving-cars-environment/), “Cars could be programed to choose the most fuel efficient route. Federal rules could penalize cars that drive unoccupied or reward those who allow their vehicles to be used for ride-sharing.” So, using an AI to choose the most efficient fuel route, taking into account all the roads, stop signs, stop lights, and more, drivers could reduce the amount of fuel spent while driving, which would help the environment significantly if all or most of the vehicles on the road were automatic.\n\nAnother potential benefit to self-driving cars is the massive amount of lives it could save every year. As stated in the Association for Safe International Road Travel [(ASIRT) website](http://cyberlaw.stanford.edu/blog/2013/12/human-error-cause-vehicle-crashes). 37,000 people die in a car accident every year in the U.S. and 2.35 million or injured or disabled. That is an insane amount of deaths, and since around 90% (according to [Bryant Walker Smith](http://cyberlaw.stanford.edu/blog/2013/12/human-error-cause-vehicle-crashes) of Stanford Law School) of car accidents are due to human error (alcohol, texting, not paying attention, etc), if we just took the human out of the equation, since robots do not sleep, talk or get distracted, and have way better reaction time, deaths from accidents could drop significantly.\n\n\n<h1>The Bad</h1>\nThe first problem, loss of jobs, is a pretty bad one. In 2014, 233,700 people were working as a taxi driver or similar, as well as 1,797,000 people working as truck drivers (as stated in Bureau for Labour Statistics)(link). So, if self-driving cars became a standard for transporting things around the country over 2 million people would lose their jobs. But there is some hope! When big industries in the past became automated (like the discovery of the printing press and the powered loom) they took away millions of jobs, however new jobs ended up being created even after huge swathes of jobs were closed off. Hopefully if we do get self-driving cars, this will be the way to solve that problem!\n\n<h1>The Ugly</h1>\n![tp.png](https://steemitimages.com/DQmRgxh1uZgp6RAUYgEXLXzCiNjG85E9edQJ2XDw7m7agmD/tp.png)\n[Image Source](https://www.theodysseyonline.com/is-utilitarianism-silent-killer)\n\nArguably the biggest problem with self-driving cars has to do with the thought experiment of “the trolley problem”. The [trolley problem](http://www.nytimes.com/2013/11/24/books/review/would-you-kill-the-fat-man-and-the-trolley-problem.html) is a hypothetical situation where a trolley is moving quickly on a track that if nothing were to stop it, it would run over 5 track workers. However in this situation you are able to choose to pull a lever that would switch the track from the 5 workers to a track with only one worker. No matter what choice you make someone will get run over, you just get to choose how many people will get killed.\n\n Why is this important to self-driving cars you ask? Well, if these vehicles start to become commonplace, eventually some car will get in the same sort of situation where it has two options that both result in someone being killed. Let’s say for example your car is on a very fast highway and you see a truck on your right about to run into you while another car is right behind you and a motorcyclist is to your immediate left. If your car would try to break it would run into the car behind you and kill both you and the other driver, if you were to turn left you would survive but the person riding the motorcycle to your left would die, and if your car were to do nothing only you would die from the tipsy truck. How would your self-driving car choose to handle this situation? Should it choose to be utilitarian and maximize the amount lives saved? Or should each individual car maximize the chance that their occupant survives? I see this as the biggest problem with adopting self-driving cars because it seems like there is no wrong or right answer, its totally debatable. And you do not want your car to be debating advanced ethical problems as you are about to be flattened by a truck.",
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      "title": "**Self-Driving Cars, the Good, the Bad, and the Ugly.**",
      "body": "![sdc.jpg](https://steemitimages.com/DQmVbchK4UBE3t6MrBuHnPfoGkqDknEFYVJBy1LB4haTURr/sdc.jpg)\n[Image Source](https://futurism.com/uber-launching-its-self-driving-cars-this-month/)\n\nI’m sure we have all seen self-driving cars in sci-fi movies, books, and video games. There are many companies that are developing and testing their own self-driving car technologies such as Google, Uber, Tesla, GM, Ford, BMW, and Apple. Most of these companies are saying that they want to have their cars ready by around 2020 with Uber already testing their car in Pittsburgh with a select few volunteers according to Business Insider writer [Danielle Muoio.](http://www.businessinsider.com/companies-making-driverless-cars-by-2020-2016-10)\n\n<h1>The Good</h1>\nWhat are the Benefits of Self Driving Cars? Well, for one, there is the environmental benefit. As reported by Time writer [Justin Worland](http://time.com/4476614/self-driving-cars-environment/), “Cars could be programed to choose the most fuel efficient route. Federal rules could penalize cars that drive unoccupied or reward those who allow their vehicles to be used for ride-sharing.” So, using an AI to choose the most efficient fuel route, taking into account all the roads, stop signs, stop lights, and more, drivers could reduce the amount of fuel spent while driving, which would help the environment significantly if all or most of the vehicles on the road were automatic.\n\nAnother potential benefit to self-driving cars is the massive amount of lives it could save every year. As stated in the Association for Safe International Road Travel [(ASIRT) website](http://cyberlaw.stanford.edu/blog/2013/12/human-error-cause-vehicle-crashes). 37,000 people die in a car accident every year in the U.S. and 2.35 million or injured or disabled. 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When big industries in the past became automated (like the discovery of the printing press and the powered loom) they took away millions of jobs, however new jobs ended up being created even after huge swathes of jobs were closed off. Hopefully if we do get self-driving cars, this will be the way to solve that problem!\n\n<h1>The Ugly</h1>\n![tp.png](https://steemitimages.com/DQmRgxh1uZgp6RAUYgEXLXzCiNjG85E9edQJ2XDw7m7agmD/tp.png)\n[Image Source](https://www.theodysseyonline.com/is-utilitarianism-silent-killer)\n\nArguably the biggest problem with self-driving cars has to do with the thought experiment of “the trolley problem”. The [trolley problem](http://www.nytimes.com/2013/11/24/books/review/would-you-kill-the-fat-man-and-the-trolley-problem.html) is a hypothetical situation where a trolley is moving quickly on a track that if nothing were to stop it, it would run over 5 track workers. 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