Blog Post #7 Assignment

About some new innovation, in the past or in the present, and view it  through the lens of the Diffusion Theory. Why did they catch on and spread? Why did so many people become early adopters? Why are some people late adopters? Or not adopters at all? What about the downsides — do you see any negative consequences in the technology? For example, why am I not on Facebook, Twitter, Instagram or any other social media? Why might I have made that choice for myself? And how would I benefit if I did? Would the positive outweigh to negative? How do you weigh that cost-benefit analysis with a new communication technology?

     When it comes down to something that has been put onto the market, no matter how popular it becomes, there will be people who buy or invest into it either early on, while it is already popular, while it is dying down, or not at all. This is called the diffusion theory.

    There are different reasons of why people would fall into different categories. For this, I will go on why people would fall into each category for when a new video game is announced and (hopefully) released. The innovators are people who heard about it early on, and were immediately excited for the product. For the video game industry, this would likely include people who are on the publishing and marketing team for a game, as well as people who funded the game to the point that it can be produced and sold. This group also includes people who worked directly on the game.

The early adapter group will more likely be fans that were invested in the game early on. This group will include people who pre-order games. These people also partake in early access content or pre-release demos if they are provided. This group also consists of news articles that talk about the game.

    Third is the early majority. These are the people who buy and play the game within the first few weeks of the game's release (that time may increase or decrease based on what kind of game it is- for example, that time is much larger for live service games, or games with post-launch updates). These people were ready to spend money on the game without knowing if the game would be good or not, despite what was previously shown- which surprisingly happens very often. People who make reviews, or make videos based on games are able to play the games and write or make content based on the games, allowing more people to learn about it and also join this group.

        Fourth is the late majority. For video games, it's hard to say when this group ends and the next begins. This may be a group that didn't originally play the game for various reasons. Maybe they didn't have the time or money to buy and play, maybe they simply didn't hear about the game. Maybe they weren't originally interested, and eventually decided to give it a try.

    The final group is the laggards. I don't entirely know how long you would have to wait to be in this group when it comes to playing a video game. For live service games, it would likely be when the game is "dead," with little or no players to play alongside or against. For console games, it may be when the game is only available on a console no longer being produced or supported (or through emulation), like the beloved Kirby Air Ride that people desperately want to return, no matter how. And then there's the group within the group that will never play this. For some, it may be a more extreme version of the "late majority" (never hearing of the game, never having enough time/money, etc), but worse, it could be people against video games. I won't go on a rant against these individuals, just know that the quickly growing field of video games can be stimulating and incredibly helpful, and in a way, is like an interactive TV show or movie.

Blog Post #10 Assignment

 Write a regular post reflecting on the video — what you learned, what you thought were important take-aways, things that surprised you, things that frightened you. Questions to spark thinking:

What are positive aspects of more and more complex artificial intelligence and machine learning?

What about privacy, pros and cons?

What about national security?

What about online security and identity theft?

    As someone who uses computers every day, am a large fan of electronic music and video game music, have an interest in coding and animating, and am planning to pursue a major in game design, it is safe to say that my activities online can be easily tracked based on how much my hobbies and interests rely on technology, and eventually potentially AI (even though there are some things that AI cannot do, like create new, interesting ideas for games, since they're creating things based on what others have done prior).

    Despite all of this, there are still benefits to AI and machine learning, as well as its constant evolution. For one, it can help law enforcement through facial recognition. It also makes some jobs easier or not have to be done by humans, which is really helpful for dangerous jobs like high-risk medical procedures, mining, and more.

    While all of this is helpful, there is a field that I haven't talked about yet: Privacy. AI can be used to breach privacy and know nearly everything about people, from their interests to what they do on a daily basis. Companies like Google and Facebook use user preferences to better understand the user, and to give them ads that would better appeal to them. They use search terms and messages written by the user to determine this. This information is also given away to 3rd party companies and sites.

    This issue goes beyond just companies, unfortunately. Governments are also able to do this, both the U.S government and others around the world. Not only are they also able to see one's interests, but they're also able to track our every move with cameras, posts, and even our own phones, an object we take pretty much anywhere. Anything that a cybercriminal can hack into, the government can hack into as well, likely with more efficiency as well. Based on the video we have watched, China is the strongest government when it comes to surveillance. With the 600m+ cameras they have in their country, as well as the ones they are sending to dozens of other countries to help spy on their own citizens, they are going to be a powerhouse in this field.

    AI and technology has shown to be both good and evil- while they can be used for both, it all depends on what us humans tell it to do. We can modify it to make our lives better, or make our lives worse, and so much less private.

Blog Post #11 Assignment

 Write a post about what you learned from a different team. Either write about that team's presentation as a whole or zero in on a term or concept you found interesting.

On October 3 of 2023, me and several other student were put into groups to talk about a variety of categories that fit in the following categories: Awareness, mediasphere, theories, policy, and age of AI. The category I would like to focus on for this blog post is theories.

Within the different categories, there were different topics that were discussed. The first one I will write about is the Overton Window theory. this theory was formalized in 2003, and considers whether an action or idea created by a politician or leader is unthinkable, radical, acceptable, sensible, popular, etc. This all can be difficult to balance, or find what would work best, since it is all based on public opinion and standards, which can shift or change over time. Not only that, but it can also be swayed by disinformation and misinformation, so what people think or believe can vastly vary throughout the population. While there are many negatives to this, there's also some positives. For example, it can be used to help know if the general population wants or does not want something to occur, and the people in government positions can act accordingly. 

Another category in this category is confirmation bias. This is when people process information by looking for or interpreting info with their own beliefs from prior. This can make it hard to accept information that is against or contradicts your own. Most instances of confirmation bias is mostly unintentional, but it is something that is shown to affect all. It is important to be able to detect when you are showing bias, and to not let it affect what you think or do. When discovering something new, try and start with a neutral opinion and to not think of anything that can sway that until after you learn a bit about what you're learning about. It is important not to jump to conclusions about something you know little to nothing about.