The Last Reading

In many ways people think that with technology becoming a bigger and bigger part of our life that coding is the new literacy. This has become so much of a thing that President Obama decided to address it in his last State of the Union Address. He believes that it would be beneficial for every student to have some computer science knowledge and that learning this should start at a young age.

One of the main arguments for introducing everyone to computing is that it offers a  broad based benefit. Whether the student learning it actually becomes a programmer or not there are many skills along the way that they pick up that can be beneficial to their everyday life. For example, students can become better at puzzle skills, problem-solving skills, and increase their sequencing skills which has proven to in turn increase reading comprehension. Computing also introduces a new way of thinking about certain topics. It breeds creativity mixed with deep critical thinking. A combination valuable to any person, young or old.

Despite a lot of good that could come from introducing an initiative of this sort, there are also some drawbacks and challenges to incorporating it. First, what impact will introducing screens into classrooms at a young age have? A lot of kids can’t tolerate any kind of screen time at all. So even educational use of screen time can cause issues. On top of this, America would be introducing a new complex, technical subject. Where are all of these teachers going to come from? Most good computing teachers have the inventive of going to industry and making a lot more money than they would be making teaching. Even if teachers were available, how would school systems fit this new subject into an already packed schedule?

My belief is that computer science courses should not replace other courses but should still be offered. I think at a young age incorporating computer science class in with the music, gym, and other extra-curricular activities would be perfect. In these classes one would learn more problem-solving skills and basics of computing, they would not actually be at a computer screen putting together code and programming stuff. These first classes, offered at a young age would be more focused on algorithmic thinking. These classes should have students breaking problems down into a series of steps. Then as the students grow older and enter into high school I think a one semester class should be mandatory to take before graduating and preferably during the freshman or sophomore year. I think many students are afraid to get into computing because they think it is too challenging, however what they don’t realize is that it is challenging for everyone in the beginning. This first course will spark their knowledge and if interested computer science electives will be available.

Finally, I think that anyone can learn to program, as evidenced by NBA stars going on code academy and learning some basic, but I think knowing how to code means nothing if you cannot think of good ways to apply it.

I think that it would be beneficial for grade-schoolers and high schoolers to at least be introduced to the idea of computer science. I do think there is some danger in teaching everyone, mainly because of security hacking issues or the power you are giving to people in teaching them to code in a world filled, surrounded, and based on  technology.

Censorship

There are many reasons why the government might be trying to censor the Internet. However I think one of the main reasons is that the government might limit freedom of speech is to make themselves look good. They do not want to cause a revolt against the government or any trouble so they block out the negative media reviews on them. For example, in the article “Bing Goes Full-on Censorship in English Search Results Within China” it claimed that at one point when would search for Wikipedia in Bing it would come up with fake biographies. Clearly the government is trying to create a fake image to create peace and force people to stay.

Enforcing these laws can be done by self regulation, punishment of service providers, and arrests. Overall, the government is very strict in terms of enforcing these laws. They have a police force dedicated just for looking into the Internet. If violators are caught the website can either be shut down or arrest could be made. China has the largest number of imprisoned journalists and cyber violators.

The ethical and moral rights are complicated in this regard. On one hand, the company must abide by the rules of the country. However, some of these rules are overbearing. I understand that people need the news and will otherwise be in the dark and not fairly educated on important issues going on in their country, but providing loopholes is also unfair. There has to be a way to fight against this without providing loopholes. I believe that censorship is a major concern. Not giving people the information they deserve and depicting a false identity is unjust. I believe that tech companies should do everything in their power to fight against these very restrictive limitations.

Artificial Intelligence

To begin with, Artificial Intelligence (AI) is a sub field of computer science that has a goal of enabling the development of computers so that they are able to do things normally done by people. More specifically, these things are associated with people acting intelligently. Going further than this basic definition, once can split AI up into 3 different groups: strong AI, weak AI, and everything in between.

Strong AI focuses on simulating human reasoning. The people working towards this are trying to build systems that think but also explain how humans think as well.

On the other hand, weak AI can be defined as just trying to get the systems to work. While we might be able to build systems that can behave like humans, the results will tell us nothing about how humans think. For example, IBM’s Deep Blue, was a system that was a master chess player, but certainly did not play in the same way that humans do.

The middle camp focuses on systems that are informed or inspired by human reasoning. The people working on this are only using human reasoning as a guide rather than trying to perfectly model this. The article “What is artificial intelligence,” claims that IBM Watson is a good example of this camp. Watson builds up evidence for the answers it finds by looking at thousands of pieces of text that give it a level of confidence in its conclusion. It combines the ability to recognize patterns in text with the very different ability to weigh the evidence that matching those patterns provides. Its development was guided by the observation that people are able to come to conclusions without having hard and fast rules and can, instead, build up collections of evidence. Just like people, Watson is able to notice patterns in text that provide a little bit of evidence and then add all that evidence up to get to an answer.

It is similar in a way that it can mimic human thoughts and reasoning, but it is hard to get it to combine all of the complex parts of a human. Humans are still much more advanced. Good proof of this comes from the AlphaGo or Deep Blue systems. While the Deep Blue system was able to defeat the chess world champion, it was not good for much else. The chess world champion on the other hand can probably think through other things and hold conversations amongst much more. Going off of this, this is why I think that these kinds of systems are gimmicks or tricks. One thing one of the article does mention that can be concerning though is that developers might have developed a way to bottle something very like intuitive sense. This is one of the main differentiating points between humans and systems. If systems can gain this sense then they might move up from just being tricks. However, there is still much more developing to be done in order to reach a human level of intuitive sense.

If an AI machine could fool people into believing it is human in conversation, he proposed, then it would have reached an important milestone. The original Turing Test wasn’t intended to see if a robot could pass for a human, but rather, for deciding whether a machine can be considered to think in a manner indistinguishable from a human. Of course this depends on which questions you ask. For example, there was one instance where a customer was trying to unravel the responder to a chat he was participating in as a robot and it actually worked. The response back was that the server could not process their request at the moment. This shows that despite how well referenced the Turing Test is, it does neglect a decent amount of human aspects.

The Chinese test is as follows: Searle imagines himself alone in a room following a computer program for responding to Chinese characters slipped under the door. Searle understands nothing of Chinese, and yet, by following the program for manipulating symbols and numerals just as a computer does, he produces appropriate strings of Chinese characters that fool those outside into thinking there is a Chinese speaker in the room. The narrow conclusion of the argument is that programming a digital computer may make it appear to understand language but does not produce real understanding. This is trying to argue that the Turing Test is inadequate. Just because a computer system can hold a conversation does not mean it actually understands what is happening or going or being said.

Overall, after reading all of the articles, I do not think that one can consider a computing system a mind. That does not mean that in the future it could not be one. There is just too many missing parts and gaps between what humans can do and what the systems can do. Going along with this, I do not think that humans are biological computers. There is a lot more to us than just input and output. Take for example all of our emotions. These are super hard to replicate and each person is effected by things differently. The human mind and body is very complex and cannot just be dwindled down to a computer.

Two main ethical implications that were mentioned were with jobs and legal reliability. This has always been a concern with new innovative technology. However, in the past things and people were able to adjust and sometimes even make more of a profit. Now introducing AI into the workforce would cause tons of people their jobs and will turn world into who knows what. The other point being made in the articles with legal reliability. If systems begin to take over human jobs and computer systems then who is responsible when a mistake is made. How often will mistakes be made, is it more or less likely to happen. There are all sorts of unanswered questions when it comes to this that must be solved and figured out before ever implementing AI into every day life.