Since the end of last century, coding is gaining more and more attention and popularity, and is considered more and more important. Such change attributes to the fact that the new society is full of technology that integrates with our lives from various perspectives, and such technology fundamentally relies on software, while software does not exist without computer programming. With such a background, I understand the existence of such a bold claims saying coding is the new literacy, but I do not completely agree with it. However, I agree with Barack Obama’s statement in his address that “In the new economy, computer science isn’t an optional skill it’s a basic skill, right along with the three Rs.” and I think it is necessary to have everyone exposed to computer science.
But one important thing to clarify is that computer science and coding could be related, but computer science is not solely about writing codes. This arises some arguments towards introducing computer or programming to all. The article “Giving Every Student an Opportunity to Learn Through Computer Science For All” points out that problems could not be solved without being broken down into pieces related to all kinds of works such as how nurses analyze data or auto mechanics are working on machines that run millions of lines of codes. But still, undeniably, basic education for computer science would benefit everyone. According to the article “Is Coding the New Literacy?”, just like mathematics helps people build a logic way of thinking, computer science education would help people learn the capability of coding code and encourage computational thinking that can be applied to various fields rather than just promoting the idea that code is only for coders. Accepting the idea to have computer science exposed to all does not complete the process. There are numbers of challenges for introducing computer science into a typical K-12 curriculum. The first and most fundamental difficulty to fully implement the proposal is the lack of qualified teachers. Alfred Thompson, a high school computer science teacher and former Microsoft engineer points it out in the NPR article “The President Wants Every Student to Learn Computer Science. How Would that Work?” that the main problems are making a balanced new schedule with the extra course, and getting qualified teachers willing to teach high-schoolers. At least at the present stage, most of CSE students come out of college looking forward to working at one of those major IT companies, and they are not likely be satisfied being high school teachers for all those money and time they devoted during their professional education. Another challenge for adapting the K-12 Computer Science Framework is that the software development is still in a high changing rate, and it is hard or even impossible for public schools to keep up with the constant change. Considering all of these barriers, I think the ideal solution is to switch the concentration of some classic courses which are fundamental to programing, such as math; or add new basic courses that are related or contributes to higher level computer science skills, such as typing skills, and computer literacy. In fact, computer science course offered in high schools should not necessarily for following the trend of programing or adapting advanced techniques, but more for helping young kids establish a logical thinking and a different think pattern for problem solving ability. The article “Is Coding the New Literacy?” says “the greatest contribution the young programmers bring isn’t the software they write. It’s the way they think”.
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Patent, with the definition given by the United States Patent and Trademark Office, is the exclusive right granted to an invention for a limited time period. Inventions are supposed to provide new and unprecedented solutions to certain problems, and patents for them are designed to help their owners preventing others from stealing or utilizing the ideas without permission.
Regarding to their original obligation, patents should be granted to eligible works. Because they serve to maintain and protect the order of markets related to intellectual properties. They builds a foundation for the relative fairness in competitions and promotes innovations with their deserved benefits. From a morality perspective, patents are essential because they ensure the ones who devote get paid with the value of their ideas. Taking others’ words or thoughts without proper reference in writing is considered plagiarism, so should be the case for taking others innovation or ideas in commercial or any other ways of utilization. Therefore, we need patent restrict and stop people before they step into the unethical zone of copying others’ intellectual works. Patents are also important for a healthy economy. Were there not patents, the market selling intellectual products would run out of order. For example, if no patents were applied, as soon as Apple iPhones were launched, thousands of other companies could easily make and sell copied versions with lower prices, leaving Apple, the one who had worked hard to create the product got beat in the competition. As mentioned above, patents are essential to encourage competition and protect innovation which ultimately bring the society great benefits, thus, in my opinion, they could be granted to outcomes of all kinds of original and valuable ideas, regardless of their tangibility. How visualized or formulated the work procedure could be should not make much difference. I think all devotions out of innovation are equally appreciable. As long as both welding metal together to build a car and developing a computer program are original and beneficial to the society, both deserve patents. However, although, in general, the patent system is still helpful, it is becoming increasingly problematic in some cases. The most distinctive evidence of the system’s flaw is the existence of patent troll. In one case, patent trolls utilize the flaws in the patent law, and apply hundreds even thousand of patents without actually producing any products, and wait for other to use the patented idea, and suit them. Since the cost of accepting and fighting for such a suit will cost too much, most suited ones will choose to conciliate with a great amount of conciliation fee. In another case, due to the lack of financial capability, small organizations could hardly hold their patent rights when competing with giant corporations. This eventually leads to monopoly of large companies in certain industry. Either of the above occasions helps with fairness in competition or balance of the industry economy. Even though they have, so far, not completely jeopardized the patent system, they could soon bring fatal consequences and break the system if we kept ignoring it and not taking any recovery actions. Car accident a growing major cause for unnatural death every year, and over-speeding as well as collisions are two of the major cases that lead to fatal injuries. Even just simply considering these facts, I am completely supportive for self-driving cars. The rigidness of computer programs is a great advantage in the case of self-driving cars. Because the as long as the self-driving systems are more programmed and fully tested, they can avoid the lack of concentration and other errors human would commonly make. Mostly likely, with a stable control of speed, application of self-driving car could significantly decrease the number of potential accident caused by over speeding. From another perspective, if self-driving technology is widely utilized in industrial transportation such as shipping trucks, it could help with better revenue management by lowering the cost of labor forces.
However, while there are pros, there are also cons for self-driving cars. At least at its current development stage, self-driving technology still has many flaws and thus bares arguments. While the technology theoretically reduced the danger of driving, it is still incapable in some situations where prompt and improvised human actions are required. The article “What We Know and What We Don’t Know About Accidents Involving Self-Driving Cars” gives and example of Google’s self-driving cars, which are tested and announced safe, yet still caught into accidents like rear-end crushes. The programming is apparently less reliable than a human in such cases. Another argument criticizes the safety of such systems for that they have limited ability to make trade-off decisions when they are programmed to primary protect the car from hit. Because decisions made by such programming will potential lead to fatal injuries in cases where a car runs into people in order to avoid a collision with an object. Besides the uncertainty about the liability and safety of such technology, people, mostly truck drivers, are also not so positive towards the potential economic consequences such technology will likely bring. Because, even though self-driving cars could save business operator a great amount of capital from hiring drivers, it would meanwhile raise the unemployment rate among truck drivers. But Innovation Economics thinks such concern is unnecessary. Similar to the industrialization and mechanization of agriculture industry, in the case of such technological advancement, we can be reasonably assured that the economy will not only recover from the loss of truck driver jobs, but become stronger as a result of innovation. A lot of issues related to self-driving cars as mentioned above are yet solved at current development stage. And it is the stage where the government should take an active role in regulating self-driving cars to support the development. It should articulate every possible rules as comprehensive as possible to build people’s trust on and reassure them with any concerns. Unfortunately, the government is not performing well in this aspect so far. States and federal governments should work together to build an applicable regulation system for the new industry as soon as possible, or else more loss would like Tesla incidents would happen. I would be willing to own a self-driving car in the future, but certainly not with its current development with the deficiencies in programming maturity and under-established legitimized regulations. Besides, even though I agree that personal-owned self-driving car would potentially be a trend in the future, I think we will more likely see a wide application of the technology in shared or public transportations. But, indeed, either way, I believe that the automation vehicle technology will bring a subversive reformation to the world’s transportation system. The biggest trade-off is that in order to use iRedmail I have to install systems like Linux and CentOS to set DNS records for the system’s server. Apparently, although these systems are not strange to computer science engineers, they are less commonly applied in commercial desktops and laptops compared to Windows and IOS. I personally do not have any devices running systems required for setting up the iRedmail server, and I have to give up on some information and resources from original systems by switching the operating system of my computers. For some individuals or organization, whose online privacy security vitally matters to their lives, may find such a process worthwhile. Yet, for me, at least as a student so far, do not think it worth such a large input for getting online safety secure that may not bring much difference to my life, work or study. Besides, running such a private cloud requires a large amount of time and energy for system maintenance, which again, may be to costing for individual or small group users.
Nevertheless, as I mentioned, for larger organizations or specific individuals, managing a private could be worthwhile. Since the private cloud system is solely serving for one single organization, the data, hardware performance and network performance are under complete control and management of the organization itself. And such advantages bring preferable tradeoffs such as the data security, compliance, customizable performance and hybrid deployments. Data security is enhanced with private cloud systems because some of them provide dedicated hardwares. The security of private cloud depends on various factors. However, if you have the proper physical security, anti-virus software, and firewall rules in place, you can rest assured your data is as safe as if it were sitting right next to your desk. With a private cloud, you know where your servers are located and that the proper physical and network security is in place. You can meet and talk to those in charge of providing support for your hardware and come visit it if you like. A private cloud can fully utilize your hardware with better resource management because the virtualization significantly increases the value of your physical server hardware. Instead of having 5 servers that average 10% CPU utilization, you can virtualize the 5 servers on one physical server, sharing the resources. For the larger company or specific individuals, the private cloud provides some alluring benefits. In the future, I believe I will use self-managed services rather than third party ones because the self-managed services provide some alluring benefits which the third party cannot provide, and there are huge spaces for self-managed services to improve such as simplifying the installation progress, lowering the storage requirement and the price. In the future, I believe most of the people will use such independent services. To be honest, I do not have the moral standing to complain about encroachment on my own privacy when I consciously give away my information to third party services. That I do not complain is not due to any trust on third party services, but for that as a student, I do not really have the important information or privacy that I need protect completely. But for business companies, they may need more secure services to guarantee the confidentiality of their information and resources, therefore, they may carry higher concerns for the issue. With a broad aspect, Artificial Intelligence (AI) can be defined as programs that can display functions, actions or any features that would normally agreed as intelligences of humans. And based on the level of intelligence, i.e. how closely imitative of human behaviors or thoughts the AI is, AI systems are defined and categorized in three distinct groups: the weak AI, strong AI, and the kind of AI in-between of the former two (Hammond, 2015).
Systems that tend to establish and conduct human reasoning process are regarded as “strong AI”, which function as not only programs that stimulate ideas themselves, but also provide the reasoning logic as human beings would have behind the thoughts (Hammond, 2015). As to “weak AI” systems, they display human-like behaviors, but are solely serves to solve problems of systems, and the intellectual human reasoning is absent. The Deep Blue system would be an example. It is intelligently competitive with human brains, but do not present any pattern of human thinking or reasoning. Currently, the most advanced AI we have seen and applied in today’s top high-tech systems such as Google’s Alpha Go and IBM’s Watson, are those in-between the level of strong and that of weak AI technologies. These systems are built based on flows and logics of human reasoning, but do not aim at copying or imitating it. In my opinion, I do not think the Turing test is valid enough as a measure of intelligence. On a Turing test competition held in 2014 at Royal Society in London, a computer program called Eugene Goostman, simulating a 13-year-old Ukrainian boy, was said to have passed the test. 33% of the judges were convinced through a five-minute-long conversation that the program was human. However, such a process is a misrepresentation of Turing test. The origin of the test was not to check whether a computer mind can gain human’s recognition, but to evaluate whether a machine is able to think in the way a human being does (Ball, 2015). Besides, the test is not effective, if the AI really achieves the intelligence level to “pass” it. Like the story told in the film Ex Machina (2015), if the machine is human-like enough, it can pretend to be not qualified to pass the test while it is actually capable. As a student of computer science major, I have been fond of the emerging area of artificial intelligence, and had long have a impression from movies on how disputable the establishment of AI could be considering the ethical and moral conflicts or terrors could brought by it. However, I do not concern much about the potential dangers imposed by artificial intelligence. I am possessing a positive view towards AI technology, for that I firmly believe what AI brings us will be uncountable conveniences instead of any “betrayal”. In fact, at least within near future, I believe that focusing on “weaker” AI that practically help us solving problem is more essential and urgent that making huge breakthroughs in the technology. As to computing system, I do not think it could be considered as a mind. I believe in the future, the technology can make the computing system “like” a mind, but it never become a real mind. Because real human mind is not simply working with logic, but affected by numerous factors such emotions, physical feelings and etc. Furthermore, “strong AI” may brought up ethical issues if it could simulate dark sides of the human natures such as the greediness and selfishness.So far, we may not yet be ready and capable to control such problems and issues. But as long as we balance technology development and human development well, I believe we will be able to create and utilize the uttermost benefits from high technologies like Artificial Intelligence. |