Annotations of A.I. Articles, Set #2

Anonymous
timer Asked: Sep 19th, 2018
account_balance_wallet $10

Question Description

Please use the following steps to complete this assignment:

Step 1: Download the Word document version of the A.I. Articles, Set #2, located in this module. Be sure to save this document to your computer, flash drive, or Google Drive. You can use the annotation tools in Microsoft Word or Google Docs, or you can print the articles and annotate by hand. It is your choice, so long as you upload your document.

Step 2: Using the methods you learned about in "Active Reading Strategies," annotate the articles, using multiple methods, such as highlighting, underlining, bold, etc. It is important that you indicate what the different methods mean. For example, Bold=Words I Need to Look Up and Highlighting=Important Ideas.

Step 3: Include some notes/comments/questions--either in the margins or in a different font/color on the article as well. Your task is to prove you read the article thoroughly.

Step 4: Upload your document to this assignment submission area.

There is a grading rubric attached to this assignment link, which you can view before you submit your assignment.

Below are two articles about Artificial Intelligence (A.I.). These articles focus on the positive aspects of this technology.Last week, you read two articles articles that focused on the pnegative aspects. Please download the articles using the Word document I have provided for you and read them carefully--perhaps more than one time. Then, using the "Active Reading Strategies" handout, annotate the articles by using underlining, highlighting, and other note-taking techniques. By Wednesday, you will be asked to submit your annotations on these articles.

also read

https://www.bustle.com/articles/134854-8-tips-for-...

Unformatted Attachment Preview

A.I. Articles, Set #2 (Positive Aspects) Learning to Love Intelligent Machines By Garry Kasparov The Wall Street Journal April 14, 2017 8:48 a.m. ET Twenty years after famously losing to Deep Blue, chess champion Garry Kasparov says that it’s time to embrace AI and its liberating potential. ILLUSTRATION: PEP MONTSERRAT It was my blessing and my curse to be the world chess champion when computers finally reached a world championship level of play. When I resigned the final match game against the IBM supercomputer Deep Blue on May 11, 1997, I became the first world champion to be defeated in a classical match by a machine. It is no secret that I hate losing, and I did not take it well. But losing to a computer wasn’t as harsh a blow to me as many at the time thought it was for humanity as a whole. The cover of Newsweek called the match “The Brain’s Last Stand.” Those six games in 1997 gave a dark cast to the narrative of “man versus machine” in the digital age, much as the legend of John Henry did for the era of steam and steel. But it’s possible to draw a very different lesson from my encounter with Deep Blue. Twenty years later, after learning much more about the subject, I am convinced that we must stop seeing intelligent machines as our rivals. Disruptive as they may be, they are not a threat to humankind but a great boon, providing us with endless opportunities to extend our capabilities and improve our lives. Many of the great early figures in computer science dreamed of creating a machine that could play chess. Alan Turing published the first chess program in 1953. A computer to run it didn’t yet exist, so he flipped through pieces of paper to run his algorithm, a “paper machine” that could actually play a recognizable game of chess. It took much longer than most early experts thought it would for machines to challenge the best human chess players. But by the early 1980s, it was becoming clear that it was only a matter of time before ever-faster hardware would crunch positions fast enough to do the job. It turned out that a computer did not need to mimic human thought to play like a chess grandmaster. Deep Blue didn’t think like I did about which move to play any more than a calculator needs a pencil and paper to perform long division. The ingredients are similar—a combination of memory, evaluation and calculation—but while a grandmaster uses experience to focus on the most relevant factors, the machine grinds through every possible move for both sides, going deeper and deeper with each pass. During my 20 years at the top of the chess world, from 1985 to 2005, chess-playing machines went from laughably weak to the level of the world champion. It was a startling transformation to experience firsthand, and it was impossible not to feel unsettled, even threatened, by their rapid progress. These are the same sensations that many are feeling today, as intelligent machines advance in field after field. Few people will experience the dramatic, head-to-head competition against a machine that I experienced, of course, but the sensation of being challenged, surpassed and possibly replaced by an automaton, or an invisible algorithm, is becoming a standard part of our society. Speaking from painful personal experience, I would suggest that this is the wrong frame of reference to approach the issue, and it is having a negative influence when we desperately need more optimism. The “human versus machine” narrative rose to prominence during the industrial revolution, when the steam engine and mechanized automation in agriculture and manufacturing began to appear at large scale. The story line grew more ominous and pervasive during the robotics revolution of the 1960s and 1970s, when more precise and intelligent machines began to encroach on unionized jobs in manufacturing. The information revolution came next, culling millions of jobs from the service and support industries. Now we have reached the next chapter in the story, when the machines “threaten” the class of people who read and write articles about them. We see headlines every day about how the machines are coming for the lawyers, bankers, doctors and other white-collar professionals. And make no mistake, they are. But this is good news. Every profession will eventually feel this pressure, and it must, or else it will mean that humanity has ceased to make progress. Waxing nostalgic about jobs lost to technology is little better than complaining that antibiotics put too many gravediggers out of work. The transfer of labor from humans to our inventions is nothing less than the history of civilization. It is inseparable from centuries of rising living standards and improvements in human rights. What a luxury to sit in a climate-controlled room with access to the sum of human knowledge on a device in your pocket and lament that we don’t work with our hands anymore! There are still plenty of places in the world where people work with their hands all day, and also live without clean water and modern medicine. They are literally dying from a lack of technology. There is no going back, only forward. We don’t get to pick and choose when technological progress stops or where. People whose jobs are on the chopping block of automation are afraid that the current wave of tech will impoverish them, but they also depend on the next wave of technology to generate the economic growth that is the only way to create sustainable new jobs. I understand that it is far easier to tell millions of newly redundant workers to “retrain for the information age” or to “join the entrepreneurial economy” than to be one of them or to actually do it. And who can say how quickly all that new training will also become worthless? What professions today can be called “computer proof”? Many jobs today didn’t even exist 20 years ago, a trend that will continue and accelerate. Mobile app designer, 3-D print engineer, drone pilot, social media manager, genetic counselor—to name just a few of the careers that have appeared in recent years. And while experts will always be in demand, more intelligent machines are continually lowering the bar to creating with new technology. Compare what a child can do with an iPad in a few minutes to the knowledge and time it took to do basic tasks with a PC just a decade ago. These advances in digital tools mean that less training and retraining are required for those whose jobs are taken by robots. It is a virtuous cycle, freeing us from routine work and empowering us to use new technology productively and creatively. Machines that replace physical labor have allowed us to focus more on what makes us human: our minds. Intelligent machines will continue that process, taking over the more menial aspects of cognition and elevating our mental lives toward creativity, curiosity, beauty and joy. These are what truly make us human, not any particular activity or skill like swinging a hammer—or even playing chess. —Mr. Kasparov is the chairman of the Human Right Foundation and a senior visiting fellow at the Oxford Martin School. This essay is adapted from his new book, “Deep Thinking: Where Artificial Intelligence Ends and Human Creativity Begins,” which will be published by PublicAffairs on May 2. Artificial intelligence isn't the scary future. It's the amazing present. By Editorial Board Jan. 1, 2017 Chicago Tribune The year 2017 arrives and we humans are still in charge. Whew! The machines haven't taken over yet, but they are gaining on us. Google's DeepMind AlphaGo computer program recently beat the world champ at Go, a complex board game, while Japanese researchers plan to build the world's fastest supercomputer for use on artificial intelligence projects. It will do 130 quadrillion calculations per second, which is, um, really, really fast. Ask Siri for details. She can explain it better than we can. The essence of artificial intelligence is massive, intuitive computing power: machines so smart that they can learn and become even smarter. If that sounds creepy, you are overthinking the concept. The machines are becoming quicker and more nimble, not sentient. There is no impending threat to humanity from computers that become bored and plot our doom. HAL, the computer villain from "2001: A Space Odyssey," is fictional. Yet ... advances in the field of artificial intelligence occur at such a breakout pace they are redefining the relationship between man and machine. Computer scientist David Gelernter says the coming of computers with true humanlike reasoning remains decades in the future, but when the moment of "artificial general intelligence" arrives, the pause will be brief. Once artificial minds achieve the equivalence of the average human IQ of 100, the next step will be machines with an IQ of 500, and then 5,000. "We don't have the vaguest idea what an IQ of 5,000 would mean," Gelernter wrote in The Wall Street Journal. A basic test of AI tolerance is your opinion of the self-driving car, which belonged to the sci-fi future a decade ago. Today you can hail one in Pittsburgh. Driverless vehicles rely in part on a form of artificial intelligence known as deep learning — algorithms that can make complex decisions in realtime based on accrued experience. Ford wants to have an autonomous truck on the roads by 2020. The great promise is that robot drivers will never make dumb mistakes at the wheel or fail a Breathalyzer test. But they could render obsolete entire professions: long-distance trucker, for example, or cabbie. Experts hoping to illustrate the potential of artificial intelligence without frightening people conjure the image of the know-it-all yet obsequious digital assistant. It will know where to buy the perfect gift, based on algorithms that understand the latest trends and your family's preferences. And oh, it noticed that you're walking funny. Is your back acting up again? At the hospital, it will analyze an MRI better than doctors can. The frontiers are limitless: analyzing stocks, managing energy use, discovering new drugs. "I think we're going to need artificial assistance to make the breakthroughs that society wants," Demis Hassabis, DeepMind's CEO, told Wired magazine. "Climate, economics, disease — they're just tremendously complicated interacting systems. It's just hard for humans to analyze all that data and make sense of it." You may already have benefited from artificial intelligence without realizing it. Several months ago, Google Translate upgraded to what it calls the Google Neural Machine Translation system. The program relies on a brainlike computational network that sifts through its database to arrive at a logical, nuanced meaning for any sentence in just about any language. Here is the old Google Translate struggling to turn a Japanese sentence of a Hemingway line back into English: "Whether the leopard had what the demand at that altitude, there is no that nobody explained." And the new Google Translate, firing its electronic neurons: "No one has ever explained what leopard wanted at that altitude." Missing an article ("the"), but otherwise perfect. Writing about Google Translate and Hemingway in a New York Times magazine article titled "The great AI awakening," journalist Gideon Lewis-Kraus pondered the significance of a machine that masters human language: It could be "the major inflection point" in the development of "true artificial intelligence." Be awed, but not afraid. Technically, computers may outthink us, but humans will always have the edge because we are more creative. After all, we built the machines. Active Reading Strategies Pre-Reading Strategies of Proficient Readers Surveying/Skimming/Previewing: What Proficient Readers Do Automatically         Look for head-notes, biographical information about the author, and other explanatory material. Survey the organization of the text; note the title; look for text divisions, section headings, and subtitles. Skim visuals; note relationship between visuals and specific text segments. Identify author, publication type, and date. Identify target audience. Read first and last paragraphs to identify the topic and the author’s conclusion/thesis. Identify terms that indicate the author’s position on the topic. Note the length of text to budget time for reading sections or entire piece. Drawing Conclusions from Pre-Reading Strategies Making Predictions Based on Textual Clues and Prior Knowledge     Infer from the title and other external features what information/ideas this text might present. Turn the title into a question and write out a one-sentence answer to the question after reading the text (repeat procedure for any section headers). Based on the previewing of the text, predict the author’s purpose for writing the text. Based on the information gathered so far, predict the position (positive or negative) the author will take on this topic. Annotating the Text Staying Actively Engaged with the Material during the Reading Process    Mark the pages and margins, using pens and/or highlighters. o Use symbols, like arrows to connect ideas. o Underline or highlight key words/phrases. o Put a question mark next to ideas you aren’t clear on. o Circle or put a box around words you need to look up in the dictionary. o Write a summary of each paragraph or section. Use post-its or flags to highlight sections or include notes beyond what you can fit in the margins. Aim to highlight about 15-20% of the text for each page. Summarizing the Text Retaining the Material after the Reading Process          An effective summary is a briefer version of a piece of writing in your own words. Learn to use a dictionary and thesaurus effectively if you need help thinking of different ways of saying things. Including than 3 consecutive words verbatim from the original source constitutes as plagiarism. Avoid quotations unless there is a very specific phrase that needs to stay intact. Always begin a summary with the title, type of source, author’s full name, and thesis (overall main idea of the reading). Stick to main ideas and major supporting details only. Use present tense and 3rd person point-of-view. Include the ideas in the same order the author did (chronological). Use templates and transitions to connect ideas (avoid a “list” summary). Avoid including your own opinion or misrepresenting the author’s original ideas. Sample Summary According to Paul Insel and Walton Roth, in the article, “Exercise for Health and Fitness,” published in The New York Times on August 4, 2012, physical fitness has many benefits for our well-being and can only be achieved through a variety of regular exercise. First, the authors define physical fitness as qualities which permit the body to accommodate various “demands of physical effort.” Next, the authors explain the many aspects of physical fitness which are Cardiorespiratory endurance, muscular strength, muscular endurance, flexibility, and body composition. In addition, the authors argue that exercise provides many benefits for people. One example is improved physical traits (better heart functioning, a more effective metabolism, improved body makeup—more muscle and less fat. Another is disease prevention (like Cancer, Diabetes, etc.). And last is improvement in psychological and emotional wellness, improved immune function, and prevention of injuries. Finally, the authors argue that exercise can help people live longer, healthier lives. Templates & Transitions *Using some of these templates (academic sentence starters) and transition words/phrases will strengthen your argumentative writing as well as vary your sentence structure. It will also help you connect your ideas more clearly for your reader. Introducing Quotations     X states, “_____________________.” According to X, “_____________________.” In his/her article, “_________________,” X maintains that “_____________________.” In X’s view, “_____________________.” Explaining Quotations in Your Own Words (Summary)               In X’s article, “____________________,” he/she asserts that ____________________. X agrees that ___________________. X claims that ____________________. X explains that ____________________. X demonstrates that ____________________. X insists that ____________________. X reminds us that ____________________. X reports that ____________________. X suggests that____________________. X emphasizes the importance of ____________________. Basically, X is arguing that __________________________. In other words, X believes __________________________. X’s point is that __________________________. To put it another way, __________________________. Providing Your Opinion about the Quotation (Analysis)  I agree that _________________ because my experience _____________ confirms it.  X is surely right about ____________ because ____________.  I wholeheartedly endorse what X calls ___________________.  X matters because ___________________.  X is important since __________________. Common Transitions to Be Used in Any Paper Addition Elaboration Cause & Effect Concession also and besides furthermore in addition in fact indeed moreover so too actually by extension in short that is in other words to put it another way to put it succinctly ultimately accordingly as a result consequently hence it follows, then since so then therefore thus admittedly although it is true that granted I concede that of course naturally to be sure Comparison Example Contrast Conclusion along the same lines in the same way likewise similarly after all as an illustration consider for example for instance to illustrate specifically to take case in point although but by contrast conversely even though however in contrast nevertheless/nonetheless on the contrary on the other hand regardless whereas while yet as a result consequently hence in conclusion in short in sum to summarize Introduction & conclusion required Add a photo, meme, or gif for each item in your list. LISTICLE TECHNOLOGY & A.I. Create a BuzzFeed-Style Article Once you have chosen a specific topic involving some aspect of technology and artificial intelligence, create a 5-10 item list that will help your reader understand it better. Some examples are “5 Reasons Robots Can Save Lives,” or “7 Ways A.I. Threatens Humanity.” Consider ordering your items emphatically—least important to most important. Also, be sure that the sources you cite are credible and current. You should cite at least one of the articles you were assigned from this course. You do not need to do outside research, but you are welcome to. You should be citing journal or newspaper articles, not web sites or blogs. While you do not need a separate Works Cited page for this assignment, you do need to include your citations somewhere, either as you go or at the end of the Listicle. Number each item in your list. Integrate quotations from 2-3 credible articles. Use at least one real or hypothetical example for each item in your list.  Your listicle should be 1,000-1,500 words total.  Integrate 5-10 words/phrases from the Templates & Transitions handout. Highlight these. Finally, this 100-point assignment will also require you to adhere to the features listed on the right-hand side of this document. English 120 Fall 2018 Prof. Sarah Martin ...
Purchase answer to see full attachment

Tutor Answer

peachblack
School: UT Austin

Please find attached. In case you need edits, feel free to let me know.

A.I. Articles, Set #2 (Positive Aspects)

Learning to Love Intelligent Machines
By Garry Kasparov
The Wall Street Journal
April 14, 2017 8:48 a.m. ET

Twenty years after famously losing to Deep Blue, chess champion Garry Kasparov says that it’s time to
embrace AI and its liberating potential.
ILLUSTRATION: PEP MONTSERRAT

It was my blessing and my curse to be the world chess champion when computers finally reached
a world championship level of play. When I resigned the final match game against
the IBM supercomputer Deep Blue on May 11, 1997, I became the first world champion to be
defeated in a classical match by a machine.
It is no secret that I hate losing, and I did not take it well. But losing to a computer wasn’t as
harsh a blow to me as many at the time thought it was for humanity as a whole. The cover of
Newsweek called the match “The Brain’s Last Stand.” Those six games in 1997 gave a dark cast
to the narrative of “man versus machine” in the digital age, much as the legend of John Henry did
for the era of steam and steel.

But it’s possible to draw a very different lesson from my encounter with Deep Blue. Twenty
years later, after learning much more about the subject, I am convinced that we must stop seeing
intelligent machines as our rivals. Disruptive as they may be, they are not a threat to humankind
but a great boon, providing us with endless opportunities to extend our capabilities and improve
our lives.
Many of the great early figures in computer science dreamed of creating a machine that could
play chess. Alan Turing published the first chess program in 1953. A computer to run it didn’t
yet exist, so he flipped through pieces of paper to run his algorithm, a “paper machine” that could
actually play a recognizable game of chess.
It took much longer than most early experts thought it would for machines to challenge the best
human chess players. But by the early 1980s, it was becoming clear that it was only a matter of
time before ever-faster hardware would crunch positions fast enough to do the job. It turned out
that a computer did not need to mimic human thought to play like a chess grandmaster.
Deep Blue didn’t think like I did about which move to play any more than a calculator needs a
pencil and paper to perfor...

flag Report DMCA
Review

Anonymous
Goes above and beyond expectations !

Brown University





1271 Tutors

California Institute of Technology




2131 Tutors

Carnegie Mellon University




982 Tutors

Columbia University





1256 Tutors

Dartmouth University





2113 Tutors

Emory University





2279 Tutors

Harvard University





599 Tutors

Massachusetts Institute of Technology



2319 Tutors

New York University





1645 Tutors

Notre Dam University





1911 Tutors

Oklahoma University





2122 Tutors

Pennsylvania State University





932 Tutors

Princeton University





1211 Tutors

Stanford University





983 Tutors

University of California





1282 Tutors

Oxford University





123 Tutors

Yale University





2325 Tutors