1 . In US emergency rooms (ER), the average wait time to see a doctor is more than two hours. There are more patients in need than there are doctors, nurses and other staff to help them. Many parents have suffered through hours in the ER with a sick, upset child, only to get sent home because their case is not considered urgent. What if there was another choice—like a house call from an intelligent machine?
Now, a new study shows that AI systems can assess (评估) a child’s medical chart and come up with a diagnosis (诊断), a determination of what is wrong with that patient.
The study took place at Guangzhou Women and Children’s Medical Center in southern China. First, a team of doctors reviewed 6, 183 medical charts. They summarized the information in these charts into a list of keywords linked to disease-related symptoms or signs, such as “fever”. Researchers then taught these keywords to the AI system. Once trained, the system scanned children’s charts for the key terms, checking if they were present or not in order to come to a conclusion. Finally, it offered diagnoses based on the charts, narrowing down from among 55 illness categories.
Dongxiao Zhu, an assistant professor of computer science at Wayne State University who did not take part in the study, however, sees this as “augmented intelligence (增强智能)” rather than “artificial intelligence”, because the system handled only 55 illness categories. Compare that to thousands of possibilities in the real world. The machine cannot yet get into the more complex aspects of a medical decision.
Zhu is also concerned about the amount of human work that went into the study—namely, the time and energy spent by human doctors. They spent hours grading the machine’s assessments and comparing them to their own. It’s no wonder that the process took four years. Considering that, it may be a while before you can skip the ER and see a robot-doctor instead.
1. What can we infer from Paragraph 1?| A．Patients pay too much for the ER. |
| B．American doctors aren’t responsible. |
| C．Children are treated urgently in the ER. |
| D．The emergency rooms are crowded with patients. |
| A．AI systems still have a long way to go. |
| B．AI systems diagnose disease like doctors. |
| C．AI systems will take over from doctors someday. |
| D．AI systems get into complex medical decisions. |
| A．By examining a patient first. |
| B．By reviewing many medical charts. |
| C．By scanning keywords about a disease. |
| D．By observing disease-related symptoms. |
| A．They need to be improved a lot. |
| B．They will replace real doctors soon. |
| C．They are suitable for complex disease. |
| D．They help doctors make a quick analysis. |
2 . One of the curious things about social networks is the way that some messages, pictures, or ideas can spread like wildfire while others that seem just as catchy or interesting barely register at all
Before you go deep into the puzzle, consider this: If you measure the height of your male friends, for example, the average is about 170 cm. You are 172 and your friends are all about the same height as you are. Indeed, the mathematical concept of “average” is a good way to capture the nature of this data set.
But imagine that one of your friends was much taller than you. This person would dramatically skew the average, which would make your friends taller than you, on average. In this case, the “average” is a poor way to capture this data set.
Exactly this situation occurs on social networks. On average, your coauthors will be cited more often than you, and the people you follow will post more frequently than you and so on.
Now Lerman from University of Southern Caledonia has discovered a related paradox, which they call the majority illusion (多数错觉). They illustrate this illusion with an example. They take 14 nodes linked up to form a small network. They then color three of these nodes and count how many of the remaining nodes link to them in a single step.
In situation (a), the uncolored nodes see more than half of their neighbors as colored. This is the majority illusion—the local impression that a specific feature is common when the global truth is entirely different. While in situation (b) the majority illusion doesn’t occur.
So how popular is it in the real world? It’s found out that the majority illusion occurs in almost all network scenarios. “The effect is largest in the political blogs network, where 60% of nodes will have majority active neigbbours, even when only 20% of the nodes are truly active,” says Lerman.
It immediately explains many interesting phenomena. For a start, it shows how some content can spread globally while other similar content does not—the key is to start with a small number of well-connected early adopters fooling the rest of the network into thinking it is common. The affected nodes then find it natural to follow the trend. A real spread finally comes into being.
But it is not yet a marketer’s charter. For that, marketers must first identify the popular nodes that can create the majority illusion for the merger audience. These influencers must then be persuaded to adopt the desired behavior or product, which is essential to the prospect of the marketing plan.
1. The phrase “skew the average” in the 3rd paragraph most probably refers to the action of __________.| A．hiding the real average to be unrecognizable to others |
| B．producing an average against the general feature of data |
| C．working out the common feature suggested by the average |
| D．ignoring the average because of the frequency by which it is reviewed |
| A．The number of the nodes in the network |
| B．The manner of the connection between the nodes. |
| C．The decision of which nodes to be colored. |
| D．The influence of the network on the nodes. |
| A．Majority illusion rarely bas impacts except in political blogs field. |
| B．The majority illusion on social networks relies on it that people you follow post more than you |
| C．The essence of successful opinion spread is to initiate the trend with well-connected sharers. |
| D．The spread scale of ideas on networks mainly depends on the quality of content. |
| A．thoroughly understand the concept of majority illusion |
| B．accurately figure out who is the powerful person to affect others |
| C．definitely decide who are the target audience for the promotion |
| D．successfully convince the influencers to practice certain action |
| A．The social network vision that tricks your mind. |
| B．Who is stealing your network identity? |
| C．Minority network opinion spread, curse or blessing? |
| D．Have you been misled during the last political voting? |
3 . I read somewhere that we spend a full third of our lives waiting. But where are we doing all of this waiting, and what does it mean to an impatient society like ours? To understand the issue, let’s take a look at three types of “waits”.
The very purest form of waiting is the Watched-Pot Wait. It is without doubt the most annoying of all. Take filling up the kitchen sink(洗碗池) as an example. There is absolutely nothing you can do while this is going on but keep both eyes fixed on the sink until it’s full. During these waits, the brain slips away from the body and wanders about until the water runs over the edge of the counter and onto your socks. This kind of wait makes the waiter helpless and mindless.
A cousin to the Watched-Pot Wait is the Forced Wait. This one requires a bit of discipline. Properly preparing packaged noodle soup required a Forced Wait. Directions are very specific. “Bring three cups of water to boil, add mix, simmer three minutes, remove from heat, let stand five minutes.”I have my doubts that anyone has actually followed the procedures strictly. After all, Forced Waiting requires patience.
Perhaps the most powerful type of waiting is the Lucky-Break Wait. This type of wait is unusual in that it is for the most part voluntary. Unlike the Forced Wait, which is also voluntary, waiting for your lucky break does not necessarily mean that it will happen.
Turning one’s life into a waiting game requires faith and hope, and is strictly for the optimists among us. On the surface it seems as ridiculous as following the directions on soup mixes, but the Lucky-Break Wait well serves those who are willing to do it. As long as one doesn’t come to rely on it, wishing for a few good things to happen never hurts anybody.
We certainly do spend a good deal of our time waiting. The next time you’re standing at the sink waiting for it to fill while cooking noodle soup that you’ll have to eat until a large bag of cash falls out of the sky, don’t be desperate. You’re probably just as busy as the next guy.
1. While doing a Watched-Pot Wait, we tend to ___________.| A．keep ourselves busy |
| B．get absent-minded |
| C．grow anxious |
| D．stay focused |
| A．The Forced Wait requires some self-control. |
| B．The Forced Wait makes people passive. |
| C．The Watched-Pot Wait needs directions. |
| D．The Watched-Pot Wait engages body and brain. |
| A．It is less voluntary than the Forced Wait. |
| B．It doesn’t always bring the desired result. |
| C．It is more fruitful than the Forced Wait. |
| D．It doesn’t give people faith and hope. |
| A．Take it seriously. |
| B．Don’t rely on others. |
| C．Do something else. |
| D．Don’t lose heart. |
| A．exploring various causes of “waits”. |
| B．describing detailed processes of “waits”. |
| C．analyzing different categories of “waits” |
| D．revealing frustrating consequences of “waits” |
