Testi Inglese orale 2 (Reading between the lines)

VIDEO U.10f INITIATION WITH ANTS

In this excerpt from the Introduction to "Blink", the author Malcom Gladwell describes the part of the brain that runs our rapid decision-making system:

The author imagines asking someone to play a gambling game. In front of the player, there are four decks of cards: two red and two blue. Each card either wins him a sum of money or costs him some money, and the player has to turn over cards from any of the decks, one at a time, with the aim of maximising his winnings. What he doesn't know is that the red decks are a minefield: the rewards are high, but so are the losses. The player can really only win by taking cards from the blue decks, which offer $50 and $100 payoffs. The question is: how long will it take him to understand this?

A group of scientists at the University of Iowa did this experiment a few years ago and found out that most of us begin to understand what is going on after having...

turned over about fifty cards. We are not certain why we prefer the blue decks but, at that point, we feel that they are a better After turning over about eighty cards, most of us have figured the game out: we have some experiences, we think them through, we develop a theory and finally we put two and two together. But the scientists went forward with the experiment: they hooked each gamer up to a polygraph, a lie detector machine, that measured the stress.

What the experiment revealed is that the gamers started generating stress responses to red decks by the tenth card, forty cards before they were able to say what was wrong about those two decks. At the same time also their behaviour started to change: they started favouring the blue decks. They began making the necessary adjustments long before they were aware of what adjustments they were supposed to be making.

This experiment is a powerful demonstration of how our mind works. It tells us that when we find ourselves

In situations where are high, things move quickly and we have to make sense of a lot of new information in a short time, our brain uses two different strategies to make sense of the situation.

• The first is the conscious strategy, through which we think about what we have learned and eventually come up with an answer. This strategy is slow and needs a lot of information: in this game it takes us eighty cards to get there.
• The second strategy starts to work after ten cards and it's really smart because it picks up the problem with the red decks almost immediately. However, it has the disadvantage that it operates below the surface of consciousness: it sends a message through indirect channels, like the sweat glands on the palms of our hands. Through this system our brain reaches conclusions without immediately telling us. ➔ Thinking fast and slow

Unit 11b

1st question: how many united nations states are African?

The correct answer is 53. What's

Psychologically interesting is that if for some reason you already had a high number in your mind, you would give a higher number as an answer. For example, if someone had just been talking with you about the weather and had said that the temperature today was 82 degrees F., your answer to the African question would have been a higher number than if you had been told it was 28 degrees C. today.

2nd question: Linda is a single 31-year-old, bright and concerned with issues of social justice. Which statement is more probable? A) she works in a bank; B) she's a feminist who works for a bank. The majority of people give the answer: "B". We are influenced by the plausible details, preferring the human history to the hard logic.

3a/ 3b question: you can either have/lose £500 for certain or have a 50% chance of winning/losing £1000. Which would you choose? It seems that most of us take fewer risks when there's a chance of winning something, so we

choose the £500 for certain. However, if we are offered a chance to get out a losing situation, most of us will take the gamble, i.e. Psychologist Daniel Kahneman's studies how we make certain judgements and decisions and for this he we'll go for the fifty percent chance of losing £1000. won the Nobel Prize in Economics in 2002. What he found was what seemed like rational decisions were often based on irrational thought processes. His research, which was based on asking people certain questions, is key to understanding how emotions can affect what should be otherwise logical decisions.➔ What Kahneman is trying to demonstrate is that our intuition can be unreliable and irrational. He describes our brain as having two systems: 1. System One: where we form intuitive responses 2. System Two: where more conscious, deliberate thought occurs. Greta Pontieri But on many occasions, System One is always trying to help System Two, often with imperfect information. And so the result

can be imperfect. Reference to the text in dispensa: the experiment described by Malcom Gladwell is a powerful demonstration of how our mind works. It tells us that when we find ourselves in situations where stakes are high or even just when we've to answer some simple questions like those in the listening, our brain uses two different strategies to make sense of the situation: a conscious strategy or a smart strategy.

22. Coming soon to the library: humanoid robots It is unusual for public libraries to offer instructions in programming robots, but Westport is the first in the nation to do it with sophisticated humanoid robots made by the French robotics firm Aldebaran. They have blinking eyes, they walk, dance, they also talk in 19 different languages and they are tall as a toddler. The director of Westport thinks that robotics is the next technology coming into our lives and it's so important also from an economic-development perspective. Westport is a really innovative center:

indeed it was one of the first in Connecticut to acquire a 3D painter three years ago and to create a maker space (an area where people of all ages can try equipment to create technology). There are also other public libraries with robots, such as the Chicago Public Library, in partnership with Google. These robots are really complex: they have two cameras, four microphones, motion sensors and sonar to detect walls. They are able to recognize faces and comprehend where sound is coming from. They can even touch and feel with the help of pressure sensors. Moreover, Aldebaran has a large development community, adding new apps to facilitate everything. The growing interest in school of science, technology, engineering gives library-based robots added relevance. Matt Latham, program and maker-space coordinator at the Hoboken, the N.J. public library, stated that 3D printing and robotics are a demonstration of what will be possible in the future. Alex Giannini, Westport's digital-experience manager,immaginate i robot programmati anche per compiti pratici, come aiutare i clienti a trovare libri o dare il benvenuto ai gruppi scolastici che visitano la biblioteca. ➔ Intelligenza emotiva Unità 11a L'intelligenza emotiva (IE) è ciò che ti aiuta a gestire le tue emozioni in situazioni stressanti. La formazione sull'IE potrebbe aiutare le persone che spesso si sentono ansiose e desiderano avere più controllo sulle cose. La formazione sull'IE consiste nel imparare a comprendere i propri sentimenti e a distinguere le emozioni costruttive da quelle dannose, al fine di capire quando seguire la ragione e quando i propri sentimenti. L'IE è anche utile in termini di comunicazione e costruzione delle relazioni perché aiuta a sviluppare una migliore comprensione di come gli altri si sentono. La nostra attitudine alle emozioni spesso si forma nella nostra prima infanzia. Il primo passo nella formazione sull'IE è rendere le persone consapevoli della propria attitudine verso le emozioni, che sia sensibile o che le reprima. Ciò ci consente di controllare meglio le nostre emozioni e gestire i sentimenti negativi.such as dark predictions and excruciating regrets. You can also learn to recognise when stress, anger or excitement might be influencing your decisions. EI training also reveals which emotions you unveil to others non-verbally through what are called "micro-expressions", unconscious facial expressions that appear for only a fraction of a second and concealed express an emotion or one that has been too rapidly processed. Understanding these micro-expressions is very useful for managing relationships. For example, if you wish someone would stop talking to you because you are bored, you might look away momentarily and the other person will almost certainly pick up on this signal. ➔ Who's working for who? Unit 11c An increasing number of people are feeling that their jobs are under threat from intelligent computers and robots. Financial Times journalist Sarah O'Connor decided to pit her writing skills against a robot called "Emma", created by the techcompany Stealth. The report they had to write was about the official UK employment statistics: Sarah knew that her artificial intelligent rival would be quicker than her but felt confident that she would produce a better report. In fact, the programme produced the story in a third of the time it took Sarah. Emma also included all the right facts, gave relevant context and even gave an opinion: that the UK economy would see a period of growth. Nevertheless, the programme was unable to make a distinction between significant facts and facts that the readers would find interesting, which is what separates accurate reporting from good reporting. This tells us that AI (artificial intelligence) is intelligent, but not yet intelligent enough to make humans obsolete. But it also tells us that there are many parts of our work that can and will be done by machines in future. For many employees this could be a great advantage: machines could take over the boring parts of the work, leaving them more time to

be creative. Unfortunately, there are three fundamental problems with this idea. The first is "technological unemployment", which means that technology might replace jobs faster than we can create new types of job. Technology has already largely replaced people in manufacturing, and it is uncertain what will occur if it does the same in the services sector (banks, restaurants, shops). The second point is "machine learning", the idea that machines can learn to do tasks for which they have not been specifically programmed. When this happens, machines begin to determine the future of employment: this is already the case in stock market trading, where over three quarters of trades are now done by machines which have learned the most effective strategies. The third is "crowdwork", tasks that machines are not good at but can be done by independent human workers from their home computers. These are monotonous, low-paid jobs which often involve checking the work done.

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