What is “the mind” and what is artificial intelligence? Coursera Quiz Answers 2022 | All Weeks Assessment Answers [💯Correct Answer]

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About What is “the mind” and what is artificial intelligence? Course

In this course, we will explore the history of cognitive science and the way these ideas shape how we think of artificial cognition.

WHAT YOU WILL LEARN

  • Describe the details of the Turing test, including its purpose, limitations, and potential impact.
  • Describe the details of Searle’s Chinese Room thought experiment, including its purpose, limitations, and potential impact.
  • Discuss previous and current attempts to create artificial systems that can pass the Turing Test in various domains.
  • Compute and outline the limitations of exponential and factorial growth functions.

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What is “the mind” and what is artificial intelligence? Quiz Answers

Week 01 Quiz Answers

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Q1. Look at the automata exhibited by the Cabaret Mechanical Theatre: cabaret.co.uk

Which of the following predecessors, do you think, is closest to the tradition in which these modern artists are working?

  • Gustave Eiffel
  • Jacques de Vaucanson
  • Eli Whitney
  • Rene Descartes

Q2. Doing some Web research, you should find that one of the following artists did astonishing (and now vanished) work in the creation of automata. Which of these artists was an automaton-builder?

  • Albrecht Dürer
  • Raphael
  • Leonardo da Vinci
  • Michelangelo

Q3. Doing some Web research, you should find that none of the following thinkers experienced a spectacular failure trying to market a “talking doll” (most people find it scary rather than appealing). Which of these thinkers ventured into the business of automata?

  • John von Neumann
  • Charles Darwin
  • Thomas Edison
  • Orville Wright

Q4. Read a bit about the “uncanny valley” on the\nWeb. Which of the following works (look them up on the Web) does not play on ideas about the “uncanny valley” to achieve a scary or eerie effect?

  • “The Sandman” by E.T.A. Hoffman
  • The movie “Dead Silence”
  • The movie “The Exorcist”
  • The story “Moxon’s Master” by Ambrose Bierce

Q5. Which of the following medieval technologies was\nmost influential in prompting people to think about similarities between living\nthings and machines?

  • Gunpowder
  • C​locks
  • Water-powered mills
  • Harbor cranes

Q6. The perceived parallels between machines and people inspire different emotional themes in literature. Which of the following themes is least prominent in this literature?

  • T​error
  • H​umor
  • W​onder
  • M​ilitary Glory

Q7. Which of the following arguments follows (according to Searle) from John Searle’s “Chinese Room” thought experiment?

  • Intelligence can only be explained by appeal to immaterial qualities that transcend scientific understanding.
  • Only evolution can produce intelligence, and since computer programs are not the result of an evolutionary process, they cannot be intelligent.
  • Arguably, animals (e.g., dogs and chimpanzees) are intelligent. Since they could not pass the Turing test, that test cannot be an adequate measure of intelligence.
  • Even if a computer did ** “pass” the Turing Test, this would not mean that the computer was exhibiting anything like human intelligence because of its lack of intentionality.

Q8. Which of the following best summarizes Searle’s response to the “Robot Reply”?

  • You could incorporate sensors and actuators (like the input from TV cameras, and motors to control arms and legs) into the Chinese characters that are used to communicate with the room.
  • Trying to build a robot to pass the Turing test is even harder than trying to program a computer to pass the Turing test.
  • Robots could never pass the Turing test unless they physically resembled humans very closely.
  • The sorts of sensors that robots might use (cameras, touch sensors, microphones, etc.) are not especially helpful to the realization of intelligence.

Q9. Jacques de Vaucanson drew parallels between machines and living beings mainly for the purpose of:

  • Advancing the philosophy of mind
  • Religious enlightenment
  • Entertainment and display
  • Studying the nature of the animal world

Q10. De la Mettrie’s ideas about mechanical interpretations of the human animal are part of a larger movement in scientific history. Which of these thinkers do you think is most representative of the tradition in which de la Mettrie was working?

  • Galileo, who emphasized the link between pure mathematics and physical experiment.
  • Newton, who visualized the solar system as a sort of “celestial clockwork”
  • Paracelsus, who linked astrological ideas and various mineral treatments to medicine.
  • Pierre de Fermat, who made fundamental advances in mathematical number theory and optics

Week 02 Quiz Answers

Practice Quiz

Q1. Self-driving cars are a particularly active (and controversial) area of current AI research. Among the following responses to the Turing test, which is most relevant (think of it as an obstacle to overcome) in creating self-driving cars?

  • The theological objection
  • The “heads in the sand” objection
  • The argument from ESP

Q2. Using the Web as a research guide, read up a bit on Joseph Weizenbaum’s famous “Eliza” (or “Doctor”) program from the early days of AI. (In fact you can even interact with a running version of the program at http://www.manifestation.com/neurotoys/eliza.php3. You take the role of patient and let the program act as your therapist.)

At the time of its creation, “Eliza” was considered an interesting AI system; today it is regarded as little more than a programming exercise. Here are some statements arguing for the unimportance of Eliza; which of these arguments is (or are) least substantial when considering Eliza as an attempt to pass the Turing test? (Choose all that apply)

  • Eliza analyzes sentences virtually entirely at a syntactic (word-based) level; so it doesn’t really know anything about the meaning of what you’re saying. A better AI program should pay more attention to semantics (or meaning), rather than simply the superficial words in a sentence.
  • Eliza doesn’t maintain anything like a model (an internal “portrait”) of the patient. It only responds to patterns of text within a few recent exchanges.
  • Doctor-patient conversations are not an interesting domain for the study of artificial intelligence or language understanding.
  • Eliza has no larger model of the conversation for instance, it doesn’t distinguish between important things you might have said (“I’m very angry at my brother today”) and unimportant (or at least obscure) things you might have said (“Nice weather today.”)

Q3. In the past year, an interesting new variation of the Turing test has emerged. Consider this article, published just this past summer in the British newspaper “The Guardian”: https://www.theguardian.com/technology/2018/jul/06/artificial-intelligence-ai-humans-bots-tech-companies

It describes a strange new variation of the Turing test (although they don’t put it that way), in which people hired by software companies, are forced into pretending to be AI systems. In other words, in this case, the person’s job is to successfully imitate a computer. (Or maybe the person’s job is to imitate an imagined computer program imitating a person. Are you lost yet?) Not unsurprisingly, this could be interpreted as a sort of troubling job to have — what if you, the customer, think you’re talking to a software system, but are actually talking to another person?… In any event, which of these strategies would be least plausible as a technique for imitating a computer in this situation?

  • Occasionally answer the customer using a slightly odd sentence structure.
  • Misspell the occasional long or difficult word in answering a question. Sometimes a given word will be spelled correctly, sometimes incorrectly.
  • Occasionally pretend not to understand the customer and ask them to rephrase a question (even when you understand it).
  • Fail to understand any references to (e.g.) current events, politics, movies, or anything “off-topic” for the main conversation.

Q4. Which of the following arguments follows (according to Searle) from John Searle’s “Chinese Room” thought experiment?

  • Intelligence can only be explained by appeal to immaterial qualities that transcend scientific understanding.
  • Only evolution can produce intelligence, and since computer programs are not the result of an evolutionary process, they cannot be intelligent.
  • Arguably, animals (e.g., dogs and chimpanzees) are intelligent. Since they could not pass the Turing test, that test cannot be an adequate measure of intelligence.
  • Even if a computer did ** “pass” the Turing Test, this would not mean that the computer was exhibiting anything like human intelligence because of its lack of intentionality.

Q5. Which of the following best summarizes Searle’s response to the “Robot Reply”?

  • You could incorporate sensors and actuators (like the input from TV cameras, and motors to control arms and legs) into the Chinese characters that are used to communicate with the room.
  • The sorts of sensors that robots might use (cameras, touch sensors, microphones, etc.) are not especially helpful to the realization of intelligence.
  • Trying to build a robot to pass the Turing test is even harder than trying to program a computer to pass the Turing test.
  • Robots could never pass the Turing test unless they physically resembled humans very closely.

Q6. Which of the following is the best summary of “Lady Lovelace’s Objection” as discussed by Turing?

  • The problem of understanding the human mind is beyond the capacity of human beings.
  • Computers, being unemotional, could never successfully imitate people.
  • Computers can only do what their programs (and thus their programmers) tell them to do; thus they are incapable of original thinking.
  • Computers are digital instruments, and living beings function on the basis of continuous (not digital) quantities, such as chemical gradients at the membranes of neurons. Thus computers could never imitate human beings.

Q7. Which of the following tasks did Turing mention as a promising beginning candidate for exploring (what would come to be called) artificial intelligence?

  • Understanding Humor
  • Chess
  • Painting
  • Aautomotive Repair

Practice Quiz

Q1. Which of the following arguments follows (according to Searle) from John Searle’s “Chinese Room” thought experiment?

  • Intelligence can only be explained by appeal to immaterial qualities that transcend scientific understanding.
  • Only evolution can produce intelligence, and since computer programs are not the result of an evolutionary process, they cannot be intelligent.
  • Arguably, animals (e.g., dogs and chimpanzees) are intelligent. Since they could not pass the Turing test, that test cannot be an adequate measure of intelligence.
  • Even if a computer did “pass” the Turing Test, this would not mean that the computer was exhibiting anything like human intelligence because of its lack of intentionality.

Q2. Which of the following best summarizes Searle’s response to the “Robot Reply”?

  • Robots could never pass the Turing test unless they physically resembled humans very closely.
  • The sorts of sensors that robots might use (cameras, touch sensors, microphones, etc.) are not especially helpful to the realization of intelligence.
  • You could incorporate sensors and actuators (like the input from TV cameras, and motors to control arms and legs) into the Chinese characters that are used to communicate with the room.
  • Trying to build a robot to pass the Turing test is even harder than trying to program a computer to pass the Turing test.

Q3. Jacques de Vaucanson drew parallels between machines and living beings mainly for the purpose of:

  • Studying the nature of the animal world
  • Advancing the philosophy of mind
  • Entertainment and display
  • Religious enlightenment

Q4. De la Mettrie’s ideas about mechanical interpretations of the human animal are part of a larger movement in scientific history. Which of these thinkers do you think is most representative of the tradition in which de la Mettrie was working?

  • Newton, who visualized the solar system as a sort of “celestial clockwork”
  • Paracelsus, who linked astrological ideas and various mineral treatments to medicine.
  • Galileo, who emphasized the link between pure mathematics and physical experiment.
  • Pierre de Fermat, who made fundamental advances in mathematical number theory and optics

Practice Quiz

Q1. First, as discussed in the preceding reading, take the “Visual Turing Test” created by New Scientist at the following website: https://www.newscientist.com/article/visual-turing-test/

O​nce you are finished taking the test, it will give you a ‘humaness’ score. What was your score? (write any percentage as a whole number e.g. write “50” for 50%)

Q2. D​o you trust this test to distinguish a human from a computer?

  • Y​es
  • N​o

Practice Quiz

Q1. W​hich piece (from the previous reading) did you think was written by a human?

  • P​iece 1
  • P​iece 2

Q2. W​hich piece did you like better?

  • P​iece 1
  • P​iece 2

Week 03 Quiz Answers

Q1. Hilary Putnam’s article “The Nature of Mental States” (1967) presents an argument for a functionalist theory of mind. Which of the following statements is not representative of the functionalist view?

  • It is easier to construct a functionalist account of a state like pain than a “brain-state” account, because the latter forces us to look for shared low-level brain-states between all sorts of different entities (like humans and crabs), whereas the functionalist account only needs to draw parallels between the abstract elements (like value judgment systems) of the two entities.
  • The functionalist account is closer than the brain-state account to explaining an entity’s behavior (e.g. it explains more directly why an animal that is “thirsty” will take steps to drink).
  • The functionalist account makes for more productive science than the brain-state account, since it generates interesting questions and experiments to explore.
  • The functionalist account is less susceptible to charges of “mind-body dualism” (the idea that mind and body are entirely different types of entities, and that an immaterial “soul” can direct the body) than the brain-state account.

Q2. Before William Harvey promoted the analogy that the heart is like a pump, most physicians followed the classical analogy (due to Galen). Using the Web a source of research, answer; which of the following does not characterize Galen’s model of the heart?

  • The heart is a source of internal heat in the body.
  • The heart’s purpose is purification of blood.
  • The heart has two major chambers (not four, as we know today).
  • The heart is soft tissue.

Q3. The idea of functionalism holds a certain natural appeal for computer scientists. Which of these statements comes closest to explaining why that’s the case?

  • Functionalist philosophers are generally people who have been professional computer programmers.
  • Functionalism emerged as a philosophical idea around the same time as the computer emerged historically as a working device.
  • Just as we can study algorithms without worrying about the fine structure of the computers on which they run, we can study cognitive models independent of the physical substrate (neural or mechanical) on which they run.
  • Computer scientists find it difficult to model the complexity of the living, physical brain.

Q4. Which of the following analogies has not played an important role in the history of science?

  • The solar system is like a clockwork.
  • Cells are like corporate organizations.
  • The structure of the atom is like that of the solar system.
  • The heart is like a pump.

Q5. Scientific analogies, in general, are not exact (nor are they supposed to be). Which of these observations does not reveal a flaw in a common scientific analogy?

  • Water running through pipes is a pretty good analogy for Ohm’s Law (V=IR), but it doesn’t provide any understanding of elements like capacitors or inductors.
  • If the atom is structured like the solar system, it isn’t clear why electrons are only found in discrete “shells” around the nucleus, rather than at any radius whatever.
  • If the solar system is like a clockwork, it’s not clear why it doesn’t “run down” the way clocks do.
  • If the solar system is like a clockwork, then we should be able to tell time by the movement of the sun, moon, and planets in the sky. We tell time this way, at least sometimes!

Q6. In responding to the behaviorist tradition of psychology, which of the following was not an element of the computational metaphor of mind?

  • We do not have to treat the mind as a “black box” because we can now “open it up” and look at (and experiment with) different computational models of thinking.
  • Computers can be linked together to communicate with each other directly, providing an analogy to conversation (or, perhaps, to telepathy).
  • Notions such as “language rules” or “associative ideas” can be modeled computationally and thus can be studied in their own right, even if we cannot directly see them operating in the human brain.
  • We can perform experiments on models of thinking by implementing them in computers, and comparing the behavior of the models to human or animal performance.

7. Which of the following is not a usual tenet of functionalism?

  • Thinking can take place only in human or animal brains.
  • Mind is to brain as software is to hardware.
  • We can study models of thinking independent (more or less) of our ideas about how the brain works, since the same models can be implemented on all sorts of physical “machinery”, including brains and computers.
  • The essence of thinking derives from the (complex) interwoven structure of algorithmic elements that comprise the programmatic description of mind.

Week 04 Quiz Answers

Practice Quiz

Q1. Look up the “hidden chair” illusion at: https://www.moillusions.com/the-hidden-chairs/

How does this illusion illustrate the difficulty of the vision problem?

  • Chairs have shapes that are too complex for our vision system to interpret correctly.
  • It’s hard to determine the shape of an object when it isn’t moving.
  • The very same two-dimensional scene can be produced by multiple arrangements of elements in three-dimensions
  • We need to touch objects to interpret their shapes correctly.

Q2. Which of the following can be said of “impossibility proofs” such as Turing’s proof of the impossibility of solving the “halting problem”?

  • Knowing that something is impossible is, historically, often an important advance to theoretical knowledge.
  • Once something is proven impossible to do, we needn’t think about the issue at all anymore.
  • It isn’t really possible to determine that something is impossible. Perhaps we haven’t thought of a better way to accomplish the task.
  • It’s usually easy to determine whether some task (like trisecting an angle with straightedge and compass) is impossible.

Q3. Why do the vision and language problems seem easy to us?

  • Vision and language are easy problems for all organisms, and for computers as well.
  • When we make mistakes in vision or language we are corrected by others around us, who effectively “teach” us how to see and speak.
  • Everyone seems to learn how to see and how to speak by a relatively early age, so the problems seem easy, though they prove to be hard to represent in program form.
  • Vision is easy since just about all animals manage it; language, being a human capability alone, is uniquely hard.

Q4. Consider the famous “farmer crossing the river with a chicken, a fox, and bag of grain” problem (a brief statement of the problem can be found at https://riddlesbrainteasers.com/fox-chicken-sack-grain/).

Which of the following is not true of this problem?

  • One cannot represent this problem in a problem space format.
  • One can solve this problem by systematic search of a problem space.
  • The size of the problem space graph for this problem is relatively small.
  • This problem is far easier than Rubik’s Cube.

Q5. Suppose we have a “brute-force” technique for checking a 3-digit combination (like “048” or “311”). It would take 1000 guesses (at worst) to go through all the possibilities. Now we add three more digits to our combination, which means that it will take a million guesses to go through all the possibilities. Now we add three more digits, which means it will take a billion guesses. Which of the following expresses the time complexity of this technique, where N is the number of digits in the combination?

  • For an N-digit combination, we need 10 * N guesses.
  • For an N-digit combination, we need 100 * N guesses.
  • For an N-digit combination we need 10^N guesses.
  • For an N-digit combination we need N^10 guesses.

Q6. Poke around the Web to see some descriptions of the Hamiltonian cycle problem. As it happens, the only sure-fire algorithm for solving the Hamiltonian cycle problem for a graph with n vertices is to list all possible arrangements of the n vertices (there are n! of those), and see whether any one of them corresponds to an actual cycle of edges present in the graph. So the problem requires exponential time (in the number of vertices) to solve. Which of the following statements is also true of this problem?

  • Making a (perhaps very lucky) guess of a correct cycle, and checking that this guess is correct by examining the graph, is relatively easy.
  • You can usually solve the Hamiltonian cycle problem by eye, even for larger graphs.
  • For a small graph (of, say, 9 or fewer vertices) it is still realistically hopeless to solve the Hamiltonian cycle problem.
  • The Hamiltonian cycle problem is an obscure mathematical oddity, so no one regards it as an important problem.

Q7. When we say of a particular problem, “This is a hard problem”, we might mean all sorts of things. Which of these very likely isn’t what we really are saying?

  • I have no idea if this problem is approachable, or even well-defined.
  • Solving this problem has been proven to be impossible.
  • We might be able to get an approximate working solution to this problem, but getting a perfect solution is impossible.
  • No one has ever stated this problem before.

Q8. Look up some videos or animations of people solving the Tower of Hanoi problem (e.g., on YouTube). These examples show an initial puzzle of (say) 6, or perhaps 7 or even 8 disks. Why doesn’t anyone show the solution for a tower of 100 disks?

  • It is hard to stack up 100 disks for the initial puzzle.
  • It is hard to afford 100 disks for a physical puzzle.
  • The solution for a small number of disks is inapplicable to larger versions of the problem.
  • The solution requires about 2^100 steps, and even if each of those steps takes only a microsecond, the resulting video would be impossibly long in human terms.

Q9. Which of these problems is not easy for a computer to solve? (Here, “easy” means: we know an algorithm to solve the problem, and the algorithm runs in “short” – that is, non-exponential – time.)

  • Find the square root of 7 to within 20 decimal places.
  • Find the largest perfect square less than 20,000,000.
  • Count the number of occurrences of the word “whale” in Moby Dick.
  • Find the best opening move in chess.

Q10. As a rule, interpreting adjectives in natural language involves some notion of vagueness (some computational treatments of adjectives employ a technique called “fuzzy logic”). Which of the following adjectives is not vague in its interpretation?

  • Prime (as applied to positive integers)​
  • Beautiful
  • Cheerful
  • R​ed

Q11. Which of the following questions does not involve some aspect of probability, uncertainty, or vagueness in its answer?

  • Is today a sunny day?
  • Will the Colorado Rockies win the World Series in 2035?
  • What is the greatest common divisor of 4,000,000 and 4,000,003?
  • Were Julius Caesar’s last words, “Et tu, Br

Practice Quiz

Back in the 1960s, the group Spiral Staircase performed a song called “I Love You More Today than Yesterday”, which includes the lyrics, “I love you more today than yesterday, but only half as much as tomorrow.” Suppose the group first sang that song on (say) January 1, 1969. By how much would the singer’s love have increased at the end of one year (January 1, 1970)?

P​lease write your answer as an exponential expression with a base of 2 (i.e. write it as “2^x”

Q2. Suppose you have a piece of paper in the shape of a circle, with a circumference of 8 feet. (It’s a pretty large piece of paper!) Now you fold the circle in half to produce a semi-circle; then fold that over to produce a quarter-circle; then fold that to produce an eight-size wedge of a circle; and so forth. How many folds (assuming, counterfactually, that the paper could withstand this) would it take before the edge of the remaining wedge is less than 0.01 inch?

Q3. If you look at a diagram of a chess game in the middle of play (the sort of diagram you might see in a news report of a chess match), it’s generally a good estimate that the player whose turn it is has about 30 alternative moves available. So let’s imagine a chess board “in mid-game”, with White to play: White has 30 alternative moves that he or she could make. In return, depending on the move that White makes, Black will have 30 alternative response moves. On the next move, White will have 30 possible responses to each of Black’s countermoves, and so forth. Now, suppose you are writing a computer program to find the best move for White with the original diagram; and you want to look ahead 5 moves-and-countermoves for White and Black. At the end of each possible sequence of 5 moves-and-countermoves, there is a distinct final chessboard arrangement. How many of these distinct possible boards are there? (Your answer should suggest to you why it is functionally impossible to write a “perfect” chess-playing program despite the fact that chess is a game with only a finite number of possible arrangements of pieces.)

Practice Quiz

Q1. The “Traveling Salesman” problem is a famous instance of a problem for which it is easy to guess and check a solution, but which requires exponential time to solve exactly. Here, informally, is the problem: You are given a map of 100 cities in the US, with the distance between each pair of cities. Your job is to start at a given city (say, Boulder); visit each of the other 99 cities exactly once; and then return to Boulder. Naturally, there are many itineraries you could choose to accomplish this. Your goal is to find the minimum-total-distance itinerary that accomplishes your goal. (Sometimes the goal is phrased by stating a target value: i.e., your goal is to find any itinerary that visits each city exactly once, and requires at most miles of travel.)

  The sure-fire approach to this problem is to (first) list out all the possible 99-city itineraries (we assume Boulder is the first and last city); sort the list according to miles traveled; and select the cheapest route. How long is our list of possible 99-city itineraries?

P​lease write your answer as a coefficient and a factorial symbol (i.e. X!).

Q2. Is this “sure-fire” method practical?

Q3. Sometimes when people first hear about the Traveling Salesman problem, they think: “Oh, that’s not hard. Start with a city on the map; move to the nearest unvisited city; and then on each subsequent step, move to the nearest still-unvisited city, until you’re done.” This strategy is called a “greedy strategy”: it always goes to the nearest allowed step.

Now consider four cities, all placed along the number line. City A is at point 0, City B at point 2, City C at point 3, and City D at point 10: 

 A          B   C                                    D

00-01-02-03-04-05-06-07-08-09-10 

Now, start a traveling salesman tour at City B, and use the greedy algorithm to choose your tour of the four cities, beginning and ending at B. How long is the greedy algorithm’s tour

Q4. Does the greedy algorithm produce the lowest-cost tour?

  • Y​es
  • N​o

Q5 . Which of the following tours will produce the shortest length tour? Choose all that apply.

  • B-A-C-D-B
  • B-A-D-C-B
  • B-D-C-A-B
  • B​-D-A-C-B
  • B​-C-A-D-B
  • B-C-D-A-B

Q6. There are proponents of a new type of computing that uses strands of DNA in a test tube to perform computations–to solve problems like the “Traveling Salesman” problem. These proponents note that in a small volume, there are trillions of small DNA chunks that could (in effect) try trillions of different tours for the salesman, and report the shortest tour. Here’s your question: Suppose the salesman has to visit N cities. How big does N have to be before the number of tours that he would have to test (in the worst case) is larger than a trillion? (And you’ll need to use a calculator!)

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Conclusion

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