APMG International APMG International Certifications ARTIFICIAL-INTELLIGENCE-FOUNDATION Questions & Answers

• Question 21:

  What are monotonous and repetitive tasks, that require accuracy BEST suited to?

  A. Human plus machine.

  B. Machine.

  C. Human.

  D. Artificial General Intelligence.

  Correct Answer: B

  Monotonous and repetitive tasks that require accuracy are best suited to machines. Machines are able to accurately and quickly perform tasks that require little to no creativity, such as data entry or image recognition. This is because machines are able to process large amounts of data quickly and accurately, and are less likely to make mistakes than humans. Additionally, machines are able to process large amounts of data without becoming bored or distracted, making them ideal for tasks that require consistent accuracy. For more information, please see the BCS Foundation Certificate In Artificial Intelligence Study Guide or the resources listed above. Search results: BCS Foundation Certificate in Artificial Intelligence Study Guide, Chapter 4: Machine Learning: https://www.bcs.org/category/19669

• Question 22:

  Healthcare can benefit from Al, and in particular Machine Learning, an example of which is?

  A. Autonomous wheelchairs.

  B. Automated blood sampling.

  C. Autonomous vehicles.

  D. Diagnostic image analysis

  Correct Answer: D

  Healthcare can benefit from AI, and in particular Machine Learning, in a number of ways. One example is diagnostic image analysis, which can help to automatically identify and classify abnormalities in medical images such as X-rays, CT scans, and MRI scans. Machine Learning algorithms can be used to detect patterns in the data which can be used to accurately diagnose diseases and illnesses.

  References:

  [1] https://www.bcs.org/upload/pdf/foundation-certificate-ai-syllabus-v1.pdf

  [2] https://www.apmg-international.com/en/qualifications-and-certifications/bc-foundation-certificate-in-artificial-intelligence/

  [3] https://www.exin.com/en/certifications/bc-foundation-certificate-in-artificial-intelligence/

  [4] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3859976/

• Question 23:

  Who was the pioneer of computer programming?

  A. Dame Wendy Hall.

  B. Karen Spark Jones.

  C. Ada Lovelace.

  D. Sophie Wilson

  Correct Answer: C

  https://www.techopedia.com/2/31564/watercooler/ada-lovelace-enchantress-of-numbers

  Ada Lovelace was an English mathematician and writer who is widely credited as the pioneer of computer programming. In 1842, she wrote an article in which she outlined the fundamental principles of computing, making her the first person

  to recognize the potential of computers and to describe algorithms that could be used to program them. Her work laid the basis for modern computing and is recognized as one of the most significant contributions to the field of computing.

  References:

  https://www.bcs.org/more/certifications/foundation-certificate-in-artificial-intelligence/

  https://www.apmg-international.com/en-gb/courses/computing-and-programming/computing-and-programming-foundation-and-certification/

• Question 24:

  An intelligent robot uses Al to do what?

  A. Sense, plan and act

  B. Plan, act and speak.

  C. Perceive, plan and act.

  D. Sense, plan and move.

  Correct Answer: C

  An intelligent robot uses Artificial Intelligence (AI) to perceive its environment, plan its actions and then act on them. This is sometimes referred to as the "sense, plan, act" cycle, and is at the heart of what makes a robot intelligent. By using

  AI, robots can sense their environment, plan their actions accordingly and then act on them in order to complete their tasks.

  For more information, please refer to the BCS Foundation Certificate in Artificial Intelligence Study Guide: https://www.bcs.org/category/18076/bcs-foundation-certificate-in-artificial-intelligence-study-guide.

• Question 25:

  What is an intelligent robot?

  A. A robot that has consciousness

  B. A robot that acts like a human.

  C. A robot that uses Al techniques.

  D. A robot that takes the place of a human.

  Correct Answer: C

  An intelligent robot is one that uses AI techniques, such as machine learning and natural language processing, to perceive, plan and act on its environment. Intelligent robots are able to process large amounts of data quickly and accurately, allowing them to make decisions and carry out tasks autonomously. Intelligent robots can be used in a variety of applications, from industrial automation to healthcare.

• Question 26:

  What technique can be adopted when a weak learners hypothesis accuracy is only slightly better than 50%?

  A. Over-fitting

  B. Activation.

  C. Iteration.

  D. Boosting.

  Correct Answer: D

  Weak Learner: Colloquially, a model that performs slightly better than a naive model.

  More formally, the notion has been generalized to multi-class classification and has a different meaning beyond better than 50 percent accuracy. For binary classification, it is well known that the exact requirement for weak learners is to be

  better than random guess. [...] Notice that requiring base learners to be better than random guess is too weak for multi-class problems, yet requiring better than 50% accuracy is too stringent.

  -Page 46, Ensemble Methods, 2012.

  It is based on formal computational learning theory that proposes a class of learning methods that possess weakly learnability, meaning that they perform better than random guessing. Weak learnability is proposed as a simplification of the

  more desirable strong learnability, where a learnable achieved arbitrary good classification accuracy. A weaker model of learnability, called weak learnability, drops the requirement that the learner be able to achieve arbitrarily high accuracy; a

  weak learning algorithm needs only output an hypothesis that performs slightly better (by an inverse polynomial) than random guessing.

  -The Strength of Weak Learnability, 1990.

  It is a useful concept as it is often used to describe the capabilities of contributing members of ensemble learning algorithms. For example, sometimes members of a bootstrap aggregation are referred to as weak learners as opposed to

  strong, at least in the colloquial meaning of the term.

  More specifically, weak learners are the basis for the boosting class of ensemble learning algorithms.

  The term boosting refers to a family of algorithms that are able to convert weak learners to strong learners.

  https://machinelearningmastery.com/strong-learners-vs-weak-learners-for-ensemble- learning/

  The best technique to adopt when a weak learner's hypothesis accuracy is only slightly better than 50% is boosting. Boosting is an ensemble learning technique that combines multiple weak learners (i.e., models with a low accuracy) to create

  a more powerful model. Boosting works by iteratively learning a series of weak learners, each of which is slightly better than random guessing. The output of each weak learner is then combined to form a more accurate model. Boosting is a

  powerful technique that has been proven to improve the accuracy of a wide range of machine learning tasks. For more information, please see the BCS Foundation Certificate In Artificial Intelligence Study Guide or the resources listed above.

• Question 27:

  What is defined as a machine that can carry out a complex series of tasks automatically?

  A. A robot

  B. A production line.

  C. A computer.

  D. An autonomous vehicle.

  Correct Answer: C

  A computer is defined as a machine that can carry out a complex series of tasks automatically. Computers are used in a variety of applications, including artificial intelligence (AI), robotics, production lines, and autonomous vehicles.

  Computers are able to carry out complex tasks thanks to their ability to process large amounts of data quickly and accurately.

  For more information, please refer to the BCS Foundation Certificate in Artificial Intelligence Study Guide: https://www.bcs.org/category/18076/bcs-foundation-certificate-in- artificial-intelligence-study-guide.

• Question 28:

  What does Prof David Chalmers describe the hard consciousness problem to be as comples as?

  A. Psychology.

  B. Turbulence.

  C. Quantum mechanics.

  D. The universe.

  Correct Answer: D

  Prof David Chalmers describes the hard consciousness problem to be as complex as the universe. He argues that understanding consciousness is as hard as understanding the universe itself, due to the number of variables and dimensions

  involved. He has compared the complexity of the problem to that of turbulence, quantum mechanics, and psychology, but believes that the problem of consciousness is even more complex than all of these.

  References:

  [1] https://www.bcs.org/upload/pdf/foundation-certificate-ai-syllabus-v1.pdf

  [2] https://www.apmg-international.com/en/qualifications-and-certifications/bc-foundation-certificate-in-artificial-intelligence/

  [3] https://www.exin.com/en/certifications/bc-foundation-certificate-in-artificial-intelligence/

  [4] David J. Chalmers, "The Hard Problem of Consciousness", in J. Shear (ed.), Explaining Consciousness: The "Hard Problem", MIT Press, 1997.

• Question 29:

  Which factor of a Waterfall' approach is most likely to result in the failed delivery of an Al project?

  A. Takes longer to deliver all functional requirements.

  B. Discourages collaboration and cross boundary communication.

  C. Takes longer to complete the design phase of the project.

  D. Discourages revisiting and revising any prior phase once it is complete.

  Correct Answer: D

  The Waterfall approach is a sequential design process in which each phase of development must be completed before the next phase can begin. This means that once a phase is complete, it is difficult to go back and make changes, as any

  changes made to the project could potentially affect all the other phases. As a result, the Waterfall approach can make it difficult to adapt to changing customer requirements or adjust to new technology. This can ultimately lead to the failed

  delivery of an AI project.

  References:

  [1] BCS Foundation Certificate In Artificial Intelligence Study Guide, Page number 19

  [2] APMG International, "What is a Waterfall Model?", https://apmg-international.com/en/blog/what-is-a-waterfall-model/

  [3] EXIN, "What is the Waterfall Model?", https://www.exin.com/blog/what-is-the-waterfall-model/

• Question 30:

  Human-centric trustworthy Al must be...

  A. quality assurance certified.

  B. continually assessed and monitored.

  C. financially sustainable.

  D. tested by humans.

  Correct Answer: B

  Human-centric trustworthy Al must be continually assessed and monitored in order to ensure that it is behaving in a safe and ethical manner. This includes conducting regular tests and audits to ensure that the Al is functioning as intended, and is not taking any actions or decisions that could potentially harm humans or their environment. References: BCS Foundation Certificate In Artificial Intelligence Study Guide, https://bcs.org/ai/certificate/ and APMG International, https:// www.apmg-international.com/qualifications/artificial-intelligence-foundation-certificate.