AI For Everyone Answers Week 4 | Coursera

DeepLearning.AI: AI For Everyone Week 4 Quiz Answer

About the course:

AI for Everyone is an insightful and comprehensive online course developed by DeepLearning.AI in collaboration with Coursera. This course provides learners with a holistic understanding of artificial intelligence (AI) and its impact on various industries. Designed for individuals with non-technical backgrounds, this course equips learners with the knowledge necessary to navigate the AI landscape effectively.

Throughout the course, learners will engage with engaging video lectures, hands-on exercises, and interactive quizzes to develop a solid foundation in AI concepts. They will gain a practical understanding of AI technologies, including machine learning, deep learning, and neural networks. By exploring real-world case studies and industry applications, participants will discover the transformative potential of AI in domains such as healthcare, finance, marketing, and more.

Key Learning Objectives:

• Understand AI Fundamentals: Gain a clear understanding of AI, its core principles, and its relevance in today's world.
• Explore AI Technologies: Learn about machine learning algorithms, neural networks, and deep learning architectures, and understand how these technologies power AI applications.
• Discover Real-World AI Applications: Explore diverse industries where AI is making a significant impact, including healthcare, finance, customer service, and transportation.
• Ethical and Social Considerations: Explore the ethical challenges and implications of AI, such as bias, fairness, privacy, and accountability, and learn strategies to address them responsibly.
• Foster AI Literacy: Develop the ability to speak and engage in discussions about AI, understand AI-related terminology, and make informed decisions regarding AI implementation.

Course Structure:

AI for Everyone is a self-paced course, allowing learners to progress at their own speed. The course consists of high-quality video lectures delivered by industry experts, practical exercises, and quizzes to reinforce learning. Additionally, learners will have the opportunity to connect and collaborate with a global community of AI enthusiasts, enabling valuable discussions and peer-to-peer learning.

Completion of the course provides learners with a certificate, highlighting their newfound AI knowledge and skills. Whether you are a business professional, manager, policymaker, or simply curious about AI, AI for Everyone is the perfect starting point to unlock the potential of artificial intelligence in today's rapidly evolving world.

Question 1)

What are the current limitations of AI technology? (Select all that apply)

• AI technology is susceptible to adversarial attacks
• AI technology can discriminate
• AI technology can be biased
• There are no limitations to AI technology
• Explainability is hard

Question 2)

What is the Goldilocks Rule of AI?

• AI’s technology will continue to grow and can only benefit society
• One shouldn’t be too optimistic or too pessimistic about AI technology
• One should allocate many resources to defend the world from giant killer robots
• An AI winter is coming

Question 3)

Say you are building an AI system to help make diagnoses from X-ray scans.
Which of the following statements about explainability of AI do you agree with?

• AI systems are intrinsically “black box” and cannot give any explanation for their outputs.
• Lack of explainability can hamper users’ willingness to trust and adopt an AI system.
• Most AI systems are highly explainable, meaning that it’s easy for a doctor to figure out why an AI system gave a particular diagnosis.
• Explainability is usually achieved through building a chatbot to talk to the user to explain its outputs.

Question 4)

Using current AI technology, if a machine learning system learns from text that reflects unhealthy biases/stereotypes, then the resulting AI software may also exhibit similarly unhealthy biases/stereotypes.

• True
• False

Question 5)

Using current AI technology, if a machine learning system learns only from text that is completely neutral and does not reflect any gender biases, then we would expect it to exhibit no, or at most minimal, gender bias.

• True
• False

Question 6)

Which of these are good practices for addressing bias in AI? (Select all that apply)

• Using an adversarial attack on the AI system to change its outputs to be less biased
• Systematic auditing processes to check for bias
• Technical solution such as “zeroing out” bias
• Using more inclusive/less biased data

Question 7)

Which of these are examples of adversarial attacks on an AI system? (Select all that apply)

• Adding a sticker to a stop sign to make an AI system fail to detect it.
• Subtly modifying an audio clip to make a speech recognition system think someone said “Yes, authorized” when they actually said “No, reject.”
• Subtly changing an image to make an AI system mistakenly recognize a dog as a cat.
• Using AI to synthesize a fake video of a politician saying something they never actually said.

Question 8)

If a developing economy has a strong and thriving coffee bean manufacturing industry (or some other vertical industry), then it has an advantage in applying AI to coffee bean manufacturing (or other vertical industry).

• True
• False

Question 9)

What are the jobs that AI is most likely to displace over the next several years?

• All jobs will be displaced
• Most jobs involving office work (white collar jobs)
• Jobs that comprise primarily of routine, repetitive work
• Jobs that comprise primarily of non-routine, non-repetitive work

Conclusion

 

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