Module 3: Business and Career Transformation Through AI
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In this post, I provide accurate answers and detailed explanations for Module 3: Business and Career Transformation Through AI of Course 1: Introduction to Artificial Intelligence (AI) – IBM Generative AI Engineering Professional Certificate
Whether you’re preparing for quizzes or brushing up on your knowledge, these insights will help you master the concepts effectively. Let’s dive into the correct answers and detailed explanations for each question.
AI Domains for Industries
Practice Assignment
1. The team is developing a robot for assembling products on a manufacturing line. To enhance the precision of the robot’s movements and ensure it can handle delicate and complex tasks, which combination of components should the team focus on, and why?
- Vision systems and real-time data processing
- Robust actuators and redundant safety systems
- High-resolution encoders and advanced control algorithms
- Force-torque sensors and machine learning models ✅
Explanation:
While encoders and control algorithms do contribute to precision, when the task involves delicate and complex handling, the system also needs to sense force and torque to avoid damaging parts — especially important for fine assembly tasks.
- Force-torque sensors provide feedback on contact forces between the robot and objects.
- Machine learning models can adapt to variability in tasks and help the robot improve its performance over time.
2. Which of the following statements best describes AI agents?
- Software programs that interact with their environment and perform tasks autonomously ✅
- Hardware devices that control machines
- Databases for storing large amounts of data
- Human assistants for technical support
Explanation:
AI agents perceive their environment, make decisions, and take actions without human intervention. They are the core of many autonomous systems.
3. Which of the following phases in the functionality of AI agents involves processing and interpreting the data gathered?
- Action
- Perception
- Decision-making
- Understanding ✅
Explanation:
The phase that processes and interprets gathered data is often referred to as understanding in the context of cognitive AI agents.
- Perception is about collecting raw data.
- Understanding is about interpreting it.
- Decision-making comes after understanding and involves choosing what to do based on interpreted data.
Practice Quiz: AI for Businesses
Practice Assignment
4. How can generative AI tools benefit a product development team?
- By eliminating human designers
- By speeding up the prototyping process
- By creating multiple design variations ✅
- By reducing the need for customer feedback
Explanation:
Generative AI can help rapidly generate prototypes and explore varied design options, allowing teams to iterate faster and test more ideas early in the development process.
5. Which of the following AI technologies is commonly used in the operations of a manufacturing industry?
- Computer vision systems ✅
- Natural language processing (NLP) tools
- Chatbots
- Virtual reality (VR) simulations
Explanation:
Computer vision is widely used in manufacturing for quality control, defect detection, and automation of visual inspection processes, enhancing efficiency and accuracy.
6. When you want to adopt AI into your business, what steps will you choose? Select all that apply.
- Build AI capabilities ✅
- Implementing AI without strategy
- Data readiness ✅
- Defining business goals ✅
Explanation:
To successfully implement AI, organizations need:
- Defined business goals → to align AI with strategic outcomes.
- Data readiness → since AI models rely heavily on data.
- AI capabilities → including skills, tools, and infrastructure.
Avoid rushing into implementation without a solid strategy.
Practice Quiz: AI for Your Work and Career
Practice Assignment
7. Which of the following option is correct?
- AI engineers create AI systems that process human language.
- NLP engineers use AI tools to create high-quality content.
- Marketers design and maintain AI systems.
- Data scientists analyze huge datasets using advanced mathematics, statistics, and data visualization tools. ✅
Explanation:
Data scientists use math, stats, and tools to analyze large data sets. The other roles are misrepresented.
8. Imagine you're a content manager in a Social Media management company. Which of the following tools will you implement for your team members to improve their writing and communication tasks?
- Tableau and Power BI
- Grammarly and QuillBot ✅
- GitHub Copilot
- Duolingo and Babel
Explanation:
These tools help with grammar, clarity, and rephrasing—ideal for writing tasks.
9. AI is transforming your work and workplace by performing which of the following tasks? Select all that apply.
- Analyzing data sets ✅
- Automating routine tasks ✅
- Accelerating innovation and creativity ✅
- Making all decisions without human intervention
Explanation:
AI assists with tasks but doesn’t replace human decision-making.
Graded Quiz: Business and Career Transformation Through AI
Graded Assignment
10. What role do actuators play in a robotic system?
- They provide the robot with sensory inputs.
- They enable communication with other systems.
- They analyze data to make decisions.
- They execute the robot’s physical movements. ✅
Explanation:
Actuators move parts like arms or wheels in response to commands.
11. Rita is a supply chain manager in a logistics company. They experience stockouts of popular items, leading to a loss in sales. She struggles with an excess inventory of slow-moving products, which adds to valuable capital. How can Rita leverage AI to streamline inventory management?
- By automating the creation of purchase orders.
- By predicting future demand for specific products. ✅
- By analyzing customer reviews and identifying potential product design flaws.
- By generating reports on current inventory levels.
Explanation:
AI can forecast demand to avoid overstock or stockouts.
12. Which of the following technologies was the first to generate high-quality images?
- Recurrent neural networks (RNNs)
- Convolutional neural networks (CNNs)
- Generative adversarial networks (GANs) ✅
- Support vector machines (SVMs)
Explanation:
GANs are known for creating realistic, high-quality images.
13. How can generative AI models help product development teams when they struggle with limited design options and the slow, iterative prototyping process?
- By improving team communication and collaboration tools
- By providing real-time feedback on design choices
- By predicting market trends with high accuracy
- By producing multiple variations ✅
Explanation:
It generates design options quickly, speeding up prototyping.
14. Which of the following industries has become the frontier in AI adoption?
- Financial services ✅
- Healthcare
- E-commerce
- Fast-moving consumer goods (FMCG)
Explanation:
Finance uses AI for fraud detection, trading, and automation.
15. How does the AI help the HR team to streamline candidate sourcing?
- By automating the video interviews with all the candidates
- By creating automated job postings for various job requirements
- By performing resume parsing to match the job requirements ✅
- By arranging virtual training and peer interactive sessions
Explanation:
AI filters resumes based on job criteria efficiently.
16. Which of the following tools can help you improve writing and communication tasks?
- Grammarly and QuillBot ✅
- Tableau and Power BI
- GitHub Copilot
- Duolingo and Babel
Explanation:
These tools improve grammar, tone, and rephrasing.
17. What does the term "cobots" refer to?
- Cobots are robots designed to perform coding and software development tasks autonomously.
- Cobots are robots that only work in isolation, away from human workers.
- Cobots are collaborative robots designed to work alongside humans, assisting them in various tasks. ✅
- Cobots refer to a special type of robot used only in entertainment.
Explanation:
Cobots support humans in shared workspaces safely.
18. How can AI improve customer experiences in businesses?
- AI limits the options customers have to choose from, making decision-making easier.
- AI can provide personalized recommendations and 24/7 customer support, enhancing customer satisfaction. ✅
- AI can ensure that all customers are treated exactly the same, regardless of their preferences.
- AI prevents businesses from interacting with customers directly.
Explanation:
AI personalizes and automates service for better experiences.
19. How does Generative AI enhance customer service in businesses?
- It generates detailed reports for customer service teams to review after interactions but does not engage directly with customers.
- It helps in automating the categorization and routing of customer service requests to appropriate departments.
- It powers chatbots and virtual assistants that provide personalized and immediate responses to customer inquiries. ✅
- It streamlines the creation of standard responses for common customer inquiries, reducing the need for personalized support.
Explanation:
Generative AI enables instant, tailored support via chatbots.
20. What is Al ethics?
- How to build and use Al in ways that align with human ethics and expectations
- An organization’s act of governing Al through its corporate instructions, staff, processes, and systems
- A multidisciplinary field that investigates how to maximize Al’s beneficial impacts while reducing risks and adverse impacts ✅
- How and why an Al system arrived at a particular outcome or recommendation
Explanation:
AI ethics is a broad and interdisciplinary field that addresses the moral and societal implications of AI. It focuses on minimizing potential harms and maximizing positive outcomes by studying how AI systems impact humans, society, and institutions.
21. In Al, what is fairness?
- An Al system’s ability to effectively handle exceptional conditions, like abnormal input or adversarial attacks
- An Al system’s ability to prioritize and safeguard humans’ privacy and data rights
- An Al system’s ability to show how and why it arrived at a particular outcome or recommendation
- An Al system’s ability to treat individuals or groups equitably ✅
Explanation:
Fairness in AI means ensuring that systems do not perpetuate biases or discriminatory practices. It involves designing models that provide equal opportunities and avoid favoring or disadvantaging any group or individual.
22. In Al, what is explainability?
- When appropriate information is shared with humans about how an Al system was designed and developed
- An Al system’s ability to show how and why it arrived at a particular outcome or recommendation ✅
- An Al system’s ability to treat individuals or groups equitably
- An Al system’s ability to effectively handle exceptional conditions, like abnormal input or adversarial attacks
Explanation:
Transparency in AI ensures that stakeholders understand how decisions are made. This involves clear documentation, explainability, and insight into the workings of the system, enabling accountability and trust.
23. In Al, what is privacy?
- An Al system’s ability to show how and why it arrived at a particular outcome or recommendation
- An Al system’s ability to treat individuals or groups equitably
- When appropriate information is shared with humans about how an Al system was designed and developed
- An Al system’s ability to prioritize and safeguard humans’ privacy and data rights ✅
Explanation:
Robustness in AI refers to the system’s capability to perform reliably under varied or unforeseen circumstances. This includes handling noisy, unexpected, or malicious data inputs without failure or significant degradation in performance.
24. In Al, what does bias do?
- Gives systematic disadvantages to certain groups or individuals ✅
- Identifies and addresses socio-technical issues raised by Al
- Solves problems faster
- Augments human intelligence
Explanation:
Bias in AI occurs when algorithms produce unfair outcomes due to prejudices in data, design, or implementation. These biases can lead to systematic disadvantages for specific groups, amplifying inequalities.
25. What is one potential cause of bias in an Al system?
- High-quality data sets
- Diverse teams
- Clear principles and pillars
- Implicit or explicit human bias ✅
Explanation:
AI systems are only as unbiased as the data and design decisions behind them. Human biases, whether intentional or unconscious, can influence datasets, model architecture, or decision-making criteria, introducing unfairness.
26. What is a regulation?
- A governance structure that works at scale
- A government rule enforceable by law ✅
- A multidisciplinary field that investigates how to maximize Al’s beneficial impacts while reducing risks and adverse impacts
- An organization’s act of governing through its corporate instructions, staff, processes, and systems
Explanation:
Regulations are legally binding rules established by governments to ensure compliance with standards, including those related to AI ethics, privacy, and safety.
27. What is Al governance?
- An organization’s act of governing through its corporate instructions, staff, processes, and systems ✅
- A government rule enforcible by law
- An Al system’s ability to prioritize and safeguard humans’ privacy and data rights
- A multidisciplinary field that investigates how to maximize Al’s beneficial impacts while reducing risks and adverse impacts
Explanation:
AI governance involves creating and enforcing internal policies to ensure AI systems align with ethical principles, organizational goals, and regulatory requirements.
28. When should developers, data scientists, and other people who work with Al consider ethics?
- Only when training the model
- Throughout the Al lifecycle ✅
- At the end of the Al lifecycle
- At the beginning of the Al lifecycle
Explanation:
AI ethics addresses the intertwined technical and societal impacts of AI. As AI reshapes industries, economies, and daily life, ethical considerations must account for both technological capabilities and societal consequences.
29. According to IBM's Betsy Greytok, what is the hottest topic in Al?
- How to use Al responsibly ✅
- How to use Al in hiring
- How to use Al in healthcare
- How to use Al in social media and marketing
Explanation:
Responsible AI use is a pressing issue as organizations strive to balance innovation with ethical considerations. This includes ensuring AI systems are fair, transparent, robust, and aligned with societal values.
30. What are the pillars of AI ethics?
- Explainability, fairness, robustness, transparency, privacy ✅
- Awareness, governance, operationalization
- Environmental impact, equitable impact, ethical impact
- Trust, efficiency, compliance
Explanation:
These pillars ensure AI systems operate ethically, emphasizing fairness in outcomes, explainability of decisions, robustness against errors, transparency in operations, and privacy protection.
31. In AI, what is privacy?
- An AI system’s ability to treat individuals or groups equitably
- An AI system’s ability to show how and why it arrived at a particular outcome or recommendation
- When appropriate information is shared with humans about how an AI system was designed and developed
- An AI system’s ability to prioritize and safeguard humans’ privacy and data rights ✅
Explanation:
Privacy in AI involves protecting user data and ensuring systems are designed to comply with privacy regulations, safeguarding sensitive information.
32. What is a first step toward mitigating bias in AI?
- Putting into place a governance structure that works at scale
- Developing different rules for different risks
- Assembling diverse teams ✅
- Designating a lead AI ethics official
Explanation:
Diverse teams bring varied perspectives, reducing the risk of bias during data collection, algorithm design, and system evaluation, promoting fairness.
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