Đề thi, bài tập trắc nghiệm online Trí tuệ nhân tạo trong kinh doanh – Đề 12

1. How can AI help businesses in risk management?

A. By eliminating all risks entirely, ensuring complete safety and security.

B. By identifying potential risks, predicting their likelihood and impact, and enabling proactive mitigation strategies.

C. By ignoring potential risks and focusing solely on potential rewards.

D. By increasing operational complexity and introducing new unforeseen risks.

2. Which of the following is NOT a benefit typically associated with AI adoption in business?

A. Reduced operational costs through automation and optimization.

B. Increased manual labor and reduced automation in workflows.

C. Enhanced customer experiences through personalization and improved service.

D. Improved decision-making based on data-driven insights and predictions.

3. Which of the following is an example of AI being used for operational efficiency in manufacturing?

A. Manually inspecting each product for defects.

B. Predictive maintenance of machinery to reduce downtime and optimize production schedules.

C. Ignoring data from production lines and relying solely on human intuition.

D. Slowing down production lines to ensure manual oversight of every step.

4. Which of the following business functions is LEAST likely to be significantly impacted by AI?

A. Human Resources (HR) - e.g., recruitment and talent management.

B. Marketing and Sales - e.g., personalized advertising and lead scoring.

C. Operations and Supply Chain - e.g., predictive maintenance and demand forecasting.

D. Creative Arts and Design - e.g., purely subjective artistic creation without data analysis.

5. In the context of AI and jobs, what is 'AI augmentation'?

A. Replacing human jobs entirely with AI-powered systems.

B. Using AI tools to enhance human capabilities and make jobs more efficient and effective, rather than replacing humans.

C. Ignoring the impact of AI on the workforce and job roles.

D. Intentionally decreasing human productivity to justify AI adoption.

6. What is the 'black box' problem in AI, and why is it a concern in business?

A. It refers to AI systems that are physically black in color and difficult to see.

B. It describes AI systems, particularly complex neural networks, whose decision-making processes are opaque and difficult for humans to understand.

C. It is a term for AI systems that are intentionally hidden from business users.

D. It means AI systems that are not connected to the internet.

7. What is a key challenge in implementing AI solutions in a business?

A. The overabundance of readily available, perfectly clean, and labeled data.

B. The ease of integrating AI systems with existing legacy infrastructure.

C. The need for high-quality data, specialized skills, and understanding of AI limitations.

D. Universally low initial investment costs for AI projects.

8. What is the primary goal of implementing Artificial Intelligence (AI) in a business context?

A. To replace human employees entirely.

B. To enhance decision-making and operational efficiency.

C. To complicate business processes and increase costs.

D. To solely focus on technological advancement regardless of business needs.

9. What is the potential impact of AI on the future of work and job roles?

A. AI will eliminate all jobs, leading to mass unemployment.

B. AI is likely to automate routine and repetitive tasks, potentially displacing some jobs, but also creating new jobs and transforming existing roles to focus on higher-level skills and human-centric tasks.

C. AI will have no significant impact on the job market; all jobs will remain unchanged.

D. AI will only create low-skill, low-paying jobs.

10. In the context of AI in business, what does 'algorithmic bias' refer to?

A. The inherent superiority of AI algorithms over human decision-making.

B. Systematic and repeatable errors in AI systems that create unfair outcomes, often due to biased training data or flawed algorithm design.

C. Random errors that occur unpredictably in AI systems.

D. The intentional programming of AI systems to discriminate against certain groups.

11. What is 'Robotic Process Automation' (RPA) in business?

A. Building physical robots to replace human workers in factories.

B. Using software 'robots' to automate repetitive, rule-based digital tasks.

C. Developing advanced AI algorithms for complex decision-making.

D. A type of AI focused on creative content generation.

12. Which of the following is a potential ethical concern related to using AI in hiring processes?

A. Increased efficiency in screening large volumes of applications.

B. Potential for algorithmic bias leading to unfair or discriminatory hiring practices.

C. Reduced cost associated with manual resume reviews.

D. Standardization of candidate evaluation criteria.

13. In customer service, AI-powered chatbots are primarily used for:

A. Replacing all human customer service agents immediately.

B. Handling simple and routine inquiries, freeing up human agents for complex issues.

C. Intentionally frustrating customers to reduce service requests.

D. Generating random responses regardless of customer queries.

14. Which of the following is a key consideration for businesses when implementing AI ethically?

A. Focusing solely on maximizing profits regardless of ethical implications.

B. Ensuring fairness, transparency, accountability, and privacy in AI systems and their applications.

C. Assuming AI systems are inherently neutral and unbiased.

D. Ignoring potential societal impacts of AI technologies.

15. How can AI contribute to improved decision-making in businesses?

A. By replacing human judgment entirely and making decisions autonomously without human oversight.

B. By processing large volumes of data quickly, identifying patterns, and providing insights to support human decision-makers.

C. By making decisions based on random chance to ensure unpredictability.

D. By deliberately ignoring relevant data to simplify the decision-making process.

16. What is a potential drawback of using AI-powered recommendation systems in e-commerce?

A. Increased customer satisfaction and loyalty due to personalized recommendations.

B. The 'filter bubble' effect, where users are only exposed to a limited range of options, potentially reducing discovery and diversity of choices.

C. Improved efficiency in product discovery and browsing.

D. Higher conversion rates and sales due to relevant product suggestions.

17. Which of the following is an example of AI being used for personalized marketing?

A. Sending the same generic advertisement to all customers.

B. Recommending products to customers based on their past purchase history and browsing behavior.

C. Manually segmenting customers without using data analysis.

D. Ignoring customer preferences and trends in marketing campaigns.

18. Which type of AI is best suited for tasks requiring pattern recognition in images or videos, such as quality control in manufacturing?

A. Natural Language Processing (NLP).

B. Computer Vision.

C. Rule-based Expert Systems.

D. Robotic Process Automation (RPA).

19. What is 'explainable AI' (XAI), and why is it becoming increasingly important?

A. It is a type of AI that is intentionally made more complex and difficult to understand.

B. It refers to AI systems designed to provide clear and understandable explanations for their decisions and actions, crucial for trust, accountability, and regulatory compliance.

C. It is a marketing term with no technical significance in AI.

D. It is a less accurate form of AI that prioritizes simplicity over performance.

20. How can AI contribute to improving customer experience?

A. By making customer interactions less personalized and more generic.

B. By providing faster, more personalized service, and anticipating customer needs.

C. By intentionally delaying customer service responses to manage costs.

D. By eliminating all human touchpoints in customer interactions.

21. Which of the following is NOT a typical application of AI in Human Resources (HR)?

A. Automated resume screening and candidate shortlisting.

B. Predictive analytics for employee attrition and retention.

C. Facial recognition for employee surveillance to monitor productivity.

D. Chatbots for answering employee FAQs and providing HR support.

22. Predictive analytics, powered by AI, can benefit businesses primarily by:

A. Guaranteeing future outcomes with 100% accuracy.

B. Identifying potential future trends and risks to inform strategic decisions.

C. Eliminating the need for human intuition and experience in forecasting.

D. Focusing solely on past data without considering external factors.

23. How can AI contribute to improving supply chain management?

A. By making the supply chain more rigid and less adaptable to changes.

B. By optimizing logistics, predicting demand fluctuations, and improving inventory management.

C. By solely relying on manual processes and ignoring data analysis.

D. By intentionally creating inefficiencies to justify AI investments.

24. In finance, AI is increasingly used for fraud detection. How does AI typically improve fraud detection compared to traditional methods?

A. AI is less accurate than traditional rule-based systems in detecting fraud.

B. AI can analyze vast amounts of data in real-time and identify subtle patterns indicative of fraud that traditional rules might miss.

C. AI relies solely on pre-defined rules and cannot adapt to new fraud patterns.

D. AI increases false positives and requires more manual review than traditional methods.

25. What is 'Natural Language Processing' (NLP) and how is it used in business?

A. It is a programming language used to build AI systems; it is used for coding AI algorithms.

B. It is a field of AI focused on enabling computers to understand, interpret, and generate human language; used in chatbots, sentiment analysis, etc.

C. It is a type of hardware designed to process language data; used in server rooms.

D. It is a business strategy focused on using only natural, organic language in marketing materials.

26. What is 'Machine Learning' in the context of AI in business?

A. A type of AI that allows systems to learn from data without explicit programming.

B. A physical machine that performs automated tasks in manufacturing.

C. A software program designed to strictly follow pre-defined rules.

D. A method of manually coding complex algorithms for specific business problems.

27. Which of the following best describes 'Deep Learning' in AI?

A. A simple form of AI that follows basic pre-programmed rules.

B. A subset of Machine Learning that uses artificial neural networks with multiple layers to analyze data and learn complex patterns.

C. A method of manually coding AI algorithms by human experts.

D. A type of AI that is only applicable to academic research and not business.

28. What is 'sentiment analysis' and how is it applied in business using AI?

A. It is the process of manually reading customer reviews and labeling them as positive or negative.

B. It is an AI technique that uses Natural Language Processing (NLP) to determine the emotional tone (positive, negative, neutral) expressed in text data like customer reviews or social media posts.

C. It is a method of ignoring customer feedback to maintain a consistent brand image.

D. It is a marketing strategy to manipulate customer emotions through advertising.

29. What is the role of data in the success of AI applications in business?

A. Data is irrelevant; AI algorithms can function effectively without data.

B. High-quality, relevant, and sufficient data is crucial for training effective AI models and achieving desired business outcomes.

C. Only small amounts of data are needed to build robust AI systems.

D. Data can be completely random and unstructured; AI can still learn effectively.

30. What is a potential risk of over-reliance on AI in business operations?

A. Decreased efficiency and slower response times.

B. Reduced innovation and adaptability due to lack of human oversight and critical thinking.

C. Increased need for human intervention and manual labor.

D. Lower operational costs and increased profitability in all scenarios.