EC-AI Sample Questions & Answers
Working with data in AI ties with adopting AI across an organization for the biggest share, ahead of four evenly tied areas: AI's history and development, ethical and legal considerations, enablers like robotics and machine learning, and future career impact.
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- Question 1Intermediate
An Introduction to AI and Historical Development · Types of AI
During a strategic planning session, a Chief Information Officer (CIO) states that the organisation should wait until 'General AI' is commercially available before investing in automation. As an AI consultant, how should you accurately respond to this statement based on current AI classifications?
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Correct answer: B
General AI (AGI or Strong AI) aims to replicate human intelligence and can hypothetically understand or learn any intellectual task a human can. However, it does not currently exist. Organisations must rely on Narrow AI (ANI or Weak AI) which operates within well-defined domains and is currently available for commercial automation.
- Question 2Beginner
An Introduction to AI and Historical Development · Definitions of key AI terms
When distinguishing between human and artificial intelligence, which of the following accurately describes the 'Scientific method' as defined in the context of AI development?
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Correct answer: D
The BCS syllabus explicitly defines the Scientific method as 'An empirical method for acquiring knowledge that has characterised the development of science.' This empirical approach underpins how AI systems are tested and validated.
- Question 3Intermediate
An Introduction to AI and Historical Development · Key milestones in AI development
A technology historian is writing a paper on the cyclical nature of AI investment. They note that between 1974-1980 and again between 1987-1993, the industry experienced significant downturns. What term is used to describe these specific periods in AI history?
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Correct answer: A
The term 'AI winters' refers to periods of reduced funding and interest in artificial intelligence research. The BCS syllabus specifically highlights two major AI winters: 1974-1980 and 1987-1993.
- Question 4Beginner
Ethical and Legal Considerations · Role of ethics in AI
When implementing a new AI customer service bot, the project manager notes that while web scraping public social media profiles to train the bot does not violate any current regional statutes, it has caused severe discomfort among user advocacy groups. This scenario best illustrates the difference between which two concepts?
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Correct answer: D
This scenario highlights the difference between law (which it does not violate) and ethics (moral principles that govern behaviour, which are causing discomfort among users). Something can be strictly legal but still considered unethical.
- Question 5Intermediate
Ethical and Legal Considerations · Guiding principles for ethical AI
A multinational corporation is looking to standardise its approach to deploying artificial intelligence safely and responsibly across all global branches. They decide to implement a formally recognised AI governance model. Which of the following is an international standard specifically designed for AI management systems?
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Correct answer: C
ISO 42001 is the international standard specifically designed for Artificial Intelligence Management Systems. It provides a governance framework for responsible AI deployment. ISO 9001 is for quality management, and ISO 27001 is for information security.
- Question 6AdvancedSelect 3
Ethical and Legal Considerations · Guiding principles for ethical AI
A public sector organisation in London is developing a new algorithm to assist with resource allocation. The Chief Data Officer insists the project must align strictly with the official UK AI Principles. Which THREE of the following are explicitly listed as UK AI Principles? (Select THREE)
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Correct answers: B, D, E
The five UK AI Principles are: 1) Safety, security and robustness; 2) Transparency and explainability; 3) Fairness; 4) Accountability and governance; 5) Contestability and redress. 'Profitability and scalability' and 'Total autonomy' are not UK AI Principles.
The five UK AI Principles are: 1) Safety, security and robustness; 2) Transparency and explainability; 3) Fairness; 4) Accountability and governance; 5) Contestability and redress. 'Profitability and scalability' and 'Total autonomy' are not UK AI Principles.
The five UK AI Principles are: 1) Safety, security and robustness; 2) Transparency and explainability; 3) Fairness; 4) Accountability and governance; 5) Contestability and redress. 'Profitability and scalability' and 'Total autonomy' are not UK AI Principles.
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