Final Exam Answers
Question: Which aspect of AI’s efficiency most directly leads to sustained innovation in an organization?
Reducing the need for data cleaning
Automating menial tasks and freeing human creativity
Ensuring perfect accuracy in all predictions
Minimizing the cost of hardware upgrades
Answer: Automating menial tasks and freeing human creativity
Reasoning: When AI handles repetitive work, human teams can focus on complex problem solving, driving long-term innovation.
Question: Which scenario best illustrates a hidden risk of using AI-driven predictive analytics for strategic decisions?
Relying on multiple data sources to confirm market trends
Applying clear labeling to all training data
Deploying a model trained only on outdated or skewed datasets
Combining expert intuition with algorithmic insights
Answer: Deploying a model trained only on outdated or skewed datasets
Reasoning: Biased or unrepresentative data can lead to inaccurate forecasts, undermining strategic decision making.
Question: Which ethical dilemma arises if an AI model designed for medical diagnoses is trained on data from a single demographic group?
Overly transparent algorithms that expose trade secrets
A system that automatically encrypts all patient records
A model that may fail to accurately diagnose patients from other demographics
A permanent reliance on manual oversight for each diagnosis
Answer: A model that may fail to accurately diagnose patients from other demographics
Reasoning: Training on a narrow dataset can embed bias, limiting the system’s effectiveness across diverse populations.
Question: Which factor most complicates the establishment of AI transparency for end-users?
Availability of high-performance computing
Complexity of deep learning architectures
Use of supervised learning in data labeling
Reliance on standardized data cleaning protocols
Answer: Complexity of deep learning architectures
Reasoning: Deep neural networks often function as “black boxes,” making it challenging to explain how they arrive at specific decisions.
Question: Which outcome is most likely when organizations disregard the need for ethical oversight in AI deployments?
Increased public trust and engagement
Greater regulatory compliance across industries
Proliferation of biased or discriminatory AI applications
Seamless integration of AI in global governance
Answer: Proliferation of biased or discriminatory AI applications
Reasoning: Without ethical guidelines, AI models can inadvertently replicate harmful biases, undermining fairness and trust.
Question: Which example demonstrates a nuanced way AI reshapes the job market rather than simply displacing workers?
Replacing all human employees with advanced robots
Introducing AI tools that require specialized maintenance and oversight roles
Training models on personal data without user consent
Eliminating data analytics positions to cut costs
Answer: Introducing AI tools that require specialized maintenance and oversight roles
Reasoning: AI creates new job categories for individuals who can manage, audit, and enhance these systems, shifting rather than removing employment.
Question: Which approach best addresses potential misuse of AI-driven surveillance technologies?
Eliminating all public data collection methods
Allowing unrestricted access to facial recognition tools
Implementing clear legal frameworks and oversight committees
Training AI models exclusively on private company data
Answer: Implementing clear legal frameworks and oversight committees
Reasoning: Proper regulations and monitoring help ensure surveillance tools are used responsibly and respect individual rights.
Question: Which challenge might arise if a smart city relies solely on automated traffic management systems without human intervention?
An overabundance of data for decision making
A consistent reduction in energy consumption
Inability to adapt to rare or unexpected events
Complete elimination of traffic jams
Answer: Inability to adapt to rare or unexpected events
Reasoning: AI systems can struggle with unusual circumstances that fall outside their training data, requiring human judgment to intervene.
Question: Which factor best illustrates the need for public awareness in AI-driven societal shifts?
Widespread acceptance of data bias as inevitable
Mandatory secrecy around AI algorithms
Active community participation in policy discussions
Exclusion of non-technical stakeholders from AI forums
Answer: Active community participation in policy discussions
Reasoning: Informed citizens can engage in debates about AI’s benefits and risks, shaping ethical and effective adoption of technology.
Question: Which scenario best embodies responsible AI deployment in a rapidly evolving market?
Training a model once and never updating it
Using unlabeled data to accelerate predictions
Continuously monitoring outcomes and adjusting algorithms
Refusing to share any information on AI decision processes
Answer: Continuously monitoring outcomes and adjusting algorithms
Reasoning: Ongoing oversight ensures the AI remains accurate, fair, and aligned with current data and ethical standards.