Team 5: What was a major concern regarding OpenAI's practices as mentioned in the case study?

Lack of transparency in data usage

Team 5: Why is explainability important in detecting biases in AI?

It enables organizations to identify and remove biases in their models.

Team 5: What is the primary goal of transparency in AI?

To provide stakeholders with a clear understanding of AI systems

Team 9: Who would be responsible if AI makes a mistake in the medical field?

The company that choses to utilize the AI model

Team 6: What does the Human-in-the-loop (HITL) model allow in the context of autonomous systems?

Humans can intervene in real-time decisions

Team 6: What is the primary concern regarding the use of autonomous systems in high-stakes environments?

They may lead to ethical risks.

Team 5: How does explainability contribute to user trust in AI systems?

Explainability helps users understand AI decisions, fostering trust

Team 2: Which healthcare data is frequently targeted by cyberattacks?

Electronic Healthcare Records (EHR)

Team 9: Which principle is essential for ensuring ethical AI development?

Transparency in decision-making

Team 2: What is a significant ethical concern with AI systems in healthcare?

Patient awareness of data usage

T9: Why must AI balance personalization with privacy, and what are the consequences of not safeguarding user privacy?

To maintain user trust; failure to protect privacy risks identity theft.

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Ethical AI

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Questions 21

Answers

1
Team 2: In 2020, a data breach affected which organization's EHR systems?
American Red Cross
The US Department of Health
Universal Health Services
World Health Organization
2
Team 5: What was a major concern regarding OpenAI's practices as mentioned in the case study?
Lack of transparency in data usage
Allegations of bias in AI decision-making processes
Issues related to the cost of developing AI technologies
Concerns about the accuracy of AI-generated content
3
Team 7: What is the purpose of obtaining explicit consent when collecting facial data?
To ensure data anonymization
To enhance data storage
To comply with privacy laws
To control data usage
4
Team 5: Why is explainability important in detecting biases in AI?
It enables organizations to identify and remove biases in their models.
It enhances the speed of data processing within the AI.
It provides a way to validate all data sources used by AI.
It ensures only expert users can access AI outputs.
5
Team 5: What is the primary goal of transparency in AI?
To eliminate human intervention in decision-making
To ensure that AI systems are fully automated
To provide stakeholders with a clear understanding of AI systems
To maximize the efficiency of AI algorithms
6
Team 9: Which of the following do not utilize web-based corpora to generate responses
Generative AI
Local database
Algorithms
Statistical modeling
7
T6: What is most the ethical option for for an autonomous vehicle's choice between swerving or hitting a pedestrian?
Maximize passenger safety
Follow traffic laws strictly
Minimize harm to all parties
Allow AI full autonomy
8
Team 2: AI technologies assist in which of the following?
Reducing the need for healthcare professionals
Increasing administrative burdens
Improving patient outcomes
Limiting data access
9
Team 9: Who would be responsible if AI makes a mistake in the medical field?
The company that choses to utilize the AI model
The doctor who followed the AI advice/recommendations
The Artificial Intelligence Company
The injured party’s insurance company
10
Team 2: What risk does AI dependency introduce in healthcare?
Faster treatment options
Enhanced patient privacy
Better diagnostics
Data breaches
11
Team 6: What is a major challenge in AI-driven systems?
Increasing data storage
Ensuring human oversight
Reducing operational costs
Maximizing AI efficiency
12
Team 6: What does the Human-in-the-loop (HITL) model allow in the context of autonomous systems?
AI operates completely independently
Humans can intervene in real-time decisions
Humans are not involved at all
Humans review decisions after they are made
13
Team 6: What is the primary concern regarding the use of autonomous systems in high-stakes environments?
They are always more efficient than human operators
They may lead to ethical risks.
They can operate without any human input.
They require constant human supervision
14
Team 5: How does explainability contribute to user trust in AI systems?
Explainability ensures that AI systems operate without any errors
Explainability guarantees that AI systems are free from biases
Explainability helps users understand AI decisions, fostering trust
Explainability reduces the need for user training on AI systems
15
Team 7: What is a key ethical concern in AI regarding facial recognition technology?
Faster processing
Enhanced marketing
Unauthorized Access
High costs
16
Team 2: Which healthcare data is frequently targeted by cyberattacks?
Electronic Healthcare Records (EHR)
Written prescriptions
Verbal doctor assessments
Non-digital patient notes
17
Team 7: Transparency in data usage is crucial for which reason?
Increase in profits
Enhancing efficiency
Reducing Storage
Maintaining trust
18
Team 7: What is a potential consequence of failing to protect personal data?
Hardware malfunctions
Identity theft
Software errors
Increased storage costs
19
Team 9: Which principle is essential for ensuring ethical AI development?
Maximizing profit
Speed of deployment
Transparency in decision-making
Autonomous use in the workplace
20
Team 2: What is a significant ethical concern with AI systems in healthcare?
Patient awareness of data usage
Lack of AI applications
High cost of implementation
Inefficient data processing
21
T9: Why must AI balance personalization with privacy, and what are the consequences of not safeguarding user privacy?
To minimize AI data usage; privacy protection ensures data efficiency.
To make AI faster; lack of privacy protection has no real consequences
To improve AI accuracy; if privacy isn’t protected, AI won’t work properly
To maintain user trust; failure to protect privacy risks identity theft.

Ethical AI Flashcards | StudBud