What is a potential risk associated with deploying General AI in multiple sectors without adequate safety precautions?
- Economic displacement of human workers.
- Enhanced collaboration with AI.
- Increased productivity and efficiency.
- Reduced energy consumption.
Deploying General AI without adequate safety precautions can lead to economic displacement of human workers. As General AI is highly capable and versatile, it has the potential to replace human workers across various industries, impacting employment opportunities.
You are designing a Human-AI collaborative system intended to assist doctors in diagnosing diseases. How would you ensure that the AI provides valuable input without overriding the expertise of the medical professionals?
- Make the AI's suggestions non-negotiable.
- Train the AI to always follow the doctor's decisions.
- Allow doctors to easily override AI recommendations.
- Keep the AI's suggestions hidden from doctors.
To ensure a valuable collaboration between AI and medical professionals, it's crucial to allow doctors to easily override AI recommendations. Making AI suggestions non-negotiable or hiding them from doctors can lead to conflicts and reduced trust in the system. The goal is to provide valuable input while respecting medical expertise.
Which principle is not commonly included in the guidelines for AI governance?
- Accountability
- Fairness
- Privacy
- Secrecy
The principle of secrecy is not commonly included in AI governance guidelines. In AI governance, transparency, accountability, fairness, and privacy are frequently emphasized to ensure responsible and ethical AI development and deployment. Secrecy contradicts the idea of transparency and openness, which are vital in AI governance.
Which of the following is a key component of an expert system in AI?
- Database Management System
- Knowledge Base
- Operating System
- Web Browser
A Knowledge Base is a fundamental component of an expert system in AI. It contains the domain-specific information and rules that the system uses to make decisions and provide expert advice.
Which algorithm is most suitable for dealing with non-linear data?
- Decision Trees
- Linear Regression
- Neural Networks
- Support Vector Machines
Neural Networks are the most suitable for dealing with non-linear data as they can model complex relationships and patterns in the data, making them highly flexible for various tasks.
Why is standardization crucial in AI technologies?
- To make AI systems more expensive.
- To limit innovation and creativity.
- To ensure compatibility, reliability, and safety of AI solutions.
- To promote competition among AI companies.
Standardization in AI is crucial to ensure compatibility, reliability, and safety of AI technologies. It allows different AI systems and components to work together seamlessly, facilitates widespread adoption, and ensures that AI technologies meet certain quality and safety standards.
Ethical considerations in AI seek to address issues related to fairness, transparency, and _______.
- Accountability
- Complexity
- Efficiency
- Profitability
Ethical considerations in AI go beyond fairness and transparency; they also encompass the principle of "Accountability." Ensuring that AI systems are accountable for their actions and their impact on society is a key ethical concern in AI development.
"_______" is a standardization organization that provides standards for Artificial Intelligence use cases and applications.
- IEC (International Electrotechnical Commission)
- IEEE (Institute of Electrical and Electronics Engineers)
- ISO (International Organization for Standardization)
- ITU (International Telecommunication Union)
IEEE, the Institute of Electrical and Electronics Engineers, is a widely recognized standardization organization that plays a key role in developing standards for various fields, including AI. They contribute to defining guidelines and best practices for AI technologies.
You are developing an NLP model to monitor and analyze social media mentions for a brand. How would you account for sarcasm and implicit meanings in the messages?
- Ignore sarcasm and implicit meanings.
- Use sentiment analysis for all messages.
- Incorporate sentiment analysis, context analysis, and emotion detection.
- Manually review all messages.
To account for sarcasm and implicit meanings, it's crucial to incorporate sentiment analysis, context analysis, and emotion detection. These techniques help the NLP model understand the true intent and emotions behind messages, including sarcastic or implicitly expressed sentiments.
Suppose an AI system responsible for credit scoring begins to exhibit erratic behavior, assigning seemingly random scores to individuals. What should be the initial step in addressing this issue, considering AI governance principles?
- Shut down the AI system immediately.
- Review the training data and model architecture.
- Ignore the issue as it might stabilize on its own.
- Reduce the complexity of the AI model.
The initial step should be to review the training data and model architecture to understand why the AI is behaving erratically. Shutting down the system might not be necessary at this stage, and ignoring it is not a responsible approach. Reducing complexity may not be the immediate solution.