ICT for iGeneration Quiz & Flashcards: Chapter 1 AI

What is a key advantage of real-time adaptive traffic signal systems compared to conventional pre-determined systems?

What technique is commonly used in machine learning for automatically detecting patterns in data?

Which of the following is a major challenge in the field of big data analytics?

What is a common concern associated with the collection and use of personal data by companies?

Which of the following is NOT a recommended practice for protecting personal data privacy?

In the context of 3D printing, what type of materials can be used to create physical objects?

What is a key application of pattern recognition techniques in artificial intelligence?

Which of the following is NOT a common technique used in machine learning?

What is a potential benefit of using a real-time adaptive traffic signal system during rush hour?

Which of the following is NOT a common application of 3D printing technology?

AI and Employment

Self-checkouts are becoming common in supermarkets and fashion retailers.
The impact of AI development prompts a debate on whether it poses a risk or an opportunity for jobs.

Artificial Intelligence (AI) and Data Science

The Internet utilizes extensive data to create a user profile that may seem more accurate than personal self-awareness.
Big data is characterized by the "4 V's": Volume, Variety, Velocity, and Veracity.

Concepts of AI

AI programs enable machines to learn from experience and make human-like decisions.
Machine learning involves providing data, identifying patterns, generating models, and making predictions.

Pattern Recognition

Pattern recognition in AI involves detecting similarities and relationships to effectively analyze complex issues.
Applications include:
- Image Recognition: Uses pixel scanning to identify features in images.
- Speech Recognition: Analyzes waveforms of spoken words to identify patterns.
- Spam Detection: Customizing filters based on collected preferences.

Data Science and Data Mining

Data science is pivotal in extracting and managing useful information across various fields.
Key components include:
- Business understanding
- Data mining
- Data cleaning
- Data exploration
- Feature engineering
- Predictive modeling
- Data visualization

Applications of AI and Data Science

AI and data science have widespread applications, influencing decision-making across sectors.

Ethics of AI

Ethical dilemmas arise regarding accountability for incidents involving AI, such as accidents caused by self-driving cars.
Concerns about data privacy and the sale of personal information to third parties.

Practical Application

Engage in hands-on labs to practice creating and training AI models, enhancing understanding of machine learning processes.

Explore the impact of technological innovations, such as AI and self-checkouts in stores. Discover the relationship between AI, data science, big data, and the Internet of Things (IoT). Delve into whether AI presents a risk or an opportunity.