Digital Technology Flashcards
(254 cards)
What is Artificial Intelligence (AI)?
A rapidly advancing field that enables computers to make decisions and solve problems without explicit programming.
AI is transforming how we live and work.
What is machine learning?
A type of AI that uses data to learn and make predictions based on patterns.
Machine learning recognizes patterns without being explicitly programmed.
What role do algorithms play in machine learning?
They recognize patterns in data without being explicitly programmed.
Algorithms are essential for making predictions and decisions.
How do machine learning algorithms make predictions?
By using patterns recognized in data.
This process allows for informed decision-making.
True or False: Alexa is the name of an AI-powered academic search engine.
False.
The correct answer is the Allen Institute for Artificial Intelligence.
What distinguishes machine learning from traditional programming?
Machine learning recognizes patterns in data while traditional programming involves step-by-step instructions written by programmers.
Why is it important to learn about AI and machine learning?
To understand AI decisions and recognize AI interactions in our lives.
What is the difference between AI and machine learning?
AI is a broad field, while machine learning is a specific type of AI.
How does machine learning work?
Machine learning algorithms recognize patterns in data to make predictions.
What impact do AI and machine learning have on daily life?
They are integrated into many aspects, including online recommendations and voice assistants.
What are some real-world applications of machine learning?
Disease detection and autonomous vehicles.
Fill in the blank: Machine learning algorithms learn from _______.
[data]
What do machine learning algorithms recognize in data?
Patterns.
Recognizing patterns is crucial for making predictions.
What do machine learning algorithms use patterns for?
To make predictions.
This is a fundamental aspect of how machine learning operates.
What is the significance of understanding AI and machine learning?
To comprehend the impact of AI and machine learning on our lives.
How are advancements in AI and machine learning shaping the future?
They present both opportunities and challenges.
What role does training data play in machine learning?
Training data shapes the accuracy and outcomes of AI models.
The quality and diversity of training data are critical for AI model performance.
What can biased training data lead to?
Biased predictions, perpetuation of harmful stereotypes and inequities.
It emphasizes the need for diverse and unbiased data.
Why is it important to collect diverse training data?
To ensure fairness and representativeness in AI systems.
Diverse data helps mitigate bias and creates equitable AI.
What must AI developers examine to mitigate bias?
Data sources, collection methods, and demographics represented.
Careful examination is crucial for ethical AI development.
How does diverse training data contribute to AI?
It helps mitigate bias in training data and leads to fairer AI systems.
Including a wide range of perspectives is essential.
True or False: Biased datasets do not affect AI predictions.
False.
Biased datasets can lead to the perpetuation of harmful stereotypes.
Fill in the blank: The accuracy of AI models relies heavily on the quality and _______ of the training data.
[diversity]
Quality and diversity are key factors in developing effective AI models.
What is crucial for building ethical and responsible AI systems?
Ensuring fair and representative training data.
This includes collecting data from multiple perspectives.