Humans vs AI
This type of intelligence belongs to people and includes emotions, creativity, and personal experience.
What is human intelligence?
AI systems use these to represent knowledge and make decisions.
What are models or rules?
Machine learning models improve by learning from this.
What is data?
Treating people equally and avoiding discrimination in AI systems is called this.
What is fairness?
AI can change this area by automating tasks and creating new types of jobs.
What is the economy?
AI is especially good at doing this with large amounts of data very quickly.
What is processing or analyzing data?
This refers to how AI organizes and stores information about the world
What is knowledge representation?
The process of teaching an AI model using data is called this.
What is training?
Protecting people's personal data is known as this.
What is privacy?
AI can affect the environment through this resource used by large data centers.
What is energy?
Humans are better than AI at this skill involving empathy and understanding feelings.
What is emotional understanding / empathy?
AI systems follow logical steps like this to reach conclusions.
What is reasoning?
Sorting data into groups like “spam” or “not spam” is called this.
What is data classification?
Using AI in ways that are safe and beneficial is called this.
What is responsible AI use?
AI tools like recommendation systems influence this part of society.
What is how people access information?
AI can outperform humans at this type of task involving repetitive calculations.
What are complex calculations or repetitive tasks?
In AI, a simplified version of reality used to predict outcomes is called this.
What is a model?
A problem that occurs when training data unfairly favors one group over another.
What is bias in training data?
Identifying unfair outcomes caused by AI is part of ensuring this.
What is ethical AI?
When discussing AI impact, we often ask this important question.
Who benefits or is harmed by AI systems?
This classroom discussion topic focuses on deciding what tasks AI should or should not do.
What are ethical boundaries for AI?
Understanding these helps us see why AI makes certain decisions.
What are assumptions behind AI decision-making?
Machine learning models look for these in data to make predictions.
What are patterns?
This term refers to the hidden preferences or unfair patterns that can appear in AI systems.
What is algorithmic bias?
Considering the long-term effects of AI on communities and resources involves thinking about this.
What is societal impact?