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This is the one skill everybody needs in the age of AI | World Economic Forum

• what have you learned in the last six months? You have to have people who want to learn and build a learning culture. 

• Analytical thinking and creative thinking remain the most important skills for workers ... Analytical thinking is considered a core skill by more companies than any other skill.

• We actually deployed AI education within our schooling. So from grade five onwards, people learn how to code. From grade nine onwards, kids in schools actually learn what artificial intelligence is, what are the ethics of it, and they also understand, whatever their career path is going to be, how AI is going to affect it. 
• Continuous learning, I think, is a hallmark.

• A statistic: The half-life of skills used to be 30 years. It's now seven years. So if you think about that, that means that an average career, you're going to change five times your overall skills.

• the only constant is change — we need to build a populace that is able to adapt to change

 

Critical Thinking in the Age of AI: Why It Matters More Than Ever

1. Question Assumptions: Encourage students to question the underlying assumptions behind any piece of information, algorithm, or technology. This fosters a culture of inquiry and skepticism that is crucial for navigating the complexities of AI.
   
2. Analyze Context: Teach students to consider the broader context in which data or technology exists. Whether it's understanding the ethical implications of a machine learning algorithm or the societal impact of a policy decision, context matters.
   
3. Seek Diverse Perspectives: Promote classroom discussions that involve multiple viewpoints. Encourage students to consult various sources and consider alternative explanations. This not only enriches the learning experience but also prepares students for real-world decision-making involving AI technologies.
   
4. Apply the Socratic Method: Use questioning techniques to stimulate critical thinking. For example, ask students to defend their viewpoints or explain the reasoning behind a particular data interpretation. This method can be particularly effective in higher education settings where complex issues are discussed.
   
5. Ethical Reasoning Exercises: Introduce case studies that involve ethical dilemmas related to AI, such as data privacy or algorithmic bias. Ask students to apply ethical frameworks to these issues, fostering a deeper understanding of the complexities involved.
   
6. Hands-On Experience: Provide opportunities for students to engage with AI technologies directly, perhaps through coding exercises or data analysis projects. This hands-on experience allows them to apply critical thinking in a practical context.
   
7. Reflective Practice: Encourage students to reflect on their thought processes and decision-making strategies. This could be through journal entries, group discussions, or individual consultations. Reflection is a key component of critical thinking and can be particularly enlightening when dealing with AI-related challenges.

 

Critical Thinking in The Age of AI - Educators Technology

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