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AI and Learning: Navigating Opportunities, Upskilling, and Ethics

Artificial Intelligence (AI) is rapidly transforming how people learn, teach, and upskill. From personalized learning platforms to generative AI tools, the landscape of education and professional development is being redefined. As professionals embrace these changes, it's crucial to ask the right questions, leverage top resources for upskilling, and grapple with the ethical dilemmas that come with AI's growing influence.

Five Key Questions for AI and Learning

1. What unique aspects of human learning can and cannot be replicated by AI?
   AI excels at pattern recognition, personalization, and automating routine tasks, but can it truly replicate human creativity, empathy, and critical thinking? Understanding these boundaries helps educators and learners use AI as a complement, not a replacement.

2. How might reliance on AI affect human decision-making, problem-solving, and critical thinking?
   Overreliance on AI tools risks diminishing learners' independent thinking and problem-solving skills. How do individuals ensure AI is a scaffold, not a crutch, in the learning process?

3. How do people empower learners to use AI ethically and responsibly?
   With AI's power comes the need for digital literacy, data privacy awareness, and ethical guidelines. What frameworks are needed to foster responsible AI use in and beyond the classroom?

4. How might uneven access to AI technologies exacerbate existing inequities?
   Subscription-based or advanced AI tools may not be available to all, potentially widening educational and economic gaps. How can access to AI-powered learning be democratized?

5. What does original thought mean in an AI-augmented world?
   As generative AI produces text, images, and even code, how do professionals define and value originality and creativity in student and professional work?

Key AI Tools to Help You Learn

These AI assistants can actively help you learn about AI itself through direct interaction:

• ChatGPT (https://chat.openai.com): The world's most popular AI assistant with 200 million users as of October 2024. Ask it to explain AI concepts, create personalized learning paths, or generate practice exercises. The latest GPT-4o model offers multimodal capabilities, allowing you to upload images and receive voice responses. Try prompts like "Explain machine learning algorithms to a beginner" or "Create a study plan for learning AI fundamentals."

• Claude (https://claude.ai): Excels at coding tasks and has the largest context window (200,000 tokens), making it ideal for analyzing lengthy documents or research papers. Ask Claude to break down complex AI research papers or create coding tutorials tailored to your skill level. Try "Help me understand how transformers work in AI" or "Create a beginner Python project to understand machine learning."

• Perplexity (https://perplexity.ai): Stands out for research capabilities with robust citation features. Unlike other AI tools, Perplexity provides sources for its answers, making it excellent for academic research on AI topics. Ask it questions like "What are the latest developments in generative AI?" or "Compare different machine learning frameworks for beginners."

• Google Gemini (https://gemini.google.com): Offers strong integration with Google's ecosystem and excels at explaining complex topics with visual aids. Try asking "Create a visual explanation of how neural networks function" or "What are the ethical considerations in AI development?"

Top YouTube Channels for Learning AI

YouTube offers some very resources for AI education (try your own search):

• Two Minute Papers (https://www.youtube.com/@TwoMinutePapers): With approximately 2 million subscribers, this channel delivers bite-sized summaries of the latest AI research papers in just two minutes, making complex topics digestible.

• Yannic Kilcher (https://www.youtube.com/@YannicKilcher): Offers in-depth AI paper analysis with around 300,000 subscribers. Ideal for intermediate to advanced learners seeking technical explanations of cutting-edge research.

• Sentdex (https://www.youtube.com/@sentdex): Features practical machine learning tutorials in Python with approximately 1.5 million subscribers. Perfect for hands-on learners who want to build real projects.

• StatQuest with Josh Starmer (https://www.youtube.com/@statquest): Breaks down the statistical foundations of AI with clear, engaging visuals. Essential for understanding the math behind machine learning concepts.

• Lex Fridman (https://www.youtube.com/@lexfridman): Offers in-depth interviews with AI experts and researchers, providing broader perspectives on AI's impact and future.

Top AI Newsletters to Stay Updated

Some key newsletters to keep up with the rapidly evolving AI landscape:

• PCDN AI for Impact Newsletter (https://impactai.beehiiv.com): Equips changemakers with tools, insights on ethics, career opportunities, funding, and upskilling resources to leverage AI in the social impact sector.

• The Rundown (https://www.therundown.ai): With over 600,000 subscribers, this daily newsletter shares trending AI projects, usage ideas, news updates, and related tools and tutorials in a quick, digestible format.

• Mindstream (https://mindstream.com): Delivers 5-minute daily updates on AI industry news, tools, and productivity tricks to over 130,000 subscribers. Each issue includes a tutorial on using a new AI tool.

• Superhuman (https://superhuman.ai): With over 650,000 subscribers, this daily newsletter by Zain Kahn focuses on leveraging AI for career growth, productivity, and self-improvement.

• The Neuron (https://theneuron.ai): Provides "all signal, no noise" AI updates to over 425,000 readers daily, including industry news breakdowns and top AI tools with a touch of humor.

• The Batch (https://www.deeplearning.ai/the-batch/): Created by Andrew Ng's DeepLearning.AI, this authoritative weekly newsletter covers machine learning research, industry developments, and practical applications.

Ethical Dilemma: AI for Impact—Who is Accountable When AI Gets It Wrong?

As AI systems become more embedded in education and decision-making, ethical dilemmas grow more complex. One of the most pressing questions is: Who is responsible when AI makes a harmful or unjust decision?

AI can inadvertently perpetuate biases present in its training data, leading to discriminatory outcomes in areas like admissions, hiring, or grading. At the same time, the "black box" nature of many AI models makes it difficult to understand or challenge their decisions, complicating transparency and accountability.

Privacy is another major concern—AI-powered learning platforms often require large amounts of personal data, raising questions about consent, data protection, and the risk of breaches. Overreliance on AI could also erode critical thinking and human agency, shifting responsibility from individuals to opaque algorithms.

The dilemma:
When an AI system leads to an unfair outcome—such as denying a student an opportunity, misgrading an assignment, or reinforcing social inequities—who is accountable? Is it the developer, the educator, the institution, or the AI itself? And how do professionals ensure transparency, recourse, and continuous improvement as AI becomes ever more central to learning and impact work?

Conclusion

AI's integration into learning offers unprecedented opportunities for personalization, access, and creativity. Tools like ChatGPT, Claude, and Perplexity can actively help you learn about AI through direct interaction, while YouTube channels and newsletters keep you updated on the latest developments. But these technologies also demand that tough questions be asked, skills be responsibly developed, and ethical dilemmas be confronted head-on. As changemakers, educators, and impact leaders, the challenge is to harness AI's potential while keeping humans at the center of the work.

Whether you love to hate AI or are "drinking the AI-kool aid," the technology is here to stay, and "the bus is passing with or without you."

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News & Resources

😄 Joke of the Day
Why did the AI teacher get kicked out of class in?
It refused to take attendance—said it only tracks data, not people.

Today in AI + Impact

📚 AI steps in where teachers are missing — but at what cost?
Facing a nationwide teacher shortage, Kenyan schools are piloting AI learning tools. Some say it’s a bold solution, others warn it's a shortcut that may deepen inequality without addressing root problems.
📰 Read: https://restofworld.org/2025/ai-teaching-tools-kenya-teacher-shortage/

🚫 Brazil says no to automating social security
A proposed AI-powered app to manage Brazil’s welfare system was rejected over fears of exclusion, privacy risks, and lack of human accountability. It's a reminder that not every service should be automated.
📰 Read: https://restofworld.org/2025/brazil-ai-social-security-app-rejected/

🧵 Big Tech’s hidden workforce in Africa
A new report uncovers how African workers are powering global AI—labeling data, moderating content, and training models under low pay and little protection. Essential labor, still largely invisible.
📰 Read: https://restofworld.org/2025/big-tech-ai-labor-supply-chain-african-workers/

💼 Looking for work that matters?
Find hundreds of remote and global roles in AI ethics, sustainability, peacebuilding, and more on the PCDN Impact Career Board. See a cool overview below.

👤 Linkedin Profile to follow:
Aravind Srinivas
Co-founder of Perplexity AI and former OpenAI researcher. He shares thoughtful insights on building smarter, safer AI—and where we need to stay cautious.