Oh the IB diploma. This is where things get mega serious. This is the 3rd in a 4 part article set on how to practically add AI education into your school.
Introduction: Charting a Future at the Diploma Programme (DP) with AI
At the DP its time to make choices. Some students will want to use AI in their future and some will want to build it. The reality is that everyone is going to interact with it just as we interact with Google search today. Our task as educators is to ensure that at the minimum, they can interact with it proficiently and responsibly. For the more keen, we have to point them in the right direction. I'd suggest 3 things we can do with great impact. First, point them in the right direction to acquire more skills. Secondly, how AI changes the way we see "truth". Third, Guide the enthusiastic towards career options.
1. Acquisition of AI Technical Skills
For all students , acquiring technical AI skills is the first crucial step. Here, we explore accessible, top-tier resources that provide both foundational knowledge and advanced insights into AI, ensuring that students are well-prepared to take on higher education and professional challenges in AI fields.
Top "Short Course" Resources:
- Elements of AI (University of Helsinki): This free online course is an excellent start for anyone new to AI. It covers AI fundamentals without requiring prior programming knowledge, making it accessible to all students. The course emphasizes understanding AI's capabilities and limitations and sparks interest in further AI studies. Elements of AI
- Machine Learning by Stanford University (Coursera): Taught by renowned AI expert Andrew Ng, this course dives deep into machine learning, one of AI's core components. It provides practical knowledge on algorithms and how they can be applied to massive datasets to create predictive models. This course is perfect for students who want to pursue advanced studies and careers in AI. Coursera - Machine Learning
- AI For Everyone (DeepLearning.AI on Coursera): Also led by Andrew Ng, this course demystifies AI for non-technical audiences. It discusses how AI impacts all sectors, making it a valuable course for students regardless of their major. It prepares them not only technically but also broadens their understanding of how AI can be harnessed in various industries. Coursera - AI For Everyone
Professional Paths: Entering the AI industry typically requires a strong educational foundation in relevant fields. Degrees in Computer Science, Data Science, or specialized programs in AI and machine learning are highly recommended.
Top Universities for AI Degrees:
- Stanford University
- Massachusetts Institute of Technology (MIT)
- University of Cambridge
- Carnegie Mellon University
- University of California, Berkeley
2. AI and the Theory of Knowledge (TOK)
The Theory of Knowledge (TOK) provides a unique platform within the DP to delve into the philosophical aspects of knowledge and technology. Integrating AI discussions in TOK allows students to explore and question the impact of artificial intelligence on our understanding of knowledge, truth, and ethics.
Educational Approach: Incorporating AI into TOK involves discussing how AI challenges traditional notions of "truth" and "knowledge." It encourages students to consider how AI influences decision-making processes, the ethics of AI, and its role in shaping our understanding of various areas of knowledge.
- Basis of Truth and Ethics: Use AI as a case study to explore philosophical questions such as "Can AI know?" and "How does AI challenge our understanding of truth?" Discuss scenarios where AI makes decisions based on data and algorithms, and examine the implications of these decisions.
- Impact on Areas of Knowledge: Evaluate how AI tools and methodologies affect disciplines like science, where AI can analyze data and create models that predict outcomes, or history, where AI can help interpret vast amounts of historical data. Discuss the role of AI in arts, considering how AI-generated art challenges our perceptions of creativity and authorship.
TOK Questions you can use today:
- Can machines possess knowledge in the same way humans do? What distinguishes human knowledge from machine knowledge?
- Is it ethical for AI to make decisions that affect human lives? What criteria should be used to judge these decisions?
- How does the use of AI in gathering and analyzing data influence our understanding of truth? Does AI enhance or obscure objective reality?
- In what ways might AI challenge our definitions of creativity and authorship? Can a machine be truly creative, or is it merely simulating creativity based on programmed algorithms?
- To what extent should humans delegate moral and ethical decisions to machines? What are the potential risks and benefits of doing so?
- How does AI affect our perception of consciousness and intelligence? Can AI be conscious, and if so, what implications would this have for our understanding of consciousness?
- What ethical responsibilities do developers have when creating AI systems? How should they address issues like bias, fairness, and transparency in AI?
- Can AI ever fully understand or emulate human emotions? What does this suggest about the nature of emotions and their role in human reasoning?
- How might the integration of AI in various fields change the nature of expertise and authority in those fields? Will AI enhance or replace human expertise?
- What are the implications of AI potentially replacing human roles in the workplace, economy, and society at large? How should society adapt to these changes?
TOK is a wonderful subject, great at getting your students to see different perspectives and break biases. Our children are going to be fed lots of information (and misinformation) about AI in the future but you can prepare them to think and assess the information critically!
As AI continues to revolutionize industries, understanding AI-driven careers becomes essential for DP students. Your career counsellor needs to be able to guide them to explore the various career paths within AI, their potential salaries, and provides resources for further exploration.
- Data Scientist: Typically earns between $85,000 and $170,000 annually. Data scientists analyze complex data sets to derive insights and build predictive models, a crucial role in many sectors.
- AI Engineer: Salaries range from $100,000 to $150,000. AI engineers develop algorithms that enable machines to perform cognitive functions similar to human brains.
- Machine Learning Engineer: With earnings from $100,000 to $150,000, these professionals focus on creating data funnels and delivering software solutions.
- Robotics Engineer: These engineers, earning between $75,000 and $125,000, design and build robots that automate tasks.
Resources for Career Exploration:
I really like encouraging my students to "follow" certain influencers to learn more about their chosen career. Its in line with their preferred way of consuming media and opens their world to the reality of different topics!
Top AI Influencers on Twitter
- Andrew Ng - Co-founder of Coursera, DeepLearning.AI, and a pioneer in AI education and deep learning. Focuses on AI learning resources and industry insights.
- Fei-Fei Li - Known for her work in computer vision and AI ethics, Co-director of Stanford's Human-Centered AI Institute.
- Yann LeCun - Chief AI Scientist at Facebook, focusing on deep learning and AI research.
- Demis Hassabis - Co-founder of DeepMind, focuses on applications of AI in health and AI's potential to solve scientific problems.
- Ian Goodfellow - Known for inventing Generative Adversarial Networks (GANs), focusing on AI security and ethical AI development.
Top AI Influencers on Instagram
- Lex Fridman - Research scientist and podcast host who discusses AI topics, making complex subjects accessible and engaging.
- Kate Crawford - Researching the social implications of AI, focusing on AI ethics.
- Elon Musk - Though his posts cover a broader range of topics, his insights into AI and its future impact are highly influential.
- Sebastian Thrun - Founder of Google X and Udacity, shares insights on AI education and autonomous vehicles.
- Fei-Fei Li - Shares her professional work on human-centered AI and AI ethics, a great resource for understanding AI's impact on society.
Top AI Influencers on LinkedIn
- Andrew Ng - Shares educational content and insights into the AI industry, useful for students interested in AI trends and learning opportunities.
- Fei-Fei Li - Offers a perspective on the intersection of AI technology and human values.
- Hadelin de Ponteves - AI entrepreneur and educator, shares content on AI advancements and learning resources.
- Allie Miller - Focuses on AI innovation and entrepreneurship, providing advice for AI startups and business development.
- Kai-Fu Lee - AI expert focusing on the development of AI in China and globally, shares insights on global AI trends.
Top AI Influencers on YouTube
- Lex Fridman - Offers interviews with other AI experts and tutorials that explain AI concepts in an understandable way.
- Siraj Raval - Provides educational videos on AI and machine learning projects, good for hands-on learning.
- Two Minute Papers - Breaks down complex AI research papers into understandable content, showing the latest advancements in AI.
- Sebastian Thrun - Shares his expertise in AI, robotics, and education technology.
- Yann LeCun - Though less active, his talks and interviews on deep learning are highly educational for advanced learners.
The future of AI is evolving so fast that its not as helpful to tell students what "IS" but rather help them learn how to find out information about "what could be" when the time comes.
Conclusion: Shaping Future Innovators and Thinkers
The DP is the time of choices, often the first time our kids have had to make a difficult decision about where their life is going. One thing is certain though, which requires no choice. AI is part of that future. Our responsibility here is to make sure they don't hide their head in the sand. We need to get them excited and confident with AI. That means integrating AI into our classrooms, talking about AI, showing them that we feel comfortable with it as Educators. Learners don't learn from what you say, they learn from what you do.
For Dr. Vincent Chian, education is as much about leadership as it is about lifelong learning and accessibility. When not engaged in teacher training, he seeks the quiet solitude of photography or the rhythmic pace of a bike trail. His nights are often filled with the art of writing in journals and enjoying anime with his family.
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6 个月It's becoming clear that with all the brain and consciousness theories out there, the proof will be in the pudding. By this I mean, can any particular theory be used to create a human adult level conscious machine. My bet is on the late Gerald Edelman's Extended Theory of Neuronal Group Selection. The lead group in robotics based on this theory is the Neurorobotics Lab at UC at Irvine. Dr. Edelman distinguished between primary consciousness, which came first in evolution, and that humans share with other conscious animals, and higher order consciousness, which came to only humans with the acquisition of language. A machine with only primary consciousness will probably have to come first.