Course: Fundamentals of AI
This module offers an in introduction to the fundamentals of Artificial Intelligence, covering its history, development, and essential concepts. Participants will gain an understanding of Machine Learning and Deep Learning and their applications in environmental contexts.
Good morning and a warm welcome to Module 3 of the Humanity Environmental Education AI course. I'm Lee Mallon, and I’ll be accompanying you on this exploration of AI fundamentals. In this module, we’ll prime you with an understanding of artificial intelligence, debunk common buzzwords, and discuss its role in storytelling and education.
Module Breakdown
This module is segmented into five key sections:
- AI's History
- Understanding AI Terminology
- Generative AI and its Importance
- Case Study: Application at COP 28
- Ethical Considerations in AI
A Brief History of AI
The journey of AI spans most of the last century, with significant advances post-WWII. However, the last 30 years have been pivotal due to cycles of rapid development and dormant periods, known as 'AI winters'. We're now at an inflection point, thanks to the advent of personal computing, cloud storage, and the aggregation of data, particularly through social media platforms.
Demystifying AI Terms
AI can be overwhelming with its plethora of terms and academic jargon. Remember, if your goal is to leverage AI for storytelling, in-depth technical knowledge is not imperative. The essence of AI boils down to data, code, relationships, and decisions. We’ll dissect these components and their relevance to the models we’ll be using.
Generative AI: The Game-Changer
Generative AI, unlike predictive models, doesn't just classify—it creates. Whether it's composing text, synthesising images, or conceptualising music, generative AI models are the main reason we're here. They mark a shift towards more humanistic AI interactions, going beyond simple tasks and engaging in complex content creation.
Case Study: COP 28
An example of AI's application is the analysis of social media for environmental impact assessment, as I presented at COP 28. We utilised AI to track changes in environmental landscapes over time, demonstrating AI’s potential to aid in both damage assessment and recovery planning.
Ethical Considerations
While AI opens up a realm of possibilities, we must navigate its use with ethical foresight. Issues of copyright, data governance, truth and bias present challenges that must be scrutinised. AI may hallucinate or introduce bias, emphasising the need for fact-checking and critical evaluation of AI-generated content.
Closing Thoughts
As we wrap up Module 3, we prepare to delve into Module 4: Talking to Information. This journey into AI is sure to enhance your narrative abilities, and I look forward to seeing how you apply these insights to your environmental education efforts.
Thank you for joining me today, and I hope this module has provided you with a solid foundation in AI fundamentals. Have a splendid afternoon!