CRESTing Artificial Intelligence
We are living in exciting times. Many say we are on the cusp of an industrial revolution with the rise of machines that can think, or artificial intelligence (AI).
Artificial intelligence is the term for computational methods and techniques that solve problems, make decisions or perform tasks that, if performed by humans, would require a great deal of thought. The growth in its use is being helped by the convergence of advances in big data (storage technology), fast processing power (computers) and wide connectivity (internet).
Artificial intelligence can be applied in almost every industry and has the potential to transform economies and greatly enhance quality of life.
CREST invites students to undertake an AI/Crest investigation exploring some potential applications that new AI methods and techniques might have to help address challenges in their community.
Here are some starter ideas:
- Using AI image recognition software to recognise various pests in their yard/farm and estimate the density/ distribution of pests in an area
- Using energy consumption data in their household and use AI software to predict future consumption based on factors such as time of the day, temperature, weekday, etc.
- Check out pages 11-13 of The Age of Artificial Intelligence in Aotearoa
Possible areas of Assessment
- Digital citizenship
- Digital Fluency
- Technological Practice
- Technological Knowledge
- Nature of Technology
- Computational Thinking for Digital Technologies 6-8
- Designing and Developing Digital Outcomes 4-6
- The age of Artificial Intelligence in Aotearoa. Royal Society Te Apārangi. www.royalsociety.org.nz/AI
- The Effective and Ethical Development of Artificial Intelligence: An Opportunity to Improve Our Wellbeing. Australian Council of Learned Academies (ACOLA). https://acola.org/hs4-artificial-intelligence-australia/
- TensorFlow (an open-source machine learning library that offers APIs for beginners and experts to develop for desktop, mobile, web, and cloud) https://www.tensorflow.org/tutorials
- Pytorch (An open source deep learning platform) https://pytorch.org/
- Scikit-learn (Simple and efficient tools for data mining and data analysis) https://scikit-learn.org/stable/
- Ludwig (an open source code-free deep learning toolbox) https://uber.github.io/ludwig/