AI and ML in Education

nVidia's GAUGAN AI image creation

Computer programming as a mandated part of the curriculum began in the UK in 2013. Six years later we are beginning to see other educational regions requiring computer programing in the curriculum. But what about some of the more advanced tool? What about Machine Learning (ML) and Artificial Intelligence (AI)? We live with intelligent tools daily now. Whether you are shopping online or asking Siri for the time you are connecting to intelligent machines. But we aren’t all discussing how to implement it in the classroom. My mission at ISTE 2019 in Philadelphia was to explore what we are doing with AI and education. Here’s what I’ve taken away. 

We have been asking an entire profession to pick up a necessary skill set by tomorrow. And we need them to do it again. Computer programming in the classroom integrated through various courses is very popular now. Many classrooms are drawn to block-based coding like Scratch or Code.org. Much of the content delivery can be done through a video tutorial and try it yourself technique. The educator doesn’t need to know much about computer programing just enough about technology to setup a digital classroom. While this is not the most effective way to educate it can get the job done. We need to begin approaching AI and ML topics in the classroom and this may be the way to get a jumpstart into it. 

AI and ML tasks are accessible now more than ever. Educational resources are out there to begin talking about and trying AI. Google has a number of projects which can spark a classroom conversation and exploration on the topic. One of my favorite tools is a visual training demonstration called Teachable Machine. Students can train the system to recognize objects. The concept of data being routed through neural networks is very clear from the visual layout of the website. It can spark conversation on the differences between sensing and perceiving. The extraction of meaning from the images to say a word, show a gif, or play a sound supports student understanding of the concept of perception. This easily integrates into biology curriculum as the human senses are explored. 

Large datasets can be engaged by our students in various ways. Gapminder provides a visually stunning display of over 100 years of data. We can see populations grow and shrink over time as it’s tracked over 6 variables. This timeline motion chart feature brings something to the classroom we would have to make a 100 page graph paper flip book to replicate in the physical world. While this is a goto dataset there are others to explore with classes. The conversation can be around math or history. It all depends on from what angle you want to look at the material. The life expectancy drops from world wars are very clear. 

The level or AI and ML learning our students need to be at when graduating high school as recommended by AI4K12.org is high. I agree with their guidelines and I’ve been working to educate myself but I still am about the level of a 6th grader.

Educators need more educational opportunities to be able to understand the emerging technology. Curriculum will be generated by the big tech companies but it’s a necessity for educators to have a bit of a deeper knowledge of the tools than the in-the-box materials provided. We need to know what’s possible in order to integrate the learning throughout our curriculum. The work of Dr. Scott Garrigan can be a wonderful place to start. He is an educator whose interest is in cognitive disabilities. He provides professional development on many topics. He understands the pedagogy and can help support in implementing AI and ML through a curriculum. 

While this is not an exhaustive list of resources they do provide places to get started. 

• Scratch AI exploration
• Machine Learning for Kids provides hands-on explorations.
• Teachable Machine perception of objects demonstration
• GAUGAN AI image creation program.
• Breve a genetic machine learning model learning to walk (no longer kept up so may crash)
• TensorFlow Playground a visual representation of what happens under the hood. 
• Calypso for Cosmo software teaches robot logic and behavior. (Cosmo is out of business but the robots are still out there)
• AI-4-all free program for high school students in AI. 
• World Intelligence Competition for Youth compete globally in AI.
• Artificial Intelligence ISTE Course.

We will very quickly approach the point that we won’t be able to tell if a computer is speaking to us or a human. Just last year Google Duplex was demoed and is now released. If this is our reality now what will it be when our students graduate? Shouldn’t we begin making the effort to include AI in our curriculum now? We are seeing a scramble to include coding in the curriculum. AI and ML have coding in them but the concepts can be vastly different. If we wait much longer to push this into our schools we will miss the opportunity and fall behind. 

In light of recent political events I was deeply struck by a quote regarding AI: “Whoever becomes the leader Artificial Intelligence will become the ruler of the world.” -Vladimir Putin, 2017. Looks like educators have some work to do. 

Don't Talk At Me, Talk With Me

I had an opportunity to attend the Google Cloud OnBoard ML yesterday in NYC. My expectations were an introduction to the Google Cloud, some Machine Learning, and a bit of a sales pitch. I expected to walk away with some minor new skill in doing a linear regression on Google's Platform. What I walked away with was a clear experience of what education should not be. Even as a theatrical experience it should not be what Google gave us. Large companies would benefit from engaging with life long educators on how to model and connect with other during their events.

On arrival I set myself up at a hightop to do some work. It wasn't long before a Googler was engaging some attendees behind me. Of the three being chatted up there was a vast range of skills sets with their experience in cloud technologies and machine learning. One had no experience, another had played with cloud products and another had run some machine learning with scikit-learn. This was a good snapshot of what I saw the rest of the day; various skill levels with a common interest to learn and know more about machine learning.

The event started in a large ballroom with close to 1000 of us seated at thin tables facing a presenter and two large screens. This was my position for the majority of the day. A brief video was presented on organizing data and machine learning. Then a kickoff by a customer relations manager. All a basic intro with housekeeping format to begin the day. This degraded educationally from here.

ROITraining lead the training elements of the day. The format was a lecture that almost wanted to be socratic but failed in a large room. Followed by a demo that moved so fast if you wanted to follow along on your own terminal you needed to have an understanding of what was being demonstrated before the demonstration. This went on for six modules with lunch and a break in between.

While I soaked up the knowledge of the Google infrastructure and gained a better understanding of how the cloud worked there wasn't an opportunity to try the skills presented or anyone easily accessible to support when stuck. The intention is to "on board" the users to machine learning on the cloud. What I experienced was being talked at for a day.

Teachers capitalize on the basic fact that students show up everyday to learn something. Often not all students want to be in the classroom learning. Large events such as what Google offered provide rare opportunities of a filled space of eager learners. When you have that level of attention on a topic of product every moment counts. Engage the learner, build connections, and develop entry level skills. Avoid a chalk and talk scenario.

• Provide opportunities for intimate questions or anonymous questions. Have a back channel going. a place for some one to ask that question they don't want to feel stupid for asking publicly or wasting time on. 
• Setup sections for various levels of support help. Provide the support for that section. 
• Direct attendees to live help in the moment. You have me in the room now. Don't direct me to an online course. I would stayed at home and done in. 
• Connect members in similar and diverse fields. Such similarities and diversities can solve more problems when connected than apart. Create the opportunities for connections. 
• Talk with me, not at me. You have me present engage me. Work with me. Provide opportunities for me to explore and be successful under your guidance. 
• Give immediate reference resources. Don't assume everyone knows how to begin a demo. provide the lowest level documentation or be clear about prerequisites. 

I've been in many effective classrooms. The most effective for older learners provide autonomy to the learner with direct facilitated support and easily accessible resources. Consider the least skill level in the room and provide ways for them to be successful and grow.