Real World Artificial Intelligence in Education

To brighten a dull, damp Saturday at the start of December, I joined a stellar line-up one inspirational speakers at this year's Geek Girl Conference in London. @GeekGirl Meetup UK is a network, for and by, women and girls interested in all things tech, design, and startups. Our ambition is to highlight female role models in the industry, create networks for knowledge exchange, mentoring and sharing ideas – and, of course, to have fun!

I was there to speak about how Artificial Intelligence is no longer the work of Science Fiction, but here now in our every-day lives, and we are just scratching the surface of what it can do to help teachers and students prepare for the jobs of tomorrow.

Charts from my talk are on Slide Share

But how did we get here?

In the past few years we have seen 3 waves of technology that are co-inciding:

• Rise of Cloud – giving access to computing power and information everywhere and anywhere
• Rise of Data – generating vast quantities of structured and unstructured data – video, text, tweets, images collected from millions of sensors and devices. In fact, 90% of the world data has been generated over the past 2 years.
• Mobility – the iPhone in your pocket now has more compute power than the old SuperComputers of the 1970s
• These 3 waves of technology are underpinned by the need for Security & Privacy

With so much information and power at our fingertips, we needed to do something to help us control and use this to help us be more productive. A.I. is a solution to these challenges by reducing the gap between machines and humans helping us to be better at what we do.

What do we actually mean by Artificial Intelligence?

A.I. in an umbrella term that includes technologies such as Machine Learning, Deep Learning and NLP (Natural Language Processing)

• Machine learning is an integral part of AI and assists computers to learnand improve with each iteration to solve problemswithout being explicitly programmedby using mathematical algorithms. For instance, machine learning is used in spam filtering,Optical Character Recognition (OCR), search engines, and computer vision applications.
• The next important technology is Deep Learning learning, a branch of machine learning that combines the advanced computing power of processors with special types of neural networks to learn complicated patterns from large volumes of data. Deep learning achieves recognition accuracy at higher levels than ever beforeand it is crucial for safety-critical applications like driverless cars.
• Another significant technology is Natural Language Processing which s concerned with day-to-day communications between humans and machines. It can derive meaningful rinterpretation of naturally occurring texts/speech that can be in any languageand respond back to humans.  

So why not use A.I in education to help teachers and students fulfil their potential and cope with increasing diverse educational needs?

At IBM, our implementation of AI is called IBM Watson.

Watson is good at analysing massive amounts of data (research publications, news, social media, organisational data, medical data, lesson plans, etc.) and providing industry professionals (doctors, teachers, accountants, etc.) with relevant and clear recommendations based on a user-level request.

IBM Watson made its debut with a state-of-the-art question- and-answer interactions on Jeopardy Quiz Show, and is now available to software developers in the form of cloud Services such as visual recognition, speech-to-text, and text-to-speech function; language understanding and translation; and conversational engines to build powerful virtual agents of their own. You can find some fantastic A.I Code Patterns for developers here.

How does IBM Watson work in Education today?

Example 1

Dino, from Cognitoysis a small plastic dinosaur that runs on AA batteries, but the real magic is that its brain is powered IBM's Watson, with extensive natural language skills. Dino is available from Amazon for just £65 - so A.I does not need to cost a great fortune! The toy answers questions from children upto the age of 9 years old and features some child-friendly customisation. It scolds curse words, refuses to answer naughty queries and can adapt it's answers to the child's age. The educational aspects to the toys include its ability to define words and teach kids how to spell.

Although Dino is a fun just for fun, recent research has found that autistic children are more comfortable interacting with robots than humans, in part because robots are more predictable and can be controlled. Experts also say teaching social skills to children with autism requires frequent repetition. Last time I checked, robots are great at repetition. So, applying A.I. and robotics to educational toys could prove a way to interact for these children, their educators and parents.

What we should teach children and A.I?

• Until now we've made the mistake of thinking coding is a distinct career path, set aside for 'techies'. However, this will change. Children will need to know how to make technologies work for them, not just be consumers of it. Specialist software developers will of course be still be needed in abundance, but every individual - whatever their chosen career - will need coding. The UK government recognises these facts, and made significant changes to the Computing National Curriculum in September 2014, with children as young as five being introduced to elements of coding.
• It's fairly easy to teach Machine Learning even to young children
• IBM Developers are here to help all Developers through their learning journeys - from the very young to the experienced professional - with building Code, Content and Community to ensure every developer can be successful in implementing AI technologies in an ethical and responsible way.

Example 2 Machine Learning for Kids

Machine Learning for Kids https://machinelearningforkids.co.uk is a free resource from IBM that introduces school kids to the principles and implications of machine learning by helping them train simple machine models and use them to make games and interactive projects. It's been written by one of our own Engineers, Dale Lane @dalelane from the IBM Hursley Labs in the U.K. Machine learning expertise is not required. The project worksheets detail everything the children will do, with explanations for why, and examples of the real-world applications of what they do.

There are 15 machine learning projects at machinelearningforkids.co.uk/worksheets each of which has its own downloadable project worksheet containing detailed step by step instructions with screenshots and explanations. Experience of using the educational tool Scratch is helpful, but not essential (for answering student questions, or helping them with any problems with their Scratch scripts).

So how can we help teachers deliver education for our digital creators of the future?

Schools which embrace AI may find the role of teachers adapting to be closer to that of a mentor , guiding children through their education. 

Example 3 - Teacher Advisor with Watson

Because of Watson's ability to identify and then refer back to relevant concepts and relationships within a large corpus of data - in this case a library of free educational resources that we uploaded to, and had enriched by, Watson- Teacher Advisor returns highly informed results and recommendations. We began with 1,000+ lessons, activities, documents, and videos for Watson to ingest, then asked teachers and math experts, as well as other technical experts to provide Watson with the necessary guidance and training along the way

All creators have a responsibility to ensure their inventions made and used ethically and responsibly.

Back in the 1960’s when IBM introduced the first programmable systems, wehelped to establish the role of computer science in Education – something that had not previously existed as a discipline.

And the same goes for AI – we have a role to help teach the world about A.I.

Last year our CEO Ginny Romety issued a rare Policy letter on the 3 guiding principles for bringing A.I to life to help us make sure it is implemented and taught effectively:

• It’s important that people develop trust in AI systems. Its purpose is to aid humans, not replace them. AI should extend the capabilities of humans.
• Transparency You need to be clear as you build AI platforms how they are trained, what data was used and the business model behind the systems. Humans need to retain control of the system. We do not believe they will have a consciousness or be self-aware     
• Skills - AI platforms must be built with people in the industry – doctors, teachers or other professionals who will use the system

“Every organization that develops or uses AI, or hosts or processes data, must do so responsibly and transparently. Companies are being judged not just by how we use data, but by whether we are trusted stewards of other people’s data. Society will decide which companies it trusts.”

-Ginni Rometty, IBM Chairman, President and CEO

Our roles - as educators, parents, inventors and implementors - will be critical to guiding these skills, to prepare children to make effective use of technologies, to enable us to put in the right services for the right jobs and re-skill people that might be affected by this powerful technology now at our finger-tips.

For more information about using Artificial Intelligence to build amazing solutions to some of the worlds most challenging problems, join our Meetup.com groups in London or Bristol for fee hands-on workshops and talks from expert developers

• https://www.meetup.com/IBM-Code-London/
• https://www.meetup.com/IBM-Code-Bristol/
• Follow us on Twitter https://twitter.com/IBMDeveloperUK
• Check out our Code Patterms for all you need to create your own solution https://developer.ibm.com/patterns/