Artificial Intelligence and Human Learning
CEO & Co-Founder of AcuiZen
The term Artificial Intelligence or AI, has been widely used since the last century. However, its in these recent years we’ve seen huge progress in this space. The term artificial intelligence is when machines mimic humans and their ways of thinking and behaving, such as learning and problem solving. In 2001, Steven Spielberg directed a film called AI, where a robot named David, in the form of a boy, had an unquenchable need for his mother’s love and sought across time. The journey of David, a life-like robot, stirred fear and caught the imagination of audiences world-wide at the turn of the century. That was 17 years ago.
Today, researchers have created robots that are advanced enough to hold conversations and express emotions. But has AI has become part of our lives? Or are we still a long way to go? How will this impact us? Will AI truly take over our jobs and our learning?
Podcast Episode Highlights
What is artificial intelligence?
AI is about mimicking human behaviour, or rather mimicking humans. Within AI, there are multiple things, such as pattern recognition, voice recognition, etc. AI is the big umbrella term, within AI is machine learning and within machine learning there is deep learning.
The term AI is missed used extensively. AI today is pure data analytics, which has been around for many years. What has changed in the last few years is the amount and variance of data that has been collected. With today’s computing power, data is collected from multiple sources, dissected in multiple ways and can be used to predict the future. The AI we have today is like Siri, where you ask a question, refer to a database, and respond with the likely answer. It’s really about processing a huge amount of data.
What is machine learning? What is deep learning?
Let me give you an analogy of machine learning. Think of machine learning as a barista, where he or she recognises you and is able to make your regular coffee order. If you are a regular customer, the barista is able to recognise how the customer likes their coffee made. This is a form of pattern recognition and machine learning makes a prediction based on previously formed patterns. This type of AI has been around for many years.
Deep learning is looking at the data sources and recognising the variance in response. For example, the barista knows that the customer is in a good mood and therefore would prefer a different drink as compared to when the customer is in a foul mood. It’s about forming connections with other data sources.
What are some examples of machine learning and deep learning in our daily lives?
A simple example Siri reminder system, where it reminds us to buy milk on the way to work. With geotagging, as you pass by supermarket, Siri will remind you to pick up the milk. The system is programmed to respond to the user; as the user does this, the program will does that.
Deep learning is not yet there. It is mostly in an experimental stage. There are no known mainstream applications as yet, much of it is in research and development stage.
Humans are naturally curious, as quoted in your article. Machines are gradually reducing the cognitive ability of man and also impacting our curiosity. How and why is this happening?
Curiosity is man’s natural ability. It’s the curiosity that helps us form neural connections in the brain. It’s only through experimentation that bonds are formed between the conscious and subconscious mind.
My fear is that if we are spoon-fed everything, by way of being told the answers, we don’t take the time to think deeply enough to form those neural connections. When one has answers, it’s more likely the person who move onto the next thing. Therefore, it is a missed opportunity to form neural connections.
Going back to the generations where people needed to go to the library to research and look through 10 different books before concluding on an answer. It is no longer the case today. If you need any information, you just go to Google.
Is it not contradictory that you are involved in AI and yet you speak about losing one’s curiosity. How do you balance that?
What we focus on is providing solutions that help learners to form neural connections. Our biggest success is when learners stop using us, which means the neural connection has been formed. The reality is that we are not going to learn one subject and live without subject for the rest of our lives. Most likely people shift from one subject to another along with their careers. Those neural connections may degrade over time. There is a need for reinforcing at the point of when it is needed.
Apart from your company there are plenty of other companies that have invested into AI. According to the McKinsey report 2017, Baidu and Google spent between $20-$30 billion in research and development and acquisition of AI. How will is rapid growth of AI impact the learning industry? What do you believe are having?
There are learning technologies and we tend to mix up learning technologies with AI. Technology such as virtual reality and augmented reality, may not really be AI at this point in time. The fundamental application of AI, when it comes to education, will probably involve a lot of personalisation. It is about looking at an individual learner and identifying which areas require further reinforcements, through asking questions, reviewing concepts and so on.
There are educators who are resistant to technology and to AI. There are instances where educators require their learners to put away their devices in the classroom. How will technology or AI impact the educators were resistant to this advancement?
Educators have a huge role to play, and it will not change any time soon. Educators need to be conscious of what their role is. If an educator views their role as a provider of information and deliver course material irrespective of what is happening to the learner, we are in for trouble. Educators need to see themselves as stirring the curiosity and interest to go deeper into the subject. It is not just about giving the right information, it is about asking the right questions. That is what machines do not have the ability to do any time soon.
Moving away from the role of being a trainer to being a facilitator is going to become increasingly important. With technology, we have to recognise that the attention spans of learners are decreasing enormously. As a facilitator, you have to be interesting at all points in time to keep the learners engaged. If you are a great storyteller, no one is going to pick up their hand phones and interrupt your story.
How can we help educators, trainers and facilitators embrace technology in the roles?
There is a lot of advantages of the technology for educators. Technology will be able to take away the mundane tasks, such as grading. There are some good examples such as flipped learning, providing generic information before a class and using the time in class for meaningful discussion. By taking away the mundane task, trainers will be able to use the time in class to facilitate and ask meaningful questions.
I believe there is a general fear, not just in education, but everywhere else, that AI will take over jobs. Is it too premature to predict that AI will take over jobs? Or do you believe humanity will find a way to survive?
I think the threat is for real. It is not impossible to predict that many jobs will be lost to AI. I have simple rule of thumb for this. My simple rule of thumb is look at the job you’re doing today, is this a job that can be described by simple standard operating procedure? If this is a job that can be described by a simple standard operating procedure, my fear is one day can be automated.
But if your job cannot be described by simple standard operating procedure, rest of assured it will take a while before technology or AI will take over your role. If you look back at some of the jobs that have been lost such as simple accounting jobs and simple call centre jobs, these are all standardised and peoples jobs were at risk. This is where educators hold an important role. It is hard to describe what a great facilitator looks like. These are skills that are developed over time, such as gauging the students and continuously tweaking the approach every time.
What do you foresee will happen in the next 5 to 10 years when it comes to AI and human learning?
The trend is going to accelerate. We are going to see more technology being used. What I see as the trend is moving away from mere learning to learning on the job and the performance of the person.
Currently, there is too much focus on provision of the information and knowledge. This will shift towards focus on the performance of the individual. The activity of learning will morph into “learning as a journey”. The personalisation of learning through technology and AI will extend beyond the classroom. I believe learning will move from being a transaction into a relation where a learner can connect with the trainer or educator over a long period of time. It will be a shift from learning to performance.
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