Introduction
Today, the term ‘learning technology’ automatically triggers associations such as online classes, MOOCs, Moodle, Miro boards, learning platforms, breakout rooms, wiki’s, facebook groups, flipped classrooms, skillShare, udemy, edX, VR, AR, ai powered learning apps, virtual classrooms, online labs, hybrid learning, …
These are all tools designed to facilitate, enhance, streamline, deliver or optimise learning experiences. In this classroom, we explore a possible future in which technology has advanced in such a way that it is able to actually take control of the whole learning process.
The class zooms in on two specific domains (ai and neurotechnology) and sketches a few ideas on how technological advances in the upcoming decades might impact learning in higher arts education. These scenarios on their hand expose future challenges related to ethics and the relation with - and trust in - technology.
Definition
Let’s kick off by trying to get a better understanding of the term ‘Technology Enhanced Learning’ (TEL). IGI Global has quite a complete definition, describing seven perspectives on TEL:
The adoption of technology in order to promote a better classroom experience for students or increase e-learning pedagogical activities.
The application of information and communication technologies to teaching and learning for the purpose of motivating and engaging the learner
A learning process (or environment) that is supported by the use of educational, virtual and online communication technologies.
An approach to the provision of distance, blended, and classroom-based learning experiences through the use of a full range of information and communications technologies undertaken by communities of educational researchers, designers, information and communications technologists, and media specialists.
Is a teaching and learning strategy where technology facilitates the efficiency of learning for individuals and groups, providing the transfer and sharing of knowledge in organisations, and understanding of the learning process by exploring connections among human learning, cognition, collective intelligence and technologies, and even artefacts.
States the support of an education and training learning activity or system that is enhanced by technology.
A learning process that is supported by technology.
The support of any learning activity through technology.
Technology Enhanced Learning is...
Technology Enhanced Learning is a central notion in the business of learning innovation, and the theoretical frameworks that shape this notion come from a vast range of different research and educational contexts. This was additionally fueled by a global pandemic that forced every educator to reflect even more than before about the merits and challenges of online learning, resulting in an enormous increase of online educational material, research about online learning and personal experiences.
In the definitions mentioned above we can discern some patterns:
A focus on the learning process, the engagement of the learner or the enhancement of the classroom experience. This means that while technological innovation can lead to very exciting new possibilities, it always comes back to what it might mean for the learning process of the individual or the class.
Taking learning and teaching together. The focus of TEL will not be on the teaching side of the spectrum, but rather on enhancing the learning experience and the efficiency of these learning experiences. This is important when we zoom in on AI-technology and ask the question what the role is of the human teacher in the future. The relationship between teaching and technology presents itself as an interesting topic with a certain tension: in one definition it is stated: ‘learning process that is supported by technology’, another states ‘the application of information and communication technologies to teaching and learning’. Will technology take over teaching in the future?
Technology in this definition is not restricted. Certain definitions talk about ‘information and communication technology’ but this is still a very broad concept covering the vast TEL landscape from simple interactive apps, over artificial intelligence to brain hacking devices.
Ok, now that we have an understanding of what TEL is or can be, let’s try travelling two decades in the future to try and make an educated guess of how technological advances might shape learning in the context of an arts school…
Tipping point
Moore’s Law describes the exponential growth of technological ability. The technological singularity referred to in the quote above, is “a hypothetical point in time at which technological growth becomes uncontrollable and irreversible, resulting in unforeseeable changes to human civilization”
CJ’s quote above triggers a lot of questions, some of which we’ll start exploring in this classroom, being just the tip of a very interesting, broad iceberg.
Which tech domains might highly impact the way we learn in the future?
What does this exponential growth mean for technology enhanced learning?
And can we expect a tipping point in which technology not only supports our learning, but actively learns with and/or for us?
What exciting opportunities might this bring?
To what extent can and/or should we trust technology in assisting our learning process?
In the same interview, CJ dreams up a future in which the combination of advanced neurotechnology and artificial intelligence opens doors to whole new worlds of creation, exploration and experimentation:
You might want to read that quote again! Let the words and ideas tickle your brain for a while… (tickle tickle tickle)
Ok, let’s dive into some of the ideas and concepts that CJ brings to the table.
“...download the whole sensory and mental experience of what it means to be human…” (CJ Carr)
This assumption implies that in 2045 neurotechnology will be precise and fast enough to measure all of the brain signals. We know now that the body sends about 11 million signals to the brain per second to our brain. These are just the signals coming in from our eyes, ears, nose, tongue and skin. This number does not include other intra-brain-signals. We know our brain is made up of about 100 billion cells, each of them interconnected with thousands of other brain cells. It is estimated that the brain might be able to execute up to about 100 billion operations per second.
“...and that means input and output…” (CJ Carr)
We’re not talking about just ‘reading’ the brain, but ‘writing’ as well. This means that the technology should also be precise and fast enough to send specific high speed signals to all of these brain cells. This concept is highly complicated and should be further explored with neuroscientists as well as experts on the learning process and the personal aspect of learning.
This needs some nuancing: we might not need access to all brain cells and signals. For example, it seems that the conscious mind can process only about 50 bits of the 11 million signals it receives every second. The vast majority of the information that the brains receives is processed un- (or sub-?)consciously. It probably even is a very good idea to entrust some of those unconscious processes - like your breathing and your heartbeat - to the experienced guidance of your brain.
These are just some first considerations. Do you feel it too? How you are getting sucked into the (admittedly super fascinating) ‘what is consciousness?’ rabbit hole. Let’s not go in there right now. Instead, let’s focus on:
“...We'll have artists developing dreams, composing experiences.…” (CJ Carr)
Oh wow! We would be able to design experiences that feel totally real! So instead of experiencing a VR ride on a scary rollercoaster, the experience feels so real that it is indistinguishable from the real experience: the wind in your hair, the G-forces working on your body, your inner ear doing funny stuff with your equilibrium…
Learning is also an experience! Could this mean that we will be able to design artificial experiences in which real learning happens? Real learning in the sense that it has a lasting impact on the learner’s knowledge and skill set? Research on lucid dreaming actually seems to back this hypothesis. At least three scientific studies have described how practicing motoric skills in a lucid dream (like tossing a coin in a cup or throwing darts) actually enhances ‘real world performance’ of these tasks. And isn’t a dream some sort of artificial experience?
Ok, now let’s add some artificial intelligence into the mix!
“...And we would also have AI models that will generate experiences, just like they're doing media synthesis right now with music and images…” (CJ Carr)
You’ve probably seen them before: photographic portraits generated by ai that are indistinguishable from real people. And you might have seen some otherworldly and trippy videos generated by AI, showing morphing uncannily-semi-realistic landscapes?
From realistic to dream-like, what these images all have in common is that the AI that generated them was trained on tons of visual material. By training on ‘data sets’, such as thousands of photographs of faces just to give one example), the AI ‘learns’ what characteristics make up a human face. Having learned this, it can now create new faces from scratch. Needless to say the quality of this output depends on both the quality and the amount of data the AI was trained on.
But AI isn’t limited to generating images only… AI can create music, novels, social media content, websites, ads, game scenarios, sculptures, building layouts, etc… In fact, anything that can be translated to digital data sets can become training material for AI. So, when CJ suggests that by 2045 we might be able to “...download the whole sensory and mental experience of what it means to be human…”, this implies that ‘human experience’ becomes a trainable asset for AI! Which in its turn implies that AI will be able to generate new and unknown human experiences.
Do you feel that too, how this idea is tickling your brain? What kind of interesting learning experiences could it generate? I might learn ideas or skills that no one has ever learned before! What if ‘glitches’ appear in these generated (learning) experiences, what would that be like? And would I even trust learning in this way? Sometimes stuff you’ve learned can be extremely hard, or impossible even to ‘unlearn’ you know…
Trust in Educational Technology
Let’s assume a not-so-distant future in which the technology described in the section above has become reality and early adopters (both learners and arts schools) have started integrating it in learning processes.
In this future scenario, now let’s explore the idea of ‘trust’ in relation to these new learning technologies… There will be ‘users’ that might have too much trust, like we experience today for example in the use of social media vs. protecting one’s individual privacy or vs. acceptance of fake news. And we’ll have the opposite as well: people and institutions radically distrusting innovations, even against scientific findings. Remember how in the early days of wikipedia ‘classic encyclopaedia’ were trusted more than crowd sourced information. Or how today even highly educated medics fail to accept that deep learning algorithms are as precise in detecting for example cancer in x-rays than experienced specialists.
So, what is ‘the good amount of trust’? Or let’s ask ourselves a more nuanced question: which parts of the learning and teaching process can we entrust to these kinds of technologies, and which are the mandate of humans only?
Before we move to the very end, here’s one last question we would like to pour into your brain for you to ponder over: how can we educate people in order to empower them with enough technological literacy to find answers to these kinds of questions themselves? Let’s serve Tim’s vision on his mission as an educator serves as a fitting finale to help digest this food for thought…
References
Table of figures in the order of their appearance
