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Showing posts with label Artificial Intelligence. Show all posts
Showing posts with label Artificial Intelligence. Show all posts

Thursday, 15 October 2015

A multi-disciplinary conversation about Collective intelligence – reflection on some missing elements

The mobile phone and its connectivity with the internet allows growing numbers of us to find, connect, and interact. That was the technological foundation for the original vision of cMOOCs (developed by George Siemens and Stephen Downes) as a democratic learning experience, and connectivism as a learning theory for a digital age (Siemens 2005).

Collectivism, as discussed in a multi disciplinary context at Nesta http://www.nesta.org.uk/event/roots-collective-intelligence, relies on the same technological infrastructure. What is collectivism and how does it differ from connectivism? We heard that the Internet allows for a new form of activism for example, political. How do individuals participate? We were given the example of number of Facebook likes as an indicator of collective intentionality, a starting point. However, how to sustain collectivism i.e. participation, was a recurrent question; how does an individual move on from the Facebook click to participate?  Participating in connectivist learning opportunities requires good infrastructure design and from the individual curiosity, motivation to learn, to contribute, openness, digital literacy (a fair amount) and I would argue that digital fluency and socio-emotional experience are the elements that sustain on-going participation.

Intelligence. Summing up the day Colin Blakemore focused on intelligence. His considered opinion was that we hadn’t spent enough time talking about what we meant by intelligence. He is a cognitive neuroscience and so unsurprisingly, he also spent some time reflecting on the contributions made by the speakers who were cognitive scientists. Those mainly cohered around what, when and how collective intelligence occurs with when and what depending on group size (Robin Dunbar) how on noise reduction, competence, persistence, reputation (Chris Frith). Others concentrated on decision making as investigated in the laboratory; the role of argumentation in decision-making and the quality of decision making. This was a useful contribution as we had already heard that a binary response as the norm could be the problem for collectivism in political contexts. Also, it has some connection with learning science, where design for collaborative learning (i.e. group work) requires a joint task and the opportunity to propose ideas, discuss them with others, negotiate a solution to disparate ideas, and contribute to a shared outcome.

Overall, the multi-disciplinary approach was very successful. However, there was a sense that the individual was objectified. The subjective was largely missing from the day; purposefulness and socio-emotional experience. Therefore, it was interesting to learn about the fall off in Wikipedia contributions since bots were introduced. The explanation provided was that the bots were overly obedient to protocol and rules - another example of the clunkiness of bot interaction as described in a previous post and that the uniquely human nature of socio-emotional experience is so often neglected

Surely, design is important both for successful knowledge building and the socio-emotional experience of collective action.


Siemens, G. (2005). Connectivism: A learning theory for a digital age. International journal of instructional technology and distance learning, 2(1), 3-38.

Wednesday, 23 September 2015

What would be the point of Education if computers replace teachers?

Turing’s work on developing early versions of computers led to the imitation game as a way of investigating whether computers can think? The imitation game (Turing test) involves a participant in one room, a human confederate (someone whose behavior is under the direction of the experimenter) in another room and a computer terminal containing a program that simulates intelligence also in another room. The task for the participant is to decide which is human. In 1951 Turing predicted that by 2000 the average person, naïve to the fact that an interaction partner was a computer program, would assume humanness 70% of the time. Undoubtedly these ideas inspired the foundation of Artificial Intelligence (AI). Its subsequent evolution is brilliantly summarized on the BBC’s iWonder website http://www.bbc.co.uk/timelines/zq376fr.  In July 2015 an article on research that uses an echoborg (a human who acts as the mouthpiece for an artificial intelligence system) for the Turing test was featured on the BBC Futures website http://www.bbc.com/future/story/20150717-the-people-possessed-by-computers and for one week in September 2015  AI was a featured topic on the BBC reflecting a contemporary fascination with sharing our personal and working spaces with intelligent agents

However, the penetration of AI into Education (AIED) was not covered. AI techniques mean that artificial agents could replace teachers. An Intelligent tutor (IT), based on adaptive AI systems, means that learning contexts can be personalized for a student. The system (IT) uses a teacher-pupil model to adjust the learning task to an appropriate level and a task model to provide appropriate feedback to the student. Pedagogically sound opportunities to learn can be extended in both reach and frequency. A teacherbot has been used to answer student questions on a massive open online course (a MOOC). Teaching presence on MOOCs is sparse so that students who enroll on a MOOC need not incur a financial cost. Therefore, researchers are investigating ways in which the teacher can be assisted, or replaced by, a bot. https://www.timeshighereducation.co.uk/news/ask-teacherbot-are-robots-the-answer/2020326.article. Other examples of AI contributions include the ECHOES project that targets atypical development issues by using virtual agents to engage with children on the autism spectrum in order to improve their communication skills. http://echoes2.org/?q=node/2.

Versions of the headline ‘Intelligent agents replace teachers’ are increasingly common. ‘What if’ this transpires? with teachers replaced by AI products (robots, bots, virtual agents). What questions does it raise for Education? For example, what would it mean for a socio-cultural pedagogy that AI products are linguistically challenged and on current appraisal likely to remain so? Furthermore, the interdependence of emotion and cognition when learning is increasingly recognised, with empathy a foundational element of successful interpersonal interaction.  There is evidence from Neuroscience that both language and empathy are uniquely human capacities with dedicated brain structures and neural pathways. For a socio-cultural perspective meanings arise through social interaction and enable us to pursue personal goals and to think beyond the actual. It is social interaction that enables creativity. Therefore, it is significant that a recent report from Nesta concluded that ‘creative occupations are more future-proof to technologies like machine learning and mobile robotics’ http://www.nesta.org.uk/publications/creativity-vs-robots.

That the ability to transform knowledge and create history through social interaction is a uniquely human ability can be supported by evidence from Neuroscience. However, according to Kevin Warwick http://www.kevinwarwick.com, by comparison with computers, our human ability to communicate information is slow, limited in reach, and error prone and our reliance on language may become ‘excess baggage’. Educational Neuroscience, a multidisciplinary area that assesses the potential of Neuroscience for informing Education, could usefully contribute to the debate.