Jul 072016
 

On 27th June I attended a lunchtime seminar, hosted by the University of Edinburgh Centre for Research in Digital Education with Professor Catherine Hasse of Aarhus University

Catherine is opening with a still from Ex-machina (2015, dir. Alex Garland). The title of my talk is the difference between human and posthuman learning, I’ll talk for a while but I’ve moved a bit from my title… My studies in posthuman learning has moved me to more of a posthumanistic learning… Today human beings are capable of many things – we can transform ourselves, and ourselves in our environment. We have to think about that and discuss that, to take account of that in learning.

I come from the centre for Future Technology, Culture and Learning, Aarhus University, Denmark. We are hugely interdisciplinary as a team. We discuss and research what is learning under these new conditions, and to consider the implications for education. I’ll talk less about education today, more about the type of learning taking place and the ways we can address that.

My own background is in anthropology of education in Denmark, specifically looking at physicists.In 2015 we got a big grant to work on “The Technucation Project” and we looked at the anthropology of education in Denmark in nurses and teachers – and the types of technological literacy they require for their work. My work (in English) has been about “Mattering” – the learning changes that matter to you. The learning theories I am interested in acknowledge cultural differences in learning, something we have to take account of. What it is to be human is already transformed. Posthumanistics learning is a new conceptualisations and material conditions that change what it was to be human. It was and it ultra human to be learners.

So… I have become interested in robots.. They are coming into our lives. They are not just tools. Human beings encounter tools that they haven’t asked for. You will be aware of predictions that over a third of jobs in the US may be taken over by automated processes and robots in the next 20 years. That comes at the same time as there is pressure on the human body to become different, at the point at which our material conditions are changing very rapidly. A lot of theorists are picking up on this moment of change, and engaging with the idea of what it is to be human – including those in Science and Technology Studies, and feminist critique. Some anthropologist suggest that it is not geography but humans that should shape our conceptions of the world (Anthrpos- Anthropocene), others differ and conceive of the capitalocene. When we talk about the posthuman a lot of the theories acknowledge that we can’t talk about the fact that we can’t think of the human in the same way anymore. Kirksey & Helmreich (2010) talk of “natural-cultural hybrids”, and we see everything from heart valves to sensors, to iris scanning… We are seeing robots, cybords, amalgamations, including how our thinking feeds into systems – like the stockmarkets (especially today!). The human is de-centered in this amalgamation but is still there. And we may yet get to this creature from Ex-machina, the complex sentient robot/cyborg.

We see posthuman learning in uncanny valley… gradually we will move from robots that feel far away, to those with human tissues, with something more human and blended. The new materialism and robotics together challenge the conception of the human. When we talk of learning we talk about how humans learn, not what follows when bodies are transformed by other (machine) bodies. And here we have to be aware that in feminism that people like Rosa Predosi(?) have been happy with the discarding of the human: for them it was always a narrative, it was never really there. The feminist critique is that the “human” was really retruvian man.. But they also critique the idea that Posthu-man is a continuation of individual goal-directed and rational self-enhancing (white male) humans. And that questions the post human…

There are actually two ways to think of the post human. One way is the posthuman learning as something that does away with useless, biological bodies (Kurzweil 2005) and we see transhumanists, Verner Vinge, Hans Moravec, Natasha Vita-More in this space that sees us heading towards the singularity. But the alternative is a posthumanistic approach, which is about cultural transformations of boundaries in human-material assemblages, referencing that we have never been isolated human beings, we’ve always been part of our surroundings. That is another way to see the posthuman. This is a case that I make in an article (Hayles 1999) that we have always been posthuman. We also see have, on the other hand, Spinozists approach which is about how are we, if we understand ourselves as de-centered, able to see ourselves as agents. In other words we are not separate from the culture, we are all Nature-cultural…Not of nature, not of culture but naturacultural (Hayles; Haraway).

But at the same time if it is true that human beings can literally shape the crust of the earth, we are now witnessing anthropomorphism on steroids (Latour, 2011 – Waiting for Gaia [PDF]). The Anthropocene perspective is that, if human impact on Earth can be translated into human responsibility fr the earth, the concept may help stimulate appropriate societal responses and/or invoke appropriate planetary stewardship (Head 2014); the capitalocene (see Jason Moore) talks about moving away from cartesian dualism in global environmental change, the alternative implies a shift from humanity and nature to humanity in nature, we have to counter capitalism in nature.

So from the human to the posthuman, I have argue that this is a way we can go with our theories… There are two ways to understand that, the singularist posthumanism or spinozist posthumanism. And I think we need to take a posthumanistic stance with learning – taking account of learning in technological naturecultures.

My own take here… We talk about intra-species differentiations. This nature is not nature as resource but rather nature as matrices – a nature that operates not only outside and inside our bodies (from global climate to the microbiome) but also through our bodies, including embodied minds. We do create intra-species differentiation, where learning changes what maters to you and others, and what matters changes learning. To create an ecological responsible ultra-sociality we need to see ourselves as a species of normative learners in cultural organisations.

So, my own experience, after studying physicists as an anthropologists I no longer saw the night sky the same way – they were stars and star constellations. After that work I saw them as thousands of potetial suns – and perhaps planets – and that wasn’t a wider discussion at that time.

I see it as a human thing to be learners. And we are ultra social learning. And that is a characteristic of being human. Collective learning is essentially what has made us culturally diverse. We have learning theories that are relavent for cultural diversity. We have to think of learning in a cultural way. Mediational approachs in collective activity. Vygotsky takes the idea of learners as social learners before we become personal learners and that is about the mediation – not natureculture but cultureculture (Moll 2000). That’s my take on it. So, we can re-centre human beings… Humans are not the centre of the universe, or of the environment. But we can be at the centre and think about what we want to be, what we want to become.

I was thinking of coming in with a critique of MOOCs, particularly as those being a capitolocene position. But I think we need to think of social learning before we look at individual learning (Vygotsky 1981). And we are always materially based. So, how do we learn to be engaged collectively? What does it matter – for MOOCs for instance – if we each take part from very different environments and contexts, when that environment has a significant impact. We can talk about those environments and what impact they have.

You can buy robots now that can be programmed – essentially sex robots like “Roxxxy” – and are programmed by reactions to our actions, emotions etc. If we learn from those actions and emotions, we may relearn and be changed in our own actions and emptions. We are seeing a separation of tool-creation from user-demand in Capitalocene. The introduction of robots in work places are often not replacing the work that workers actually want support with. The seal robots to calm dementia patients down cover a role that many carers actually enjoyed in their work, the human contact and suport. But those introducing them spoke of efficiency, the idea being to make employees superfluous but described as “simply an attempt to remove some of the most demeaning hard task from the work with old people so the wor time ca be used for care and attention” (Hasse 2013).

These alternative relations with machines are things we always react too, humans always stretch themselves to meet the challenge or engagement at hand. An inferentialist approach (Derry 2013) acknowledges many roads to knowledge but materiality of thinking reflects that we live in a world of not just case but reason. We don’t live in just a representationalism (Bakker and Derry 2011) paradigm, it is much more complex. Material wealth will teach us new things.. But maybe these machines will encourage us to think we should learn more in a representative than an inferentialist way. We have to challenge robotic space of reasons. I would recommend Jan Derry’s work on Vygotsky in this area.

For me robot representationalism has the capacity to make convincing representations… You can give and take answers but you can’t argue space and reasons… They cannot reason from this representation. Representational content is not articulated by determinate negation and complex concept formation. Algorithmic learning has potential and limitations, and is based on representationalism. Not concept formation. I think we have to take a position on posthumanistic learning, with collectivity as a normative space of reasons; acknowledge mattering matter in concept formation; acknowledge human inferentialism; acknowledge transformation in environment…

Discussion/Q&A

Q1) Can I ask about causes and reasons… My background is psychology and I could argue that we are more automated than we think we are, that reasons come later…

A1) Inferentialism is challenging  the idea of giving and taking reasons as part of normative space. It’s not anything goes… It’s sort of narrowing it down, that humans come into being in terms of learning and thinking in a normative space that is already there. Wilfred Sellers says there is no “bare given” – we are in a normative space, it’s not nature doing this… I have some problems with the term dialectical… But it is a kind of dialective process. If you give an dtake reasons, its not anything goes. I think Jen Derry has a better phrasing for this. But that is the basic sense. And it comes for me from analytical philosophy – which I’m not a huge fan of – but they are asking important questions on what it is to be human, and what it is to learn.

Q2) Interesting to hear you talk about Jan Derry. She talks about technology perhaps obscuring some of the reasoning process and I was wondering how representational things fitted in?

A2) Not in the book I mentioned but she has been working on this type of area at University of London. It is part of the idea of not needing to learn representational knowledge, which is built into technological systems, but for inferentialism we need really good teachers. She has examples about learning about the bible, she followed a school class… Who look at the bible, understand the 10 commandments, and then ask them to write their own bible 10 commandments on whatever topic… That’s a very narrow reasoning… It is engaging but it is limited.

Q3) An ethics issue… If we could devise robots or machines, AI, that could think inferentially, should we?

A3) A challenge for me – we don’t have enough technical people. My understanding is that it’s virtually impossible to do that. You have claims but the capacities of AI systems so far are so limited in terms of function. I think that “theory of mind” is so problematic. They deteriorise what it means to be human, and narrow what it means to be our species. I think algorithmic learning is representational… I may be wrong though… If we can… There are poiltical issues. Why make machines that are one to one to human beings… Maybe to be slaves, to do dirty work. If they can think inferentiality, should they not have ethical rights. In spinostas we have a responsibility to think about those ethical issues.

Q4) You use the word robot, that term is being used to be something very embodies and physical.. But algorithmic agency, much less embodied and much less visible – you mentioned the stock market – and how that fits in.

A4) In a way robots are a novelty, a way to demonstrate that. A chatbot is also a robot. Robot covers a lot of automated processes. One of the things that came out of AI at one point was that AI couldn’t learn without bodies.. That for deep learning there needs to be some sort of bodily engagement to make bodily mistakes. But then encounters like Roxy and others is that they become very much better… As humans we stretch to engage with these robots… We take an answer for an answer, not just an algorithm, and that might change how we learn.

Q4) So the robot is a point of engaging for machine learning… A provocation.

A4) I think roboticists see this as being an easy way to make this happen. But everything happens so quickly… Chips in bodies etc. But can also have robots moving in space, engaging with chips.

Q5) Is there something here about artifical life, rather than artifical intelligence – that the robot provokes that…

A5) That is what a lot of roboticists work at, is trying to create artificial life… There is a lot of work we haven’t seen yet. Working on learning algorithms in computer programming now, that evolves with the process, a form of artifical life. They hope to create robots and if they malfunction, they can self-repair so that the next generation is better. We asked at a conference in Prague recently, with roboticists, was “what do you mean by better?” and they simply couldn’t answer that, which was really interesting… I do think they are working on artifical life as well. And maybe there are two little connections between those of us in education, and those that create these things.

Q6) I was approached by robotics folks about teaching robots to learn drawing with charcoal, largely because the robotic hand had enough sensitivity to do something quite complex – to teach charcoal drawing and representation… The teacher gesticulates, uses metaphor, describes things… I teach drawing and representational drawing… There is no right answer there, which is tough for robototics… What is the equivelent cyborg/dual space in learning? Drawing toolsa re cyborg-esque in terms of digital and drawing tools… BUt also that diea of culture… You can manipulate tools, awareness of function and then the hack, and complexity of that hack… I suppose lots of things were ringing true but I couldn’t quite stick them in to what I’m trying to get at…

A6) Some of this is maybe tied to Schuman Enhancement Theory – the idea of a perfect cyborg drawing?

Q6) No, they were interested in improving computer learning, and language, but for me… The idea of human creativity and hacking… You could pack a robot with the history of art, and representation, so much information… Could do a lot… But is that better art? Or better design? A conversation we have to have!

A6) I tend to look at the dark side of the coin in a way… Not because I am techno-determinist… I do love gadgets, technology enhances our life, we can be playful… BUt in the capitalocene… There is much more focus on this. The creative side of technology is what many people are working on… Fantastic things are coming up, crossovers in art… New things can be created… What I see in nursing and teaching learning contexts is how to avoid engaging… So lifting robots are here, but nursing staff aren’t trained properly and they avoid them… Creativity goes many ways… I’m seeing from quite a particular position, and that is partly a position of warning. These technologies may be creative and they may then make us less and less creative… That’s a question we have to ask. For physicists, who have to be creative, are always so tied to the materiality, the machines and technologies in their working environments. I’ve also seen some of these drawing programmes…. It is amazing what you can draw with these tools… But you need purpose, awareness of what those changes mean… Tools are never innocent. We have to analyse what tools are doing to us