Addressing the Epistemology of Post-Truth

I ended Part 1: Ontology and Epistemology of Post-Truth with “So what do we do about that?”

Not exactly a call to action, but perhaps a springboard for one.

What do we do once we frame “Post-Truth” as an epistemological stance of  subjectivity? Does it make a difference in our actions–how we approach the “problem”, especially as academics and instructional designers?

I think it does. I think we must consider “Post-Truth” not just as an effect of low digital and media literacy but as an epistemological perspective in order to create a lasting and impactful change. Not that digital literacy isn’t important! Because I certainly think it is! But because our personal epistemology frames our literacies.

So what do we do now?

I’m going to approach this from a critical instructional design perspective.

The most important word in that sentence being critical. We must be critical. We must give power to learners and offer them opportunities to create knowledge–not a free-for-all–but knowledge supported by evidence through crafted arguments. We must make room for uncertainty, for both instructors and the instructees.

We must embrace education not as an interaction between an authoritative teacher and receptive students, but as an interaction among peers. Peers who are equally capable of bringing important insights to the table. Peers who support and challenge one another: in being critical, in seeking out multiple sources of evidence and shaping arguments; in having emotions and processing feelings; in being representatives of humanity.

We must have a pedagogy and praxis of love.

And we must focus on local truths, rather than one grand-narrative. Destroy the notion of objective versus biased, and accept that things are inherently and deeply connected to our experiences and interpretations of the world. Not everyone will interpret things in the same way. And that is OK. A multitude of voices and perspectives is valuable.

There are many ways to do this.

We start by evaluating out own epistemology, our own beliefs about knowledge, knowing, and reality. Reflecting on our practices and how our epistemology shapes them and imposes beliefs on others–especially when we serve as instructional designers and teachers–where we have power, and voice, and agency.

And we continue by giving that power, and voice, and agency to others. We create opportunities for questioning. And welcome uncertainty. We require evidence and well reasoned arguments, rather than “correct” choices. We focus on the local rather than the standardized.

We embrace the complexity and messiness of life. Of learning.

As an instructional designer, I challenge you to make your performance objectives (and thus assessments!) more open-ended. If you use Bloom’s taxonomy, aim higher–use verbs like: explain, describe, suggest, provide evidence for…  Create instruction that gives your learners room to grow, to question, to challenge, to create their own knowledge, to define local truths.

And treat them as peers who have something valuable to offer. Because they do.

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Ontology and Epistemology of Post-Truth

Post-Truth. It’s the biggest buzzword of the moment. Enough to be named Oxford Dictionary’s 2016 Word of the Year. According to the Oxford living dictionary, Post-Truth is “an adjective defined as ‘relating to or denoting circumstances in which objective facts are less influential in shaping public opinion than appeals to emotion and personal belief’.”

You can find a plethora of articles addressing the impact of Post-Truth on  2016 U.S. politics. You can find calls for the importance of digital and media literacy in education in this “Post-Truth world. ” But what I haven’t seen so far is an ontological and epistemological evaluation of “Post-Truth” or the personal epistemology that goes along with this frame of mind.

Post-Truth, by definition, makes a number of ontological and epistemological assumptions. The largest of which are that there are “objective facts” and “personal beliefs” and these are of not only different, but of differing value when it comes to “Truth.”

Note I am using capital T for Truth here, denoting one reality, that is accurate for everyone, and that we may or may not be able to come to know. This is in contrast to lower-case t for truth, which denotes a multiplicity of realities, reflecting different experiential and situated realities, which we can come to know. There is a lot of complicated philosophy that goes into making this nuanced distinction, but I think it is important. Because if you believe in Truth or truth matters and changes how you come to understand and conceive of the world.

So back to Post-Truth. Although not explicitly stated, it can be assumed that the ontological perspective assumes Truth; this can be taken from the phrase “objective facts” which suggests that 1) there is a way to be objective and separate your personal beliefs from your interpretation or experience of a situation, and 2) that there are facts-indisputable information–at all. Put together, that there is information that is indisputable and separate from interpretation. And that because of the phrasing of the definition, and connotations of the words it uses, it is assumed that this Truth–these “objective facts“, are more valid and more important than personal beliefs–let alone [gasp] emotion.

So we have an ontology of Post-Truth; what about the epistemology. What does that mean for coming to know something, what does that mean about knowledge?
I argue it means that there is an authority in what is knowledge–what is objective facts. That this authority determines what is knowledge, what is right and wrong, and transmits that down to everyone else. And that subjective–personal–information is not fact but rather something not True. You come to know from the authority, not through your interpretation.

Now I don’t believe this. Personally. I believe in little-t truth. I believe we all create knowledge, and coming to know something is a process of interpretation necessarily shaped by one’s experiences and understanding of the world. It is necessarily based on personal beliefs and emotion. But that doesn’t mean I’m in support of a free-for-all, anything goes, epistemology either. What is true is contextual, situated in certain experiences and supported by evidence. There is a truth, but no way to be post-truth, because there are no indisputable objective information. Everything is laden with information that clarifies meaning. We come to know by gathering evidence, constructing our knowledge from supporting information. Things are subject to different interpretations. And because of that we should always be critical. Always be gathering evidence to support the perspective we are taking, and change our perspective when the evidence doesn’t support it.

So where does that leave the “Post-Truth” phenomenon for me? As a clear expression of Subjective Personal Epistemology. That is, where there is no Truth, and therefore no authority; everyone is entitled to their beliefs because that is their beliefs. Knowledge is what you make it. And anything goes.

From literature on Personal Epistemology, which bad Britni–I won’t be citing, this is the hardest epistemology to move out of. It is also the most prevalent epistemology (particularly when considering personal epistemology as an overall belief system rather than domain specific).

And it doesn’t surprise me that we find ourselves here.

Our education system, at least in the U.S., encourages an absolute perspective of knowledge. There is a Truth. Your teacher knows it, and tells it to you. You memorize it, show you know it by picking it out on some test. You are right or wrong.

This is especially descriptive of Kindergarten through 12th grade public education.

Then we find out not everything we learned in school is True. There is no omniscient authority. And from years of training not  to have an active role in knowledge creation and crafting evidentiary opinions and arguments, it’s easy to see how we decided that knowledge is a free for all.

So what do we do about that?

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Learn Like Humans

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Artificial intelligence is a frequent and reoccurring theme in educational technology. One I’ve touched on before from a perspective of surveillance, but want to explore a bit more.

What is it about artificial intelligence that makes it seem more worthy of praise, worthy of modeling learning after? What about efficiency, speed, and a false-notion of “unbiased” makes artificial intelligence more appealing than the labor of love and empathy? Than taking our time to process and reflect and consider? Than humanity?

I say “unbiased” pointedly; after all, a human has to code up the artificial: give it it’s marching orders, set constraints and boundaries. Even when the unintentional occurs–like the twitter bot that made it 24hours before turning racist, and robots upholding racist notions of beauty–it is because of the underlying humanity that is programmed into them. That they acquire from the humans they are modeled after.

So how is that better than praising the actual human-ness of humanity?

Why should we “learn to learn” (a phrase I absolutely loathe) like machines: stiff and constrained, efficient but limited in perspectives and empathy?

Machines don’t learn from failure; machines can’t grow. Even artificial intelligence, based on machine learning and neural networks, isn’t truly learning… its ranking and comparing and reordering statistical likelihoods. If the system is wrong, if something doesn’t work as intended (by the human programmers) the machine will never know.

We don’t need to learn to learn like a machine.

We need for authentic intelligence. Authentic experiences. Authenticity over artificial. We need to dig deep into our humanity and embrace love in our work and actions, seek out empathy and sympathy for those around us, and practice kindness and collective social concern. We need to learn like humans.

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Community

I recently joined Mastodon, a developing open source and federated social media server. In particular I have come to participate in the mastodon.social incidence. And as this platform grows and is shaped by its users so has the discussion about community. What is community? Where does it come from? How do we foster and develop it?

What community do we want here?

And it got me thinking and reflecting back on a definition of community I worked up earlier this year, and posted on my original portfolio blog… a modified version reposted here:

communitiesconstructivism

I developed this visual while participating in a Constructivism in Education course. I wanted to wrap my mind around how all the different constructivisms fit together, because as I’ve mentioned before, I hate putting things nice little boxes with clean divisions. I like my world messy.

I think it does represent communities well though; and on multiple levels.

In the image you have a representation of the world individuals resided in. The world consists of both an experiential and social portion–referred to as “Experiential World” and “Social World” within the image. The social world takes up most of the image, as everything is primarily experienced through social influences, but there is a small divide there: all of the social world is experiential, but not all of the experiential world is social.

Within the social world we have a number of individuals; one individual serves as representative for all of the individuals in that the same processes going on within that individual is going on within all the individuals diagrammed. The individuals are represented as either filled circles, or empty circles, to note the difference between a foundation generation and later generations.

The concept of generations specifically comes from Social Constructionism. Here, the foundation generation–generation A/B–creates structures and processes which work for them. As the generations increase, and those structures and processes are reproduced they become institutions. Institutions have often lost meaning behind structures and processes, simply propagating behaviors and beliefs because “that’s how it’s always been.” To say it in a different way, one generation or group creates information, which gets passed on to subsequent generations/groups. As that information is passed on, it becomes assumed that the information is “Real”. Everyday life is taken as a given, so we act as if it is. Social realities are based on regularities of thoughts and actions within and between self and others, and Institutions are those regularities generalized at a society level.

Some example institutions are: racism, social classes, buying engagement ring, sport entertainment… the list goes on and on. These are fairly broad examples, but institutions can arise in much smaller situations as well, like procedures during club meetings or the way things are done in your office.

Within each institution is a community. People with similar beliefs, practices, behaviors. Of course, there is overlap between members of institutions–which is not shown in the diagram, just to keep it from being to much of a beast to interpret. And there are likely many smaller communities within the institutions shown in the diagram.
The concept remains the same though: People with some overlap in beliefs, practices, and behaviors working towards something in common; a collection of individuals influencing each other and the world they experience together.
To me that is what a community is.

Communities are inherently caught up in institutions, because communities are representations of the regularities of thoughts and actions among a collective.

So how do we shape these communities? Can we decide what actions we want to be generalized and know for? In doing so do we inadvertently become a different beast all together? As generations come and go, shift and make changes that work for them an institution and community are not stable but rather complex organisms that live and breathe with us. What can we do to be responsible members of community, curators of institutions?

Mastodon proves to be interesting further in its federations and instances. You can host your own instance, create your own community that somehow is separate but linked to the others (I’m still unsure of all the technicalities of this, so please forgive and correct me if I am wrong).  We are willing communities into existence. We are building institutions from the ground. And because it is open, we are doing it in a way that really puts it in the hands of the communities that will make it. Hopefully with everyone on a bit more equitable standing than an institution lead by a particular controlling interest (say, Twitter or Facebook).

I am interested to see where this goes; where this grows. What will we be generalized into?

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#safetypin

With this simple #safetypin know I stand with you. I will do my best to protect you. To provide you safe spaces. If you need support or solidarity, I am here for you.

This is a safe space.

I made this little image. Feel free to use for yourself, to share, to spread the word that we support those around us. That we stand for safety of all. That there are safe spaces out there.

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Technology that Tracks Us.

Yesterday I had a very brief discussion on Twitter regarding artificial intelligence and surveillance in education. It was prompted by this tweet and the article it links to.

I read the article and responded with my gut reaction:

Then I elaborated when prompted:

This feels more pressing right now, at the wake of the U.S. presidential election. Surveillance seems like it will underscore our future even more now than it has in the past.

Surveillance in our lives to make cogs that better fit in the system deemed “great.” Not truly room for growth…especially not growth on an innovative and expansive level that requires trust and experimentation; that embraces differences for the multitude of perspectives and experiences they bring.

 

Underscoring my thoughts is this brilliant thread by Robin DeRosa this morning:

 

I get the appeal of using technologies and analytic to “improve” and “enhance” learning education. To reproduce and make efficient a system that churns out a desired belief system and populous. I even can empathize with the well-meaning and idealism that leads us to believe we can use these technologies, use surveillance, use artificial intelligence (which is only a propagation of a programmer’s belief systems! The epistemology of artificial intelligence and machine learning, a topic for research and another time). But these hopes are outweighed by the now apparent levels of fear that dictate their use. We must always stay vigilant in being critical of our technologies, of our ideals. We must stay skeptical of their use until we can guarantee  they will not cause more harm, more marginalization; that they will not strip freedoms from those we are trying to “help.”

 

Featured image: Surveillance by Tara Hunt, CC

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Narratives in Natural Sciences

I got the opportunity to meet with Chuck Pearson (@ShorterPearson) on his way home from #OpenEd16. We chatted about the conference over burgers, Chuck having participated in-the-flesh, and me participating remotely. It was a fantastic way to end a conference.

During our dinner chat Chuck asked me what I took away from the conference, having participated on the peripheral.

My first answer, of course, was that it was the conference of superstars. My twitter heroes. People I consider friends and people I’d love to meet and would be completely starstruck about. The list includes:  Sean Michael Morris, Jesse Stommel, Robin DeRosa, Ken Bauer, Amy Collier, Laura Gogia, Kate Bowles, Autumm Caines, Rebecca Hogue, Daniel Lynds,  Lee Skallerup Bassette, Christina Hendricks, Jen Maddrell, JR Dingwall, Gardner Campbell, Audrey Watters!, Sara Goldrick-Rab! … and more.

But more content specific, the themes of being critical, and narratives really stood out to me.

In particular, Chuck and I got onto the topic of narratives. Which Chuck observed was interesting, since both of us having a background in natural sciences. The natural sciences which tend to pretend what they do is something separate from telling stories…which they don’t; they tell stories–based on evidence–but stories nonetheless.

It was a quick dinner and chat, but it wedged the idea of narratives as assessment in the natural sciences into my mind. This morning I woke up pondering on how we could make narratives as a form of assessment not only seem reputable (in a world of quantitative driven data), but also how it can be situated in an authentic way. Because why do it if it isn’t authentic?

And it struck me, we have students write lab reports and analyze their data, but why don’t we make that more authentic? That’s what scientists do–analyze, report–but also they construct a story about what their findings mean, and how they fit into the larger scope of the field.

Why don’t we expect our students to do the same thing?

Write academic papers instead of template lab reports. Sure, it’s more work on us to evaluate the quality of the work (although perhaps we could build in a class peer review system too?), but its much more authentic an activity and it emphasizes that science doesn’t magically create some sort of “fact” that is always True but rather that there is a human aspect: Interpretation is an essential aspect of science, and story telling is the way we share our interpretations. Narratives are the way we make sense of our world, of our data.

 

Featured image: Stories by Melissa Dooley CC Attribution

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