This week we were asked to create two narratives around our potential relationship with media, education, text and technology in the next 30 years. I don’t claim that my ideas are particularly original. Frankly, at times I have difficulty wrapping my head around where we currently are with these things. I could never have imagined things as they are today even 10 years ago, and don’t suppose I have any sense of where things might be in 30. For what it’s worth, here are my thoughts.

Speculative future #1 – return to an oral culture

I think one trend that will continue is the decline of text-based resources and books with a continued increase in popularity of videos, whether on YouTube or a new platform, and podcast type media. Certainly, I am seeing this trend in my post-secondary classes where students seem more and more reluctant to read the textbook (even though they have never really been enthusiastic about it anyway). This past semester I have had several questions from students on content they have encountered in videos they have watched. These are videos they have sought out on their own – nothing that I have recommended, nor connected to the course in any way. When I ask if they have read the textbook and completed the activities that I have asked them to do, they admit they haven’t. It is an interesting – and frustrating – phenomenon that their go to is YouTube before they even consider looking at the material assigned for and specifically relevant to the course.

I think this phenomenon is pretty much a given. What cannot be predicted is the extent to which audio/visual media will replace print. Is it possible that, in 2050, printed books will be few and far between? Perhaps we will still have books and print media but purely in digital form. Possessing a physical book may become a rarity just as it was before the invention of the printing press. Owning books might be more of a collector’s venture.

From an education perspective, this could be problematic for a few reasons:

1. There is some research that digital reading negatively impacts how we respond to text (https://www.bbc.com/future/article/20160124-are-paper-books-really-disappearing). Will we, as a human race, be, in general, less intelligent than we are today as a result (however we might define or measure intelligence)?
2. Who will be the “gatekeepers” or authorities of these digital and open resources? As noted above, my students have encountered material that is either not correct, or not relevant to our course. How are they to evaluate their sources? As Corbette Doyle noted in the Leading Lines podcast, how will we know what to trust? On the flipside, it could be possible that algorithms could be used to vet the validity of an author and to include that reporting with the text. Students, and more broadly, people, may be better aware of the need to consider the validity of the source of everything they encounter, which would be a positive outcome.
3. We know that our reading vocabulary is the largest, writing vocabulary is next, and spoken is the smallest. If we swap videos for written texts, we may lose some of our vocabulary. As we learned from Lara Boroditsky in module, language shapes our thoughts.   Will students in 30 years think differently as a result of changes in language and vocabulary?

Regardless of the possible problems, it seems this is where we are heading and humanity will adapt to the changes just as it has throughout the ages.

Speculative future #2 – Democratizing academic journals and research

This idea was inspired more by the recent weeks’ material around algorithms – how they are currently used, some of the potential problems with machine learning but also the potential to use them for good.

Working at a post-secondary institution, research and publishing is an often discussed topic. What tends to be discussed frequently are the existing problems inherent in the current state of the process. To name just a few:

• To publish in a journal, researchers turn over copyright of their work to those journals for no direct compensation (excluding any salaries earned at an institution or grants received). At times, the exact opposite happens and researchers have to pay to submit their articles and have them published.
• The review process can be problematic. Some areas of research are highly specialized, and a researcher may have few, if any, true “peers” in their field. These peers are often not the reviewers assigned to review and comment on the article. This leads to feedback that is irrelevant, and even obstructive.
• Editors and reviewers may have a motivation to reject research that contradicts their own positions (ideological or otherwise), regardless of the validity of the research findings. Referred to as publication bias, this can lead to certain ideas being promoted only because research to the contrary is locked out, not because they are the best ideas/results/theories.
• Published research is generally protected behind paywalls. If one does not have access through a post-secondary institution, one would have to pay for access to material that the journal did not have to pay for.
• The process can be extremely time delayed. For example, a colleague submitted a paper for review nearly one year ago and is still waiting to hear from the journal. In the meantime, he cannot submit the article elsewhere, and so is completely hung up and is hostage to the journal’s timelines.

Many of these problems exist because the process has high human involvement. I can’t believe that this field, in 30 years, will be immune to automation in some way to reduce the reliance on human time which seems to be tremendously back logged.

While one could simply put their research out to the internet for people to access, peer review adds validity to the findings and write up. I believe most researchers would not want to abandon this step to just get the research “out there”, and so automation and digitization likely needs to retain this element.

I certainly don’t know how the details would work out, but there could be potential for algorithms to be used to widely democratize the results of academic research. Again, algorithms are programmed by humans and so the programmers would have to have the political will to remove any and all of the biases that currently exist.  I expect that peer review, in some way, would remain an important element, but perhaps it will be machines that will conduct the review rather than humans. In 30 years, it may even be the machines that gather and analyze the data with huge populations to draw samples from.

Algorithms could be used to learn one’s area(s) of interest and expertise. Through this learning, members of the academic community could be notified of new publications applicable and they could then review and offer feedback. This feedback could be in a variety of forms: upvotes/downvotes, commentary, etc. AI could further track an individual track record and include or exclude their feedback as needed. For example, if a reviewer always votes down any research with a particular result, such that they are displaying blatant bias, they could be excluded from further reviews.

There certainly seems to be some potential there, and it will be interesting to see how, and if, automation impacts this field.