From Teaching in a Digital Age by A. W. Bates I came across this 1954 video of Skinner explaining his Teaching Machine inspired by behaviourism. The machine runs a paper script, but it isn’t that different from the computer based drill training today. You get a question, you write your answer, and you get feedback.
Later we got machines that projected slides and hypertext systems. See Programmed Instruction and Teaching Machines.
Wired Magazine has a nice essay on Hey, Computer Scientists! Stop Hating on the Humanities. The essay by a computer scientist argues that CS students need to study the ethical and social implications of what they build. It can’t be left to others because then it will be too late. Further, CS students should be scared a little:
Professors need to scare their students, to make them feel they’ve been given the skills not just to get rich but to wreck lives; they need to humble them, to make them realize that however good they might be at math, there’s still so much they don’t know.
This year I kept notes about the Digital Humanities 2017 conference at McGill. See DH 2017 Conference Report. My conference report also covers the New Scholars Symposium that took place before.
The NSS is supported by CHCI and centerNet. KIAS provided administrative support and the ACH provided coffee and snacks on the day of. We were lucky to have so many groups supporting the NSS which in turn supports new scholars to come to the conference and to articulate their issues in an unconference format.
DH 2017 itself was a rich feast of ideas. There was too much going on to summarize in a paragraph, but here are two highlights:
The participants of the New Scholars Symposium identified the following as topics to watch and think about:
Thanks to Sarah I was led to a nice custom set of visualizations by Salahub and Oldford of Secretary Clinton’s Email (Source: Wikileaks). The visualizations are discussed in a paper titled Interactive Filter and Display of Hillary Clinton’s Emails: A Cautionary Tale of Metadata. Here is how the article concludes.
Finally, this is a cautionary tale. The collection and storage of metadata from any individual in our society should be of concern to all of us. While it is possible to discern patterns from several sources, it is also far too easy to construct a false narrative, particularly one that fits an already held point of view. As analysts, we fall prey to our cognitive biases. Interactive filter and display of metadata from a large corpus of communications add another tool to an already powerful analytic arsenal. As with any other powerful tool it needs to be used with caution.
Their cautionary tale touches on the value of metadata. After the Snowden revelations government officials like Dianne Feinstein have tried to reassure us that mining metadata shouldn’t be a concern because it isn’t content. Research like this shows what can be inferred from metadata.
Each of our lectures will explore one specific facet of bullshit. For each week, a set of required readings are assigned. For some weeks, supplementary readings are also provided for those who wish to delve deeper.
On Twitter I came across this terrific syllabus: Calling Bullshit: Syllabus. The syllabus is learned, full of useful links, clear and funny. I wish I could write a syllabus like this. For example, here are some of the learning objectives:
What could be more important an objective in the humanities?
Teaching machines to understand – and summarize – text is an article from the The Conversation about the use of machine learning in text summarization. The example they give is how machines could summarize software licenses in ways that would make them more meaningful to us. While these seems a potentially useful application I can’t help wondering why we don’t expect the licensors to summarize their licenses in ways that we can read. Or, barring that, why not make cartoon versions of the agreements like Terms and Conditions.
The issues raised by the use of computers in summarizing texts are many:
Last week I was at the Congress of the Humanities and Social Sciences attending the Canadian Society for Digital Humanities 2017 conference. (See the program here.) It was a brilliant conference organized by the folk at Ryerson. I loved being back in downtown Toronto. The closing keynote by Tracy Fullerton on Finer Fruits: A game as participatory text was fascinating. You can see my conference notes here.
Stéfan Sinclair and I were awarded the Outstanding Achievement Award for our work on Voyant and Hermeneutica. I was also involved in some of the presentations:
From Humanist I learned about a project called Just Review: All Genders, All Genres, All Reviewed that “conducts reserach and develops tools and resources for combatting gender bias in book reviews.” For example, they have a Topic Bias Study of the New York Times. Their web site promises more.
On Thursday I presented a paper at Digital Narratives Around the World, a colloquium organized by Astrid Ensslin and Jérémie Pelletier-Gagnon. The colloquium brought together a nice mix of papers about digital story-telling. I kept my conference notes on Philosophi.ca.
The paper I gave discussed the surveillance software Palantir as a story-telling environment. Palantir is designed not to automate intelligence work, but to augment the analyst and provide them a sandbox where they can try stories about groups of people.
On Friday I delivered the opening keynote at an conference Colloque ACFAS 2017 « La publication savante en contexte numérique » organized by CRIHN. The keynote was on “Hermeneutica: Le dialogue du texte et le jeu de l’interprétation,” presenting work Stéfan Sinclair and I have been doing on how to integrate text and tools. The context of the talk was a previous colloquium organized by CRIHN:
Après un premier colloque à l’ACFAS du Centre de Recherche Interuniversitaire sur les Humanités Numériques en 2014 (sur les besoins d’analyser l’impact du numérique sur les sciences humaines), l’objectif de notre colloque en 2017 est de repenser d’un point de vue théorique et pratique l’édition savante à l’époque du numérique.
In the talk I demonstrated a new tool based on Eliza that we call Veliza. Veliza implements Weizenbaum’s Eliza algorithm but adds the ability to pull a random sentence from the text you are analyzing and send that to the machine. The beta version (not the standard one yet) I was using had two other features.
We ended the talk showing the new Voyant enabled literary programming environment called Spiral (as in Spiral notebook.) It is based on JavaScript and like IPython, but it can access Voyant. You can call up Voyant panels (like Veliza) and change their parameters. Above you can see a notebook where I have added a new set of rules to the scrip and then call up the Veliza panel using that new rules.
This talk was actually the first time we have showed either Veliza or Spiral. Both are still in beta, but will be coming soon to the distribution Voyant.