Sitting on a hill with a view of Mt. Fuji across the water is the Shonan Village Center where I just finished a research retreat on Modelling Cultural Processes. This was organized by Mits Inaba, Martin Roth, and Gehard Heyer from Ritsumeikan University and the University of Leipzig. It brought together people in computing, linguistics, game studies, political science, literary studies and the digital humanities. My conference notes are here.
Unlike a conference, much of the time was spent in working groups discussing issues like identity, shifting content, and constructions of culture. As part of our working groups we developed a useful model of the research process across the humanities and social sciences such that we can understand where there are shifts in content.
Today I learned about Pius Adesanmi who died in the recent Ethiopian Airlines crash. From all accounts he was an inspiring professor of English and African Studies at Carelton. You can hear him from a TEDxEuston talk embedded above. Or you can read from his collection of satirical essays titled Naija No Dey Carry Last: Thoughts on a Nation in Progress.
In the TEDx talk he makes a prescient point about new technologies,
We are undertakers. Man will always preside over the funeral of any piece of technology that pretends to replace him.
He connects this prediction about how all new technologies, including AI, will also pass on with a reflection on Africa as a place from which to understand technology.
And that is what Africa understands so well. Should Africa face forward? No. She understands that there will be man to preside over the funeral of these new innovations. She doesn’t need to face forward if she understand human agency. Africa is the forward that the rest of humanities must face.
We need this vision of/from Africa. It gets ahead of the ever returning hype cycle of new technologies. It imagines a position from which we escape the neverending discourse of disruptive innovation which limits our options before AI.
JSTOR, and some other publishers of electronic research, have started building text analysis tools into their publishing tools. I came across this at the end of a JSTOR article where there was a link to “Get more results on Text Analyzer” which leads to a beta of the JSTOR labs Text Analyzer environment.
This analyzer environment provides simple an analytical tools for surveying an issue of a journal or article. The emphasis is on extracting keywords and entities so that one can figure out if an article or journal is useful. One can use this to find other similar things.
What intrigues me is this embedding of tools into reading environments which is different from the standard separate data and tools model. I wonder how we could instrument Voyant so that it could be more easily embedded in other environments.
With no clear methods to effectively monitor, halt or eliminate toxic behavior, many in the gaming community have simply tried to ignore it and continue playing anyway. Many of the titles cited most for toxic players remain the industry’s most popular.
This paper uses frame analysis to examine recent high-profile values statements endorsing ethical design for artificial intelligence and machine learning (AI/ML). Guided by insights from values in design and the sociology of business ethics, we uncover the grounding assumptions and terms of debate that make some conversations about ethical design possible while forestalling alternative visions. Vision statements for ethical AI/ML co-opt the language of some critics, folding them into a limited, technologically deterministic, expert-driven view of what ethical AI/ML means and how it might work.
I get the feeling that various outfits (of experts) are trying to define what ethics in AI/ML is rather then engaging in a dialogue. There is a rush to be the expert on ethics. Perhaps we should imagine a different way of developing an ethical consensus.
For that matter, is there room for critical positions? What it would mean to call for a stop all research into AI/ML as unethical until proven otherwise? Is that even thinkable? Can we imagine another way that the discourse of ethics might play out?
The history is not the heroic story of personal computing that I was raised on. It is a story of how women were driven out of computing (both the academy and businesses) starting in the 1960s.
A group of us at the U of Alberta are working on archiving the work of Sally Sedelow, one of the forgotten pioneers of humanities computing. Dr. Sedelow got her PhD in English in 1960 and did important early work on text analysis systems.
Article: Applying an Ethics of Care to Internet Research: Gamergate and Digital Humanities
Thanks to Todd Suomela’s lead, we just published an article on Applying an Ethics of Care to Internet Research: Gamergate and Digital Humanitiesin Digital Studies. This article is a companion to an article I wrote with Bettina Berendt on Information Wants to Be Free, Or Does It? We and others are exploring the Ethics of Care as a different way of thinking about the ethics of digital humanities research.
He started by talking about whether textual traditions had any relationship to the material world. How do texts relate to each other?
Today stemata as visualizations are models that go beyond the manuscripts themselves to propose evolutionary hypotheses in visual form.
He then showed what he is doing with the Canterbury Tales Project and then talked about the challenges adapting the time-consuming transcription process to other manuscripts. There are lots of different transcription systems, but few that handle collation. There is also the problem of costs and involving a distributed network of people.
He then defined text:
A text is an act of (human) communication that is inscribed in a document.
I wondered how he would deal with Allen Renear’s argument that there are Real Abstract Objects which, like Platonic Forms are real, but have no material instance. When we talk, for example, of “hamlet” we aren’t talking about a particular instance, but an abstract object. Likewise with things like “justice”, “history,” and “love.” Peter responded that the work doesn’t exist except as its instances.
He also mentioned that this is why stand-off markup doesn’t work because texts aren’t a set of linear objects. It is better to represent it as a tree of leaves.
Paolo showed me a neat demonstration of Word2Vec Vis of Pride and Prejudice. Lynn Cherny trained a Word2Vec model using Jane Austen’s novels and then used that to find close matches for key words. She then show the text of a novel with the words replaced by their match in the language of Austen. It serves as a sort of demonstration of how Word2Vec works.