The problem isn’t that poor children don’t have access to computers. It’s that they spend too much time in front of them.
The New York Times has an important Opinion about America’s Real Digital Divide by Naomi S. Riley from Feb. 11, 2018. She argues that TV and video game screen time is bad for children and there is no evidence that computer screen time is helpful. The digital divide is not one of access to screens but one of attitude and education on screen time.
But no one is telling poorer parents about the dangers of screen time. For instance, according to a 2012 Pew survey, just 39 percent of parents with incomes of less than $30,000 a year say they are “very concerned” about this issue, compared with about six in 10 parents in higher-earning households.
On Humanist there was an announcement from the Hagley Museum and Library that they had put up a 1969 Sperry-UNIVAC short film An Introduction to Digital Computers. The 22 minute short is a dated, but interesting introduction to how a digital computer works. The short was sponsored by Sperry-UNIVAC which had its origins in the Eckert-Mauchly Computer Corporation founded by Eckert and Mauchly of ENIAC fame.
The museum is in Delaware at the site of E.I. du Pont gunpowder works from 1802. The Hagley library is dedicated to American enterprise and has archival material from Sperry-UNIVAC:
Hagley’s library furthers the study of business and technology in America. The collections include individuals’ papers and companies’ records ranging from eighteenth-century merchants to modern telecommunications and illustrate the impact of the business system on society.
[N]etworks themselves offer ways in which bad actors – and not only the Russian government – can undermine democracy by disseminating fake news and extreme views. “These social platforms are all invented by very liberal people on the west and east coasts,” said Brad Parscale, Mr. Trump’s digital-media director, in an interview last year. “And we figure out how to use it to push conservative values. I don’t think they thought that would ever happen.” Too right.
The Globe and Mail this weekend had an essay by Niall Ferguson on how Social networks are creating a global crisis of democracy. The article is based on Ferguson’s new book The Square and the Tower: Networks and Power from the Freemasons to Facebook. The article points out that manipulation is not just an American problem, but also points out that the real problem is our dependence on social networks in the first place.
Having just finished teaching a course on Big Data and Text Analysis where I taught students Python I can appreciate a well written tutorial on Python. Python Programming for the Humanities by Folgert Karsdorpis a great tutorial for humanists new to programming that takes the form of a series of Jupyter notebooks that students can download. As the tutorials are notebooks, if students have set up Python on their computers then they can use the tutorials interactively. Karsdorp has done a nice job of weaving in cells where the student has to code and Quizes which reinforce the materials which strikes me as an excellent use of the IPython notebook model.
Text Analysis with Topic Models for the Humanities and Social Sciences (TAToM) consists of a series of tutorials covering basic procedures in quantitative text analysis. The tutorials cover the preparation of a text corpus for analysis and the exploration of a collection of texts using topic models and machine learning.
Stéfan Sinclair and I (mostly Stéfan) have also produced a textbook for teaching programming to humanists called The Art of Literary Text Analysis. These tutorials are also written as Jupyter notebooks so you can download them and play with them.
One irony is that, in many of those discussions, conservative commentators accused humanities scholars of the left of ignoring issues of truth. And Ben-Merre acknowledged that some may say poststructuralists such as the late theorist Jacques Derrida may have contributed to the current situation by questioning then-prevailing attitudes about what constituted truth.
If the truth is ideologically constructed then what’s wrong with Trump’s base constructing their own truth? Are we doomed to our silos? These MLA talks seem to be a rich set of ways of understanding the issues of fake news in terms of fiction and truth, but I think we also need to think of ways of bridging the truths which is why I liked In Conversation: Robert Reich and Arlie Hochschild (video of conversation from 3quarksdaily.) Hochschild talks about her new book, Strangers In Their Own Land which listens to a Tea Party community in Alabama. Hochschild also talks about how one can build bridges by stretching values so they can be shared and provide a ground for dialogue. Yet another way of making truths.
What are the different forms of interactive stories? Which are the biggest and smallest, the simplest and most complex? What are the most typical and the most unusual? When we consider the structures of interactive narratives, are there local features or overall shapes that correspond to particular genres, authors, languages, time periods, or media forms?
The project web site is simple and informative. It includes a blog with short essays by research assistants. What you can see is the different topologies of these gamebooks from the tall ones with lots of choices but little narrative to the wide ones with lots of story, but little branching.
3quarksdaily, one of the better web sites for extracts of interesting essays, pointed me to this essay on Are Algorithms Building the New Infrastructure of Racism? in Nautilus by Aaron M. Bornstein (Dec. 21, 2017). The article reviews some of the terrain covered by Cathy O’Neil’s book Weapons of Math Destruction, but the article also points out how AIs are becoming infrastructure and infrastructure with bias baked in is very hard to change, like the low bridges that Robert Moses built to make it hard for public transit to make it into certain areas of NYC. Algorithmic decisions that are biased and visible can be studied and corrected. Decisions that get built into infrastructure disappear and get much harder to fix.
a fundamental question in algorithmic fairness is the degree to which algorithms can be made to understand the social and historical context of the data they use …
Just as important is paying attention to the data that is used to train the AIs in the first place. Historic data carries the biases of these generations and they need to be questioned as they get woven into our infrastructure.
One of the oddest Ethereum projects in operation, CryptoKitties is a three-way cross between Tamagotchis, Beanie Babies and animal husbandry. Users can buy, sell and breed the eponymous cats, with traits inherited down the generations.
It is abundantly clear why we see so much bad process with this item: because the fix was already in. There is no real mention of the thousands of net neutrality complaints filed by consumers. Why? The majority has refused to put them in the record while maintaining the rhetoric that there have been no real violations. Record evidence of the massive incentives and abilities of broadband providers to act in anti-competitive ways are missing from the docket? Why? Because they have refused to use the data and knowledge the agency does have, and has relied upon in the past to inform our merger reviews. As the majority has shown again and again, the views of individuals do not matter, including the views of those who care deeply about the substance, but are not Washington insiders.