Last week I presented a paper based on work that Stéfan Sinclair and I are doing at the University of South Florida. The talk, titled, “Cooking Up Literature: Theorizing Statistical Approaches to Texts” looked at a neglected period of French innovation in the 1970s and 1980s. During this period the French were developing a national corpus, FRANTEXT, while there was also a developing school of exploratory statistics around Jean-Paul Benzécri. While Anglophone humanities computing was concerned with hypertext, the French were looking at using statistical methods like correspondence analysis to explore large corpora. This is long before Moretti and “distant reading.”
The talk was organized by Steven Jones who holds the DeBartolo Chair in Liberal Arts and is a Professor of Digital Humanities. Steven Jones leads a NEH funded project called RECALL that Stéfan and I are consulting on. Jones and colleagues at USF are creating a 3D model of Father Busa’s original factory/laboratory.
David Sepkoski has published a nice essay in Aeon about What a fossil revolution reveals about the history of ‘big data’. Sepkoski talks about his father (Jack Sepkoski), a paleontologist, who developed the first database to provide a comprehensive record of fossils. This data was used to interpret the fossil record differently. The essay argues that it changed how we “see” data and showed that there had been mass extinctions before (and that we might be in one now).
The analysis that he and his colleagues performed revealed new understandings of phenomena such as diversification and extinction, and changed the way that palaeontologists work.
Sepkoski (father) and colleagues
The essay then makes the interesting move of arguing that, in fact, Jack Sepkoski was not the first to do quantitative palaeontology. The son, a historian, argues that Heinrich Georg Bronn in the 19th century was collecting similar data on paper and visualizing it (see spindle diagram above), but his approach didn’t take.
This raises the question of why Sepkoski senior’s data-driven approach changed palaeontology while Bronn’s didn’t. Sepkoski junior’s answer is a combination of changes. First, that palaeontology became more receptive to ideas like Stephen Jay Gould’s “punctuated equillibrium” that challenged Darwin’s gradualist view. Second, that culture has become more open to data-driven approaches and the interpretation visualizations needed to grasp such approaches.
The essay concludes by warning us about the dangers of believing data black boxes and visualizations that you can’t unpack.
Yet in our own time, it’s taken for granted that the best way of understanding large, complex phenomena often involves ‘crunching’ the numbers via computers, and projecting the results as visual summaries.
That’s not a bad thing, but it poses some challenges. In many scientific fields, from genetics to economics to palaeobiology, a kind of implicit trust is placed in the images and the algorithms that produce them. Often viewers have almost no idea how they were constructed.
This leads me to ask about the warning as gesture. This is a gesture we see more and more, especially about the ethics of big data and about artificial intelligence. No thoughtful person, including myself, has not warned people about the dangers of these apparently new technologies. But what good are these warnings?
Johanna Drucker in Graphesis proposes what to my mind is a much healthier approach to the dangers and opportunities of visualization. She does what humanists do, she asks us to think of visualization as interpretation. If you think of it this way than it is no more or less dangerous than any other interpretation. And, we have the tools to think-through visualization. She shows us how to look at the genealogy of different types of visualization. She shows us how all visualizations are interpretations and therefore need to be read. She frees us to be interpretative with our visualizations. If they are made by the visualizer and are not given by the data as by Moses coming down the mountain, then they are an art that we can play with and through. This is what the 3DH project is about.
Last week I presented a keynote at the Digital Cultures, Big Data and Society conference. (You can seem my conference notes at Digital Cultures Big Data And Society.) The talk I gave was titled “Thinking-Through Big Data in the Humanities” in which I argued that the humanities have the history, skills and responsibility to engage with the topic of big data:
First, I outlined how the humanities have a history of dealing with big data. As we all know, ideas have histories, and we in the humanities know how to learn from the genesis of these ideas.
Second, I illustrated how we can contribute by learning to read the new genres of documents and tools that characterize big data discourse.
And lastly, I turned to the ethics of big data research, especially as it concerns us as we are tempted by the treasures at hand.
The Common Crawl is a project that has been crawling the web and making an open corpus of web data from the last 7 years available for research. There crawl corpus is petabytes of data and available as WARCs (Web Archives.) For example, their 2013 dataset is 102TB and has around 2 billion web pages. Their collection is not as complete as the Internet Archive, which goes back much further, but it is available in large datasets for research.
I’ve been playing with DataCamp‘s Python lessons and they are quite good. Python is taught in the context of data analysis rather than the turtle drawing of How to Think Like a Computer Scientist. They have a nice mix of video tutorials and then exercises where you get a tripartite screen (see above.) You have an explanation and instructions on the left, a short script to fill in on the upper-right and interactive python shell where you can try stuff below.
AI is not going to take over the world the way the sci-fi stories have it.
The effect will be on tasks as AI takes over tasks that people are paid to do, putting them out of work.
How then will we deal with the unemployed? (This is a question people asked in the 1960s when the first wave computerization threatened massive unemployment.)
One solution is “Keynesian policies of increased government spending” paid for taxing the companies made wealthy by AI. This spending would pay for “service jobs of love” where people act as the “human interface” to all sorts of services.
Those in the jobs that can’t be automated and that make lots of money might also scale back on their time at work so as to provide more jobs of this sort.
Domenico Fiormonte has recently blogged about an interesting document he has by Father Busa that relates to a difficult moment in the history of the digital humanities in Italy in 2002. The two page “Conditional Agreement”, which I translate below, was given to Domenico and explained the terms under which Busa would agree to sign a letter to the Minister (of Education and Research) Moratti in response to Moratti’s public statement about the uselessness of humanities informatics. A letter was being prepared to be signed by a large number of Italian (and foreign) academics explaining the value of what we now call the digital humanities. Busa had the connections to get the letter published and taken seriously for which reason Domenico visited him to get his help, which ended up being conditional on certain things being made clear, as laid out in the document. Domenico kept the two pages Busa wrote and recently blogged about them. As he points out in his blog, these two pages are a mini-manifesto of Father Busa’s later views of the place and importance of what he called textual informatics. Domenico also points out how political is the context of these notes and the letter eventually signed and published. Defining the digital humanities is often about positioning the field in the larger academic and public political spheres we operate in.
They are applying the CIDOC Conceptual Reference Model.
The CIDOC Conceptual Reference Model (CRM) provides definitions and a formal structure for describing the implicit and explicit concepts and relationships used in cultural heritage documentation.
They have a visual search (which doesn’t seem to find anything at the moment.)
They are looking at Research Space (which uses CRM) for a research linked data environment.
I’ve just come across some important blog essays by David Gaertner. One is Why We Need to Talk About Indigenous Literature in the Digital Humanities where he argues that colleagues from Indigenous literature are rightly skeptical of the digital humanities because DH hasn’t really taken to heart the concerns of Indigenous communities around the expropriation of data.
