Serendipity35

I wrote earlier this week about what I see happening in the digital humanities, some history, and the biggest shift I have observed. Today I'm thinking about what is called the "public humanities."

The term public humanities refers to activities, initiatives, and scholarship within the humanities that engage with broader public audiences outside of academia. It encompasses a range of practices aimed at making humanistic knowledge and perspectives accessible, relevant, and meaningful to diverse communities beyond the traditional confines of the university.

I think the goal of public humanities is to bridge the gap between academia and the wider public. This can mean democratizing access to humanistic knowledge. It is an effort to foster a deeper appreciation for the value of the humanities in contemporary society. It reflects a commitment to the idea that the humanities have relevance and significance beyond the walls of the university and can contribute to the enrichment of public life and the promotion of democratic ideals.

How can this be accomplished? It often involves collaboration with community organizations, cultural institutions, and non-profit groups. A meaningful dialogue and partnerships with local communities can help address issues of shared concern and interest. This kind of civic engagement may encourage promoting critical thinking, cultural literacy, historical awareness and may also address social justice issues and advocate for positive social change.

DH programs can include public lectures, workshops, film screenings, exhibitions, and other events that bring together scholars, artists, activists, and members of the public to explore topics of cultural, historical, or philosophical significance.

Digital technologies can help the humanities reach wider audiences through online platforms, digital archives, social media, and interactive multimedia projects.

Public scholarship is something that public humanities scholars often produce. This is work that is accessible to non-specialist audiences, such as books, articles, podcasts, and blog posts. They may also contribute to public debates and discussions on contemporary issues, drawing on insights from the humanities to inform public discourse.

I found this recent article on humanitieswatch.org listing ten forms of public humanities.

1.     public-facing academic work
2.     knowledge derived from practitioners
3.     humanistic knowledge created through collaboration with people that come from various publics
4.     data on the humanities in public
5.     activism informed by humanities research
6.     policymaking related to the humanities
7.     the value of the humanities in the public, and of the public humanities in academia
8.     graduate programs in public humanities
9.     pedagogy for public humanities;
10.  histories, theories, and critiques of the field of public humanities.

I wrote earlier in this week's series a bit about Digital Humanities history which goes back to what was called "humanities computing" in 1940s and 50s. An early example being Roberto Busa's efforts in the 1940s to create, using an IBM mainframe, a computer-generated concordance to Thomas Aquinas' writings.

The term "digital humanities" is believed to have been coined in the late 20th century. There isn't a single definitive origin point, but I first started to hear the term in academic circles in the 1990s. I recall a bunch of people doing research and writing dissertations on the intersection of computing technologies and humanistic inquiry.

In 1996, John Unsworth, a professor at the University of Virginia, used the term in his essay "What is Humanities Computing and What is Not?" The term "digital humanities" (DH) has become increasingly common in academia and it encompasses a broad range of activities that involve applying digital tools and methods to humanities research and scholarship.

DH includes a number of new ways of doing scholarship that involve collaborative, transdisciplinary, and computationally engaged research, teaching, and publishing. For some older faculty, there was resistance because DH brings to the study of the humanities a recognition that the printed word is no longer the main medium for knowledge production and distribution.

The first specialized journal in the digital humanities was Computers and the Humanities, which debuted in 1966. The Computer Applications and Quantitative Methods in Archaeology (CAA) association was founded in 1973. The Association for Literary and Linguistic Computing (ALLC) and the Association for Computers and the Humanities (ACH) were founded in 1977 and 1978, respectively.

Soon, there was a need for a standardized protocol for tagging digital texts, and the Text Encoding Initiative (TEI) was developed and launched in 1987 and published the first full version of the TEI Guidelines in May 1994. This led to Extensible Markup Language (XML), which is a tagging scheme for digital editing.

Researchers also began experimenting with databases and hypertextual editing, which are structured around links and nodes, as opposed to the standard linear convention of print. In the 1990s, major digital text and image archives emerged at centers of humanities computing in the U.S. (e.g. the Women Writers Project, the Rossetti Archive, and The William Blake Archive[demonstrated the sophistication and robustness of text-encoding for literature.

The advent of personal computing and the World Wide Web meant that Digital Humanities work could become less centered on text and more on design. The multimedia nature of the internet has allowed Digital Humanities work to incorporate audio, video, and other components in addition to text.

The shift from calling this work "humanities computing" to "digital humanities" has been attributed to John Unsworth, Susan Schreibman, and Ray Siemens who, as editors of the anthology A Companion to Digital Humanities (2004). The newer term created an overlap between fields like rhetoric and composition.

In 2006 the National Endowment for the Humanities (NEH) launched the Digital Humanities Initiative (renamed Office of Digital Humanities in 2008), which made widespread adoption of the term "digital humanities" in the United States. DH got a big boost at the 2009 MLA convention in Philadelphia, where digital humanists had their field hailed as "the first 'next big thing' in a long time."

What comes next?

Embedded below is a video of Bryan Alexander's virtual keynote at the DEC 2024 conference. Bryan is a futurist, researcher, writer, speaker, consultant, and teacher, working in the field of higher education’s future. The event was held at New Jersey's Mercer County Community College (and online).

Though AI was not the theme of the conference, it came up in every session I attended. If you are looking for additional professional development opportunities discussing AI, the Instructional Technology Council is holding a virtual spring summit on Friday, April 12th. It will feature presentations and discussion panels examining the benefits and challenges of AI at community colleges across the country.

 

Watch other sessions

Bryan Alexander speaks widely and publishes frequently, with articles appearing in venues including The Atlantic Monthly, Inside Higher Ed. He has been interviewed by and featured in the New York Times, the Washington Post, MSNBC, the Wall Street Journal, US News and World Report, National Public Radio (2017, 2020, 2020, 2020, 2020), the Chronicle of Higher Education (2016, 2020), the Atlantic Monthly, Reuters, Times Higher Education, the National Association of College and University Business Officers, Pew Research, Campus Technology, The Hustle, Minnesota Public Radio, USA Today, and the Connected Learning Alliance. He recently published Academia Next: The Futures of Higher Education for Johns Hopkins University Press (January 2020), which won an Association of Professional Futurists award. He next book, Universities on Fire: Higher Education in the Age of Climate Crisis, is forthcoming from Johns Hopkins. His two other recent books are Gearing Up For Learning Beyond K-12 and The New Digital Storytelling (second edition). Bryan is currently a senior scholar at Georgetown University and teaches graduate seminars in their Learning, Design, and Technology program.

When chatGPT hit academia hard at the start of this year, there was much fear from teachers at all grade levels. I saw articles and posts saying it would be the end of writing. A Princeton University student built an app that helps detect whether a text was written by a human being or using an artificial intelligence tool like ChatGPT. Edward Tian was a senior computer science major. He has said that the algorithm behind his app, GPTZero, can "quickly and efficiently detect whether an essay is ChatGPT or human written."

GPTZero is at gptzero.me. I was able to attend an online demo of the app now that it has been released as a free and paid product, and also communicated with Tian.

Because ChatGPT has exploded in popularity, it has gotten interest from investors. The Wall Street Journal reported that parent company OpenAI could attract investments valuing it at $29 billion. But the app has also raised fears that students are using the tool to cheat on writing assignments.

GPTZero examines two variables in any piece of writing it examines. It looks at a text's "perplexity," which measures its randomness: Human-written texts tend to be more unpredictable than bot-produced work. It also examines "burstiness," which measures variance, or inconsistency, within a text because there is a lot of variance in human-generated writing.

Unlike other tools, such as Turnitin.com, the app does not tell you the source of the writing. That is because of the odd situation that writing produced by a chatbot isn't exactly from any particular source.

There are other tools to detect AI writing - see https://www.pcmag.com/how-to/how-to-detect-chatgpt-written-text

Large language models themselves can be trained to spot AI-generated writing if they were trained on two sets of text. One text would be AI and the other written by people, so theoretically you could teach the model to recognize and detect AI writing.