What is meant by the liberal arts? Here is a succinct dictionary definition: “The academic course of instruction intended to provide general knowledge and usually comprising the arts, humanities, natural sciences, and social sciences, as opposed to professional or technical subjects.” And, here is a more thorough explanation: “A liberal arts education is by nature broad and diverse, rather than narrow and specialized… [it] is not intended to train you for a specific job, though it does prepare you for the world of work by providing you with an invaluable set of employability skills, including the ability to think for yourself, the skills to communicate effectively, and the capacity for lifelong learning.”
Over the past few decades, business, engineering, and other professions not previously associated with the liberal arts have embraced a number of its attributes. A few years ago, for example, I came across an article about the efforts of Roger Martin to transform business education. At the time, Martin was the Dean of the Rotman School of Management at the University of Toronto. He had long been advocating “that students needed to learn how to think critically and creatively every bit as much as they needed to learn finance or accounting. More specifically, they needed to learn how to approach problems from many perspectives and to combine various approaches to find innovative solutions.” Such a transformation would require business schools to move into territory more traditionally associated with the liberal arts.
Similarly, in a 2006 report, the National Academy of Engineering called for reforming engineering education. “New graduates were technically well prepared but lacked the professional skills for success in a competitive, innovative, global marketplace. Employers complained that new hires had poor communication and teamwork skills and did not appreciate the social and nontechnical influences on engineering solutions and quality processes.”
A few years ago, USC’s Annenberg School of Communications and Journalism conducted a study to better understand the key competencies companies were looking for. Future leaders, the study found, must be strong in quantitative, technical and business skills. But to advance in their careers, they also need to be good strategic thinkers and must have strong social and communications skills. Companies were looking for so called T-shaped professionals who combine deep quantitative, technical, problem solving hard skills with broad multidisciplinary, communications, and social soft skills that enable them to collaborate with experts in other fields.
But increasingly, liberal art disciplines in the humanities, - e.g., history, literature, linguistics, art, music, - have started to embrace technical, quantitative, data analysis, and other hard skills generally associated with STEM disciplines to better complement their traditional soft skills. This is nicely explained in Digital Humanities: How data analysis can enrich the liberal arts, an article recently published in The Economist.
As the article argues, the clearest benefits of digital technologies to the humanities are speed and scale. Research projects that once lasted a lifetime now require much less time. As an example, it cites the work of Barbara McGillivray, a computational linguist at the UK’s Alan Turing Institute, who created a major digital resource for conducting research on works in ancient Greek. “After starting as the institute’s first humanist in 2017, she and a colleague needed just three months to convert 12 centuries of classics into an annotated corpus of 10m words. The final product compresses Homer, Socrates and Plato into 2.5gb of tidy Extensible Markup Language (xml), complete with the grammatical properties of each word.”
“Curating such enormous archives is just the starting-point. The trick is to turn the data into interesting findings. Along with four co-authors, she tested whether an algorithm could track the meaning of Greek words over time. They manually translated 1,400 instances of the noun kosmos, which initially tended to denote ‘order’, then later shifted to ‘world’ (a celestial meaning that survives in the English ‘cosmos’). Encouragingly, the machine agreed. A statistical model reckoned that in 700bc kosmos was frequently surrounded by ‘man’, ‘call’ and ‘marketplace’, a cluster suggesting ‘order’. By 100ad a second cluster emerged, suggesting ‘world’: ‘god’, ‘appear’ and ‘space’.”
“The thrill of getting ‘a computer to blindly agree with us’, explains Ms McGillivray, is that she could now apply it easily to the 64,000 other distinct words in the corpus. She has already spotted that paradeisos, a Persian loan-word for ‘garden’, took on its theological context of ‘woman’, ‘god’ and ‘eat’ around 300bc, when the Old Testament was first translated into Greek. At a few keystrokes, the algorithm tapped into one of history’s great intellectual exchanges, between Judaistic theology and Greek literature.”
Other examples come from the application of computational criticism to the study of literature at the Stanford Literary Lab. “In contrast to ‘close reading’, by which humans spot nuances on a couple of pages, the lab’s 60-odd contributors have pioneered ‘distant reading’, by getting computers to detect undercurrents in oceans of text.” For example, one of the lab’s projects examined nearly 3,000 British novels written between 1785 and 1900 to determine which types of language had gone in and out of style by calculating how frequently specific words appeared in each decade. The project found that sentimental and moralistic words like integrity, modesty, sensibility, and reason fell increasingly out of fashion from roughly 1% of all words in 1785 to 0.5% in 1900. At the same time, more concrete words denoting actions, body parts, physical adjectives, numbers and colors rose from 2.5% to 6%.
This kind of research is not surprising given the big data and data science revolution of the past few decades, which has now enabled us to analyze many aspects of the world that had never been quantified before. One of the most exciting aspects of data science is that it can be applied to just about any domain of knowledge given our newfound ability to gather valuable data in almost any area of interest, including the humanities.
But plenty of academics object to the use of such data science methods, notes The Economist. “The number-crunchers are not always specialists in the arts, they point out. Their results can be predictable, and the maths is reductive and sometimes sketchy. So too are the perspectives often white, male and Western. Many also fear that funding for computer-based projects could impoverish traditional scholarship.”
“However, little evidence yet exists that the burgeoning field of digital humanities is bankrupting the world of ink-stained books.” In 2008, America’s National Endowment for the Humanities (NEH), set up an office for supporting digital projects. Just this past December, the NEH announced $33 million in grants to support 213 digital humanities projects all around the nation. “These grants will safeguard extensive collections on Appalachian history at Kentucky’s Appalshop archives, enable production of an interactive timeline of African-American music at Carnegie Hall, and support the use of multispectral imaging and X-ray spectroscopy on archaeological objects to better understand color in the ancient world.”
Bringing technologies and skills from the STEM world to the humanities might well help protect their future by positioning them as complementary skills in a well rounded liberal arts education. “Ms McGillivray says she has witnessed a ‘generational shift’ since she was an undergraduate in the late 1990s. Mixing her love of mathematics and classics was not an option, so she spent seven years getting degrees in both. Now she sees lots of humanities students ‘who are really keen to learn about programming and statistics’.”
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