Digital Humanities: a fairy tale? (Guest Post)

We’re very pleased to host our first guest post here on the blog. After our recent post Digital Humanities: Challenges, Difficulties, Reflections, and Questions, we thought it would be interesting to get the perspective of Comp’s side of things, since our post mostly focused on the view of Hums. We invited Dr. Tarek Besold of the KRDB Research Centre at the Free University of Bozen-Bolzano and Sarah Schulz of the Institut für Maschinelle Sprachverarbeitung at Universität Stuttgart to share their thoughts on the issues people on the ‘Digital’ side of Digital Humanities have getting into the ‘Humanities’ side.

And it came to pass, that two curious explorers went out to foreign realms, ruled by two kings that could not be more different in their rules and aims. Moving carefully not to upset the other kingdom, the explorers exercised diplomacy. Gently, they strove to understand each other’s worlds. But what they didn’t know was that their diplomacy and cautious approach could do more harm than good…

In this or a similar way, the story of Digital Humanities could have started. But are Digital Humanities a fairy tale or do they really exist — and if they exist, where can they be found?

Countless attempts to access the nature of DH have been started, sheer endless seems the pool of explanations what it does and what it is aiming for (cf. whatisdigitalhumanities). Dependent on who defines it and despite all carefulness, it is not uncommon that the digital disciplines are reduced in their role to a serving science, aiding Humanities to reach their traditional aims using (possibly speedier or more efficient versions of) their traditional methods. The possibilities of evolution on both sides, powered by a cooperation on equal footing — with potential for a real fusion of disciplines in the long run — instead of a hierarchical interaction with clear primacy of one discipline over the other (usually the H being in the stronger position than the D), are often neglected. By the way, these possibilities do indeed exist on both sides and not as widely assumed by Humanities scholars just on their side. We have often been asked: “Why do you want to help us? Why do you spend your time on this” This answer is quite simple. From a computational point of view the diversity of data and modality poses a big challenge for Computer Science. The problems arising in such projects are often much closer to real-world problems than those tackled in the ivory tower until now and techniques developed in this context will bring advances for all sort of real-world applications.

Furthermore, DH is a field that is not just shaped by the risk of miscommunication of totally different disciplines, but moreover a field that carries the fear of its very own scholars along. Afraid of being left behind by an evolving form of their science of origin, researchers seem in constant fear to lose their right to exist. Thinking back to our study times, when students of theater science spent an entire semester of their basic education on justifying why theater science should be an independent science, it is surprising to see the opposite trend in Digital Humanities. Whereas the upcoming science of theater was fighting for its emancipation, the newly developing field of Digital Humanities embraces many disciplines. But instead of the scientists who are strolling in this new and undiscovered realm searching for the right to define this new field, single disciplines try to position themselves inside of it, desperate to show their surplus value unable to let go the old for something new. Interestingly, this finds its expression in the withdrawal to laboriously developed vocabularies and terminologies of specific fields, to equal parts jeopardizing the diplomacy and communication of our abovementioned explorers.

The right question to ask might therefore not be what Digital Humanities are but rather what they could be once the two explorers let go of their shyness and fear. The most promising characteristics of what is apparent so far might be a strong will. The will to collaborate despite all frustrations, all communication barriers and all compromises that have to be made with the prospect of a gain. Of which kind this gain might be remains to be seen. But it must be this gain that will define this newly developed science. As a defining part of science is the contribution of new knowledge to mankind, there must be more to it than just the pure simplification of the manual labor of a Humanities scientist. So far, DH is more a potential than a science. DH is something that has yet to develop.

Usually, people make a division: on the one side are the computer scientists, on the other side are the Humanities scholars, and when both sides meet, DH comes to be. To be honest, we are not sure that we are really and wholeheartedly able to believe in this simple formula. To be even more honest, we don’t even want to believe in it. Because if this simple rule was true, DH would have no reason (and consequently also no right) to call itself a new field. It would just be a new and fancy tool in the toolbox that Humanities scholars use to tackle their research questions. Still, having grown up in a world of accelerating progress in Computer Science — and in artificial intelligence in particular — we share the strong conviction that there must be more to it.

What is this more that we are calling for? What we are asking for are new methods and new knowledge. Methods which are genuinely new and only come to pass due to the application of computers and AI techniques and technology to questions in the Humanities. Knowledge that would have remained hidden without these methods and the corresponding consolidation. We envision results that, no matter how much time a human Humanities researcher would invest manually in striving for, she would fail. We are convinced that DH cannot, shall not, and will not only be a speed-up and scale-up of conventional methods as practiced for decades and partially centuries. Computer science can offer the skills to work out multimodal collaborations between different fields of Humanities. When art meets sound, when text meets pictures, knowlegde comes to light that otherwise would have remain hidden.

The practice of Humanities as a field of study are in a certain way one of the “most human” activities imaginable. As they have research subjects created by humans like works of art, poems or films, it seems to be an indispensable condition that the researcher needs to share the humanness with the originator in order to understand. Scholars often have to rely on their interpretation of incomplete or lacking information, especially in the arts much is conveyed in an implicit manner and left to the recipient to add, and so forth. Where we have good reason to believe that all humans share basic principles and qualities in their cognition, this also means that we have to accept that we all share the same biases and limitations – both, on the perceptual and on the mental/reasoning level.

Artificial systems aren’t human — they don’t employ the same “hardware”, they don’t work according to the same functional or mechanistic principles, and their strengths and weaknesses seem almost orthogonal to our own. To many (not only, but especially on the Humanities side of things), this makes AI appear absolutely incompatible with the goals of Humanities research. Still, coming from fields such as cognitive AI or computational cognitive modelling, we are convinced that misunderstanding and prejudice are at the basis of this conclusion: It is true, AI still is far from achieving its ambitious goals in overcoming more and more parts of this distinction between man and machine. Nonetheless, cognitive systems and computational models of cognition over the last decades have made great progress and already today put us in the position to model significant parts of human cognition in ways which 20 or 30 years ago would still have been unimaginable. Modelling frameworks such as SOAR or ACT-R allow us to build psychologically-plausible task models down to the level of cognitive memory processes or even activation patterns in a simulated neural network not unlike parts of the brain — why not apply all these possibilities in modelling tasks in the Humanities, complementing and completing the reasoning based on introspection and observation of actual humans as practiced today?

But we want to go even further. Many researchers in Computer Science and AI over the years have learned to appreciate and leverage — rather than deride and avoid — the already mentioned foundational differences between man and machine. An AI does not “see with human eyes”, human perceptual and cognitive primitives are foreign to it, its entire way of perceiving and conceptualizing are qualitatively different — and, thus, allow for different forms of sensing, perceiving, and structuring of its environment and of information in general. Using artificial systems and computational methods might offer genuinely new perspectives on these subjects — perspectives which are new and enriching precisely because they are not human, because they do not adhere with our shared “cognitive program”, but instead are only achievable by taking the human out of the loop and letting the machine do the sensing, perceiving, and reasoning.

And we think what is in our way to find these new means and approaches of gathering knowledge, is the research question itself. What is needed is exploration without fear and the perception of prejudice as a chance (namely in overcoming it) rather than as a valid reason for staying where we are and doing what we do. The non-human and, thus, this far unknown objectivity artificial systems can introduce to DH should be welcomed as an opportunity to see well-known objects of investigation under new light and with literally new “mechanic” eyes. What this requires on our side is neither the mind of a Humanities scholar nor the mind of a computer scientist, but the mind of a curious explorer without fear of breaking laws in one or the other kingdom. And the courage to allow also non-human aspects into the very field called Humanities to make a fairy tale come true.

1 Comment

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One response to “Digital Humanities: a fairy tale? (Guest Post)

  1. I just want to start this response with the fact that I am rather
    grumpy today so this might come across badly.

    I really wanted to like this post; it starts and ends well but the
    middle is something to which I object.

    My first objection, to what I feel, is the AI/CompSci triumphalist
    tone in the middle section. I do not want to get into the weeds of
    arguing about the state of AI but I do want to note that I seen this
    hype cycle before repeatedly. For instance, Deep Neural Networks are easily fooled in image
    recognition tests (see Deep
    Neural Networks are Easily Fooled: High Confidence Predictions for
    Unrecognisable Images
    ; see also IEEE Spectrum’s interview with Yann
    ). While I do not object to using tools from
    Computer Science to explore my own research questions, I remain
    unconvinced that it requires an entirely new discipline (whatever
    happened to Humanities Computing?). I also remain deeply sceptical of
    AI research claims to cognition.

    My second objection is that I do not know what a “Humanities
    scientist” is and I do am not sure I have ever met one. This seems,
    to me, to be an attempt to co-opt a term to bring it into “science” for
    a reason that seems unexplained here. As if the pinnacle of
    everything must be “science”, whatever that may mean.

    Again this may just be the grumpiness coming through, but I am happy to be an explorer but on my own terms and for my own ends.

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