In this paper, we explore the synergies between Digital Humanities (DH) as a discipline and Hybrid Intelligence (HI) as a research paradigm. In DH research, the use of digital methods and specifically that of Artificial Intelligence is subject to a set of requirements and constraints. We argue that these are well-supported by the capabilities and goals of HI. Our contribution includes the identification of five such DH requirements: Successful AI systems need to be able to 1) collaborate with the (human) scholar; 2) support data criticism; 3) support tool criticism; 4) be aware of and cater to various perspectives and 5) support distant and close reading. We take the CARE principles of Hybrid Intelligence (collaborative, adaptive, responsible and explainable) as theoretical framework and map these to the DH requirements. In this mapping, we include example research projects. We finally address how insights from DH can be applied to HI and discuss open challenges for the combination of the two disciplines.

In postwar Germany, the federal government is usually formed by several political parties (Schmidt, 2007, p. 97). Over the past 16 years, these government coalitions were led by the Christian Democratic parliamentary group (CDU/CSU), most recently in cooperation with the Social Democratic Party (SPD), which, following the federal election in 2021, was unwilling to negotiate with their former partner, calling for new alliances to achieve a majority in parliament. Finally, the leaders of the Free Democratic Party (FDP), the Greens and SPD, despite mixed support from the party bases, signed a coalition agreement. Some journalists even regarded the FDP, which gained access to two key ministries, the secret winner of the negotiations (Fürstenau, 2021), also because the Greens did not see some of their desired climate change policies implemented (Lauter, 2021). In this research, we are interested in how the coalition agreement was assembled regarding the individual party contributions. To that end, we utilize methods from Natural Language Processing, which have seen widespread adoption in political science (Wilkerson and Casas, 2017; Merz et al., 2016; Rauh, 2015; Slapin and Proksch, 2008).

Remember, it isn't magic, it doesn't create pure objective truth, but it can be an extremely powerful tool when used correctly. Don't give up close reading (sorry, Franco Moretti) but give distant reading a shot -- you won't regret adding it to your toolkit.

The post-modern novel 'Wittgenstein's Mistress' by David Markson (1988) presents the reader with a very challenging non linear narrative, that itself appears to one of the novel's themes. We present a distant reading of this work designed to complement a close reading of it by David Foster Wallace (1990). Using a combination of text analysis, entity recognition and networks, we plot repetitive structures in the novel's narrative relating them to its critical analysis.