Key topics include: How has tools development interacted with professional writing? What does the case of implementing AI in a multilingual newsroom reveal? Why can applied linguists contribute to a sustainable AI shift of public discourse?
Tracing the future of digital newswriting has resulted in three key learnings from empirical evidence. First, tools make a change that can scale up from practices to professions and society at large. Second, in seemingly unstoppable grand movements, counterchange often starts bottom-up, from positive deviants. Third, as applied linguists and transdisciplinary researchers, we are to identify the creative practices that can disrupt mainstream disruption.
As humans, we can speak by using body-internal tools. By contrast, writing requires external tools, ranging from stone plates and chisels to databases and algorithms. How do such tools, in particular AI tools, interact with text production in the newsroom? As applied linguists (→1.1), we have addressed this research question in a series of transdisciplinary projects (→.2) together with practitioners from the language industry (→.3). In doing so, we focus on digital literacy, ethics, and creativity (→.4), which we analyze through the lenses of complementary research frameworks (→.5).
Repetitive language use in daily life and the professions has resulted in established practices (→2.1) and its analysis in empirically grounded typologies (→.2). From a temporal standpoint, activity types follow each other in patterns, characterized by phases in which certain activities dominate (→.3). The concepts of activity type and phase scale up from a single text production process to decades of professional development. For journalism, our longitudinal analyses have shown a shift from focused writing to fragmented writing (→.4) in five phases since the rise of digital technologies (→.5).
Analyzing real-life phenomena such as the digital literacy shift requires multi-method approaches that grant access to all the relevant levels of language use — from social to individual patterns and reflection (→3.1). The methods combined can transgress research cultures and their methodological traditions (→.2). In search of understanding the interdependency of communication and writing tools, we blended the French tradition of genetic criticism (→.3) with a German focus on writing processes (→.4). Progression analysis, our multi-method approach, is open to the AI coding of large data corpora (→.5).
With AI, the growing co-generative potential of text tools in the newsroom has become evident. We re-coded data from three decades of progression analyses, focusing on the activity field of handling tools environment (→5.1). Within this activity field, longitudinal analyses suggest differentiating between three activity scopes (→.2) as well as four activity layers, ranging from instrumental and operational to economical and societal (→.3). On these layers, specific ethical dilemmas relating to tool use can occur (→.4). They may be overcome by positive deviants’ emergent creative solutions (→.5).
Our analyses suggest that, from a journalism perspective, understanding the unique value offered by humans has become key in AI-supported newsrooms. Such knowledge can help upskill people and co-create both tools and professional education. From a research perspective, it means widening the scope for the layered contexts of writing (→5.1); going longitudinal to identify constants and variables (→.2); preparing for clean AI analyses of large data corpora (→.3); automatizing instant feedback for practitioners (→.4); and, most importantly, building trust in the field under investigation (→.5).
Key topics include: How has tools development interacted with professional writing? What does the case of implementing AI in a multilingual newsroom reveal? Why can applied linguists contribute to a sustainable AI shift of public discourse?
Tracing the future of digital newswriting has resulted in three key learnings from empirical evidence. First, tools make a change that can scale up from practices to professions and society at large. Second, in seemingly unstoppable grand movements, counterchange often starts bottom-up, from positive deviants. Third, as applied linguists and transdisciplinary researchers, we are to identify the creative practices that can disrupt mainstream disruption.
As humans, we can speak by using body-internal tools. By contrast, writing requires external tools, ranging from stone plates and chisels to databases and algorithms. How do such tools, in particular AI tools, interact with text production in the newsroom? As applied linguists (→1.1), we have addressed this research question in a series of transdisciplinary projects (→.2) together with practitioners from the language industry (→.3). In doing so, we focus on digital literacy, ethics, and creativity (→.4), which we analyze through the lenses of complementary research frameworks (→.5).
Repetitive language use in daily life and the professions has resulted in established practices (→2.1) and its analysis in empirically grounded typologies (→.2). From a temporal standpoint, activity types follow each other in patterns, characterized by phases in which certain activities dominate (→.3). The concepts of activity type and phase scale up from a single text production process to decades of professional development. For journalism, our longitudinal analyses have shown a shift from focused writing to fragmented writing (→.4) in five phases since the rise of digital technologies (→.5).
Analyzing real-life phenomena such as the digital literacy shift requires multi-method approaches that grant access to all the relevant levels of language use — from social to individual patterns and reflection (→3.1). The methods combined can transgress research cultures and their methodological traditions (→.2). In search of understanding the interdependency of communication and writing tools, we blended the French tradition of genetic criticism (→.3) with a German focus on writing processes (→.4). Progression analysis, our multi-method approach, is open to the AI coding of large data corpora (→.5).
With AI, the growing co-generative potential of text tools in the newsroom has become evident. We re-coded data from three decades of progression analyses, focusing on the activity field of handling tools environment (→5.1). Within this activity field, longitudinal analyses suggest differentiating between three activity scopes (→.2) as well as four activity layers, ranging from instrumental and operational to economical and societal (→.3). On these layers, specific ethical dilemmas relating to tool use can occur (→.4). They may be overcome by positive deviants’ emergent creative solutions (→.5).
Our analyses suggest that, from a journalism perspective, understanding the unique value offered by humans has become key in AI-supported newsrooms. Such knowledge can help upskill people and co-create both tools and professional education. From a research perspective, it means widening the scope for the layered contexts of writing (→5.1); going longitudinal to identify constants and variables (→.2); preparing for clean AI analyses of large data corpora (→.3); automatizing instant feedback for practitioners (→.4); and, most importantly, building trust in the field under investigation (→.5).