Welcome back to our CLCF profile series, where each month we interview a CLCF researcher to hear more about their projects (check out our previous profiles here). This month, we’re excited to feature a conversation with Dr. Hadiya Roderique, Assistant Professor of Journalism Studies, Research and Practice in the Department of Arts, Culture, and Media at the University of Toronto. Prior to joining the department, Hadiya worked as a consultant, speaker, broadcast commentator, journalist, and lawyer. Her current research projects focus on barriers to hiring and advancement for racialized journalists, discourses of racism in media, and differences in how racialized and white reporters use language in their reporting on race and gender.

Photo courtesy of Hadiya Roderique

M.E.: In a nutshell, who are you as a researcher?

Hadiya: I would describe myself as a mixed-methods scholar of media inequity and how media can be more equitable. Thematically, I’m interested in the ways in which the media reports on marginalized communities and how the industry can do that better. I look at that in a number of ways – for example, from a textual lens, a perceptual lens, and an organizational lens, given my background in both journalism and organizational behaviour. Methodologically (and in life!) I get bored doing the same thing, so I dabble in a variety of methods – experimental research, critical discourse analysis, interview based qualitative work, and surveys, amongst others!

Doing journalism and being a journalist is also an active part of my research practice – practice based research, as we call it in the Arts, Culture, and Media department! I engage in my own creative practice on issues related to marginalised communities, to contribute to the ‘counter-discourse’ that centers and properly represents people who look like me in the media. I have written pieces centered around my experiences as a Black woman in a variety of spaces, such as dating, the workplace, joy, and contemplating parenthood. In addition, my reporting on topics such as work, crime, the justice system, takes an informed, intersectional approach.

 

Daphne: We’ve seen active organizing and resistance from creative workers to generative AI in fields like film and television, especially around copyright and monetization. How are journalists responding to AI’s growing role in their field?

Hadiya: On the production side, I think there are a range of responses from fear/trepidation to full on embrace. Some creative workers are leaning into AI to improve their productivity and workflow, and to become more efficient. For example, in the olden days, you used to need to pay humans to transcribe interview tapes or do it yourself. Now, there are tools like Otter AI that will transcribe and summarize interviews for you. Alerts and social media monitoring, and even production and analytic tasks are being done by AI.  The theory is that taking these labour intensive rote tasks frees a journalist up to do the things that AI can’t do.

Others are using AI for some of the creative production elements of journalism – generating interview questions, editing writing, or even using it to write an entire article.  You may have read about the ‘Summer Reading List” article, that was AI generated and hallucinated made up books by real authors. It was published in several major outlets in the US. But, I would guarantee that there are also hundreds, thousands more that didn’t get caught or flagged.

Naturally, a lot of journalists and future journalists are afraid of being replaced, and an already shaky industry having even fewer spaces and opportunities for them. One thing I tell my students is that if they start to use AI to do their student journalism, and don’t work the writing muscle and actually learn how to become better writers, that eventually, media organizations will cut out their positions and pay someone much less to feed prompts into an LLM to generate journalism. So to keep the industry and their job prospects alive, they have to resist the urge to have a computer do the writing for them.

Furthermore, those who often lose those opportunities first are the people who are already marginalized in the industry. One of my predictions is that journalism that incorporates AI will all start to sound the same, and then there will be a pivot away from AI and having people who can write in a unique voice that stands out from AI generated content.

 

Daphne: Based on your research, how does the use of generative AI in Canadian news media exacerbate or complicate discourses of domination?

Hadiya: Recent research I have done on discourses of domination, where are the discourses that maintain white supremacy in Canadian media, has found a real reluctance to name and identify racism, islamophobia, and white supremacy in media headlines, which are the most salient parts of journalism articles. Given the already existing and significant concerns about the proliferation of real-world biases by AI tools, a movement toward, for example, AI written headlines, would amplify and exacerbate these biases. I’m embarking on a research project that looks into how AI generated articles use discourses of domination in their text as compared to actual news articles on the same topic. I predict that the use of discourses of domination in the AI generated text will be greater.

 

Rafael: What’s your star sign?

Hadiya: I’m a true Leo – both Leo sun and moon. Big Leo energy over here when I’m in an extroverted mood.

Follow Hadiya’s work with CLCF here.