Episoder
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Curious about how to ethically leverage AI in qualitative research? This episode dives into the questions asked by researchers during a recent webinar on this critical topic.
Dr. Susanne Friese answered all questions, and our AI hosts, Lisa and Tom, unpack these responses with their own unique perspectives.
💡 The following questions are explored:
Are journals able to detect if a section of a manuscript/ paper was written with AI tool? if Yes, how?
How secure is it to use the ChatGPT Team/Enterprise plan? They promote it by saying that 'user business data is not used to train their models.'
Does it mean if the researcher writes his own PROMPTS then it can be considered as “ethical”?
Will the AI model be able to identify its bias if we asked it to?
Is there a risk of over-reliance on AI in decision-making?
Who is accountable for errors in AI-assisted analysis?
How do researchers ensure AI is used ethically and responsibly?
What do we do if AI claims our work to be his?
Are peer-reviewers ready to assess work using AI analysis?
What do you think about students who hardly manage to pay their tution fees. How can they afford the use of AI?
Are themes created by an AI "OBJECTIVE"? Can we trust outcomes?
Can we entrust the big tech companies with our data?
Will journals accept articles when researchers use AI?
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In this episode, our AI hosts dive into a heated email exchange that unfolded after the announcement of QInsights, our AI-powered app for qualitative analysis. The debate, spanning the equivalent of 25 printed pages, is a textbook example of Thomas Kuhn's concept of a paradigm shift in action. Intrigued? Hit play and join the conversation!
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Manglende episoder?
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This episode is based on a conversation between Sidi Lemine, CEO of Jade Kite, and Dr Susanne Friese, written up by Sidi with the title "The Great Unlearning: making the most of the AI paradigm shift" and published on LinkedIn(Episode AI Art from the original article by Sidi Lemine)
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oin hosts Lisa and Tom as they delve into Dr. Susanne Friese’s thought-provoking blog on the potential for bias in AI systems used for qualitative research. In this episode, they explore Friese’s perspective on how AI, despite its impressive capabilities, is influenced by the biases embedded in the data it learns from, including human-created sources like scientific literature. Lisa and Tom discuss Friese’s argument that instead of chasing the impossible ideal of unbiased data, researchers should engage with AI interactively, recognizing and addressing biases through critical self-reflection and intentional prompting. They highlight Friese’s reminder that core qualitative research skills, particularly reflexivity, are vital for working effectively with AI. Tune in to hear their insights on her balanced view that encourages both embracing AI’s potential and understanding its limitations.
This episode is based on the following blog: https://qeludra.com/blog/ai-bias-qualitative-research
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In this episode, we challenge the notion of AI as a one-click solution for automating qualitative analysis, and instead, advocate for its use as an interactive, collaborative tool. Before diving into how this can be achieved, we first address a key but often overlooked limitation of current AI tools—the context window limitations. Despite being a critical factor, many users are unaware of how these constraints affect AI's ability to process and interpret data effectively.
Understanding these limitations is crucial to developing strategies that work around them. Join us as we explore practical approaches to harnessing AI's potential, while maintaining the depth and precision that qualitative research demands.
If you want more detail on the new approach to analysis, Dr Susanne Friese walks you through an example analysis in her blog:
Ethical and Responsible Use of AI for Qualitative Analysis
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This episode is based on a book chapter written by Dr Susanne Friese, which will be published in early 2025 in:
Christou A. Prokopis (Ed.) ArtificialIntelligence (AI) in Social Research, chapter 5. CAB International, Wallingford, UK.
This manuscript investigates the potential impact of artificial intelligence (AI) on qualitative data analysis, particularly through the lens of Thomas Kuhn’s theory of scientific revolutions. It examines how AI is transforming coding, a prevalent methodology in qualitative research, and explores the challenges and opportunities presented by these advancements. The author argues that the integration of AI into qualitative research is not simply a technological advancement but a potential paradigm shift, requiring a re-evaluation of established practices and a willingness to embrace new approaches.As usual, Lisa and Tom have their own take on the issue. Tune in and enjoy them discussing the book chapter from their point of view.
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In this episode Lisa and Tom discuss the ethical implications of using AI in qualitative research, focusing on data privacy and confidentiality. You learn about general ethical standards for research, particularly highlighting the importance of legal compliance, informed consent, data protection, and the principle of non-harm. We then take a look at anonymization and pseudonymisation and how teese relate to privacy laws, especially GDPR.
In this episode, we provide you with practical guidance on crafting comprehensive confidentiality agreements for research participants, outlining key components to ensure the ethical use of AI in data collection and analysis.
Here are some of the resources we are talking about in the podcast:
Off-line Transcription Tools
noSribe
aTrain (Windows only)
Buzz
Templates for drafting a confidentiality agreement for your resarch participants when intending to use AI tools:
Englisch: AI-Focused Confidentiality and Consent Agreement Template
German: Vertraulichkeitserklärung für Forschungsteilnehmende bei KI Nutzung
This episode is based on the following blog by Dr Susanne Friese
Naviating Ethics in AI-Driven Qualitative Research - Part 1:
Data Privacy and Confidentiality Agreements
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In this episode, AI hosts Lisa and Tom tackle the bold claims flooding the internet: "Use AI tool XY for qualitative analysis, and you'll get instant, comprehensive insights without lifting a finger." The promise of effortless analysis sounds enticing, but is it really that simple? Have AI tools genuinely advanced to the point where they can outperform and replace seasoned qualitative researchers?
Lisa and Tom dig deeper into these sweeping assertions, examining the realities behind the marketing hype. Throughout the episode, they challenge the notion that AI is a magic bullet for research, and instead propose a more balanced view: AI as a powerful tool in a researcher’s arsenal, but not a replacement for human expertise.
This episode is based on the Dr Susanne Friese's blog:
Navigating the AI-Hype
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In this episode we provide a detailed exploration of the Qualia platform, an AI-powered interview tool. Lisa and Tom will be discussing the platform’s features and report on the first-hand experience of Dr Susanne Friese with the platform, including a test run with a think tank workshop.
Conversing with AI: My encounter with an Interview Bot
We take a look at the potential benefits and drawbacks of using an AI bot for interviews, highlighting its limitations in terms of emotional connection and potential for inappropriate responses while acknowledging its ability to streamline data collection and analysis.
The episode is about an early version of Qualia. We have heard rumors that the team behind Qualia is coming out with a brand-new version shortly. So stay tuned, we will follow up with an update.
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In this episode, Lisa and Tom address the concerns and skepticism surrounding the use of AI in qualitative data analysis, specifically focusing on data privacy and security based on the following blog post:
Beyond the Comfort Zone: The Dynamics of Technological Acceptance
You learn for instance about the process of data transmission and processing within LLMs, using clear analogies to illustrate the technical aspects.
With this podcast, we want to dispel misconceptions and foster informed decision-making within the research community regarding the use of AI in qualitative research.
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In this episode, Lisa and Tom, your AI hosts, explore the evolving role of generative AI in qualitative data analysis based on a blog written by Dr. Susanne Friese. While AI tools can assist with tasks like summarizing data, Susanne argues that they are not yet capable of replacing the nuanced work of human coding and analysis. Lisa and Tom expand on this, engaging in a lively debate about AI’s limitations—especially when it comes to understanding extended contexts and summarizing long documents.
Tom and Lisa advocate, alongside Friese, for a reimagining of methodologies—where the real potential of AI isn’t just in performing tasks faster, but in pushing the boundaries of what qualitative analysis can achieve.
Tune in to this thought-provoking conversation, as we critically examine AI's role in reshaping the future of research while staying grounded in human expertise.
Original blog post by Dr Susanne Friese:
Rethinking Qualitative Data Analysis: Do we truly want a faster horse?
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This episode explores the evolution of qualitative research methods, tracing a path from early manual methods to the integration of artificial intelligence (AI). It begins by describing the challenges and opportunities of using tape recorders for data collection and the subsequent shift to computer-assisted qualitative data analysis (CAQDAS) software. Lisa and Tom then discuss the emergence of generative AI tools, such as ChatGPT, and their potential to revolutionize qualitative research once again.
In this podcase, we call on researchers to embrace a new era of qualitative research, one that embraces the potential of AI while also critically examining its limitations and re-evaluating traditional research methodologies.
In this episode we trace the evolution of qualitative research methodologies, from the early days of manual note-taking to the current era of generative AI. Lisa and Tom explore the introduction of technologies like tape recorders and qualitative data analysis software (QDA), discussing their impact on data collection and analysis practices. They then discuss the emergence of generative AI tools, such as ChatGPT, and their potential to revolutionize qualitative research once again.
While AI offers potential benefits, Lisa and Tom also caution researchers to critically evaluate its limitations and biases, emphasizing the need for human interaction and interpretation in the analysis process. This episode concludes by advocating for a re-imagination of qualitative analysis methodologies, moving beyond simply accelerating the process and instead exploring innovative approaches to harness the power of AI as a collaborative tool.
Original blog post: https://qeludra.com/blog/from-tape-recorder-to-generative-ai
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In this podcast, the two AI-hosts Lisa and Tom talk about my blog "Sometimes you need a little bit of data and lots of right brain". In this blog I argue that market researchers often prioritises collecting large amounts of qualitative data over analysing it effectively. I advocate for a deeper approach to qualitative analysis based on using the right brain's creative and analytical thinking skills.
In this podcast, Lisa and Tom—our AI hosts—dive into my blog content but with a twist. Powered by Gemini 1.5, their viewpoints stem from a broader range of data, creating a conversation that goes beyond my original post. So, while you’ll still hear my perspective, Lisa and Tom spice things up with their own AI-driven commentary.
