The Modern Researcher’s Guide: Mastering Digital Identity and AI Tools
By Dilip Barad
Video recording of the online session
In the rapidly evolving landscape of academia, the traditional image of a scholar buried under a mountain of dusty books is being replaced by the digitally savvy researcher navigating complex ICT tools.
In a recent engaging session on "Practical Skills for the Use of ICT in Research," Professor Dr. Dilip Barad, a senior academic with over 26 years of experience, laid out a roadmap for scholars navigating the digital age. From managing digital footprints to leveraging AI for literature reviews, here are the key takeaways from the session.
1. Your Digital Identity is Your "Aadhar" of Research
One of the most pressing issues identified during the session was the lack of digital visibility among scholars. A pre-session survey revealed that out of 49 participants, only a handful possessed updated profiles on platforms like Google Scholar or Scopus.
Dr. Barad emphasized that a digital profile is not just vanity; it is essential for data transparency and national ranking systems like IRINS (Indian Research Information Network System). He noted a stark contrast in digital adoption across India, observing that Southern states have significantly higher registration numbers on IRINS compared to the North, East, or West.
The Solution? ORCID. Dr. Barad describes the ORCID iD as the "Aadhar card" (unique identification number) for researchers. It serves as a persistent digital identifier that connects you to your contributions.
• Why you need it: Digital tools and AI fetch data through unique identity markers. Without an ORCID iD, your work may remain invisible to the algorithms that drive global citations.
• Actionable Tip: Create an ORCID profile today. It allows you to sync your biography, employment, and publications across other platforms like Web of Science and Vidwan with a single click.
2. The Elephant in the Room: AI and Ethics
Is using AI in research cheating? Dr. Barad addressed this head-on, comparing the ethical dilemma to John Dryden’s analysis of Ben Jonson. If a "great emperor" (or a sophisticated tool) plunders ideas, it is often viewed differently than a common thief.
However, in the context of modern research, AI should be viewed as a consultant, not an author.
• The Golden Rule: If human consultancy is valid, machine consultancy is also valid—provided it is disclosed.
• Publisher Guidelines: Major publishers like Elsevier and UNESCO now permit the use of Generative AI for language refinement and research organization, but with strict caveats: AI cannot be listed as a co-author, and its use must be transparently declared.
3. Practical Demo: Deep Research with NotebookLM
The highlight of the session was a live demonstration of Google’s NotebookLM, a tool generating buzz in the academic community. Dr. Barad demonstrated a "Deep Research" workflow using prompt engineering to accelerate the literature review process.
Here is the step-by-step workflow demonstrated:
1. Fast vs. Deep Research: The tool allows for "Deep Research" on a specific topic, searching websites to curate a list of sources (in this demo, 48 resources were found).
2. Structuring the Data: Instead of reading blindly, the first prompt requested a table showing publication dates, author credentials, and whether the sources were primary or secondary.
3. Citation Analysis: A subsequent prompt asked the AI to identify which sources were most frequently cited by other sources in the notebook, helping to identify the most authoritative texts.
4. Finding the Gap: Perhaps most importantly, the tool was used to identify research gaps. The AI highlighted a lack of research regarding the "long-term cognitive consequences of automation"—essentially, what happens to the human brain when AI takes over our thinking processes.
5. Drafting the Review: Finally, the tool drafted a literature review complete with hypotheses and research questions based on the identified gaps, adhering to frameworks like PRISMA.
4. The Human in the Loop
Despite the power of these tools, Dr. Barad concluded with a vital reminder: Human agency is irreplaceable.
While AI can synthesize data and generate hypotheses, the researcher must verify the output. For instance, the demonstration uncovered a fascinating potential research topic: "The Cognitive Consequences of Automation" and the "Human in the Loop" theory. This refers to the risk of "brain rot" or reduced cognitive function due to over-reliance on AI—a hypothesis supported by preliminary studies from MIT.
Final Thoughts
The transition from physical print to digital platforms is not just about convenience; it is about relevance. As Dr. Barad noted, digital tools can only communicate with digital data; they cannot read a physical book sitting on a shelf. To ensure your research is discoverable and impactful, you must embrace the digital ecosystem—starting with your ORCID profile and extending to the ethical use of AI tools.
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This blog post was drafted based on the transcript of the video "Practical Skills for the Use of ICT in Research," featuring Dr. Dilip Barad.
