Dear Shahzaib Shahzaib,

In my opinion, in an era of the growing role of artificial intelligence (AI) in data analysis and article writing, human research skills still remain crucial. While AI can analyze data and identify patterns, humans have the ability to generate original ideas and solutions that are unattainable by machines. Creativity, innovation and the ability to think critically are qualities that distinguish human researchers. In the context of the ethics and complex decisions that are part of scientific research, human judgment remains irreplaceable. In addition, interpersonal skills and the ability to collaborate in multidisciplinary teams are invaluable in the implementation of research projects. AI is already being used in various fields such as medicine, finance, marketing and education, improving the efficiency of research processes. Generative AI technology and Big Data Analytics support multi-criteria data analysis, which is particularly useful in the fields of engineering and urban planning. Key theories in this field, such as machine learning and information theory, are being developed by established researchers. Despite the sophistication of AI, the human role in research remains essential for original and valuable research, combining technology with creativity and critical thinking.

Artificial intelligence technology has been rapidly developing and finding new applications in recent years. The main determinants, including potential opportunities and threats to the development of artificial intelligence technology are described in my article below:

OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT

Article OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL I...

I invite you to join me in scientific cooperation on this issue,

Best wishes,

Dariusz Prokopowicz

Hi Shahzaib,

My conclusion is actually the opposite: Now it’s a great time to do a PhD!!

If you know the right digital literacies and have solid research skills, you can generate amazing results -things that neither you nor AI could achieve on your own. The role of the researcher now is super exciting; it’s kind of like teaching a child. You have to tell the Generative AI exactly how to do things, instead of it deciding for you what to do. You need to provide example data for it to learn (like few-shot learning), or you can fine-tune models using your own data, getting results that even the best versions of LLMs can't manage. This is because you do need to keep control, or else you’ll end up with absolute chaos in disguise.

The AI is simply a tool, just like software, and currently, there is no AI that can replace human research skills. There are several tests comparing the best models from OpenAI (GPT-4), Google (Gemini Advanced), Anthropic (Claude), Baidu (GTM), etc., and they all still lack true "creativity". Now, if at some point in the future Artificial general intelligence (AGI) is realized, then theoretically it could create new knowledge (but actually is just a dream). To give you some points:

Hope this helps the discussion!

I would look at AI as a tool that can aid and enhance capabiltiies for PhD researchers, speaking from my experience.

But your fellow student's perspective reflects a growing concern in the academic and research community about the role of AI in reshaping how we conduct and value research.

I would enlist number of qualities humans posess when it comes to this topic:

• Complex Judgement: Humans are capable of assessing nuanced, context-dependent scenarios where there isn’t a clear, data-driven answer.
• Researchers must often navigate moral dilemmas and make decisions based on principles that AI, limited by its programming, cannot fully comprehend.
• Original Thought: Humans excel at generating original hypotheses and exploring unconventional research directions.
• Contextual understanding such as Cultural and Societal Insights: Humans have the ability to understand and integrate cultural, historical, and social contexts into their research.
• Interdisciplinary Connections: Human researchers often draw on knowledge from multiple fields to create a holistic understanding of a problem. This synthesis requires insight into different disciplines and how they can be interconnected, which AI struggles with beyond basic integration.
• Communication and Persuasion: Humans are adept at presenting their ideas, persuading others, and collaborating effectively in team settings. The nuances of human conversation, debate, and consensus-building are key parts of research, especially in collaborative projects.
• Empathy in Research Design: When conducting research that involves human participants or impacts communities, empathy helps researchers design ethical, respectful, and participant-centered studies and questions.
• Philosophical reasoning: Questions about "why" and the deeper implications of research are still areas where humans excel.
• Adaptability: Humans are capable of adapting their research strategies when they encounter unexpected results.

I genuinely think no PhD researcher is at risk by being superceeded by AI's capabiltiies to do the same. Contrary, it can make life easier.