Interview Overview

In this interview, I talked about the fascinating world of generative artificial intelligence models and, importantly, their impact on productivity. I explained how these advanced models work – basically, generating text, audio, video, or images based on instructions we give them. The conversation focused on how this technology could significantly boost the productivity of even highly skilled workers, the expected positive effects on the global economy, and also touched on the natural concerns people have about job security in this new era. The interview is in Azerbaijani, but English subtitles are available.

Full Interview

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Key Points Covered

Here’s a breakdown of the specific points I discussed during the interview:

  • I started by defining generative AI models, explaining their ability to create different kinds of content like voice, text, video, or images, based on human instructions.
  • I noted that while these models have become very popular recently, especially over the last ten years, we are now truly beginning to see their real effects on people’s lives.
  • I highlighted findings from studies showing that using generative AI can increase the productivity of highly skilled individuals by as much as 40%. I also suggested the impact might be even bigger for those starting with less expertise in a particular field.
  • Economically, I discussed the projections for generative AI’s impact, pointing to estimates like McKinsey’s, which suggests a potential boost to the world economy of $11-17 trillion by 2040. This really shows the scale of the change we’re talking about.
  • I identified specific fields where I expect the impact to be largest – areas like sales, marketing, scientific research, and software development. These are often fields where there’s a big difference in knowledge and skills among workers, and AI can help close those gaps.
  • On a practical level, I emphasized how individuals can use generative AI in their daily routines, especially for tasks involving text and images.
  • A key technique I focused on was “prompt engineering” (or “təlimat mühəndisliyi” as we might say in Azerbaijani). I explained that writing clear, effective instructions is really important to get the best results from these models.
  • I shared some specific prompt engineering strategies, like asking the AI to take on a specific role, sometimes even offering a sort of “reward” for doing a good job, and usually preferring short, clear instructions, often with examples.
  • To show how it’s used in the real world, I gave examples like a dyslexic plumber using AI to write emails, doctors using it to help draft radiology reports, and even shared my own experience using it during my PhD studies to come up with arguments, counter-arguments, and connecting paragraphs.
  • It was important for me to say that generative AI is just a tool, and it can be used for good or bad things. So, being aware of the possible negative uses is essential.
  • I specifically warned about financial fraud as a major risk. AI can be used to create very believable fake text messages or profiles to pretend to be bank staff or customers. I urged listeners to be extremely careful and always double-check information, especially when it involves money.
  • Regarding job security, I admitted it’s uncertain. There isn’t a simple “yes” or “no” answer to whether AI will replace human workers. While some jobs might disappear, I compared this to past technological changes, suggesting that new kinds of jobs and opportunities are also likely to appear.
  • Finally, I predicted that bringing AI into workplaces will probably involve regulations, starting with AI being used mostly as a helper or assistant tool rather than a complete replacement for people.

Main Takeaways

Based on our discussion, these are the key messages I wanted to leave the audience with:

  • My view is that Generative AI is a game-changing technology that can significantly improve productivity and change the global economy.
  • I stressed that using it well depends on getting good at prompt engineering – learning how to give clear instructions to these AI models.
  • I showed that Generative AI isn’t just an idea; it has many practical real-world uses already affecting different jobs and parts of daily life.
  • Importantly, along with the good things, we have to recognize the risks, especially the chance of more financial fraud and the ongoing discussion about job losses. This means users need to be careful, and we need sensible rules.
  • Looking at history, I’m still optimistic that even though new technologies cause disruption, they usually end up creating new kinds of job opportunities.