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Programming is going through an evolution in which generative artificial intelligence is able to tackle increasingly hard coding problems. Human creativity and the specialized craft of programming can now be performed by intelligent algorithms. I recently started a Python coding course myself, so was able to experience what it is like to leverage generative AI tools in learning to code. AI-generated code had a significant impact on my learning experience, which made me consider the function of programmers and the future of programming in general.

Last summer, I wanted to expand my horizon and dive into the world of programming. I signed up for a CS50 Python course, wherein I had to solve numerous coding problems. A tip a friend of mine gave, is that ChatGPT can simply provide the necessary code based on given input. As the course progressed and the problems got harder, I found myself relying on code that was generated by AI in an increasing amount. It significantly reduced the time I needed to work through the course, but made me heavily reliant on generative AI and sometimes unaware of the logic behind the codes. But hell, they worked!

Programmers were, in the past, responsible for every aspect of software development, including code generation. Currently, generative AI can take over the tedious task of typing codes and serve as creative inspiration for codes, resulting in experienced programmers being able to execute their tasks increasingly fast (Deniz et al., 2023). Negative side effects include the potential loss of creativity in coding, through AI tools following certain patterns, and fears of job losses. Programmers are still required for examining code for bugs and errors, contributing organizational context and overseeing tricky code requirements. Whereas generative AI can give a programmer a head-start, human intervention remains necessary.

In my personal experience with code generated by AI tools, I noticed I had less urgency towards understanding how the codes worked, since they were functional. It made me question whether it is effective to use generative AI tools when learning how to code. Experienced programmers who already understand coding can greatly benefit from productivity increases, resulting in them having more time for value-adding activities such as innovation.

Do you think learning to code can be effectively accompanied by generative AI tools?

Deniz, B. K., Gnanasambandam, C., Harrysson, M., Hussin, A., & Srivastava, S. (2023). Unleashing developer productivity with generative AI. McKinsey & Company. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/unleashing-developer-productivity-with-generative-ai

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Attempting to become a firm’s PowerPoint expert can result in mixed feelings for interns. It is a chance for them to demonstrate design capabilities and contribute to a team’s achievement. However, it is also a tiresome and time-consuming activity, after putting in hours of work to design, update and edit a couple of slides. These tasks do not allow much opportunity for creative thinking or intellectually challenging problem-solving.  

The technological revolution of generative AI is set to reshape the role of the intern. This post will discuss how generative AI can change the game in the classical intern role of being a slide deck creator, creating room for more meaningful work and value-adding activity for the company.  

Generative AI focuses on generating content, which in our case is PowerPoint presentations. It leverages deep learning, which are artificial intelligence algorithms, to replicate human creativity. Thereby, generative AI is able to analyze the content it receives and immediately create slides with little human intervention. Common tools such as Midjourney and Dall-E-2 create high-quality images, whereas a number of applications, such as Simplified, Slides AI and Beautiful AI generate complete presentations based on the input that is provided (McLean, 2023). Reduction of hours spent on manually designing and formatting slides, consistent results compared to varying human designer output, and personalized output that is programmed to align with the organization, can be expected from generative AI.  

As a result, interns become free to explore more meaningful work as they have more time to come up with novel ideas, think critically, and engage in mentally stimulating work. Furthermore, internships focus on being a learning experience instead of a formatting course. Not only interns themselves, but also the companies they work for benefit of an engaged and motivated intern that can put his effort into adding novel perspectives and ideas to the team.  

 McLean, D. (2023). 6 Best AI Presentation Tools in 2023 (Compared). Elegant Themes Blog. https://www.elegantthemes.com/blog/business/best-ai-presentation-tools#1-simplified