Is the golden age of data science finally over?
If you are reading this article, you probably already have a job in the data industry, or are looking to get into the field.
And with all the advancements that have been made in the field of generative AI in the past year, you are concerned about whether data science jobs will be automated away.
One year ago, I would’ve scoffed at anyone who even brought up the possibility of automating my data science job.
In fact, I even wrote an entire article mocking the idea that AI could ever replace data scientists—I mean, we write code, build machine learning models, analyze data, and break down complex information to non-technical stakeholders.
Our job is difficult. These skills take years to hone. AI could improve efficiency and collaboration between data teams, but it couldn’t possibly replace the actual work we were doing.
The above blog post, however, was written before ChatGPT was released.
Since then, we have witnessed paradigm-shifting advancements in the field of generative AI.
In this article, I will re-evaluate my stance on the future of data science based on existing developments in the field of generative AI.
Based on my extensive research and insights from industry experts, I will present a range of viewpoints explaining why ChatGPT might replace data scientists, as well as the reasons why it may not.
I will examine both sides of the debate and leave it to you, the reader, to make an informed decision as to whether generative AI will render data scientists obsolete.
If you prefer a video format, watch this: