AI machines: the role of humans in data analysis

The internet lit up the day ChatGPT launched. Almost everyone on every social media platform has tuned in to rate how smart he is. Undoubtedly, it caught people's imaginations and opened their mouths in ghostly amazement.

Like jeez, he not only wrote computer programs, poems, essays, and everything in between; he also wrote them with such finesse, clarity and relativity that can be attributed to a brilliantly intelligent human. He even got 1020 on the SAT. How amazing!

I remember my friend, a physicist, coming home from his office and kept shouting in admiration at what people were doing with ChatGPT on Twitter. Then he began to speculate on what such a display of intelligence by AI now means for human employment. " You do not understand ; this thing can do anything, boy! He launched: "A lot of people will lose their jobs!" He was sure that humans would lose some of the jobs they held. However, I expected him to tell me what kind of jobs would be lost to AI in general.

Will AI replace data analysts?

I didn't care until he told me that he had read somewhere that AI would replace data analysts. Immediately I was invested in figuring out how. So I hired ChatGPT to find out what qualities of human intelligence he can demonstrate now and, most likely, in the future.

First, I started with domain-specific questions, which the app did credibly - very well. Next, I moved on to coding assignments, and ChatGPT performed very well under assignment specificity.

Finally, I moved to a more data-centric mission, and guess what? I was not shocked as my friend had painted that I would.

What is the current role of humans in data analysis?

Maybe I expected too much. When I described what I wanted to do algorithmically, the app came up with solutions in a way that made me productive, especially discovering methods that make data processing faster.

However, it could not perform all the data analysis processes on its own, which according to Google Analytics are Ask, Prepare, Process, Analyze, Share and Act.

Despite advances in technology and the availability of tools and systems capable of performing some of the tasks of data analysis, humans play a crucial role in data analysis.

For example, while machines and algorithms can process and analyze large amounts of data quickly and accurately, they are not able to completely replace the ability of human beings to understand and interpret the results of data analysis.

Humans ask the right questions

The role that humans play in data analysis is crucial today, as humans bring a level of context, insight and judgment to data analysis that is essential for making decisions insights based on data.

First, humans can ask the right questions, identify patterns and trends, and draw meaningful conclusions from the data. They can also communicate the results of the analysis in a way that is understandable and actionable to decision makers.

In addition, humans are responsible for setting the goals and objectives of the analysis, selecting and preparing data for analysis, and additionally designing and implementing the plan analysis.

The human touch is also responsible for ensuring that data is collected and managed in an ethical and responsible manner, and for considering potential data biases and limitations.

Overall, the role of humans in data analysis is to use their analytical skills, critical thinking, and creativity to extract value and insights from data and to use that insight to inform and improve decision making.

Why AI machines can't replace humans in data analysis

While the question is whether AI machines, like ChatGPT, have replaced humans in critical areas like data analysis, it has been shown that they cannot perform tasks such as formulating research questions, researching data or performing analyses.

Although they can provide information and advice on these topics, the actual performance of these tasks requires the involvement of human beings with the necessary skills and resources.

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