How to become an AI influencer

As data science and analytics have become one of the hottest fields to pursue a career in the last couple of years, we have also seen the emergence of social media influencers across platforms like Twitter, YouTube, and Instagram, among others. While popular names like Yann LeCun, Andrew Ng, Fei-Fei Li, and Kirk Borne are some of the most followed and respected people in this space, we are seeing more and more people entering to “influence” youngsters as it is a very lucrative area to be in right now.

Sachin Birla, who works as a data scientist in EY, adds, “Unlike traditional software jobs, the data science field contains persons with various backgrounds. Hence, influencers easily find a large target audience from backgrounds other than computer science. Thus, maximum viewership gets attracted. Appealing use cases of AI are also a reason for this growth in influencers in this domain.”

Biswajit Biswas, chief data scientist at Tata Elxsi lists out five reasons as to why we are seeing so many content creators in this space.

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  •  This area of content creation sounds “cool”, easy to grab attention, and easily marketable. The general crowd do not delve much into detail further, making it more convenient to be an influencer in this domain.
  •  Information Overflow- There is plenty of information out there. Not just for AI, for everything. There is always an overnight expert on any subject.
  • Micro blogging  – There are 3 min read, 7 min read type of contents which talks superficially and there is no obligation to get into details. 
  •  Create a hype – Try to be the first mover with a claim which is yet not verified / peer reviewed
  •  FOMO effect – The fear of missing out and peer pressure can also be seen as a reason behind this trend. 

What kind of content creation works

  • Conceptual – A big chunk of the content, especially on YouTube and Instagram, is around data science concepts. These include statistical concepts and tutorials on programming languages like R and Python.
  • Career and job opportunities, data science and AI landscape – The most popular area for content creation in this field is around jobs and different types of careers in data science and AI field. Creators often talk about how to go about networking, how to edit one’s CV as per job roles and experience, etc. Some even host mock interviews to give a real feel of the actual process. 
  • Business concepts – A data scientist needs to properly understand business settings to derive insights from the data and help in business decision-making. Influencers often base their content around real-life business use-cases to give their users a feel of how business decisions are made.

Responsibilities as an influencer 

An influencer has huge responsibilities to fill. As someone with a big following, it is important to understand the kind of impact they can have on their target audience, especially if they are young or just starting out in their career.

Venkat Raman, co-founder of Aryma Labs, a data consulting firm, lists down a few things influencers should keep in mind while creating their content.


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  • Don’t give false hopes

An influencer should not give people false hopes. He adds, “I see many posts and tweets where some influencers proclaim that one does not need to know advanced math to break into data science. The poor aspirants believe it, and when they face the tough curriculum, they give up. I think we need to be honest. This will help set the correct expectations.”

  • No fake transition stories

There is the issue of showing fake “successful transition” posts as well. Some influencers—just to boost their followership or class enrollment, create fake stories of successful transitions.

  • Don’t teach wrong

Many influencers in the field teach statistics through their content. Statistics is one of the core foundations of data science. Raman adds, “I have seen even the most popular YouTubers teach statistics wrongly.”

The foundation can’t be left shaky. The influencers owe it to their audience to teach the right stuff. Unfortunately, in the chase for ‘number of followers’ and pressure to create content every now and then, they end up creating substandard content.

He adds, “The real peril of all this is that the data science aspirants learn these wrong concepts and convey the same during interviews. Needless to say, they are rejected in interviews after interviews.”

  • Not flashy and attractive to just bait more clicks

Rizul Goyal, data scientist, Oriserve feels that the content should be thoroughly researched, peer reviewed and explanatory and not flashy and attractive to just bait more clicks. Sharing educational information is much more than sharing life updates on social media. It is a more responsible position, therefore the information should be factual in nature.

Ayan Basak, a data scientist at Snapdeal, says, “Influencers should be extremely careful about the quality and veracity of the content they are propagating. They must remember that a lot of people are looking up to them for personal as well as professional development. Before talking about any topic, they should be confident and possess sufficient knowledge in the same.”

What followers should be careful of

Not just the influencers but their subscribers or followers should also know what or not to consume in terms of content from the influencers. Raman points out a few ways they can do this. 

  • Healthy amount of scepticism 

Many students and young professionals don’t have the knowledge and experience to gauge the content from influencers, especially when it comes to statistics. They rely on false proxies like the eloquence of explanation or some theatrics.

The students must not rely only on praises from fellow students about an influencer or get carried by a huge number of followers an influencer might have.

Raman adds, “My advice to students would be that they have a healthy amount of scepticism and that they do their own homework. The students could talk to established statisticians/data scientists and run the influencer’s content with them.”

  • Trust reliable sites

Another way could be to use the internet to check various good sites like Stack Exchange to get the content cross-validated. The students can also post questions on StackOverflow or Reddit if they have doubts about the integrity of the content from the influencers. 

  •  Credit points for influencers

Biswas points out that there should be  credit points (like upvotes) etc for each blogger / influencer, similar to what we have for Stack Overflow suggestions. This can help in getting more authentic content.

  • Do not fall for clickbait content

Clickbait content is created to grab eyeballs and may not represent the actual situation. Ayan Kumar Bhunia, currently pursuing a PhD in computer vision at the University of Surrey adds, “A lot of the content  out there has catchy captions like “Why you should not learn AI in 2022” or “Why data science is overrated”, and so on. It is readily evident that a majority of the influencers are not really experts in their domains, and thus, they try to gain a follower base by creating eye-catchy content that naive students fall prey to. Suppose one is genuinely interested in the domains mentioned above. In that case, they should spend time reading various blogs and may even follow various freely available online courses (from many reputed professors) to actually explore the domain and not simply bank on the words of any influencer.

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Sreejani Bhattacharyya
I am a technology journalist at AIM. What gets me excited is deep-diving into new-age technologies and analysing how they impact us for the greater good. Reach me at sreejani.bhattacharyya@analyticsindiamag.com

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