Want to know about how Instagram uses AI and ML, you’re at the right place. If you are a regular Instagram user, there is a good chance that you would have come across the words “Instagram algorithm”. Business accounts, sports, meme pages, amongst others, often remind their followers about an algorithm having some effect on their viewership.
and that users should interact with the posts more often to avoid missing out on content.
You might have also noticed how sometimes Instagram ads tend to be eerily specific to your tastes. You could be discussing football boots with your mates online. then casually come across ads for Nike shoes in your feed. Even more intriguing is when you see ads for products that you’ve only ever searched once or twice outside the app.
or worse when the product in question never left the confines of your mind.
This can happen with the explore page as well. The more pet posts that you interact with, the more cats you come across on the explore page.
Have you ever wondered how all this was happening? Without domain knowledge, one might assume that they are being stalked! – and quite understandably so. However, if you are familiar with machine/deep learning, these features on Instagram Uses AI. Resulting into intelligent algorithms working together with the data collected by the app.
Spam/Abusive Content Filter:
These algorithms are capable of doing more than recommending ads and posts to users. Recent developments in AI technology have enabled the developers of Instagram to automate the process of eliminating spam and offensive content. Until a while ago, you manually report offensive materials and spam content, for them to remove it. With the automation of this process, Instagram has been far more successful in battling cyber-bullying – a rampant issue on social media platforms.
When Instagram notices content that goes against their policies, the violators gets automated warnings – sometimes even banned without further notice!
Studying Human Culture:
Owing to the nature of the content on Instagram, the algorithms also get an in-depth view of human lives. Users can post their Favorite travel photos, what they had for lunch, their closest relations, beloved celebrities, daily routines and so on. Adding to this are the messages that sent and received between users.
When strung together, all of this information represents typical human Behavior. In a sense, we are akin to guinea pigs in a social experiment of the largest scale.
If the developers of Instagram wanted to recreate the typical characteristics of a human being onto a machine, they would possess all the data required to achieve this.
Dozens of movies have shown us why this is a very bad idea!
To sum it up in one image:
[Source: https://i.imgflip.com/zaysa.jpg]
Let’s put aside the thought of Instagram having a dystopian future in store for us.
Instead, we turn our attention to the benefits of these algorithms in social media apps like Instagram.
Consider a scenario where you are new to this platform, and as such, you sign up for an account. To begin with, you follow your favourite football team’s page and a few of your favourite players. The algorithms kick in at this stage. They identify patterns in your interactions so far and accordingly recommend accounts to follow. If you follow your real-world friends – and they followed you back, the algorithms also identify common patterns between you and your followers.
This is similar to how streaming services like Netflix, recommend movies or shows to its users as they also use it as Instagram Uses AI.
They make use of techniques like Collaborative and Content-based filtering.
Note: The workings of both techniques are not covered here. They have their own posts. I recommend you to check the other posts out – to get some clarity on the subject if nothing else.
Social Media Marketing | Instagram Uses AI
Businesses make use of such recommendations to reach a wide range of potential consumers. Tracking user data regarding their interactions and performing data analysis, enables brands to generate targeted advertisements. They can identify potential clusters of customers and only target these clusters, thereby preventing unnecessary usage of resources.
For example, there would be no point in showing people who live in India, ads for some Taxi service operating in the UK – that would just be a waste of money.
According to official statistics, the advertising reach on Instagram ~ around 850 million users and business accounts receive one-third of all interactions done users!
A well-targeted ad could potentially cause sales to sky-rocket!
For obvious reasons, Instagram Uses AI does not get explicitly mentioned . However, Word-Embeddings are quite common in this area of machine learning. In simple terms, this method makes comparisons between words in captions, messages or stories, identifies patterns and groups them accordingly. In the Football example, the
algorithm compares the words in posts that you have interacted with and finds similar posts or accounts to recommend. Posts with the hashtags #football, #footy, #soccer and so on, will be ranked and filtered. These ranks affect how users view recommendations on their Explore page – higher rank results in posts displayed first. The algorithms simultaneously check for copyright issues, spam or violations.
As you can see below, when I start following the Indian Football team’s account, Instagram provides suggestions on accounts related to Indian football.
If you would like to customise your feed or explore page, start interacting more with the type of posts you would like to see.
The example above is meant to provide an idea of how the system works. The actual implementation involves a more complex mixture of recommender systems (from the other posts) and algorithms to perform these tasks.
Conclusion |Instagram Uses AI
We have seen how useful machine learning is when dealing with an enormous amount of data, as with Instagram content. However, the biggest concern is how much data we are willingly and unwillingly sharing on the platform. Machine or Deep learning models perform better when they are provided with more data – and with a greater variety of data. The basics of AI involve mimicking human actions and behaviours. Together with such a diverse and enormous dataset that is continuously updated, creating the perfect artificial mind is not far fetched.
The idea of recreating the Human mind might seem like an exaggeration, but AI experts have been debating over the repercussions of such technology – especially in the wrong hands!
Always be aware of the content you share online!
article by: Shivaadith Anbarasu
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