NutriNet – a personal assistant for your grocery shopping
18
October
2024
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Have you ever taken hours browsing around supermarkets searching for the most nutritious food options? Did it take you too much time figuring out which recipes to cook best, with the groceries you bought? Struggles when dealing with food are numerous, starting from choosing products with appropriate nutrients simply not knowing enough recipes.
Therefore, we introduce NutriNet – a mobile application that is going to make shopping and meal planning easier!
NutriNet simplifies grocery shopping and meal planning, by analyzing which products and recipes fit the users’ desired grocery item wishes, nutrition values and store preferences best. NutriNet aims to address the challenges being implicit to personalized nutrition and helps consumers make healthier food choices by simplifying the grocery shopping and meal planning process. This shall be done by eliminating the need to perfectly understand all nutrition values or to search for numerous recipes. NutriNet completes all these tasks for you in real-time and provides clear and accessible recommendations for you.
• Real-time personal assitant: NutriNet acts as a multifunctional application providing value to consumers by solving various food related problems in real-time. Appearing as a chatbot, it is aimed at taking general grocery shopping lists or meal wishes as input query, combined with preferences for food characteristics (e.g., nutrients, allergies) and grocery stores. It then provides brand specific and personalized grocery shopping lists, as well as meal recommendations, if so desired. Moreover, grocery items can also be added into the initial grocery shopping list query, by scanning them with the integrated AR tool. The product will then be detected visually and thus will be integrated into the shopping list input query.
• Long-term customer engagement: NutriNet distinguishes from competition by providing personalized and customized advice. This is possible, as NutriNet consists of a database, having incorporated stock and product information of the major supermarkets in the Netherlands. In contrast, classic applications, which try to meet similar needs (e.g., meal recommendation) rather focus on counting nutrients for the purpose of short-term weight loss, instead of personalizing grocery shopping lists and meal recommendation to enable a healthier lifestyle for users. Those applications are usable on short term but are proven to have low adherence over the time (Chen et al., 2015).
• Personalized recommendations: NutriNet leverages generative AI to offer accurately personalized recommendations. Users can simply enter their preferences, while prompting a grocery list or a meal, such as gluten-free or high in protein, and the generative AI powered application will provide accurately personalized results. However, personalization and raising awareness for healthy foods are not the only purposes of NutriNet. It also addresses sustainability issues that supermarkets are facing. By gathering consumer purchase and search data in the application, consulting services can be offered to supermarkets, enabling them to plan ordering and stockholding processes more efficient. Hence, supermarkets should be able to reduce food waste due to overstocking on long-term.
NutriNet offers a 2-sided network platform, yielding important value to both, consumers as well as supermarkets.
Contributors
574051 – Duong Dao 728070 – David Wurzer 738898 – David Do 562387 – Roxi Ni
References
Chen, J., Berkman, W., Bardouh, M., Ng, C. Y. K., & Allman-Farinelli, M. (2019). The use of a food logging app in the naturalistic setting fails to provide accurate measurements of nutrients and poses usability challenges. Nutrition, 57, 208-216.
The Anatomy of an AI generated TikTok post
9
October
2024
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Many of us like to indulge in scrolling our phones in our free time. It’s a quick guaranteed way to kill some time while waiting around, or gathering the strength to finally get out of bed. While our options were limited to classic picture-and-text posts until a few years ago, the meteoric rise of short-form video content has been dominating the doomscrolling niche in recent times. After personally seeing a specific type of content (rehashed reddit drama stories), I began to wonder, could you automate this with GenAI?
Down the rabbit hole
I first began by analyzing the catalyst for my idea, hoping to find the exact mental tasks necessary to pass to GenAI to automate it, however, I got sidetracked. After listening to the specific video closely, I have noticed that the voice and sound design were extremely high quality, it was as if someone who specialized in narrating commercials took some time out of their working hours, and used their studio setup in order to record the voiceover. The display of text and editing also seemed off for a typical TikTok post, it had a few errors that in my mind were “no-brainers”, editing choices that made the story less understandable. That’s when I realized that I didn’t spend my time looking at someone’s geniune effort, I was staring right at my own idea, implemented before I did it.
Shifting gears
At that point, I was both disappointed and amazed, my original idea would probably not find the success that I hoped it could, after all the market for AI generated short stories in video form was presumably already saturated, however, I wanted to know more about this topic. I never personally found this type of content to be of amazing artistic quality, but it could be the springboard for future GenAI development in entertainment. I decided to still go ahead with the project until a proof-of-concept stage, to capitalize on the learning opportunity.
When finally I had the code up and running, churning out videos with little-to-no human input, taking a fraction of the time (and artistic integrity) that a human would, I felt like I stumbled onto the crux of emotional manipulation of contemporary social media. I felt like I found something that every one of my friends should at least know about. Even more disturbingly, during the research for this project, I have not found any complete documentation of what this content is and how it’s made. I only had my account of my experiences and thoughts to go on.
This blogpost outlines my findings and opinions on how this content is made, with the hope that at least getting this knowledge out there will restore some fairness in knowing what you consume to social media.
However, there are still a topic of discussion I could not answer even at the end of the project. Is this truly a new form of entertainment? Am I quick to condemn something new and exciting? Therefore throughout the blogpost I will try to give as much practical information as possible (without encouraging or condemning the non-illegal parts) and hope that this topic will sort itself out in due time if more people have the ability to do it.
How the sausage is made
After conducting some research (if you can call scrolling TikTok for a few hours research), I have found some elements that are common across many of these videos:
Profile picture
Automating away the process of selecting a profile picture seems to be an exercise in futility, after all, why spend any time on automating something that will only occur once, right? Well, online speculation is focused on the conjecture that most platforms purposefully de-amplify AI generated content, and the channel itself will hit a low ceiling on how high it can get in the algorithm. Therefore, I speculate that most organizations that run channels like the one I was trying to create, actually run multiple channels concurrently, thus cheating the “algorithmic ceiling” imposed on them.
Voice
The main way that the underlying story is conveyed to the viewer, is the AI generated voiceover. It is extremely common, with only a small percentage of these videos opting for a musical background or simply no voice. These voices can be created by training a neural network on a few thousand hours of publicly available speeches of one specific person and the transcript. The main objective is to find a voice that is both soothing and fitting for the type of story. Voice can only be done “wrong” after all, by selecting a voice that is irritating or hard to understand, excluding potential viewers from consuming the content.
Most posters use a third-party service (most commonly Elevenlabs) to acquire this aspect of the post. Most AI voiceover services (including Elevenlabs) charge between 30-100 euros per month of API access (compared to a rumored figure of 20-50$ of income per million views), but offer a free tier, given that the user first registers with their Google account. This creates a large incentive for unscrupulus (but strongly business minded) posters to buy stolen Google accounts (which entails supporting the theft of gmail accounts) to generate the voiceover. Free alternatives exist, but require a quite strong PC to actually run and generally slightly underperform when compared to paid services.
Story
Finding an interesting story to put into video form is hard work. However, as most of these stories are selected for their strong language, uncontroversial interpretability and general relatability, there is a really good proxy to look for when selecting them. As Reddit has a rating system, these stories are easy to find, go on a subreddit (a sub forum where related topics are discussed), sort by highest rated, set the filter to “highest rated of all time”, and just like that, you have a scoop…. or at least I initially thought so.
The problem with this approach is that these stories are “internet famous”, there is a high likelyhood that your viewer will have heard the story before; They’ll listen for the first few seconds, conclude that they don’t need to listen to it again, swipe down, and tank your video’s rating to the bottom of the algorithm.
Thankfully, if you are willing to abandon artistic integrity (or don’t view it as such), you can fine tune a generative AI model to write the stories for you. By collecting the top stories from a given story niche (or better yet, collecting it from many niches and using an unsupervised machine learning algorithm to classify them into niches), you can make sure that your generative AI model will be able to create tall tales to entertain the world.
Scenery
A defining feature of these types of short-form videos is the background video. Most posters strive to find something that occupies the part of the viewers brain that isn’t actively engaged in listening to the story. For this, bright colors and easy to interpret picture content is a must. The end goal is to totally engage the viewer at all levels, making them focused on the content. Familiar video content (the games Subway Surfers, Minecraft and GTA 5 work exceptionally well) makes interpretation more fun for the viewer, evoking feelings of either nostalgia or active interest.
Generative AI does not play a role in this part of the content. While it is theoretically possible to train an AI model to play games for background video, it is currently easier to find a large chunk of video content that can be cut up into many small pieces.
Again, the problem of the most obvious solution being suboptimal rises. There is a finite amount of explicitly royalty free content that fit well with this medium. If viewers recognize the specific background video from a competing channel, it will engage them less. Therefore, some posters opt to either pay royalties (again, hopelessly eating away at the profit margin), or just stealing content that wasn’t royalty free.
As most of the footage originates from YouTube and the story content is posted on TikTok, this leverages a gap in content moderation policy. The two sites rarely coordinate on copyright issues, especially if the piece of content is of low value (for example someone’s ages old minecraft gameplay), ensuring that this method entails low risk.
Editing
The last component of a post of this nature is the editing. There are 3 main aspects that have to be covered, cutting the background footage to last until the story does, displaying subtitles and animating said subtitles. There are currently many Python libraries that offer rudimentary video editing that fit this purpose, such as MoviePy.
A simple approach would entail defining static rules around these tasks. The subtitles in this type of content usually utilize a “pop” effect, where the text enlarges and slightly shrinks in quick succession. This captures the viewer’s attention, as humans are hard-wired to pay attention to fast moving objects, naturally drawing the viewers attention to the subtitles.
This leaves only two tasks, cutting the video to fit the story (keeping in mind to only show attention grabbing sequences) and displaying the subtitles (keeping in mind to display related words together). For this task, GenAI outperforms static rules, most general knowledge large language models that support video RAG (retrieval augmented generation) can be prompted to accomplish these tasks. Better yet, they’re able to write code themselves that they can interact with, setting the appropriate parameters for each video.
Running these models locally might not make business sense, as these models require a strong PC, which might prohibitively eat away at the profit margin. Third-party solutions do exist and I trust that by now you have noticed a pattern. The token pricing is too high to be sustainable for the enterprise. All that is necessary to acquire this capability below market price is to get a hold of a stolen API key for any state-of-the-art model, offloading the computational task to a server far away.
FIN
With this, you now know all the details that I uncovered behind this type of content. I found that this content is very troublesome to make. My overarching theory behind the creation pipeline is that it is simply too expensive to create compared to the little income it brings in for any organization. Tiktok reportedly pays around 20-50$ per million views, this is simply not enough to support an ethical creation of this type of content right now. However, I sincerely believe that this will change, at which point the internet will have to collectively decide the fate of short-form storytime content. We all play a part in this conversation, so I encourage to leave your opinion down below in the comments section.
Want to Be the Star? SocialAI Makes You the Main Character!
20
September
2024
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Instagram, Facebook, Snapchat, TikTok, and X (previously Twitter) all have one thing in common: we connect with friends, followers, or subscribers. Yet, for most of us, we will never reach the stage of celebrity where every post is directly responded to by dozens of messages. What if I tell you that a brand-new application can solve that? Social.AI puts you in the center of attention by giving you AI-powered bot followers that will engage with any of your posts.
As dystopian as it may sound, it’s hardly surprising that artificial intelligence has entered the field of social media, given the technology’s expansion. With new platforms like ChatGPT having more than 600 million visits per month (Duarte, 2024). AI is becoming an integral part of our daily lives.
Social.AI first seems like X, a well-known site where people share ideas, opinions, and posts. The difference is that you are interacting with a community of AI bots who are eager to respond to anything you say, rather than with actual people. In essence, SocialAI provides a social environment in which the user is the center of attention. No quiet on the radio, no ghosting. The designed bots are constantly available, prepared to offer advice and support, engage in discussion, or even engage in trolling.
Figure 1 Figure 2
Michael Sayman, the platform’s founder, calls it “liberating.” He clarifies that his goal was to provide a secure environment where people could communicate in private with one another and get input from a variety of AI characters. Users may choose from 32 distinct bot “types” on the app, ranging from adoring admirers to sardonic critics, depending on the kind of response they’re looking for (Lomas, 2024).
After some tries, some of us will feel more at ease knowing that there is still work to be done on this app before it can be said to compete against mainstream social media platforms. As you can see from the figures (Figures 1 and 2), each bot has a distinct personality, and you can easily perceive that the answer is from an AI chatbot, as they feel very oriented towards certain behaviors.
Ultimately, Social.AI is not perfect yet, but it serves as a reminder of how AI can reshape social spaces. Even if this application is not on point, it reminds us that progress is not stopping and asks us a deeper question: As AI continues to evolve, do we want to be the stars of lifeless computers?
References:
Duarte, F. (2024, July 27). Number of ChatGPT Users (Aug 2024). Exploding Topics. https://explodingtopics.com/blog/chatgpt-users Lomas, N. (2024, September 17). SocialAI offers a Twitter-like diary where AI bots respond to your posts.
Deepfakes are AI-generated media that can mimic real people’s appearances and voices. These have rapidly evolved from a technological curiosity to a significant force which reshape digital business models. Nowadays deepfakes offer a wide range of commercial applications from personalized advertising and virtual influencers to content creation and customer service automation (Herbert Smith Freehills, 2024; Ferraro et al., 2024). However, as the technology advances this brings complex ethical especially about misinformation.
Digital business models are using deepfake technology to innovate and enhance customer engagement. Companies are exploring virtual influencers who engage with audiences and offer brands a new way to connect without the use of human influencers. Deepfakes also play a role in personalized marketing where tailored AI driven content creates more compelling advertisements. However, the rise of deepfakes goes hand in hand with ethical challenges. Which includes concerns about authenticity, consent, and misuse. As businesses adopt these technologies, they must carefully consider the potential risks alongside the opportunities.
Ethical challenges connected to the use of deepfakes are significant and particularly now when digital transformation spreads across industries. A major concern is the use in spreading misinformation such as deepfake videos of politicians on big social media platform like Meta and X. This as a result can have an undermining impact in public figures and institutions. Additionally, deepfakes involve consent and privacy issues. This because the media can be created and shared without the permission of an individual. Therefore, companies aiming or using this new technology must implement ethical guidelines that clearly label synthetic media and do their utmost best to prevent misuse and consent violations.
As deepfakes influence digital business models companies must balance innovation with responsibility. While deepfakes offer immense potential in marketing, entertainment, and customer engagement, they also pose significant risks. Companies need to explore these opportunities but must also set ethical standards and develop safeguards to protect individuals and society. The future of deepfakes in business depends on leveraging their potential while carefully managing ethical implications.
Deepfakes in advertising – who’s behind the camera? | Herbert Smith Freehills (2024). https://www.herbertsmithfreehills.com/notes/tmt/2024-02/deepfakes-in-advertising-whos-behind-the-camera
Ferraro, C., Demsar, V., Sands, S., Restrepo, M., & Campbell, C. (2024). The paradoxes of generative AI-enabled customer service: A guide for managers. Business Horizons, 67(5), 549–559. https://doi.org/10.1016/J.BUSHOR.2024.04.013
Weapons of mass destruction – why Uncle Sam wants you.
14
October
2023
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The Second World War was the cradle for national and geopolitical informational wars, with both sides firing rapid rounds of propaganda at each other. Because of the lack of connectivity (internet), simple pamphlets had the power to plant theories in entire civilizations. In today’s digital age, where everything and everyone is connected, the influence of artificial intelligence on political propaganda cannot be underestimated. This raises concern as, unlike in the Second World War, the informational wars being fought today extend themselves to national politics in almost every first-world country.
Let us take a look at the world’s most popular political battlefield; the US elections; in 2016, a bunch of tweets containing false claims led to a shooting in a pizza shop (NOS, 2016), these tweets had no research backing the information they were transmitting, but fired at the right audience they had significant power. Individuals have immediate access to (mis)information, this is a major opportunity for political powers wanting to gain support by polarising their battlefield.
Probably nothing that I have said to this point is new to you, so shouldn’t you just stop reading this blog and switch to social media to give your dopamine levels a boost? If you were to do that, misinformation would come your way six times faster than truthful information, and you contribute to this lovely statistic (Langin, 2018). This is exactly the essence of the matter, as it is estimated that by 2026, 90% of social media will be AI-generated (Facing reality?, 2022). Combine the presence of AI in social media with the power of fake news, bundle these in propaganda, and add to that a grim conflict like the ones taking place in East Europe or the Middle East right now, and you have got yourself the modern-day weapon of mass destruction, congratulations! But of course, you have got no business in all this so why bother to interfere, well, there is a big chance that you will share misinformation yourself when transmitting information online (Fake news shared on social media U.S. | Statista, 2023). Whether you want it or not, Uncle Sam already has you, and you will be part of the problem.
Artificial intelligence is about to play a significant role in geopolitics and in times of war the power of artificial intelligence is even greater, luckily full potential of these powers hasn’t been reached yet, but it is inevitable that this will happen soon. Therefore, it is essential that we open the discussion not about preventing the use of artificial intelligence in creating conflict and polarising civilisations, but about the use of artificial intelligence to repair the damages it does; to counterattack the false information it is able to generate, to solve conflicts it helps create, and to unite groups of people it divides initially. What is the best way for us to not be part of the problem but part of the solution?
References
Facing reality?: Law Enforcement and the Challenge of Deepfakes : an Observatory Report from the Europol Innovation Lab. (2022).
Fake news shared on social media U.S. | Statista. (2023, 21 maart). Statista. https://www.statista.com/statistics/657111/fake-news-sharing-online/
Langin, K. (2018). Fake news spreads faster than true news on Twitter—thanks to people, not bots. Science. https://doi.org/10.1126/science.aat5350
Traveling Back in Time with TikTok’s 80’s AI Yearbook Photo Trend
6
October
2023
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For about a week, a new trend has risen in popularity in the TikTok community.
From the start, TikTok was a platform where creativity bloomed, and the current craze for “80s AI yearbook photos” trend has gone an extra step in taking nostalgia to unprecedented levels. Generative AI has made it possible for people once more to go to a decade associated with neon lights, perm, and large jackets. Even more, for people to experience fashion trends that they were never a part of.
The app that enables its users to do this is called Epik. They charge their users $5 dollars to create 60 yearbook pictures that are delivered in 24 hours, or $10 dollars if they want express delivery in 2 hours. So far almost every video that has been posted about the process of making the photos shows a queue of 1.000+ which goes to show that this is likely to be extremely profitable for the creators of this AI/app.
Generative AI continues to prove its ability in producing engaging and entertainment-rich experiences. In a matter of minutes, these sophisticated AI algorithms take a picture of your face and flawlessly put it into ‘80s yearbook photo frames that contain typical hair-cuts, fashionable styles and environment typical for this period. This is not just an ordinary filter, but rather a kind of time machine for photographing oneself.
This is in line with some of the major points we have made while studying this course. This highlights the possibility of using AI for purposes of entertainment and creativity. As a result, generative AI is not only about data analysis, but it can also become a means of artistic expression, converting ordinary selfies into notable creations of digital art.
This TikTok trend makes us think about the future of Generative AI in entertainment. Are we going to witness other movements where AI is used to revive ancient periods in time by methods that will be invented in the future? What implications could this have on our perceptions of nostalgia and cultural references?
To sum up, TikTok’s ‘80s yearbook photo trend is an enjoyable take on the use of AI in creating entertaining, but nostalgia driven content. This is an important message for our time. It means technology connects us both with the past and present so that we can investigate and appreciate different aspects of history.
Exploring HeyGen AI: The Gateway to Effortless Video Translation
19
September
2023
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One thing I found in my studies abroad is that learning a language means more than communicating with the local population; it also allows access to an extensive set of content and culture. Now think of yourself as a freelance content creator, or you are working for the company that created an amazing video. It’s educational, entertaining, and it has the potential to appeal to people all over the world. But to do so, there is still a language barrier that needs to be broken. It would normally require a team of translation and dubbers to painstakingly duplicate your video in more than one language.
In the rapidly evolving landscape of digital content creation, a new player has emerged to simplify the process of video translation: HeyGen AI. For creators who want to make their content available to a global audience while preserving the authenticity of their message, this groundbreaking service offers a unique solution.
With one click, this tool aims to simplify the whole translation process. In order to ensure that this translation stays true to the original charm of the video, it employs a real voice clone which closely imitates the actual speech style of the creator. Your content is always true to your tone, no matter what language you speak.
To illustrate this concept, let’s consider the example of Mr. Beast, a renowned content creator known for his philanthropic endeavors and engaging videos. Mr. Beast has set up a company to assist him in reaching an international audience at this time, by dubbing and translating the videos in 14 different languages (Creator Global, 2023). However, with HeyGen AI, he and his team can effortlessly create videos in various languages without delay for manually dubbing, and expand his global reach without compromising the essence of his content.
The goal of HeyGen AI isn’t to break the language barrier, it’s to open up new possibilities for creators and viewers.
Creator Global. (2023). Creator Global. Retrieved from Creator Global: https://www.creatorglobal.com
Filter bubbles
13
October
2022
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I first heard of the term filter bubble a few years ago during one of my lectures during my bachelor. I found it an interesting topic as filter bubbles are everywhere, and I believe even more widespread during the pandemic. For those of you who don’t exactly know yet what a filter bubble is: you find yourself in a filter bubble, every time that you are surrounded by news and opinions that are in line with your opinion (Farnam Street, n.d.). This probably does ring a bell now, as for our generation we can easily link it to the algorithms that our favorite social media apps use. One well-known example of filter bubbles is when Trump (suddenly) won the presidential elections in 2016. A lot of people didn’t see it coming that Trump actually had won the elections as they were almost sure that Hillary Clinton would win (Baer, 2016). This happened because many people actually ‘lived’ in a filter bubble. This happened because the algorithms that are used by social media platforms like Facebook, generate a personalized timeline that is more adjusted to your preferences every time you open or like an article. The algorithm personalizes the content, which results in only content that is in line with your opinion showing up on your timeline at some point. The fact that it is so easy to surround yourself with other people who share the same opinions also reinforces the creation of filter bubbles. A lot of people tend to believe they are well-educated on certain topics because they read content all day. But the problem is that this content is so tailored to their beliefs, that it often only tells one side of the story (Baer, 2016).
Another example of when filter bubbles were a hot topic was during the peak of the pandemic when polarization occurred in society due to the different beliefs of people. Two groups were created, and more people started believing that vaccines were only causing harm and that the pandemic was a hoax. In the United States, 42% of Americans have seen a lot or some news about the coronavirus outbreak that seemed completely made up (Mitchell & Oliphant, 2020). This number is alarming, as this can be caused by people living in filter bubbles. People who questions the pandemic started clicking on some articles that agreed with their doubts, causing the algorithm to show them more and more similar articles that are in line with their opinions. This causes people to believe that what they think is true because that’s the only news they see at some point. However, the problem is that they only see a very small fraction of the actual news on the pandemic and thus barely have an idea that there are other facts that can be true.
Personally, I think this is a serious problem and one of the downsides of social media. People can start believing in their own reality and not listen to others anymore, because all they see is news that is in line with their believes. What do you guys think of it? And do you believe that there is a clear solution for the problem of filter bubbles?
References
Baer, D. (2016, November 9). The ‘Filter bubble’ explains why Trump won and you didn’t see it coming. The Cut. Available at: https://www.thecut.com/2016/11/how-facebook-and-the-filter-bubble-pushed-trump-to-victory.html (Accessed: October 13 2022)
Farnam Street (2019, November 14). How filter bubbles distort reality: Everything you need to know. Farnam Street. Available at: https://fs.blog/filter-bubbles/ (Accessed: October 13 2022)
Mitchell, A. & Oliphan, J. (2020, March 18). Americans Immersed in COVID-19 News; Most Think Media Are Doing Fairly Well Covering It. Pew Research Center [Blog Post]. Available at: https://www.journalism.org/2020/03/18/americans-immersed-in-covid-19-news-mostthink-media-are-doing-fairly-well-covering-it/ (Accessed: October 13 2022)
Somebody is watching me
11
October
2022
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Rockwell said it first, “I always feel that somebody is watching me and I have no privacy.” How many times has it occurred to you to discuss that you are interested in buying a product or paying for a service, and right after you unlock your smartphone and…what a coincidence! Your feed on Instagram, Facebook, TikTok, and other social media and search engines is full of ads related to the desired item. Maybe the universe is listening and displaying all the relevant ads. Maybe not.
Let’s use an example to make it more clear. Take, for instance, the use case that you are living in Rotterdam and you are visiting a friend of yours in Amsterdam. That friend of yours is really excited about the iPhone 14 that she ordered online, and she is trying to convince you to buy it. You say that you will think about it and the conversation ends there. You return home, unlock your smartphone, and…surprise! It is literally everywhere in your online presence. How is that possible? You call your mom and start discussing conspiracy theories and how Mark Zuckerberg and Adam Mosseri are eavesdropping. They are not. But if they are not, how do our thoughts and discussions about products magically convert into ads? They have master’s degrees in tracking and watching our actions in the online and offline worlds as well. If you are not naive or more politically correct, if you have ever read the terms and conditions on Facebook, you would have realized by now that you have consented to surveillance in your online behavior. Every digital step that you make (aka every click) leaves a digital footprint behind, which is turned into data that is saved to your unique online customer profile. Tracking is not restricted to the online world. Back to the I-phone 14 example Facebook tracked your location and found out that you and your friend were together. And, respectively, they track her purchasing history and focus on the last purchase, the iPhone 14. To be honest, anyone who would have paid that amount of money would talk about it. Facebook takes advantage of the probability that your friend discussed that purchase with you and decided to give it a shot with you.
Besides location tracking, Facebook’s algorithm detects similarities and differences in your and your friend’s interests, demographics, places you have been, groups you are a part of, hashtags you follow, and so on (Selman, 2021). If you are influenced by the conversation, you will be tempted by the ads and click on them to find further info. Then the footprint is yours and more ads will be displayed. If you ignore the ads, eventually, after a while, they will be replaced with ads that you are more likely to engage with.
To conclude, there are no conspiracy theories and nobody is listening to your private conversations through your smartphone. That is what Edward Snowden should have probably said in order to not live freely, but he lived many years under asylum because the NSA and CIA wanted to…make him quiet.
Sources:
Selman, H. (2021). Why We See Digital Ads After Talking About Something. [online] McNutt & Partners. Available at: https://www.mcnuttpartners.com/why-we-see-digital-ads-after-talking-about-something/ [Accessed 11 Oct. 2022].
More than Killing Your Time? The Trend, Future, and Growth of Consumer Internet
2
October
2022
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Undoubtedly, Meta cannot ignore the competition from TikTok and its parent company, ByteDance nowadays. The temptation of content ranking based on social graphs for users is increasingly inferior to the taste and convenience of recommended content. However, three trends are emerging in the consumer Internet, from media to algorithms to interaction. Meta, or Facebook and Instagram together, is on the way to differentiating itself meanwhile building the safeguard with resources on user and technology.
Immersive Medium
It has been witnessed that Facebook gained explosive growth after it added photo sharing from the text mode, and Instagram expanded rapidly after adding the video function to photo media. The progression of the medium, from text to images, then videos, 3D afterward, and till then VR, is the most signification advancement that all the consumer internet companies above are devoting into.
Involvement of AI
Computers are becoming smarter and more convenient. As time passed, Facebook changed from a collection of personal information to time stamp posts, then to ranking feed with weight and signal. The recommendation is another stop with a huge step: the content pool is more than your interests and following but from the whole internet. Afterward, AI generation and creation will be the next focus.
Dynamic User Interaction
The third trend for consumer internet would be the transformation of user-orientated towards computer-controlling. While “click”, “scroll,” and “tap” were used in the initial versions of Facebook and Instagram, TikTok applied “swipe” to simplify the process in a more user-friendly way. Other companies, such as Youtube, are using “autoplay”, which is a more interchangeable and less-interaction method.
No matter what technology or direction those consumer internet companies are heading to, the attractive part is that they’re combining those trends and making them boundless. In the long run, the diverse content creation environment and lower cost of AI could realize a vision far more than user engagement, but what users choose to interact with.
Reference
Rebecaa F. (2019). The Strategy Behind TikTok’s Global Rise. Harvard Business Review, September, 19.
