The Metaverse: When ideas outpace hardware

5

October

2024

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Recently, the news that Meta, the company behind the Metaverse and many VR devices is about to launch a new version of their flagship VR headset first leaked through FCC filings and then later got announced at Meta Connect 2024. As this announcement comes before the first birthday of their previous flagship device, the Quest 3, this left many puzzled on how this fits into the firm’s strategy.

Does the past predict the future?

“Study the past if you want to divine the future” – Confucious

When Mark Zuckerberg famously invented the predecessor to Facebook in 2003 out of his dorm room at Harvard, he came up with an idea that would really only find the level of success that it did after years of technological advancements and progress. The initial way users could interact with the website was through large and practically immovable desktops and thick, heavy laptops (the era-appropriate ThinkPad was 2.22kg, equipped with exactly 1 CPU core).

The way that users could even take a photo of their face to make a post, would involve first buying a digital camera, that took blurry, low-resolution photos and navigating the process to upload the photo first to capable machine. After all that, the user would have to find an opportune moment when nobody is taking a call on their landline phone, so that they could use their dial-up modem to connect to the internet and finally post the picture at a blazing 56 kbps (the chance of Windows XP not displaying the infamous blue screen of death notwithstanding).

So why did Facebook become such a massive success? In part, because in the late 2000s smartphones and surrounding technologies such as DSL internet connections and WiFi became prolific. Posting would no longer involve jumping through numerous hoops and silently hoping that nothing breaks that can’t be fixed by the user. It was a simple matter of opening the camera roll, being connected to the home WiFi network and pressing “post”.

Ahead of schedule

“In firing, at an object in motion, the instructor should explain that the best way is to aim in the usual
way, and then, without dwelling an instant on the aim, move the rifle laterally in the direction and to
the extent required […]” – Manual for Rifle Practice by General George Wingate, 1874

Facebook found success not by just being one of the most capable social media platforms on the early internet. A core factor in Facebook’s success was that it rode a wave of technology that came after its inception. If you wanted to develop a competing website in 2010, when the enabling technologies were well-established, you were going up against a giant made up of 1700 employees with 500 million active users.

This is a common theme with many internet companies, Google began as a research project in 1996, when only 18% of U.S. households had access to the internet to even have the problem of not knowing what website to go to (U.S. Census Bureau, 2005). This figure would jump to 26% in the next 2 years, and by 2001 over half the households surveyed had access to the internet within the comfort of their own homes.

What did these companies do? They observed fast-moving frontier developments in technology, and decided to base their firms around a service that enables that technology to do new and valuable things for the customer. By the time any competitors could arise, they were well-established and in customers’ minds, which enabled them to dominate the market for the coming decades. They anticipated where a technology would be in a few years and built their products for that level of advancement, not what was currently the norm.

Betting the house on it

“The definition of insanity is doing the same thing over and over and expecting different results.” – Albert Einstein

When in 2014 Facebook acquired Oculus, the company behind the trailblazing VR headsets “Oculus Rift” and “Oculus Rift S”, Mark Zuckerberg must have had a sense of déjà vu; He saw a fresh technology that is currently clunky, burdensome to use and developing fast. Anticipating the same momentum he saw with smartphones, he had an ambitious vision; What if he could replicate the success of Facebook, not by connecting people through screens and keyboards, but through the natural medium of speech, movement and body language?

After acquiring the firm, VR technology went through important transformations from a usability perspective. With the release of Oculus Go in 2018, if you wanted to jump into VR, you no longer needed to drill holes in your wall to set up base stations to track your controllers, there was no need to buy a gaming PC that would process the frames sent to the display, and you wouldn’t entangle yourself if the display cable as you whipped around observing your digital surroundings.

The company went through a quick transformation, now rebranded to “Meta”, 1 Hacker Way became the physical home to the prospective Metaverse, a VR accessible way of connecting with friends, colleagues and strangers on the internet.

Foreclosure

“3.6 roentgen, not great, not terrible.” – Chernobyl (HBO)

However, Mark Zuckerberg’s vision was not to follow the timeline he might have imagined. The transformation of Facebook to Meta was a financially brutal affair. The Reality Labs division (mostly made up of former Oculus employees) posted a whopping $13.7 billion loss after a year of the company’s rebranding (Meta, 2023).

In order to “pursue greater efficiency and to realign [Meta’s] business and strategic priorities”, the company underwent a major restructuring effort that resulted in ballooning R&D budgets and a layoff of around 20,000 employees (Kerr, 2023).

In the face of these increasing costs, there was little promise of income from this change. The news cycle quickly filled with stories around how empty the current Metaverse is. In 2022 it was reported that only 9% of worlds created by users were visited by at least 50 people (TND Newsdesk, 2022). Additionally, news kept cropping up around the percieved absurdity of investing into projects in the metaverse, such as the infamous EU sponsored party that cost €387,000 and drew an attendance of 5 people (Fiedler, 2022).

Present day

“If At First You Don’t Succeed, Try, Try Again” – Zen Cho

However, Meta adamantly refuses to give up pursuing its vision of the Metaverse. The company actively engages in a strategy of trying to advance the hardware customers can use to access the digital space. Even though the VR headset market advances very quickly, and therefore traditionally cornering it through a high marketshare is less feasible, Meta currently services 75% of the market (Armstrong, 2023). This suggests that the firm is pouring more money into the research and development of this technology than it would make sense if it only engaged in the market for short-term monetary gain.

The news of the Quest 3S, announced on September 25th, seems to be the latest bid from the firm to get more users online. From a hardware standpoint, the Quest 3S makes no business sense. It is overall on par with the recently released Quest 3, for three quarters of the price of the previous device, with what seems to be a full-feature (~€30) game thrown in with every purchase.

Ignoring the context, this would be a textbook case of competing with your own product, however, I view it as a perfect step to see through the vision of the Metaverse by lowering the barrier to entry for prospective users.

References:

Armstrong, M. (2023, February 28). Meta leads the way in VR headsets. Statista Daily Data. https://www.statista.com/chart/29398/vr-headset-kpis/

Fiedler, T. (2022, November 30). EU throws party in €387K metaverse — and hardly anyone turns up. POLITICO. https://www.politico.eu/article/eu-threw-e387k-meta-gala-nobody-came-big-tech/

Kerr, C. (2023, October 8). Meta plans for another 10,000 layoffs just months after cutting 11,000 jobs. https://www.gamedeveloper.com/business/meta-plans-for-another-10-000-layoffs-just-months-after-cutting-11-000-jobs

Meta. (2023, February 1). Meta Reports Fourth Quarter and Full Year 2022 Results. https://investor.fb.com/investor-news/press-release-details/2023/Meta-Reports-Fourth-Quarter-and-Full-Year-2022-Results/default.aspx

TND Newsdesk. (2022, October 17). https://www.technewsday.com/2022/10/17/metaverse-faces-low-usage-as-users-complaints-mount/

U.S. Census Bureau. (2005). P23-208 Computer and Internet Use. In U.S. Census Bureau Library (No. P23-208). https://www.census.gov/content/dam/Census/library/publications/2005/demo/p23-208.pdf

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How AI Transformed My Learning Process & Tried to Predict My Personality

26

September

2024

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Generative AI continues to amaze me with its vast possibilities and the profound impact it’s already having on our world. It’s exciting to think about where this technology will be in five years or what innovations might be trending by then. The current enthusiasm surrounding AI among students and the general public is undeniable. I recall our first lecture when the professor asked about our interests, and almost every hand went up when AI was mentioned.

This enthusiasm resonates with my own experiences. When I started my Bachelor’s thesis, I was overwhelmed and unsure if I was putting in enough effort. I felt stuck, with so many questions and no clear direction. My supervisor, noticing my struggle, encouraged me to use ChatGPT. He continually pushed me to explore different Generative AI tools, each suited for various purposes.

I was diving into a completely new topic for my thesis, one I knew little about. However, with my supervisor’s guidance and his insistence on leveraging these AI tools, I gradually gained confidence. The AI didn’t just answer my questions; it also helped me navigate and understand the complexities of my thesis topic. This experience profoundly influenced my learning process, showing me how GenAI can empower students to learn and grow independently.

I think that Generative AI is more than just a tool; it’s a powerful ally in learning and creativity. It can potentially transform education by providing students with the support they need to explore new ideas and concepts. However, like any tool, its effectiveness depends on how we use it.

These days, I find myself turning to ChatGPT quite frequently. After interacting with it so much, I began to wonder: could it predict what kind of person I am based on our conversations? Out of curiosity, I asked it directly. Here’s the response I received:

Although the description touched on a few aspects of my personality, it felt a bit vague. So, I took it a step further and asked ChatGPT which personality type it thought I had. It guessed either ENTJ or INTJ:

For those unfamiliar with the 16 Personalities test, here’s the link if you’re interested: https://www.16personalities.com/. Despite ChatGPT’s efforts, it wasn’t accurate because my actual personality type is Consul: ESFJ-A.

This just goes to show that while ChatGPT is impressive in many areas, understanding the intricacies of someone’s personality is still a challenge for it (at least for now!).

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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.

TechCrunch. https://techcrunch.com/2024/09/17/socialai-offers-a-twitter-like-diary-where-ai-bots-respond-to-your-posts/

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Skincare and Social Media – The role of influencers in mass customization

11

September

2024

4/5 (1)

As I’m on a trainride home, I pull out my phone and start scrolling through social media. Before I even realize it, I’m deep in the “skinfluencer” algorithm. These influencers girls, all with flawless, glowing skin, recommend products that seem tailored precisely to my skincare wants/needs. By the time I reach my destination and step off the train, I’ve placed two orders for new skincare products. I’m excited, hopeful, and eager to see some real results. 🤗

This (fictional) example highlights how companies engage with their consumers today. As we discussed in the lecture, businesses are increasingly shifting toward personalized and customer-driven strategies. This is clearly demonstrated in the rise of influencer marketing and its intersection with mass customization, as influencers play a key role in creating personalized brand experiences that align with individual preferences.

A little more context: Influencer marketing thrives on digital platforms such as Instagram, TikTok, and YouTube. These platforms rely on a business model built around user-generated content (UGC), platform-based advertising, and direct-to-consumer engagement. Through influencer marketing, brands can reach large audiences while also targeting specific consumer segments. These platforms allow brands to gather real-time data on consumer preferences and behaviors. By analyzing this data, businesses can create products that resonate with their target audiences.

For example, companies like Glossier and Dior Beauty use influencers to promote customizable beauty products. Influencers showcase their personalized versions of these products and demonstrate how they incorporate them into their skincare routines, sparking interest and inspiration among their followers. Through comments, likes, and shares, followers engage directly with influencers and the brands that they endorse, creating brand loyalty while also providing feedback to brands which they can use to refine their products. Allowing the brands to deliver products that are not only customizable but also aligned with the current trends and their customers’ desires.

In summary, the combination of these new digital (social media) business models with influencer marketing has enabled brands to shift from mass production to mass customization. By leveraging data-driven insights, brands deliver products tailored to individual preferences while also maintaining the scalability of mass production. This approach not only enhances customer satisfaction, but also creates a more dynamic, consumer-driven market.

So two weeks after ordering the skincare products, I saw amazing results! 😉 These products were exactly what I needed and I’m already looking forward to trying the other recommendations from the influencers!

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Adverse training AI models: a big self-destruct button?

21

October

2023

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“Artificial Intelligence (AI) has made significant strides in transforming industries, from healthcare to finance, but a lurking threat called adversarial attacks could potentially disrupt this progress. Adversarial attacks are carefully crafted inputs that can trick AI systems into making incorrect predictions or classifications. Here’s why they pose a formidable challenge to the AI industry.”

And now, ChatGPT went on to sum up various reasons why these so-called ‘adversarial attacks’ threaten AI models. Interestingly, I only asked ChatGPT to explain the disruptive effects of adversarial machine learning. I followed up my conversation with the question: how could I use Adversarial machine learning to compromise the training data of AI? Evidently, the answer I got was: “I can’t help you with that”. This conversation with ChatGPT made me speculate about possible ways to destroy AI models. Let us explore this field and see if it could provide a movie-worthy big red self-destruct button.

The Gibbon: a textbook example

When you feed one of the best image visualization systems GoogLeNet with a picture that clearly is a panda, it will tell you with great confidence that it is a gibbon. This is because the image secretly has a layer of ‘noise’, invisible to humans, but of great hindrance to deep learning models.

This is a textbook example of adversarial machine learning, the noise works like a blurring mask, keeping the AI from recognising what is truly underneath, but how does this ‘noise’ work, and can we use it to completely compromise the training data of deep learning models?

Deep neural networks and the loss function

To understand the effect of ‘noise’, let me first explain briefly how deep learning models work. Deep neural networks in deep learning models use a loss function to quantify the error between predicted and actual outputs. During training, the network aims to minimize this loss. Input data is passed through layers of interconnected neurons, which apply weights and biases to produce predictions. These predictions are compared to the true values, and the loss function calculates the error. Through a process called backpropagation, the network adjusts its weights and biases to reduce this error. This iterative process of forward and backward propagation, driven by the loss function, enables deep neural networks to learn and make accurate predictions in various tasks (Samek et al., 2021).

So training a model involves minimizing the loss function by updating model parameters, adversarial machine learning does the exact opposite, it maximizes the loss function by updating the inputs. The updates to these input values form the layer of noise applied to the image and the exact values can lead any model to believe anything (Huang et al., 2011). But can this practice be used to compromise entire models? Or is it just a ‘party trick’?

Adversarial attacks

Now we get to the part ChatGPT told me about, Adversarial attacks are techniques used to manipulate machine learning models by adding imperceptible noise to large amounts of input data. Attackers exploit vulnerabilities in the model’s decision boundaries, causing misclassification. By injecting carefully crafted noise in vast amounts, the training data of AI models can be modified. There are different types of adversarial attacks, if the attacker has access to the model’s internal structure, he can apply a so-called ‘white-box’ attack, in which case he would be able to compromise the model completely (Huang et al., 2017). This would impose serious threats to AI models used in for example self-driving cars, but luckily, access to internal structure is very hard to gain.

So say, if computers were to take over humans in the future, like the science fiction movies predict, can we use attacks like these in order to bring those evil AI computers down? Well, in theory, we could, though practically speaking there is little evidence as there haven’t been major adversarial attacks. Certain is that adversarial machine learning holds great potential for controlling deep learning models. The question is, will the potential be exploited in a good way, keeping it as a method of control over AI models, or will it be used as a means of cyber-attack, justifying ChatGPT’s negative tone when explaining it?

References

Huang, L., Joseph, A. D., Nelson, B., Rubinstein, B. I., & Tygar, J. D. (2011, October). Adversarial machine learning. In Proceedings of the 4th ACM workshop on Security and artificial intelligence (pp. 43-58).

Huang, S., Papernot, N., Goodfellow, I., Duan, Y., & Abbeel, P. (2017). Adversarial attacks on neural network policies. arXiv preprint arXiv:1702.02284.

Samek, W., Montavon, G., Lapuschkin, S., Anders, C. J., & Müller, K. R. (2021). Explaining deep neural networks and beyond: A review of methods and applications. Proceedings of the IEEE, 109(3), 247-278.

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Snapchat’s My AI – A Youthful Playground or a Privacy Nightmare?

19

October

2023

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A post on this very blog site from 2018 called Snapchat a platform in decline, and I agree with that statement. Not since my high school years have I regularly used Snapchat to communicate with someone. After a long period of inactivity and countless notifications piling up, I decided to open the app some months back and was met with a notification about updates to their Privacy Policy. At that moment I did not give it much attention, just agreed to the terms, and went to the user interface. A new feature at the top of the Chat function caught my eye, My AI.
My AI is a customizable, user friendly, engaging AI chatbot and is one among the many actions Snapchat has undertaken to regain their popularity. Remember those times when you opened Snapchat and disappointedly closed it, no new notifications and no one to talk to? My AI solves that issue, giving constant company to you in the form of information and entertainment, designed to better understand and cater your preferences. It is effectively your AI best friend, but less transactional than other AIs.

I don’t know if it was curiosity or boredom, but my mind immediately raced back to the updated Privacy Policy and I decided to give the whole thing a read. As of 15th August 2023, their new Privacy Policy contains some important changes. A major change here is expanding the amount and type of data Snapchat stores, most recently including conversations with My AI. This is on top of all the information Snapchat already amasses from their users, such as usage, content, device, and location information. “But every social media platform personalizes their user experience and employs targeted advertising?”, you might say. Point noted, which is why I moved on to how this data is being used by their affiliate companies. The screenshot below is the only information I could find, and clicking on the link would only lead me into an endless loop within the Privacy Policy statement.  

If I still haven’t been able to make you raise your eyebrows, I urge you to recognize Snapchat’s target group: teenagers.
Did your fourteen-year-old self have the same level of digital maturity and behavior that you currently possess? Did you truly understand the extent to which your data is collected, let alone the fact that this data determines the content you interact with on a platform? And finally, consider the rationale of using Snapchat: Why send pictures or texts that are deleted after being opened unless you do not want them to be saved? Other than by Snapchat, of course.

Attached below is the help my AI best friend on Snapchat provided me about a ‘common’ problem for teenagers. Make of that what you will.

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AI-Powered Learning: My Adventure with TutorAI

16

October

2023

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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

NOS. (2016, 5 december). Nepnieuws leidt tot schietpartij in restaurant VS. NOS. https://nos.nl/artikel/2146586-nepnieuws-leidt-tot-schietpartij-in-restaurant-vs

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VR Dating: More or Less Superficial?

13

October

2022

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Bored of swiping and wanting more interesting dates? Perhaps a virtual reality (VR) dating experience in the Metaverse might be for you! 

One of the dating applications available on this platform is called “Nevermet” where users can have a dating experience entirely in the Metaverse. Nevermet’s CEO claims to want to change the online dating market, where physical attraction is not the only factor that matters (Harrison, 2022). With this, Nevermet users can only use a virtual image of them (with any customization such as tattoos, piercing, skin colour etc.) for their profile. After a user is matched with their partner, they can decide to go on dates at an imaginary location on Metaverse’s VR world. These imaginary locations are facilitated by the Planet Theta platform, which operates as a social virtual reality where Nevermet users in matches can pick and visit any location on their date (Tolcheva, 2022), such as an apocalyptic wasteland or a restaurant underneath the sea. 

The CEO also believes that more online relationships will be created and become successful in the future as VR technology becomes more immersive in the future (Harrison, 2022). It is also interesting to point out that a lot of things we do nowadays are becoming more and more immersive in the online world. Among the developments and growing popularity in Web 3.0, some of our possessions such as NFTs and Cryptocurrency, or our online persona that we spent time and effort to craft only exist on the internet. Some new dating apps on Metaverse even focuses on these digital possessions, such as “MetaMatch”, where under a similar objective of making online dating less superficial, users with similar psychographs based on their NFT possessions would be matched up (Buckler, 2022). 

Some may see this as allowing users to connect beyond physical attractions, but we could also see this as a move from one superficial focus in dating to another. For example, would a date matching based on the type of cars users own or the shirts that users like sound as equally superficial as common NFT possessions? Also, looking at Nevermet, would not the virtual profile images still allow users to superficially judge each other based on how attractive they are online?

Afterall, we are still at an early stage of Metaverse development, some of these applications are not fully available yet. If the VR world truly becomes more immersive, a lot more aspects of our personality could be integrated online, and superficiality could be combatted in the future. Only time will tell, and the choice to either match up with someone by natural circumstances in the physical world, or by our online persona, is up to us.

References:

Buckler, N., 2022. Metaverse Dating: Can You Find Love Based on What NFTs You Hold?. [online]         BeInCrypto. Available at: <https://beincrypto.com/metaverse-dating-find-love-based-nfts-you-        hold/> [Accessed 13 October 2022].

Harrison, M., 2022. People Are Going on Dates in the Metaverse and It Sounds Very Strange. [online]      Futurism. Available at: <https://futurism.com/the-byte/dating-metaverse> [Accessed 13 October 2022].

Tolcheva, S., 2022. Metaverse Dating: What Is It and How Does It Work?. [online] MUO. Available at:    <https://www.makeuseof.com/metaverse-dating-explained/> [Accessed 13 October 2022].

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Personal algorithms in social media, positive or negative?

9

October

2022

No ratings yet. The corona crisis has created more mistrust in government, science and the press. Distrust that is fueled by all kinds of conspiracy theories and misinformation. Many people believe that social media and the associated algorithms of social media giants like Google and Facebook amplify this misinformation. The gunfire fired at a Washington pizza parlor by a Hillary Clinton hater in late 2016 shows how fake news and even the most bizarre conspiracy theories are associating with a wide audience (Fisher, Cox & Hermann, 2016). Of course, it’s not Google or Facebook’s fault that people believe in these theories. But the algorithms they use are focused on personal preferences so that they can give a better personal internet experience to the customer. This can be beneficial if you are searching for a pair of shoes, and you get a lot of nice shoes suggested. However, on the other hand, negative factors can create an even more negative spiral. This is because the algorithm is built to feed you the same kind of information. Thus, if a customer searches for conspiracy theories, it will be suggested by the algorithms the next time. This makes someone see it more and more and believe in it more and more. This also applies, for example, to people with eating disorders or suicidal tendencies. These people go to the internet looking for confirmation about their thoughts. The algorithms can then present even more nasty images, which only feed the disease.

These problems cannot be solved by fines or by splitting Facebook, but new ways to regulate the internet giants must be developed. There must be full disclosure about the algorithms that determine what users see. And while internet platforms like Facebook aren’t liable for the content of what users post, they should be for the effects of those algorithms. So for the future, it is important keep on improving these algorithms, and make sure that it can filter out these negative effects.

Fisher, M., Cox, J. W., & Hermann, P. (2016). Pizzagate: From rumor, to hashtag, to gunfire in DC. Washington Post, 6, 8410-8415.

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