Instagram’s Invisible Hand: How Algorithms Fuel Online Radicalization

16

September

2025

5/5 (5)

When Charlie Kirk died, my Instagram feed changed quickly.

At first, I saw NOS posting on Instagram, reporting that Charlie Kirk had been fatally shot. Within an hour, more and more news outlets were reporting the same thing. Then, something shifted. My Instagram ‘For You’ page shifted from mourning to outrage, then from outrage to ideology. I had liked two posts, not necessarily out of agreement, but as a means of engagement. By then, the algorithm had noticed my attention and began changing my feed accordingly.

It began showing me tribute posts, previous podcast clips of him, and responses of people to his death. Soon, it showed me content that had nothing to do with Kirk at all. It showed me posts about immigration, nationalism and the collapse of Western values. While scrolling, these were the only posts I’d get, unless I went back to my ‘For You’ page and consciously picked a thumbnail that didn’t look political. Even then, my reels started to get political again after a while. As someone who follows both political sides to stay informed, I was shown increasingly extreme content, both from left- and right-wing views. The algorithm didn’t know what I believed. It only knew I was paying attention.

Digital disruption has changed how news is consumed (Nawale et al., 2023). Digital disruption refers to changes driven by digital technologies that happen at a speed and scale that transform established ways of value creation (Digital Disruption Research Group, n.d.). Where once we got information at set times, such as newspapers or TV at set times, we now get it constantly through Instagram reels and other forms of social media. Traditional news companies such as De Telegraaf or The New York Times had to adapt, and no longer necessarily control the narrative. Now, algorithms do.

In my opinion, these consequences are dangerous. Extremist groups exploit trending events to spread ideology under the radar of casual scrolling. This, combined with algorithmic reinforcement, creates a loop where radical content thrives (Akram et al., 2023). According to Ravi et al. (2024), platforms like Facebook and TikTok don’t just reflect beliefs, they actively shape them. I fear that as a society, we will become more polarized, either pushed to the extreme left or extreme right. Not by conscious choice, but by the invisible hand of algorithmic design.

References

Akram, M., & Nasar, A. (2023). Systematic review of radicalization through social media. Ege Akademik Bakış (Ege Academic Review), 23(2), 279–296. https://doi.org/10.21121/eab.1166627

Digital Disruption Research Group. (n.d.). Digital Disruption Research Group. The University of Sydney. https://www.sydney.edu.au/business/our-research/research-groups/digital-disruption-research-group.html

Nawale, R. D., & Kumar, L. (2023). Exploring the impact of social media on the dynamics of news consumption: A study on its effectiveness. International Journal of Current Science, 13(2), 303–305. https://www.ijcspub.org/papers/IJCSP23B1040.pdf

Ravi, K., & Yuan, J.-S. (2024). Ideological orientation and extremism detection in online social networking sites: A systematic review. Intelligent Systems with Applications, 15, 200456. https://doi.org/10.1016/j.iswa.2024.200456

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The SaaS Paradox: From Yesterday´s Disruptors to Today´s Victims

11

September

2025

5/5 (1)

In the early 2000s, Salesforce revolutionized the software industry with the launch of its cloud-based CRM solution. Businesses started to swift from expensive on-premise installations of software programs to cloud-based systems with subscription models, later catalogued as Software as a Service (SaaS) companies. However, the market is in a completely different situation: Now we see that yesterday’s disruptors are being categorized as today´s incumbents. 

This market sentiment is demonstrated by the stock price of leading companies such as HubSpot, which is -28,32% YTD (Yahoo!Finance, 2025), Salesforce, which is -26,32% YTD (Yahoo!Finance, 2025), and Adobe, which is -21,35% YTD (Yahoo!Finance, 2025). This general stock downfall is partially driven by the statements of executives at, coincidentally, other technological companies. Charles Lamanna, Microsoft’s corporate vice president leading business applications and platforms, believes that SaaS companies will be replaced by AI business agents, which understand and adapt better to businesses’ needs without predefined systems and menus (Taft, 2025). Klarna’s CEO recently announced they got rid of over 1,200 software tools and built their own AI-powered system instead, making use of LLMs to reduce the data fragmentation (Klarna, 2025).

To respond to the current disruption generated by AI, SaaS companies are trying to fight back. In 2023, Salesforce announced the release of Einstein GPT, a generative AI for its CRM platform (Salesforce, 2023). In 2024, SalesForce unveiled AgentForce, a suite of autonomous AI agents (Salesforce, 2024). In the case of Adobe, they tried to acquire Figma in 2023, even though the deal was abandoned due to fears of anti-trust regulations (Peters, 2023). Earlier this year, they launched Adobe Marketing Agent and Adobe Express Agent to dive into the AI agent sector (Adobe, 2025). 

From your point of view, do you think that Software as a Service (SaaS) companies are going to be displaced by AI agents? Or is it just that SaaS companies have experienced excessive investor speculation, similar to the dot-com bubble? Are we reaching the consolidation phase?

References

Adobe. (2025, March 18). Adobe and Microsoft Empower Marketers with AI Agents in Microsoft 365 Copilot. Adobe Newsroom. Retrieved September 11, 2025, from https://news.adobe.com/news/2025/03/adobe-and-microsoft-empower-marketers-with-ai-agents-in-microsoft-365-copilot

Klarna. (2025, June 12). Klarna opens direct line to CEO Sebastian Siemiatkowski – powered by AI. Klarna. Retrieved September 11, 2025, from https://www.klarna.com/international/press/klarna-opens-direct-line-to-ceo-sebastian-siemiatkowski-powered-by-ai/

Peters, J. (2023, December 20). Adobe explains why it abandoned the Figma deal. The Verge. Retrieved September 11, 2025, from https://www.theverge.com/2023/12/20/24008189/adobe-figma-deal-eu-explained-decoder

Salesforce. (2023, March 7). Salesforce Announces Einstein GPT, the World’s First Generative AI for CRM. Salesforce. Retrieved September 11, 2025, from https://www.salesforce.com/news/press-releases/2023/03/07/einstein-generative-ai/

Salesforce. (2024, September 12). Salesforce Unveils Agentforce–What AI Was Meant to Be. Salesforce. Retrieved September 11, 2025, from https://www.salesforce.com/news/press-releases/2024/09/12/agentforce-announcement/

Taft, D. K. (2025, August 16). Microsoft: AI ‘Business Agents’ Will Kill SaaS by 2030. The New Stack. Retrieved September 11, 2025, from https://thenewstack.io/microsoft-ai-business-agents-will-kill-saas-by-2030/

Yahoo!Finance. (2025, August 12). HubSpot, Inc. (HUBS) Stock Price, News, Quote & History. Yahoo Finance. Retrieved September 11, 2025, from https://finance.yahoo.com/quote/HUBS/

Yahoo!Finance. (2025, September 11). Adobe Inc. (ADBE) Stock Price, News, Quote & History. Yahoo Finance. Retrieved September 11, 2025, from https://finance.yahoo.com/quote/ADBE/

Yahoo!Finance. (2025, September 11). Salesforce, Inc. (CRM) Stock Price, News, Quote & History. Yahoo Finance. Retrieved September 11, 2025, from https://finance.yahoo.com/quote/CRM/

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The destructive effects of generative AI

11

September

2025

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Recently, a tremendous shift in the use of technology has taken place. When ChatGPT was first introduced, people treated it as an interesting novelty that you could use to create entertaining content. However, as generative AI became increasingly advanced, people started using it for a broader spectrum of uses. (Liang et al., 2025) In this moment in time, an overwhelming number of people use generative AI daily. (Beshay & Beshay, 2025) While generative AI is technologically very exciting, I think we should all proceed with great caution and be more aware when we use it.

The first reason for this is the massive burden that generative AI imposes on the environment. The enormous number of resources it takes to maintain the status quo is immense. (Zhuk, 2023) In an era where we are already being challenged with environmental issues on many fronts, minimizing the impact of generative AI on the environment should prove to be significant, and compared to other environmental issues, an easy win. (Berthelot, Caron, Jay, & Lefèvre, 2024)

Not only are we suffering from the effects of generative AI on a global scale, but also in our personal lives. I think there would be great benefits in limiting our usage of generative AI. By using generative AI as a personal companion, we can lose touch with reality. (Fang et al., 2025) Generative AI tends to react in a way that validates whatever we say. (Sharma, Liao, & Xiao, 2024) So, if we are faced with different opinions in real life, a feeling of detachment can arise. (Idem.) In addition, there are more implications on a personal level, such as a negative impact on attention (Zhai et al., 2024).

While generative AI is a tool that can be very effective in a work environment, I think we should refrain from using it excessively. It is still a very novel technique, so long-term effects have not been studied yet. However, it is a fact that it impacts the environment negatively. I think it is also safe to say that not relying on generative AI too much will positively impact our brain health.

References:

Beshay, & Beshay. (2025, April 3). 1. Artificial intelligence in daily life: Views and experiences. Pew Research Center. https://www.pewresearch.org/internet/2025/04/03/artificial-intelligence-in-daily-life-views-and-experiences/

Berthelot, A., Caron, E., Jay, M., & Lefèvre, L. (2024). Estimating the environmental impact of Generative-AI services using an LCA-based methodology. Procedia CIRP, 122, 707–712. https://doi.org/10.1016/j.procir.2024.01.098

Fang, C. M., Liu, A. R., Danry, V., Lee, E., Chan, S. W. T., Pataranutaporn, P., Maes, P., Phang, J., Lampe, M., Ahmad, L., & Agarwal, S. (2025, March 21). How AI and human behaviors shape psychosocial effects of chatbot use: a longitudinal randomized controlled study. arXiv.org. https://arxiv.org/abs/2503.17473

Liang, W., Zhang, Y., Codreanu, M., Wang, J., Cao, H., & Zou, J. (2025, February 13). The widespread adoption of large language Model-Assisted writing across society. arXiv.org. https://arxiv.org/abs/2502.09747

Sharma, N., Liao, Q. V., & Xiao, Z. (2024). Generative Echo Chamber? Effect of LLM-Powered Search Systems on Diverse Information Seeking. Roceedings of the CHI Conference on Human Factors in Computing Systems (CHI ’24), 1–17. https://doi.org/10.1145/3613904.3642459

Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students’ cognitive abilities: a systematic review. Smart Learning Environments, 11(1). https://doi.org/10.1186/s40561-024-00316-7

Zhuk, A. (2023). Artificial intelligence impact on the environment: Hidden ecological costs and Ethical-Legal Issues. Journal of Digital Technologies and Law, 1(4), 932–954. https://doi.org/10.21202/jdtl.2023.40

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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.

• Grocery shopping & meal planning simplification:

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.

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.

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Unlocking Culinary Potential: How tasteTAILOR elevates your Cooking Experience with Generative AI

18

October

2024

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In today’s fast-paced world, health-conscious individuals and families often struggle to find the time and inspiration to cook nutritious meals. Therefore, we are presenting tasteTAILOR: a revolutionary digital culinary assistant that harnesses the power of Generative AI (GenAI) to streamline your cooking experience. It is designed to create recipes tailored to users’ diet choices, available ingredients, and kitchen appliances – offering a unique and personalized way of cooking. To streamline the cooking experience even further, tasteTAILOR seamlessly integrates its ingredient list with partner supermarkets. TasteTAILOR even offers a social community where users can share their experiences in the kitchen, get inspiration from other users, and connect with individuals with similar culinary interests.

Objectives and Value Proposition

TasteTAILOR’s most important objective is to grant customers the highest level of user satisfaction possible by making meal planning easy, seamless shopping through APIs, and engaging with the community through food recommendations powered by GenAI. Fundamentally, tasteTAILOR is committed to reducing food waste and fostering sustainable and healthy cooking with recipes to fit every taste.
We at tasteTAILOR present a multi-dimensional value proposition. We propose new dishes tailored to specific tastes but it will also generate shopping lists in supermarket applications in a hassle-free manner. Our customers can benefit from the step-by-step visual and audio instructions so that cooking can become enjoyable for everybody. The community feature provides an exciting way to connect with other like-minded culinary enthusiasts. 

Target Customer Segments

TasteTAILOR’s services are a perfect fit for several customer segments, for instance, busy professionals who have limited time to cook  but desire healthy recipes, students who are on an extremely tight budget and advanced hobby cooks who want to experiment with different types of cuisine and connect with other home cooks. The application also applies to people with special diet needs, making it the most suitable solution for those looking for a personalized cooking experience.

Key Activities and Resources

Key activities of tasteTAILOR include the design of customized recipes, using the power of GenAI technology. The personalization power comes from the analysis of user behavior, tracking one’s activity in the community, and through capturing user’s (daily) preferences.  Logically, the key resource of tasteTAILOR is the GenAI system that is woven throughout the entire business model, from generating recipes to chatbots intended for user interaction, and analytics that are inducted continuously for better personalization.

Challenges and Solutions

While the integration of GenAI offers significant benefits to the tasteTAILOR platform, it also comes with potential pitfalls, such as data privacy issues or technical glitches. The platform has taken stringent actions to consider these risks, implementing robust security measures and algorithm enhancement. The education of users through tutorials and community building is another crucial component in the adoption of AI-powered cooking solutions.

The Future of Meal Planning

Among the new generation of meal-planning applications and technological substitutions in a broader perspective, tasteTAILOR stands at the very top of elevating one’s cooking experience. TasteTAILOR offers personalized solutions that are not just tailored to the individual but are also ecologically-conscious. Taking everything into account, tasteTAILOR is not a meal planner; instead, it is a community-driven solution to empower its users to cook healthy recipes based on their own preferences. TasteTAILOR powered by GenAI is making cooking joyful.

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GenAI Video Clipping: Misinterpreting Context and (or) Going Viral

29

September

2024

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Generative AI (GenAI) tools can be increasingly observed within the video-clipping industry for the creation of short videos. GenAI video clipping tools like OpusClip gain increased importance for creators and clippers. Creators and video-clippers use platforms for short videos like TikTok or Instagram which are heavily consumed and favored by many young people to gain virality and revenue. OpusClip as an example allows a creator or individual to turn long videos into shorts within seconds. Next to the fact that the services from OpusClip are costly, one is only required to insert a link and gets multiple shorts of the related video within seconds. 

What particularly sparked my interest here is that OpusClip provides a virality score with the possibility of the short going viral, therefore predicting the popularity of the short. This means that the GenAI from OpusClip can identify potentially viral sequences of a video and recognize what humans might prefer to see. By this, creators as a result can specifically focus on uploading shorts with a high virality score to increase their revenue, virality, and consumer engagement within the comment section. Additionally, the short videos can be directly uploaded to several social media channels within Instagram, TikTok, or YouTube (OpusClip, 2024). With the functionality of GenAI video clipping tools, let us look at the challenges these bring. With the example of a 2-hour-long video interview, our GenAI video clipping tool OpusClip can identify appealing sequences and turn them into shorts. While creating the short, there is one important aspect missing, namely the ability to identify the complete context. Identifying potentially viral sequences is of high importance not only to create virality scores for shorts but also to grab the attention of the viewer. This can lead to the creation of shorts where context will be potentially misinterpreted by the viewer, but at least the virality score is high a creator might think. OpusClip identifies a sequence that might grab the viewers’ attention but potentially misses the message’s complete meaning. Another aspect that one misses in such shorts is the personalized touch of the creator, but will this be compensated with the productivity of the creator in terms of the number of uploaded shorts? I guess this depends on the consumer of the short and his relation to the creator. For creators, GenAI video clipping enhances consumer engagement under viral shorts and therefore can increase their reach, while saving time and increasing revenue (Blanc, n.d.). However, there is an existing risk that their initial message might be misinterpreted or out of context. 

References

Opus. (n.d.). OpusClip: Repurpose your long videos into viral clips. Opus. https://www.opus.pro/

Submagic. (n.d.). Opus Clip review: AI video repurposing made easy. Submagic. https://www.submagic.co/blog/opus-clip-review#:~:text=Opus%20Cip%20harnesses%20AI%20to,%2C%20TikTok%2C%20and%20Instagram%20Reels

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The Rise of AI in Fashion: How Artificial Intelligence is Transforming Design and Retail

27

September

2024

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AI in Fashion Design

Artificial Intelligence is transforming the fashion industry leading to innovations in both design and retail activities. AI revolutionizes how designers create, how trends are predicted and how retailers manage their stock and interact with consumers with the analysis of large datasets and automated processes (Luce, 2018). In this blog, we’ll explore how AI is being applied across various stages of the fashion ecosystem, from creative design to personalized shopping experiences.

Using AI, designers blend technology and creativity. Machine learning alogrithms allow designers to analyze historical trends, consumer preferences and data to generate new or innovative designs. Fashion houses like Alexander McQueen have begun to incorporate AI into their design processes. This allows for experimenting with new styles and materials (Renee, 2023). In addition, AI contributes to sustainable fashion by helping brands reduce waste and optimize material choices, and production processes.

Trend Forecasting with AI

Predicting fashion trends has traditionally been a complex and instinct-driven process, but AI is providing brands with more accurate and data-driven insights. Machine learning algorithms scan social media platforms, online influencers, and sales patterns to identify emerging trends. Companies like Heuritech use AI to analyze millions of images on Instagram to predict future fashion trends months ahead of time (Poncelin, 2024). Brands react more quickly to consumer demands, reduce overproduction and meet better the market expectations due to the advanced forecasting.

AI-Driven Inventory Management

Inventory management is another area where AI is making a significant impact. AI systems can process vast amounts of sales data, seasonal trends, and even weather forecasts in order to help retailers optimize stock levels. AI helps brands maintain the right balance between supply and demand so that the chances of overstocking or stockouts are significantly reduced. Major fashion retailers like Zara and H&M have embraced AI to manage their inventories which leads to more efficient supply chains and less waste (Ünal et al., 2023). Therefore, retailers can ensure that popular items remain available while minimizing markdowns and unsold inventory.

Personalized Shopping Experiences

AI is enhancing the shopping experience by providing personalized recommendations and services tailored to individual customers. Retailers like ASOS and Stitch Fix use AI-powered recommendation engines and virtual stylists to analyze customer preferences and browsing behaviors. That way they deliver product suggestions uniquely suited to each shopper’s style (Fix, 2023). This personalization simultaneously improves customer satisfaction and helps retailers build stronger customer loyalty and increase sales.

AI is transforming the fashion industry by bringing innovation to design, trend forecasting, inventory management, and retail experiences. Brands that adopt AI technologies are staying ahead of consumer demands and improving efficiency and sustainability. As AI continues to advance, its role in fashion will only expand and lead to shaping the future of the industry in innovative ways.

References:

  1. Luce, L. (2018). Artificial Intelligence for Fashion: How AI is Revolutionizing the Fashion Industry. https://link.springer.com/content/pdf/10.1007/978-1-4842-3931-5.pdf
  2. Renee, K. (2023, December 15). How Artificial Intelligence is Revolutionizing the Fashion Industry. RYN. https://www.therynapp.com/post/how-artificial-intelligence-is-revolutionizing-the-fashion-industry
  3. Poncelin, C. (2024, June 28). How Heuritech forecasts fashion trends thanks to AI. Heuritech. https://heuritech.com/articles/how-heuritech-forecasts-fashion-trends-thanks-to-artificial-intelligence/
  4. Ünal, Ö. A., Erkayman, B., & Usanmaz, B. (2023). Applications of Artificial Intelligence in Inventory Management: A Systematic Review of the literature. Archives of Computational Methods in Engineering. https://doi.org/10.1007/s11831-022-09879-5
  5. Fix, S. (2023, June 29). How We’re Revolutionizing Personal Styling with Generative AI – Stitch Fix Newsroom. Stitch Fix Newsroom. https://newsroom.stitchfix.com/blog/how-were-revolutionizing-personal-styling-with-generative-ai/

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Digital Disruption: How Robotaxis Are Shaping the Future of Taxi Market

20

September

2024

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Current state of robotaxis

Since Google began developing autonomous driving technology in 2012, we have witnessed rapid advancements in the field. In 2020, China’s Baidu launched its autonomous driving trials, further accelerating the technology’s progress. By 2021, both Cruise and Waymo began limited commercial operations in the U.S. As of May 2024, Baidu’s RobotGo has launched Robotaxis across major cities in China. In the first half of 2024, RobotGo completed 680,000 rides in Wuhan, reflecting the growing adoption of Robotaxis in China.

How does Robotaxis work?

  • Customer experience

The customer experience of using a Robotaxi can be described as exceptionally smooth. Users simply request a ride through an app, much like Uber, by entering their pick-up and drop-off locations. The Robotaxi autonomously drives to the pick-up point, and customers unlock the door using the app. Once inside, customers can confirm the driving route, adjust the temperature, and even play music. Upon reaching their destination, the fare is displayed, and after confirming the bill and making payment, the ride experience is complete.

  • Algorithms and technologies behind Robotaxis

Robotaxis use technology like LIDAR, cameras, radar, and AI to navigate and operate without a driver. These cars have sensors to see what’s around them, software to plan routes and avoid obstacles, and controls for steering and braking. These technologies use high-definition mapping and, in some cases, vehicle-to-everything (V2X) communication to exchange data with infrastructure and other vehicles.

There are two main types of Robotaxis. The first involves retrofitting existing vehicles with sensors and software. This method is faster and cheaper but may limit design effectiveness. The second approach involves building vehicles from scratch, optimized for autonomy with advanced sensors and no manual controls, but at a higher cost and longer production time.

Robotaxis companies currently hire safety supervisors to make sure customers are safe. In-vehicle safety operators monitor the vehicle’s autonomous systems and are trained to take control in emergencies. Some companies are also transitioning to remote supervision, where operators monitor and intervene from a control centre.

The Impact of Robotaxis on Passengers, Drivers, and the Automotive Industry

  • For passengers

Robotaxis affect passengers in many ways. Fares are typically 60-80% of what Uber charges, making it a cost-effective alternative. Robotaxis are safer, especially for women travelling late at night. They follow traffic laws, so there is less speeding and reckless overtaking. Robotaxis are also quiet and private, which is good for business people.

However, passengers have concerns too. Some people think Robotaxis drive slowly or don’t handle traffic well because they follow the rules too strictly. There are also privacy concerns. Robotaxis have so many sensors that may capture personal information, which raises questions about passenger privacy. They could also be vulnerable to hacking, which could compromise passenger safety. Additionally, in situations of sudden network failure, passengers worry about how the Robotaxi would respond, highlighting the need for robust backup systems.

  • For Taxi Drivers

For taxi drivers, Robotaxis pose significant challenges. Robotaxis compete directly for passengers, reducing the customer base for traditional taxi drivers. Sharing the road with Robotaxis also introduces complications. As Robotaxis strictly follow traffic rules, they often hesitate to turn, occupy lanes for long periods or change lanes slowly, all of which can disrupt the flow of traffic and reduce the driving efficiency of taxi drivers, causing frustration and delays.

However, the situation creates new opportunities as well. Companies such as Robotgo are hiring numerous remote supervisors, which could represent a new career path for taxi drivers whose roles may be taken over by Robotaxis.

  • For Car industry

The rise of Robotaxis is transforming the automotive industry by shifting consumer preference from car ownership to mobility services, resulting in a decline in traditional vehicle sales. Manufacturers are adapting by redesigning vehicles specifically for autonomy, eliminating traditional controls to enhance passenger comfort and safety. Additionally, significant investments in advanced technologies, such as AI and sensor integration, are necessary to remain competitive and ensure the safe operation of these vehicles. As these changes take place, the industry will focus on innovation and the evolution of urban mobility.

Conclusion

In my view, Robotaxis represent the future of the taxi industry. I would definitely try and choose to ride in a Robotaxi, as I can no longer tolerate rude, reckless drivers. While there are currently many safety and technical concerns, I believe that with improved industry regulations and advancements in technology, Robotaxis will become increasingly sophisticated—much like many new technologies that faced initial skepticism but later gained widespread acceptance.

So, what are your opinions? Would you choose to ride in a Robotaxi instead of an Uber? Feel free to share your opinions in the comments!

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Seamlessness between Digital Ecosystems comes at a Heavy Price

19

September

2024

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We are living in a generation that yearns for convenience. The same can be said about the digital ecosystems provided by notable tech giants—Google, Amazon, Meta, Apple, and Microsoft (GAMAM)—which have become indispensable parts of our day-to-day lives. For instance, Apple’s ability to facilitate cross-connectivity among all its products and Microsoft’s 365 suite providing strong SaaS-based tools for productivity are prime examples of how simple it has become to interact with technology.

However, the ease between platforms and software costs digital giants a fortune, leading to speculation from regulatory bodies over potential violations of antitrust laws. Firms like GAMAM often produce incremental advances within their established systems but refrain from investing in new, digitally disruptive innovations to protect their revenue streams and existing user base. This strategy of focusing on refinement rather than disruption allows them to maintain control over vast ecosystems, raising concerns about reduced competition. Maintaining market position is their main focus, which has eventually led to domination and possible violations of antitrust laws.

The Monopoly Moment: Redefinition of Tech Regulation

Monopolistic practices first came under major scrutiny in the 1990s when Microsoft faced antitrust accusations for bundling its Internet Explorer browser with the Windows operating system, effectively pushing out competitors like Netscape Navigator. This practice not only harmed rivals but also limited consumer choice. Although the court initially ruled to break up the company, the decision was overturned, resulting in a settlement that required Microsoft to share its software interfaces with third-party developers.

The verdict of this case revolutionized the public’s perception of the tech industry, prompting governments to take a closer look at antitrust investigations involving companies like Google and Apple. Dozens of cases have been filed against these giants over the past few years.

Living Under the Microscope

Monopolistic practices leading to scrutiny include Google’s default search engine deals, Amazon’s use of non-public seller data for competitive advantage, and Microsoft bundling Teams with Office. While these practices create a frictionless and predictable user experience, they also make it difficult for smaller players to compete and lead to a digital lock-in for consumers. This reduces the incentive for these firms to innovate and encourages them to acquire or push out smaller firms that pose a threat.

There is a fundamental tension between innovation, consumer convenience, and market control. This seamless ecosystem can be both a blessing and a curse. The more entrenched these ecosystems become, the more competition shrinks, and technological advancements stagnate.

The question we must ask ourselves is whether today’s seamlessness comes at the expense of tomorrow’s innovation.

Sources

  • Altchek, A., & Shamsian, J. (2024). Google’s monopoly drama should have Apple, Meta, and Amazon nervous. Retrieved from https://www.businessinsider.nl/googles-monopoly-drama-should-have-apple-meta-and-amazon-nervous/
  • Hills, C. (2023). Big Tech’s dominance over US stocks poses no risk according to history. Retrieved from https://www.tradealgo.com/news/big-techs-dominance-over-us-stocks-poses-no-risk-according-to-history
  • Podesta, A., & Tsoni, M. (2022). Antitrust: Commission accepts commitments by Amazon barring it from using marketplace seller data, and ensuring equal access to Buy Box and Prime. Retrieved from https://ec.europa.eu/commission/presscorner/detail/en/ip_22_7777 
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Can even the oldest industries be platformized? VonWood tries to disrupt the timber marketplace

18

September

2024

No ratings yet.

Two years ago I was asked by an acquaintance if I had time do a basic chore at his family member’s start-up. Some simple data entry work in Microsoft Excel. I agreed, and later that week found myself in a small office filled with three employees. Catalogs from Scandinavian sawmills were spread across the table. My task? Enter their product specifications into a spreadsheet. Their company was 2 months old, what exactly were they trying to do? Revolutionize one of the oldest existing industries; the timber industry.

The founders noticed a significant issue in the timber supply chain: numerous intermediaries, none of whom added real value. So, they created a platform to connect sawmills directly with customers—specifically, construction professionals. The model had clear potential: cutting out middlemen meant lower timber costs for buyers (provided they purchased in bulk), and sawmills could reach a broader customer base while offering lower prices, thereby boosting demand.

However, VonWood faces a familiar challenge for platform businesses—balancing supply and demand. While they’ve already raised €2.7 million in funding (VonWood, 2023), their key challenge is scaling both buyers and sawmills at the same pace. As more construction professionals use the platform, it becomes more attractive to sawmills, who can bypass middlemen. Yet, the platform must continue to offer enough variety and competitive pricing to entice new customers. Success hinges on achieving the network effects that fuel many platform businesses, but VonWood is still working toward that critical tipping point.

On the supply side, sawmills are intrigued by the platform’s potential to open new markets, but convincing them to join in significant numbers remains an ongoing effort. The founders emphasize that removing intermediaries not only makes timber more affordable but also makes pricing more transparent—a significant selling point. It is interesting to me – I would think to any BIM student – to keep track of their development. Even more so now that I learn more about information goods strategy. For instance, VonWood applied platform envelopment by partnering up with Finmid, a fintech company. This collaboration allows for the customers of the platforms to get access to financing for their timber (VonWood, n.d.)

The company adopts a transaction cut strategy, taking a small percentage from each sale. I figure the founders understand that pricing needs to remain competitive to gain traction. Charging too high a fee could deter early users, so the founders try to maintain a balance, working to encourage growth without sacrificing the platform’s financial sustainability. As the platform continues to grow, and demand-side economies of scale develop, the company can increase its fee accordingly.

VonWood remains in active pursuit of its ambitious vision: to revolutionize the timber trade by leveraging technology and platform dynamics. Although it has yet to reach the scale of a dominant marketplace, the foundation is being laid for a future where the platform can fully harness the power of network effects to transform an age-old industry

Sources

https://www.vonwood.com/nl/blog/collaboration-between-vonwood-and-finmid

https://www.vonwood.com/nl/blog/press-release-investment-announcement

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