Building Applications Has Become Easier Than Ever

10

October

2025

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A couple of months ago, a client at my student consultancy job asked us to automate a document anonymization process at their real estate agency. Due to data protection requirements, the processing had to be done locally or within their Microsoft environment.

After some unfruitful experimenting with Power Automate, we decided to give building our own tool with Claude (an LLM by Anthropic) a try. With a bachelor’s degree in international business, I had no coding knowledge whatsoever. The results were amazing. Within a few hours, we had some basic capabilities established.

After a while, I wanted to make the process more efficient than having to copy paste Claude’s changes into my project files. A new version, named Claude Code, had been released. It enables the AI to work in your project files directly. I had to watch a few tutorials and do some error-fixing with ChatGPT to get it to work in container (a sealed-off environment on my laptop). After about two hours we were ready to go.

The result was a developer working at lightning speed. It could code, test, readjust and retest until it works, all in one go. You see it break down the task into sub-tasks and tackle them one-by-one. Alternatively, you can put it in plan-mode so it will brainstorm about what you want, come up with multiple alternatives with pros and cons and execute one when you give the word. While it is executing that piece, you can open a second, third or fourth window to work on a different issue. You can quite literally run an entire team of coders at the same time, while you only manage them.

However, it’s not perfect. Especially fixing more complex bugs can be an issue. Sometimes, after showing the problem and asking for a solution several times, it won’t be able to fix it. Since I do not know anything about code myself, I had to be creative.

Firstly, working modularly helps you pinpoint the issue to a specific module. You can then ask Claude to zoom in on that module and come up with possible causes. With just logic you can often judge its suggestions. That way you can help Claude get closer to fixing the issue.

Sometimes, it gets stuck in a certain thinking path it has gone down. In that case, it can help to get a second opinion. You open a second window or ask a different LLM (e.g. ChatGPT) to look at the issue. This way it is not biased by the context in your current conversation or its LLM specific knowledge. This has more than once resulted in it immediately recognizing the real issue, and me being frustrated with the fact that I spent half an hour trying to fix it in the initial chat.

All in all, I was really amazed with the possibilities. Getting it all set up was a bit of trial and error, and it takes quite some time to brainstorm about the implications of architectural choices. But once you have done that, it builds full-fledged applications in minutes.

New AI tools are being released quicker than we can learn to use them, so adaptability seems more important than ever. Just being able to build applications is not enough either. Just like before coding became so much easier, you need a business case for the application too. All in all, I think it’s a great time to be a business student with an interest in technology.

To anyone else who has been experimenting with AI tools for coding: what tools do you use and what best practices have you discovered?

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Do We Think Less When AI Thinks for Us?

25

September

2025

5/5 (2)

Generative AI: From Helper to Thought Partner?

The first time I heard of an generative AI tool was in my exchange semester in Budapest. A fellow student introduced Chat GPT to me and it felt almost like magic. My fellow student asked ChatGPT to summarize a research article I had been struggling with, and within seconds I had a clear overview. It would have taken me at least an hour. I used it for a few weeks and introduced it to some of my other friends who were amazed aswell. Since then, I have experimented with different tools: text-to-text models like ChatGPT for writing support and easy explanations of difficult exercises, and text-to-image models like DALL·E or MidJourney for creating visuals in presentations.

The most remarkable aspects are the speed and inspiration these tools offer. When preparing for group projects for example, I used ChatGPT to brainstorm as an example to give me an outline for a digital strategie for a company. The ideas weren’t perfect, but they helped my group to get started much faster. In addition to that, image generators helped us visualize concepts that would have been difficult to explain with words alone. In this sense, GenAI acts like an assistant that can take on many tasks and implement them super quickly.

At the same time, the limitations are quite obvious. The quality of the results varies often, the information is sometimes outdated or simply incorrect. I have also found that relying too heavily on AI can affect my own critical thinking, as I am sometimes tempted to accept the first answer rather than question it.

In the future, I would like to see improvements in two areas. First, better integration of reliable sources (imagine if ChatGPT could always generate citations in APA style correctly) and more transparency about how answers are generated and where the information comes from.

How about you? Do you use GenAI more as a brainstorming tool, or do you rely on it for polished results? And should universities encourage students to use these tools  or restrict them to protect independent thinking?

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AI in Housing Valuations: Make it explainable

19

September

2025

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AI can now help to set property values. What are the risks involved?

I came across this paper called Enhancing Explainable AI Land Valuations Reporting for Consistency, Objectivity, and Transparency. By Y. Yim and C. Shing (2025). The paper goes into detail on how explainable AI can ethically support the valuation of properties. This is a sensitive topic, since the valuation of properties affects many parties, like banks, buyers, sellers and the cities. There are major efficiency gains to be made by implementing artificial intelligence and machine learning in this sector. However, their integration also raises legal and ethical questions.

The Core problem

Many models act like a black box; this undermines the duty of the valuer to deliver transparent and consistent valuations. The legal system requires the properties to be thoroughly inspected. and the process to be well-documented.

A possible solution: Making AI explain itself

There are 3 pillars to ethically implement these innovations while integrating these technologies. Consistency: The model should provide repeatable results, following the same process. Objectivity: There should be a clear separation between the developers and validators of a model. Transparency: the model, data and limits should be well documented and easy to understand.

XAI tools like SHAP can be used to make the AI explain itself. These tools show how each feature/variable pushes the price up or down. The chart shown below ranks drivers such as zoning, building age, and floor area. This turns a score into a story that a client can follow.

“The visualisation sets a foundational baseline value (E[f(X)]) of 13.98 on the x-axis, representing the model’s average prediction when no specific feature information is provided. This is the expected value if we were to make a prediction without any additional information. The Output Value (f(x)), which in this instance is 14.07, reflects the actual prediction after accounting for the cumulative effect of the individual features. The colour-coded bars represent the push and pull of each feature on the prediction: the red bars show the features that contribute to an increase in the predicted land value, while the blue bars indicate a decrease.“

Takeaway

AI can increase efficiency and scale valuations. But it must earn trust. Build on three pillars: consistency, objectivity, and transparency. Use SHAP for explanations. Ship reports with a clear checklist and keep human judgement in charge.


References:
Yiu CY, Cheung KS. Enhancing explainable AI land valuations reporting for consistency, objectivity, and transparency. Land. 2025;14(5):927. https://www.proquest.com/scholarly-journals/enhancing-explainable-ai-land-valuations/docview/3212060417/se-2. doi: https://doi.org/10.3390/land14050927.

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Who Will Own TikTok? What the U.S.–China Deal Teaches Us About Platforms and Competition

18

September

2025

5/5 (1)

Context

Back in 2020, President Donald Trump announced the plans to ban TikTok in the United States. At the same time, the justification was national security concerns over the potential access of data by the Chinese government through TikTok’s parent company, ByteDance. The ban was never materialized, but it marked the first moment when a social media app became the center of a geographical standoff. Fast forward to today, with Trump now back in power, he is once again pushing for a “solution”. This time, according to CNN News, the proposed deal with Chinese President Xi is that the majority of the shares would be transferred to the American investors, like Oracle, while ByteDance would only retain a minority stake. The arrangement is meant to resolve concerns without killing the app that has 139 million active American users (Castmagic, 2025)

But, as U.S. Treasury Secretary Scott Bessent revealed this week, China was clearly not in favor of the “deal” and resisted giving up control of such a valuable platform. According to Bessent:

“What turned the tide was a call that Ambassador Jamieson Greer and I had with President Trump the night after the first day of negotiations, and President Trump made it clear that he would be willing to let TikTok go dark,” Bessent told CNBC on Tuesday.

In other words, the threat of a complete shutdown forced China back to the table and created a path for the current ownership deal, which is going to be announced in the coming weeks.

Comparison with TikTok vs. Kwai

This global drama reminds me of the case we studied in class about Douyin (Chinese TikTok) versus Kuaishou (Kwai) in China. Both platforms benefited from strong network effects: more content creators attracting more viewers, which attracted even more creators, reinforcing a positive feedback loop. But the competition also showed how differentiation matters. TikTok is relying on its recommendation algorithm and global expansion, while Kwai has built more community-driven interactions and is turning its focus to lower-tier Chinese regions. That rivalry was shaped by market forces and strategy. In the U.S., TikTok’s rivalry is not with another substitute app, instead, it is with the government itself. Here, geopolitics has become the real “competitor” reshaping the platform’s future.

Further Discussion

My personal opinion regarding this geopolitical tension between China and US is balanced. While the new deal may reduce the immediate tensions, it does not fully solve the deeper issue below the surface. The algorithm that drives TikTok’s content is still developing in China and liscensed out, which means concerns about influence and data insecurity won’t simply vanish in America or any parts of the world. Meanwhile, splitting ownership or separating TikTok and Douyin could reduce TikTok’s innovation cycle since ByteDance is no longer involved or barely involved, this could give more rooms for rivals to grow and expand.

What I found most intriguing is whether this U.S.-China split will create a two-parallel TikTok and Douyin world, similar to how TikTok and Kwai co-exist in China. Could the US-owned TikTok evolve differently from Douyin in China, with separate features, rules, and communities? Or will this separation weaken TikTok’s vision, strategies, reputation, network effects, and so on until the point where potential competitors (e.g. RedNotes) finally catch up and replace it?

References

Castmagic. (2025). TikTok Users by Country in 2025: Global Stats & Rankings. Castmagic.io. https://www.castmagic.io/post/tiktok-usage-by-country#which-country-has-the-most-tiktok-users

Treene, A., & Goldman, D. (2025, September 16). We now know who the new owners of TikTok will be – if Trump gets his deal done with Xi. CNN. https://edition.cnn.com/2025/09/16/tech/tiktok-ban-extension-trump

Imran Rahman-Jones. (2025b, September 16). TikTok to stay in the US as Donald Trump says deal is done. BBC. http://www.bbc.com/news/articles/c7847q9xvwgo

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Meta’s Ray-Ban Glasses Just Levelled Up

18

September

2025

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———-

Do you remember Meta’s Ray-Ban glasses from 2023? You probably do (since we just mentioned them in class), but they weren’t exactly ground-breaking. But on September 30th, the second generation is being released, and this time the air smells different.

This iteration of the Meta Ray-Ban Display features an in-lens display visible only to the wearer, marking a significant step toward AR technology. While it isn’t true Augmented Reality yet, since the display doesn’t interact with your surroundings, this is a sign that the technology is rapidly advancing in that direction. More interesting is how you control it. The glasses connect to a neural wristband, a watch-style band that detects electrical impulses from your wrist muscles. This means you can control the display with subtle gestures, even from inside your pocket, unlike older camera-based tracking systems.

But is this truly disruptive? Not yet. At $800, it’s positioned like a flagship phone, but still lacks a broad app ecosystem. There is also a social barrier: are people willing to accept chunky glasses and an always-ready camera in shared spaces? Secondly, Meta´s reputation is fragile when it comes to trust and privacy. Clear recording indicators, strict on-device processing, and transparent data will matter just as much as the spec sheets. Also, the possibility of ads or brand placements drifting into your field of view is non-zero. One thing is sure, stronger privacy regulation will be crucial.

If those concerns are addressed, the upside is real: live captioning and translation, live guided navigation, quick capture and messaging, all controlled with a flick of fingers from a pocket.

But your phone can breathe a sigh of relief…

(for now)

References:

https://www.meta.com/nl/en/ai-glasses/meta-ray-ban-display

https://www.theguardian.com/technology/2025/sep/17/meta-ray-ban-smart-glasses

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AI use in Government

18

September

2025

5/5 (2)

Last week, while reading the news, one article in particular got my attention. I stumbled upon the following article, ‘Albania makes AI minister of contracts in battle against corruption‘ (Article is in Dutch). In short, the Albanian government has decided to make one of its ministers an AI agent, visualized by a woman called Diella in traditional Albanian clothing, to battle the widespread corruption in the country. The main reason would be that Diella would not be tempted by bribes, scared by threats, or have any conflicts of interest. Diella would be totally objective when deciding which firms get government contracts.

I think this is an interesting strategy to avoid corruption, but I did immediately identify some glaring issues. My main concern was who the person responsible for the AI’s ministry would be, whether there would still be a human overseeing its operations, or whether the AI would be the highest in command. It highlights a new ethical issue: can AI be held accountable for its own actions? Ministers should be held accountable for any mistakes and issues that occur under their management, but can we hold a bot to the same standards, and if not, can we still allow AI to be in such important positions without any accountability? I think this dilemma of responsible usage of, and even substitution by, AI will be an incredibly important topic in this age of unprecedented digital disruption.

The premier of Albania, Edi Rama, also did not provide any details about how the AI will be trained and how potential bias in its training and oversight will be mitigated.

I think that the lack of transparency and accountability, at least up until now, could actually lead to better disguised corruption, hidden by a cloak of in-depth technological know-how, that only a few people will be able to understand and dissect. The public will no longer be able to easily understand the decision-making process behind government contracts worth millions. 

I would love to hear your thoughts about the accountability of AI and the effect of an AI minister on corruption in the government. Let’s discuss!

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Russia’s CyberWarfare on Europe: Why Cybersecurity improvements are imperative

17

September

2025

5/5 (2)

Russian hackers breached a Norwegian dam earlier this April, taking control of its operation for over 4 hours before detection. They opened a floodgate, releasing water at over 500 liters per second. (Bryant, 2025)

Even though damage was limited, this cyberattack, like many others, serves as a tool to spread fear and chaos among populations. These aggressive operations have expanded from espionage or political coercion to vital infrastructures across industries. 

Norway’s dam was not energy-producing; it was used for fish farming. This matters because Europe’s lifeline infrastructure is based on dams, hydropower stations, and energy systems. By manipulating even a small dam, Russia exposed weakness, signaling: ‘We can reach your energy systems too.’ 

Just yesterday, hackers targeted hospitals and urban water supplies in one of Poland’s largest cities. Dariusz Standerski, deputy minister for digital affairs, confirmed that the government is allocating €80mn this month to strengthen the cyber defenses of water management systems (Milne, 2025).

Beyond physical damage, Russian cyberattacks also aim at eroding trust in government. Liverpool City Council has revealed that, for the past two years, its IT infrastructure has been under relentless attack from the Russian state-funded group Noname057(16). Several other UK councils have faced similar assaults during the same period. (Waddington, 2025)

These incidents highlight a broader truth: cyberwarfare represents digital disruption in its most dangerous form (Weill & Woerner, 2015). Europe’s safety is now threatened by its digital vulnerabilities, and thus the bloc needs a swift response. AI-driven monitoring and anomaly detection offer ways to anticipate and neutralize attacks in real time (Zhao et al., 2023; Li, 2023). Moreover, as Furr & Shipilov (2019) argue, building resilience does not require disruption; it can come from incremental adaptation. Europe should add layers of protective systems over its old infrastructure without crippling operations (Birkinshaw & Lancefield, 2023). 

In practice, Europe must move past reactive spending and focus on building a reliable, AI-integrated cybersecurity strategy across vital infrastructure. The battleground is no longer just physical or near the Russian border. It is increasingly digital and affects everyday lives across the continent. 

This raises the question: Should cybersecurity be treated as a matter of national defense, or as an EU-wide responsibility shared across borders?

Sources:

  • Bryant, M. (2025, August 15). Russian hackers seized control of Norwegian dam, spy chief says. The Guardian. https://www.theguardian.com/world/2025/aug/14/russian-hackers-control-norwegian-dam-norway
  • Birkinshaw, J., & Lancefield, D. (2023). How professional services firms dodged disruption. MIT Sloan Management Review, 64(4), 34–39. 
  • Furr, N., & Shipilov, A. (2019). Digital doesn’t have to be disruptive: The best results can come from adaptation rather than reinvention. Harvard Business Review, 97(4), 94–104. 
  • Milne, R. (2025, September 12). Russian hackers target Polish hospitals and city water supply. Financial Times. https://www.ft.com/content/3e7c7a96-09e7-407f-98d7-a29310743d28 
  • Waddington, M. (2025, September 17). Liverpool City Council under “increasing” Russian hack bot attack. https://www.bbc.com/news/articles/cgj18z99dx0o
  • Weill, P., & Woerner, S. L. (2015). Thriving in an increasingly digital ecosystem. MIT Sloan Management Review, 56(4), 27–34. 
  • Zhao, W. X., Zhou, K., Li, J., Tang, T., Wang, X., Hou, Y., Min, Y., Zhang, B., Zhang, J., Dong, Z., & Du, Y. (2023). A survey of large language models. arXiv preprint arXiv:2303.18223. https://doi.org/10.48550/arXiv.2303.18223

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Unicorn Status App that Empowers Women’s Health

15

September

2025

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The other day, I was astounded by Dr. Stacy Sims’ findings, which she shared on Steven Bartler’s podcast (“The Diary of a CEO”, 2025). She advised women to stop attempting to follow men’s exercise and nutrition research and instead learn about the length, common symptoms, emotional imbalance, energy levels, and even body temperature connected with each of their “seasons”. This would enable the development of a suitable training plan, as well as the provision of suitable food, to achieve peak performance while avoiding overload and exhaustion.

Yet, how does one get the knowledge and support needed to gain a better understanding of their own cycle?

In 2015, Dmitry and Yuri Gurski from Belarus focused on a big, underserved market with minimal competition and created Flo, a disruptive app that used predictive technology, data analytics ,and AI to guide women’s reproductive and general wellness (Olabinjo, 2024). Today, this all-in-all tracker with its engaging interface and personalized features is an absolute industry leader with 45 million active users worldwide. In 2022, the company expanded into B2B, catering to businesses looking to educate and empower their female employees through data-powered features like Health Insights, Health reports, and an AI symptom assistant (Flo, 2022). 

Established as an omnichannel digital business model, Flo’s architecture produces significant value for users while concentrating on retention loops. The data gathering process begins with the first login, and with each subsequent data input, the predictions get more accurate, encouraging better customization and helping the user to achieve their goals faster. Retention is an important KPI for apps. Aside from great personalization, Flo used various additional strategic techniques to retain customers. For example, messages with data logging reminders or heads-ups for impending activities that are scheduled with predefined intervals. Furthermore, the software developers continuously offered and introduced additional value-generating features such as Secret Chats (a place to secretly discuss private matters) and Flo Stories (identical to Instagram Stories).

Personally, I’ve been a long-time user of the app and have seen how quickly it has evolved and expanded, thanks not just to the seamlessly integrated customer experience, but also to community-building activities, strong privacy, and evidence-based insights.

Nevertheless, despite this nearly flawless success story of a unique and well-executed niche-market company idea, the road is not always lined with roses. In the backdrop of multiple challenges with data monetization posed by the launch of the decentralized Web 2.0, which began a year before Flo’s establishment (Harvard Business Review, 2022), the company recently got involved in a big public controversy concerning selling personal data to Meta for targeted advertisements without user consent (Sifted, 2025). This demonstrates how important it is for any fast-paced, disruptive company to constantly maintain control of its processes and ensure data protection at all costs before losing its established competitive advantage.

List of References:

The Diary of a CEO, 2025 Exercise & Nutrition Scientist: The Truth About Exercise On Your Period! Take These 4 Supplements!,

Flo, 2022, Flo Health Launches Flo for Business, An Inclusive Approach to Women’s Health for Employees Available at: https://flo.health/newsroom/flo-for-business-launch (Accessed 13 September 2025).

Harvard Business Review, 2022, What Is Web3? Available at: https://hbr.org/2022/05/what-is-web3 (Accessed 15 September 2025).

Olabinjo, A., 2024, Flo Growth Case Study: How This Women’s Health App Became A Unicorn Available at: https://growthcasestudies.com/p/flo-growth-case-study (Accessed 13 September 2025).

Sifted, 2025, Flo Health faces multi-billion dollar lawsuit over claims it unlawfully shared data with Meta Available at: https://sifted.eu/articles/flo-health-meta-court-case-privacy/ (Accessed 15 September 2025).

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Does Easy-To-Use Local Image Generation AI Applications Have Commercial Potential?

10

October

2024

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There are many AI applications for image generation, but many of them are based on the Internet and the cloud, and are charged by subscription or based on the number of times used. Unlike these, Stable Diffusion WebUI, as an open source and free image generation tool, has attracted widespread attention with its powerful capabilities. However, it also has a relatively high threshold for use. Based on my experience in using Stable Diffusion WebUI, I will briefly talk about the potential commercial prospects of low-threshold, easy-to-use local image generation AI applications.

Advantages of Stable Diffusion WebUI

The advantage of Stable Diffusion WebUI is not only that it is completely open source and free, but also that its model is deployed locally (that is, similar to the end-side AI mentioned at the iPhone16 conference). Since it runs directly on local hardware, it does not need to upload any data to the cloud. This means that users can fully call on the computing resources of their own devices without connecting to the network.
Compared with cloud applications such as MidJourney, the protection of data privacy is a major advantage of local applications. Neither the user’s input nor the generated images are uploaded to the server, but are processed locally, which is suitable for users who are sensitive to data security and privacy.
At the same time, because it runs on local hardware, its performance can be very high. It can flexibly call on the computing power of a high-end GPU, which is especially suitable for users with high performance hardware. It is not affected by network bandwidth and gives full play to its powerful image generation capabilities. All this makes it an extremely excellent tool.

The Threshold of Using Stable Diffusion WebUI

Although Stable Diffusion WebUI is powerful, its threshold of use also makes many ordinary users discouraged. This is my personal experience in installation, model import and debugging parameters.
First of all, the installation and operation process is relatively complicated. You need to download tools and deal with many environmental dependencies, such as Python and other necessary libraries. These steps are relatively complicated for many new users. Without the help of various forums, blogs and GPT, I would definitely not be able to do it.
In addition, the selection and import of models is also a big challenge. Although there are a large number of free model resources on the Internet, it is not easy to find a model that suits your needs. It will also take a lot of time to choose the SORA model. In the end, you need to adjust many parameters including the number of steps, sampling method, and resolution by yourself to achieve the desired effect. Its complexity also makes it difficult for users to control.

Civitai – A platform for sharing, discovering and downloading Stable Diffusion models and AI painting creation resources

Launch Simple Applications to Attract More Users

If we can launch a simpler and easier-to-use app based on Stable Diffusion WebUI, which is aimed at the consumer market and the general public, we will be able to push it to a wider market.
The key is to lower the threshold for use. By integrating environmental dependencies, such as pre-installing all necessary libraries and operating environments, users can skip the configuration process. The application can also provide a one-click model download and purchase channel to help users quickly obtain high-quality generated models.
At the same time, user-friendly interface design is also essential. While following various interactive design principles, optimize UI and UX, and simplify complex parameter adjustments into several key options. Let ordinary users easily generate the pictures they want without losing flexibility. For example, users can control the quality and style of the generated pictures through simple sliders or preset modes, avoiding complex technical details.

Commercial Potential

From a commercial perspective, local image generation applications based on Stable Diffusion WebUI have broad prospects.
The use of Stable Diffusion WebUI not only avoids the occupation of cloud resources, but also makes pricing more flexible. Compared with the payment model of conventional online image generation AI such as MidJourney, Stable Diffusion’s local application can adopt a variety of pricing strategies, such as buying out software, paying for advanced models, or allowing users to use the generation service unlimited times within a certain period of time through a subscription system.
Overall, through the simplified operation experience and flexible and low pricing, we may be able to build an “unpopular” image generation AI application based on the Stable Diffusion WebUI, attracting a wide audience and looking forward to its large-scale application.

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Law & Order & AI – How Californias Bill SB1047 will impact AI development in the USA

27

September

2024

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The USA are often praised for their openness to innovation, while the EU is seen as lagging behind. But there is one aspect where the USA are now following the EU: AI regulation. In this blogpost I will discuss the Californian Bill “SB 1047: Safe and Secure Innovation for Frontier Artificial Intelligence Models Act” which currently awaits ratification by the Governor of California. (California Legislative Information, 2024)

While not yet enacted, the EU has created one of the most far reaching efforts in the world to regulate AI with the Artificial Intelligence Act (AI Act). As we had discussed in class the AI Act focusses on different aspects such as a risk-based framework, accountability and transparency, governance, and human rights. (European Parliament, 2023)

How does the SB 1047 compare? First off, it is important to note that the Bill would only be turned into law in California. Nonetheless, this more or less means a nationwide application since most affected companies are based in Silicon Valley, California.

SB 1047 focusses on a few different aspects, I have highlighted the ones I think are most far reaching:

  1. Developers must implement controls to prevent the model from causing “critical harm”
  2. Developers must provide a written and separate safety and security protocol
  3. Developers must include a “kill switch” through which a full shutdown can be enacted
  4. Developers will have to have their models be tested, assessed, and regularly audited. (Gibson Dunn, 2024)

Like the AI Act, SB 1047 would focus on high-risk, high-impact AI models, while focusing on safety and security of the people impacted by AI.

But why would you care? Will this even affect everyday people? Isn’t this just stifling innovation and risking loss of competitive advantage?
Before you jump to the comments let me first highlight one of the bills supporters – Elon Musk. On his platform X, Musk has posted about his support for the bill, stating that AI should be regulated like “any product/technology that is a potential risk to the public” (Tan, 2024) I don’t often align with Musk’s views, but I really agree with this stance on regulation!

Screenshot of Musks Tweet suppporting the SB1047 bill.

Why should we let AI and its development stay completely unchecked but still use it for vital parts of our daily life? Why should we not want to know how AI works beneath the engine? Time and time again, history has taught us that leaving big systems unchecked because they were deemed “too complex” or because we trusted the people who run them to do so in the best interest of the public, does not always lead to the desired outcomes.
From job applications, health, safety, to privacy we already use AI in most aspects of life. I, for one, do not want these parts of my life to be guided by the ethics (or maybe lack thereof) of individuals. I want there to be clear legislature and a framework in place to guide the future development of AI. Because even though most people might not clearly see how their life is (beneficially) impacted by AI currently, I don’t want anyone to ever experience how AI might detrimentally impact their life.

Resources used:

California Legislative Information. (2024, September 3). Senate Bill No. 1047: Safe and Secure Innovation for Frontier Artificial Intelligence Models Act. California Legislature. https://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=202320240SB1047

European Parliament. (2023, June 1). EU AI Act: First regulation on artificial intelligence. European Parliament News. https://www.europarl.europa.eu/topics/en/article/20230601STO93804/eu-ai-act-first-regulation-on-artificial-intelligence

Gibson Dunn (2024, September 24). Regulating the Future: Eight Key Takeaways from California’s SB 1047, Pending with Governor Newsom. Gibson Dunn. https://www.gibsondunn.com/regulating-the-future-eight-key-takeaways-from-california-sb-1047-pending-with-governor-newsom/

Musk, E. [@elonmusk]. (2024, September 15). AI should be regulated like any product/technology that is a potential risk to the public [Tweet]. Twitter. https://x.com/elonmusk/status/1828205685386936567?ref_src=twsrc%5Etfw%7Ctwcamp%5Etweetembed%7Ctwterm%5E1828205685386936567%7Ctwgr%5Eb0d709a708c02735de6f79bae39d6c06261b27d9%7Ctwcon%5Es1_&ref_url=https%3A%2F%2Fwww.businessinsider.nl%2Felon-musk-says-hes-backing-californias-controversial-ai-bill%2F

Tan, K. W. K. (2024, 27 augustus). Elon Musk says he’s backing California’s controversial AI bill. Business Insider Nederland. https://www.businessinsider.nl/elon-musk-says-hes-backing-californias-controversial-ai-bill/

The Image set as the featured image was generated by ChatGPT

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