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 IEEE109(3), 247-278.

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AI-Powered Learning: My Adventure with TutorAI

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October

2023

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Weapons of mass destruction – why Uncle Sam wants you.

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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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“Let me see you cards” say the Fin-Techs; what PSD2 is doing to let the Fin-Techs win

8

October

2021

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EU’s first Payment Services Directive (PSD1), initialised in 2009 in order to increase market competition and transparency in the EU market. It gave an entrance to Fin-Tech companies to be included in the financial services branch by being bale to enter the payments market and carrying out financial transactions. Most importantly, PSD1 allowed the Fin-Tech firms to be able to see all the information such as services and fees, including maximum payment execution times and so on. Following PSD1, PSD 2 was created in order to facilitate “open banking” which also breaks up banks information monopoly forcing them to reveal even more customer payment data. However, these initiatives bring a huge advantage to the Fin-Tech industry. However what are the potential dangers of this?

The Fin-Tech industry is of absence of multiple regulations. Banks as an example have multiple; Basel I, Basel II, Basel III and even SIFIs. Thus banks are very well regulated and will prevent any default however the regulations do limit them. Additionally, Fin-tech companies’ have an technological structure, thus are able to get more big data in general, thus are already held at an informational advantage over banks. Another problem with Fin-Techs such as peer-to-peer lending to cryptocurrencies is that the credit risk can be very high. Due to the fact that the borrowers have low credit ratings or lack of credit history, will not give them access to apply for a conventional loan. Furthermore, the riskiness is also on the lender in the case of peer-lending, as there are limited insurance or government protection in the case that the borrower defaults. However, both of these risks are in the hands of the borrower and lender, but not to the platform.

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The shared e-scooter war in Rotterdam

8

October

2020

No ratings yet. Rotterdam is the main Dutch battleground for shared e-scooter companies. In this blog I’ll explain how these companies try to gain a foothold and the characteristics of the local market. Last, you get some tips for testing them yourself.

But first, how did it start? In 2018, the start-up Felyx was the first to arrive in the city. The founders weren’t unfamiliar with Rotterdam as one of them is a former EUR student. The business concept was born when driving a car2go in Amsterdam. However, a car in the big city is far from the fastest way to move around. The scooter is. To get a municipality like Rotterdam on board there needed to be something in it for them, too. The e-scooter was the answer as it isn’t loud and locally polluting (Hollingsworth, J., Copeland, B. and Johnson, J.X., 2019). The sharing functions are enabled by IoT technology.

Soon there were hundreds of free-floating scooters to be found all around the city. At first, students were the main target group later expanding into young professionals and freelancers as well (Top of Minds. 2020). The new concept was mainly appealing as it was fun to drive the scooters, but customers soon identified improved convenience and freedom of this transport mode in comparison with their own bike. In that way it is surprising that this concept can be successful in a biking country like The Netherlands.
Fast forwarding to now, there are yet two companies that have joined Felyx in Rotterdam: Check and GoSharing. They all have different ways in which they try to lure you to their platform. Felyx has the advantage of being the incumbent with Felyx being an acronym for e-scooter. They leverage this by charging a relatively high per-minute fee and no staring fee. GoSharing uses volume deals to get you addicted to scooter sharing. Starting with an average per-minute fee when using the scooters without a deal but getting pretty cheap when you buy large minute packages. They limit the amount of free minutes when joining the platform. Check did exactly the opposite by rampaging into Rotterdam with a low per-minute fee, no starting fee and 15 euros of worth of riding for free.

The market-entry tactics have led to a strange dynamic in this market. Felyx is going reasonably steady as they haven’t performed stunts to gain market share at any time. At Check, this is a different story: their market-entry tactics have lead to giving out so many free minutes of riding that it took them months to boost revenues. The upside is a considerable gain in the number of users. The upcoming months will tell if they can retain them now that riding is not free and a starting fee is introduced. GoSharing is found to compete less on price. What they are doing is connecting edge cities and suburban areas of Rotterdam by creating service areas in villages. Commuters are able to pick scooters up close to home and drop them in the city centre. At the end of the day they can find an available scooter again to travel back.

Time will tell whether this is a winner takes all market, like many recently disrupted markets are. In the meantime all of the providers have found investors with deep pockets, currently favoring the consumer. I think there will be space for multiple providers. Furthermore, I believe that the most important aspect is the availability of scooters in the right places at the right time and second is the ease of combining trips with other transport modes such as the subway.

Are you interested in trying one of these services out? Get some free riding minutes with Check promocode MMN-GN4, Felyx code RSqGv8CW or GoSharing code XZ26IZ.

If you’re already using shared e-scooters in Rotterdam I’m looking forward to hearing from you in the comments. Which provider do you like and why? And do you think the market will eventually head towards a monopoly or will there be space for 3 or more providers in the future?

References:
Hollingsworth, J., Copeland, B. and Johnson, J.X., 2019. Are e-scooters polluters? The environmental impacts of shared dockless electric scooters. Environmental Research Letters, 14(8), p.084031.

Top of Minds. 2020. Carrière Advies Van Quinten Selhorst En Maarten Poot | Top Of Minds. [online] Available at: [Accessed 8 October 2020].

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0 to 60 mph in 1.9 seconds: The Tesla Roadster.

8

October

2020

The pinnacle of electrification of cars.
As the successor to the first production car of Tesla, which was the 2008 Roadster, the development of the new Tesla Roadster was announced by Tesla CEO Elon Musk in November 2017.

TeslaRoadster2

The fully electric vehicle is said to be released after the release of the renewed Model S, currently Tesla’s most famous model car. Tesla promises a 0-60 of 1.9 seconds with a top speed over 250 mph (400 km/h). The Roadster would be capable of such incredible performance figures due to its staggering 10,000 Nm of torque and all-wheel drive system. This would make the Tesla Roadster the fastest car in the world.

The Roadster would break all records for acceleration and performance compared to traditional super cars with combustion engines. With an expected range of 1,000 km, the range for electric vehicles would be greatly outperformed. Currently, this record is also held by Tesla, with the Tesla Model Y which has a range of 508 km. This is the most interesting point to me. Although the Tesla Roadster might look like an electric toy for rich people, in reality, I think the Tesla Roadster will achieve 2 things that are very important in our search for a sustainable future.

The 2 reasons:
1. Just like with their Model S, the Tesla Roadster will make electric vehicles more appealing. Before the introduction of the Model S, electric vehicles were mostly low performance cars with boring designs. The segment was mainly intended for early adopters: drivers with a strong interest in sustainability and wanting to compromise on performance and design, in return for a more eco-friendly footprint with regards to their driving. After the Model S took the market by storm, the image of electric vehicles was completely changed. No longer where electric cars associated with compromising performance and boring designs. Instead, Tesla made electric vehicles a reasonable choice in the executive segment. The Tesla Roadster is capable of doing the same. Outperforming “classic” super cars, the Roadster will increase the appeal of electric driving world wide.

Elon happy

2. The tesla Roadster will push electric vehicle technology further with record breaking acceleration, top speed and most importantly: range. Currently, electric vehicles are known for their acceleration. The electric drive train makes it possible for the cars to have full access to their potential power from the moment you hit the pedal. However, their topspeed and range are often limited, due to the battery size. Batteries are heavy and therefore companies have to find a balance between the required performance (speed, acceleration, range) and how heavy they want the car to be. After all, the heavier the car, the more the weight is influencing the desired performance. I think the Tesla Roadster will push other car manufacturers to further develop the electrification of cars. This will result in more widely available models with increased performance at a more consume friendly price.

0to100realquick2

Do you have some savings laying around and has this blog article made you interested in the Tesla Roadster?
Prices are still to be announced for the European market, but the base model is expected to cost 200,000 dollar in the US, but the first 1,000 production cars (announced as the Founder series) will be priced at 250,000 dollar in the US. Future customers can pre-order the Roadster with a base reservation of 43.000 euro and a founders-serie reservation of 215,000 euro (for the Netherlands). For more information, check out Tesla’s  website:  https://www.tesla.com/nl_NL/roadster?redirect=no

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BIM, Meet Gertrude!

6

October

2020

Gertrude enjoying a well deserved drink during her performance. 

In August 2020, famous tech entrepreneur Elon Musk revealed his latest technological project: a pig called Gertrude. On first sight, Gertrude looks like an ordinary Pig. She seems healthy, curious, and eager to taste some delicious snacks. When looking at her, it is hard to imagine how she managed to get one of the world’s most radical and well known tech entrepreneurs so excited. Gertrude just seems normal.

This is exactly the point!

ElonMuskGotcha

Elon Musk “Gotcha”

Gertrude is no ordinary pig. She has been surgically implanted with a brain-monitoring chip, Link V0.9, created by one of Elon Musk’s latest start-ups named Neuralink.

Neuralink was founded in 2016, by Elon Musk and several neuroscientists. The short term goal of the company is to create devices to treat serious brain diseases and overcome damaged nervous systems. Our brain is made up of 86 billion neurons: nerve cells which send and receive information through electrical signals. According to Neuralink, your brain is like electric wiring. Rather than having neurons send electrical signals, these signals could be send and received by a wireless Neuralink chip.

To simplify: Link is a Fitbit in your skull with tiny wires

The presentation in August was intended to display that the current version of the Link chip works and has no visible side-effects for its user. The user, in this case Gertrude, behaves and acts like she would without it. The chip is designed to be planted directly into the brain by a surgical robot. Getting a Link would be a same day surgery which could take less than an hour. This creates opportunities for Neuralink to go to the next stage: the first human implantation. Elon Musk expressed that the company is preparing for this step, which will take place after further safety testing and receiving the required approvals.

The long term goal of the Neuralink is even more ambitious: human enhancement through merging the human brain with AI. The system could help people store memories, or download their mind into robotic bodies. An almost science-fictional idea, fuelled by Elon Musk’s fear of Artificial Intelligence (AI). Already in 2014, Musk called AI “the biggest existential threat to humanity”. He fears, that with the current development rate, AI will soon reach the singularity: the point where AI has reached intelligence levels substantially greater than that of the human brain and technological growth has become uncontrollable and irreversible, causing unforeseeable effects to human civilization. Hollywood has given us examples of this with The Matrix and Terminator. With the strategy of “if you cannot beat them, join them”, Elon Musk sees the innovation done by Neuralink as an answer to this (hypothetical) catastrophical point in time. By allowing human brains to merge with AI, Elon Musk wants to vastly increase the capabilities of humankind and prevent human extinction.

Singularity
Man versus Machine

So, will we all soon have Link like chips in our brains while we await the AI-apocalypse?

Probably not. Currently, the Link V0.9 only covers data collected from a small number of neurons in a coin size part of the cortex. With regards to Gertrude, Neuralink’s pig whom we met earlier in this article, this means being able to wirelessly monitor her brain activity in a part of the brain linked to the nerves in her snout. When Gertrude’s snout is touched, the Neuralink system can registers the neural spikes produced by the neurons firing electronical signals. However, in contrast: major human functions typically involve millions of neurons from different parts of the brain. To make the device capable of helping patients with brain diseases or damaged nervous system, it will need to become capable of collecting larger quantities of data from multiple different areas in the brain.

On top of that, brain research has not yet achieved a complete understanding of the human brain. There are many functions and connections that are not yet understood. It appears that the ambitions of both Elon Musk and Neuralink are ahead of current scientific understanding.

So, what next?

Neuralink has received a Breakthrough Device Designation from the US Food and Drug Administration (FDA), the organisation that regulates the quality of medical products. This means Neuralink has the opportunity to interact with FDA’s experts during the premarket development phase and opens the opportunity towards human testing. The first clinical trials will be done on a small group of patients with severe spinal cord injuries, to see if they can regain motor functions through thoughts alone. For now a medical goal with potentially life changing outcomes, while we wait for science to catch up with Elon Musk’s ambitions.

 Neuralink-Logo

Thank you for reading. Did this article spark your interest?
For more information, I recommend you to check out Neuralink’s website https://neuralink.com/

Curious how Gertrude is doing?
Neuralink often posts updates on their Instagram page https://www.instagram.com/neura.link/?hl=en

Want to read more BIM-articles like this?
Check out relating articles created by other BIM-students in 2020:

Sources used for this article:

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Professors! Get online or get out!

16

October

2019

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As a BIM master student, I was quite surprised when I heard that none of the courses were recorded and therefore available online. Everyone I ever spoke about it was enthusiastic about recorded lectures. Maybe all of my friends are just lazy students (like me), who prefer to stay in bed rather than going to a 9 am lecture, but I genuinly think it offers more convenience than it has disadvantages. Me wondering this was the main reason for me to write on this subject.


MOOC stands for Massive Open Online Courses, and are (often free) courses that are available to the public through online lectures and assignments (EdX, 2019). It provides great advantages as you can enroll from anywhere around the world, as long as you have access to a decent internet connection.

First of all, and maybe the most obvious advantage of MOOC’s, it that the internet knows no borders. Of course we all know the Great Chinese Firewall, but someone from South-Korea is able to enter a website from a Colombian local bee farm. Therefore, people from more abandoned areas, like sub-Saharan Africa are able to enter these courses as long as there is a decent internet connection and a streaming device. According to UNESCO (2016), sub-Saharan Africa has the highest rates of education exclusion in the world. Almost 60% of all youth between 15 and 17 there are not in school. Yes, they still require a streaming device, but a phone screen is in theory enough, and video projectors can be installed in classrooms.

This brings us to another advantage of MOOC’s, there is (in theory) no maximum student capacity. As it is a digital product, it can in theory be copied infinitely without reducing in quality. This means an enormous amount of people could follow the course of a single professor. This seems like a situation that only has benefits, but there are some risks. If a single professor is enough to educate a massive group of people, then I foresee a decrease of the need for professors. This may lead to many professors losing their job, and having to seek other ways to earn a living.

MOOC’s being a digital good also brings a major risk, the risk of the course content being copied and spread without consent and compensation. Screens can be recorded and assignments being copied. Websites like The PirateBay that provide a lot of illegal content are nowadays still available, whether it is through a proxy server or not). A solution must be sought to prevent piracy, because a single pirate is enough to create a lot of damage.

 

Another advantage of MOOC’s is that it provides an opportunity to gather data about its students. It can be tracked how much and when students spend time on the website, and which classes and courses are more and less attractive. Students may be able to provide a rating and a comment after every course. A risk of having too many students enrolled, is that a single professor may not be able to answer all questions or analyze feedback. This proves that a MOOC is not simply a professor with a webcam, but really requires a well-structured team or organization.

I would advise professors and universities to brainstorm about threats and opportunities in the increasingly digitized society. I believe that it’s very important not to miss the boat and to exploit first-mover advantages. Otherwise, you will remain the incumbent, while others become the disruptors.

 

References

EdX. (2019). mooc.org. Retrieved October 16, 2019, from http://mooc.org/.

UNESCO. (2016). Education in Africa. Retrieved October 16, 2019, from http://uis.unesco.org/en/topic/education-africa.

 

5/5 (2) The Threat of Deepfakes

12

October

2019

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Last summer an app called DeepNude caused a lot of controversy in the (social) media. Deepnude was an AI based piece of software with the ability to create a very realistic nude pictures of any uploaded face in the app. Mass criticism followed, the app’s servers got overloaded by curious people and not much later, the app went offline permanently. Deepnude stated on twitter that the probability is misuse was too high and that the world “was not ready yet”. The app never came back online ever since  (Deepnude Twitter, 2019). It shows that deepfake technology is becoming available to the public sooner than we thought, including all potential risks.

A definition for DeepFake is “AI-based technology used to produce or alter video content so that it presents something that didn’t, in fact, occur” (Rouse, 2019). As deepfake is AI-based technology it is able to improve over time, as the amount of data input increases and the technology learns to how to create better output. In my opinion deepfake has an amazing potential in the entertainment industry, but there is a serious risk when the technology gets misused. The AI technology makes it harder and harder for humans to distinguish real videos from fake ones. Deepfake videos of world-leaders like Trump and Putin are already to be found on the internet. Also deepfake porn videos of celebrities are being discovered once in a while.

With the upcoming presidential elections of 2020 in the United States, politicians and and many others are seeking solutions to prevent a similar scenario like the 2017 elections. The 2017 presidential elections were characterized by the spread of fake news and the ongoing allegations resulting from it. These events very likely influenced the outcome of those elections (CNN, 2019). Recently the state of California passed a law which “criminalizes the creation and distribution of video content (as well as still images and audio) that are faked to pass off as genuine footage of politicians. (Winder, 2019).” In 2020 we’ll find out whether deepfakes have been restricted succesfully.

I hope developers and users of deepfake technology will become aware of the huge threats of deepfake, and will use it in a responsible way. It is also important for society to stay critical at their news sources and that they prevent supporting these types of technology misuse. According to Wired (Knight, 2019), Google has released thousands of deepfake videos to be used as AI input to detect other deepfake videos. Another company called Deeptrace is using deep learning and AI in order to detect and monitor deepfake videos (Deeptrace, sd).

See you in 2020…

References

CNN. (2019). 2016 Presidential Election Investigation Fast Facts. Retrieved from CNN: https://edition.cnn.com/2017/10/12/us/2016-presidential-election-investigation-fast-facts/index.html

Deepnude Twitter. (2019). deepnudeapp Twitter. Retrieved from Twitter: https://twitter.com/deepnudeapp

Deeptrace. (n.d.). About Deeptrace. Retrieved from Deeptrace: https://deeptracelabs.com/about/

Knight, W. (2019). Even the AI Behind Deepfakes Can’t Save Us From Being Duped. Retrieved from Wired: https://www.wired.com/story/ai-deepfakes-cant-save-us-duped/

Rouse, M. (2019). What is deepfake (deep fake AI). Retrieved from TechTarget: https://whatis.techtarget.com/definition/deepfake

Winder, D. (2019). Forget Fake News, Deepfake Videos Are Really All About Non-Consensual Porn. Retrieved from Forbes: https://www.forbes.com/sites/daveywinder/2019/10/08/forget-2020-election-fake-news-deepfake-videos-are-all-about-the-porn/#26a929963f99

 

 

Why do we trust Facebook more than banks?

9

September

2019

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Digital revolution, also referred to as the 4th industrial revolution, is bringing extraordinary opportunities for startups and tech-savvy companies, but what about the established businesses? Are they going to follow the trend or are they going to die a natural death? Some researchers predict that, in contrast to startups, existing companies will experience a lot of threats caused by digitization (Weill, Woerner, 2015). These can be as simple as the fact that the given product or service is needed anymore. When I think about it, an example that always comes to my mind are the tech repair shops. I still remember that when I was younger and our TV or computer broke, we would always take it to a local repair shop to fix it. Nowadays, when something breaks, eighty percent of time, the item is just simply not fixable anymore and one needs to buy a new one. I think in a few years, people would not even bother trying to fix their broken gadgets.

On the other hand, some threats are much more complicated and much harder to tackle by companies. In my opinion, this is caused by the fact that for the companies they were (and are) very much unexpected. Let’s take as an example a long-established banking industry. Up till few years ago, when faced with fintechs, banks did not expect any threat to challenge them in any near or far future (Brown, 2019). If the digital trend continues (and it most certainly will), in few years the banks as we know them might not be needed at all anymore (Weill, Woerner, 2015).

What I think is very interesting to see is how people slowly tend to start trusting familiar apps on their phone more than their bank advisors. Were banks not supposed to be, by default, institutions of public trust? Nowadays people (and I probably also fall into this group sometimes) allow Facebook (or any other app) to access information on their iPhone (which is ultimately the central database of our lives) without much thought. However, when it comes to signing a document in a traditional bank we tend to be a bit distrustful.

To many of us, the fact that Chinese giant WeChat gathers personal, behavioral and financial information about its users seems comparable with Orwell’ s utopian Oceania (Orwell, 1949). But if we don’t change our habits, using Facebook instead of a traditional bank may not seem as such a distant future (Mearian, 2019).

Works Cited:

Brown, J. C. (2019, January 03). Automation will be the end of banks as we know them. Retrieved September 2019, from TechCrunch: https://techcrunch.com/2019/01/03/automation-will-be-the-end-of-banks-as-we-know-them/

Mearian, L. (2019, June 18). Facebook is going into the banking business with blockchain. Retrieved September 2019, from Computerworld: https://www.computerworld.com/article/3403342/facebook-is-going-into-the-banking-business-with-blockchain.html

Orwell, G. (1949). 1984. London: Secker and Warburg.

  1. Weill, S. L. Woerner. (2015, June 16). Thriving in an Increasingly Digital Ecosystem. MITSloan, 56(4), 27.

 

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