Stephan Bos

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A famous quote made by one of the biggest tech entrepreneurs in the world, Bill Gates, starts to become more and more of a reality. Bill Gates once said: “Banking is necessary, banks are not” referring to the fact that the middle man, which are the banks, are not necessary for a financial transaction between different parties. Banks currently function as the middle man who executes the transactions made by an organization or person, but banks are not accessible for everyone. Due to the big advancements in technologies and the endless possibilities of blockchain, banks could soon become obsolete.

DeFi, or decentralized finance, could be the next big thing to shake up the financial world. DeFi could be defined as “An ecosystem of financial applications and projects built on the blockchain technology” [1]. Advocates of DeFi state that this new financial system will reduce risks of fraud, corruption, and mismanagement of assets [2]. This is possible because it is secured by blockchain technology. With DeFi, transactions don’t have to be executed with the intervention of a middle man. Instead of a middle man, “smart contracts” are used to complete the transactions. Smart contracts are programs that run on the blockchain and are activated when certain conditions are met [3]. People can directly transfer money to each other without the intervention of a bank and it generated more transparency because no third party is involved and the encrypted records of the transaction are shared between all parties.

Currently, the Ethereum blockchain is providing an infrastructure for DeFi and is one of the most recognized parties [4]. But there are also some problems on the horizon. Lawmakers are not sure how to handle DeFi and legislation could prevent the growth of DeFi. Another problem with DeFi is the fact that it is slower than the current centralized systems [5].

In conclusion, DeFi could change the financial world forever but there are still some obstacles to overcome. Is DeFi becoming a reality or is blockchain a technology that will never fulfill its promise?

This blog gave a small introduction into the world of decentralized finance. Want to know more? Watch the video made by CNBC about the current state and future of DeFi: https://www.youtube.com/watch?v=_tXd9SC9xZw

By Stephan Bos

[1] https://www.youtube.com/watch?v=_tXd9SC9xZw

[2] https://gocardless.com/en-us/guides/posts/what-is-decentralized-finance/

[3] https://www.ibm.com/nl-en/topics/smart-contracts

[4] https://ethereum.org/en/defi/#how-defi-works

[5] https://www.eqifi.com/the-problems-with-defi-and-how-to-solve-them/

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It is more often shown in the news these days: intelligent computer systems that can discover things themselves. For example, Siri (Apple’s built-in speech assistant) has been running on a self-learning computer system since July 2014 that learns from users’ input and improves as a result (Nu.nl, 2016). This technology is also called a neural network and is part of machine learning. Apple isn’t the only company involved in machine learning, and there are plenty of other examples of this technology in action. For example, the researchers at MIT discovered that machine learning can turn a photo of food into a recipe that belongs to that photo (Nu.nl 2017).

Machine learning can be defined as the means of intelligent systems’ self-improvement through past experiences (Mohri, Rostamizadeh, Talwalkar, 2018). Machine learning is a very diverse and interdisciplinary understanding of science and mathematics (Ghahramani, 2004).

Machine learning can be used in a myriad of industries. An application for which machine learning is used is to combat hate speech on social media platforms. For example, Facebook uses AI to detect hate speech and is already making great strides with it (Facebook, 2020). The detection rate of Facebook went up from 80.5% to 94.7% in the time span of a year.

Figure 1 – Facebook’s proactive detection rate

Insulting people has become more and more accessible since the introduction of social media. Anyone can make inappropriate comments on a social platform. More than 140,000 young people between the ages of 12 and 25 in the Netherlands experienced online bullying, stalking, or threats in 2018 (CBS, 2020). Machine learning can provide a way out by flagging and removing hateful content.

A lot will have to be overcome before machine learning can deduce all hate comments, but big tech companies are working hard on the subject due to the added pressure provided by users of the platforms and government agencies.

Do you think that machine learning can prevent hate speech?

References

CBS. (2020, Januari 10). CBS over online stalken of laster. Opgehaald van CBS: https://www.cbs.nl/nl-nl/nieuws/2020/02/meisjes-vaker-dan-jongens-last-van-online-stalken-of-laster

Facebook. (2020, 19 november). How AI is getting better at detecting hate speech. Facebook ai. https://ai.facebook.com/blog/how-ai-is-getting-better-at-detecting-hate-speech/

Mohri, M., Rostamizadeh, A., & Talwalkar, A. (2018). foundations of machine learning. In M. Mohri, A. Rostamizadeh, & A. Talwalkar, foundations of machine learning (p. 1). Cambridge, Massachusetts: MIT press.

Nu.nl. (2016, augustus 24). Siri. Nu.nl: https://www.nu.nl/mobiel/4311953/siri-gebruikt-al-twee-jaar-zelflerende-technologie.html

Nu.nl. (2017, Juli 22). algoritme eten. Nu.nl: https://www.nu.nl/internet/4851369/slim-algoritme-koppelt-recepten-fotos-van-eten.html

Nu.nl. (2020, September 23). Adverteerders en sociale media zetten babystapjes tegen haatdragende inhoud. Nu.nl: https://www.nu.nl/tech/6079274/adverteerders-en-sociale-media-zetten-babystapjes-tegen-haatdragende-inhoud.html

Is DeFi taking over the financial system?

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Can machine learning prevent online hate?

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