Wenrui Jiang

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Back in the days going online on the Internet means a connection to the world, a way to connect individuals together. However, there has been a shift in how information is circulating online. Most people are aware that our web experience is in some way customized for us by our browsing history and other factors. We do all this skimming, sharing and clicking on the Internet and many of us are uninformed about or uninterested in the forces that are controlling what we see online and how these contents might affect us in return.

The concept “filter bubble’’ is first introduced by Eli Pariser and refers to what we encounter online as results of algorithms. According to Eli Pariser (2011), the filter bubble is “your own personal unique universe of information that you live in online.” Algorithms make use of filter bubble to alters the way we encounter information. Eric Schmidt from Google once said: “It will be very hard for people to watch or consume something that has not in some sense been tailored for them.’’

Nowadays, many websites offer personalized content selection based on our browsing history, location, gender, age, and other data about you. This result in information or feed that match our current opinions and perspectives to make sure we enjoy what we see. Which is to say, even if two people look up for the same term on Google at the same time, the result will differ. This is because Google personally tailors our search queries.

Some people might think that it’s a good thing since we can make sure that every piece of content we encounter is something we are interested in. However, we tend to forget that the filter bubble creates different categories and filter out things they think is unnecessary. We as human have the tendency to think that what we see is all there without realizing that what we see is actually being filtered by these innocent algorithms called filter bubbles.

Barack Obama also voiced his concerns regarding the danger from the social media filters in his farewell speech “[We] retreat into our own bubbles, especially our social media feeds, surrounded by people who look like us and share the same political outlook and never challenge our assumptions. And increasingly, we become so secure in our bubbles that we start accepting only information, whether it’s true or not, that fits our opinions, instead of basing our opinions on the evidence that is out there.” (Obama, 2017). Filter bubbles can cause cognitive biases to manifest while amplifying the negative impact on our thinking ability in a logical and critical way. According to Eli Pariser (2011), the filter bubble is designed to consume information that conforms to our ideas of the world which tends to dramatically amplify confirmation bias. Consequently, we constructed a world from the familiar from which there is nothing to learn from.

The question now arises: are we manipulated by the filter bubbles and actually become more narrow-minded because of the internet?

References

Obama, B. (2017) Read the full transcript of President Obama’s farewell speech. Retrieved from https://www.latimes.com/politics/la-pol-obama-farewell-speech-transcript-20170110-story.html

Pariser, E. (2011). The filter bubble: What the Internet is hiding from you. Penguin UK.

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Sharing economy is an economic model which includes providing or sharing goods and services, mostly at a peer-to-peer base. Quite straightforward from the literal implication, sharing economy emphasises on the behaviour of sharing to produce revenues from assets which may use to be underused. For instance, there are co-working platforms, peer-to-peer lending platforms, fashion platforms, and freelancing platforms that constituted the sharing economy (Kenton, 2017). Typical examples would be Airbnb and Uber which introduces drastic changes to their industries. There were no similar models of shared taxies or houses, yet these two companies had gained great success and made great impacts on traditional businesses. Based on the outstanding performance of these two companies, the sharing economy is expected to increase from $14 billion in 2014 to $335 billion by 2025 (Kenton, 2017).

The trend of sharing economy offers opportunities for new entrants and also introduce challenges to existing companies if they struggle to adapt to these drastic changes. Since most companies in the sharing economy utilize assets or utilities that were underused, they have a low entering cost thus are able to offer prices lower than the industry average. In this way, they can challenge the leading positions of existing companies or beat the traditional industry leaders. In addition to the choices of sharing transportation or accommodation as Uber and Airbnb did, other goods and services can also join the sharing economy. In the market of professional and personal services, the concept of sharing economy plays an important role. There are companies such as Fiverr which provide platforms for people to hire contractors, and skilled freelancers can share their expertise for extra money (Miller, 2018). Furthermore, sharing economy can even fit into the healthcare industry. According to Miller (2018), most of the medical equipment is estimated to be unused in 58% of its life, thus sharing equipment with other healthcare facilities became an effective solution to optimize the usage of medical equipment while decreasing costs at the same time.

In the future of sharing economy, the growth will be even more rapid and hard to predict. Both Uber and Lyft planned to go public and Lyft had just filled in the IPO documents on 1^st March (Hawkins, 2019). Uber is now valued at $120 billion and also plans to go public in the first two quarters of 2019 (Rinne, 2019). According to Rinne (2019), revenue of sharing economy only accounts for 5% of the total revenue for ten sectors which include five traditional rental sectors and five sharing economy sectors in 2013. It is predicted to grow explosively from $15 billion to $335 billion in 2025, accounting for half of the total revenue for ten sectors. However, the fast growth of companies which incorporate the business model of sharing economy might be uneven. A failed case is Ofo, the bike-sharing company based in China which is on the edge of bankruptcy (Rinne, 2019). Ofo used to be regarded as a superstar in the bike industry, yet it did not stay at the winning place for a long time and quickly embraced its failure, probably due to its reckless expansion in both China and international markets.

There are controversies and criticisms of sharing economy and the one that draws the most attention is the regulatory issues of sharing. It is not only about how governments can prevent companies to take advantages of the vague requirements for licensing in offering rental goods or services, but also about how to proactively intervene to regulate and ensure a safe environment for both providers and consumers. There are so many uncertainties due to the peer-to-peer nature of the sharing economy, thus governments will need to decide whether to play a more proactive role in the markets or not.

References

Hawkins, A., (2019). Lyft becomes the first ride-hail company to go public, beating Uber. The Verge. Retrieved from https://www.theverge.com/2019/3/1/18246328/lyft-ipo-ride-share-bikes-scooters-uber-public-sec

Kenton, W., (2017). Sharing Economy. Investopedia. Retrieved from https://www.investopedia.com/terms/s/sharing-economy.asp

Miller, D., (2018). What Is the Sharing Economy (and How Is it Changing Industries)? The balance small business. Retrieved from https://www.thebalancesmb.com/the-sharing-economy-and-how-it-changes-industries-4172234

Rinne, A., (2019). 4 big trends for the sharing economy in 2019. World Economic Forum. Retrieved from https://www.weforum.org/agenda/2019/01/sharing-economy/

Are We Becoming Narrow-minded Because of the Internet—— Filter bubbles?

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Will Sharing Economy Become a Norm?

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