Is freelancing the future of working?

11

October

2022

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Gig economy has caught a lot of attention in recent years. It can be defined as a labor market in which employers rely heavily on independent contractors and freelancers rather than full-time permanent employees (Chappelow, 2019). Growth of the gig economy is being fueled by digital platforms that allow contractors to connect with employers. Gross volume of the gig economy in the United States is projected to reach 455 billion U.S. dollars in 2023 (MasterCard, 2019). Currently, there are over 70 million freelancers in the US and they are forecasted to make up more than half of the country’s workforce in 2027 (Upwork, 2017).

Uber and Airbnb are the companies that are getting the most attention, however, the complexity of work done through freelancing is limited not only to transportation and accommodation industries. Very exciting part of the freelancing market are freelancing platforms which allow professionals from different fields to connect with exciting opportunities from all around the world and earn additional or even the main source of income. Some of the most popular skill areas for digital freelancers include IT, design, sales, marketing, writing, customer support, finance, engineering and legal. There are multiple platforms that allow for professionals to connect with companies, namely Toptal, Fiverr, Freelancer.com and Upwork. The last one is currently dominating the market, so it will serve as a basis for this evaluation.

Being a digital platform, Upwork facilitates the interactions between companies and freelancers. What made the company such a success story are its additional functionalities that make the process of signing the contract safe and simple. Firstly, hiring companies can see the portfolios of freelancers which serve as proof of the quality of their work. Additionally, employers bear any costs only after the work has been approved by them, so the risk of having to pay for work of inadequate quality is reduced virtually to zero. Moreover, the company emphasizes its focus on data security and privacy (Upwork, 2022). All these factors contribute to the fact that the average rating of professionals by clients stands at 4,9 out of 5. Main company’s values – freedom from the physical office, flexibility and efficiency – don’t come without their shortcomings (Popiel, 2017). Notable trade-offs of freelancing on the platform include the infrequency of work, intense global competition and barriers to high wages (Popiel, 2017).

Is freelancing the future of working, though? In 2020 the freelancers on Upwork earned $2.3 billion cumulatively – given the fact that there are millions of contractors registered on the platform, it does not seem like much (Upwork, 2022). My prediction is that freelancing will be becoming increasingly important in the coming years, but we won’t see 9-5 jobs coming away anytime soon. I believe that stable, indefinite employment contracts with all benefits that come with them will still be of preference for the substantial part of workers.

References

Chappelow, J. (2019). Gig Economy. [online] Investopedia. Available at: https://www.investopedia.com/terms/g/gig-economy.asp.

MasterCard. (2019). Projected gross volume of the gig economy from 2018 to 2023 (in billion U.S. dollars). Statista. Statista Inc.. Accessed: October 09, 2022. https://www.statista.com/statistics/1034564/gig-economy-projected-gross-volume/

Popiel, P. (2017). ‘Boundaryless’ in the creative economy: assessing freelancing on Upwork. Critical Studies in Media Communication, 34(3), pp.220–233. doi:10.1080/15295036.2017.1282618.

Upwork. (2017). Number of freelancers in the United States from 2017 to 2028 (in millions). Statista. Statista Inc.. Accessed: October 09, 2022. https://www.statista.com/statistics/921593/gig-economy-number-of-freelancers-us/

Upwork. (2022). Upwork | Hire Freelancers. Make things happen. [online] Available at: https://www.upwork.com.

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AI changes the transportation industry. And it’s not all about self-driving Teslas.

8

October

2022

5/5 (1)

When you think about Artificial Intelligence in the transportation industry, probably the first thing that comes to your mind are shiny, brand-new Teslas with their famous Autopilot feature. Tesla is indeed the highest capitalized motor vehicles company right now, but there is much more change in the transportation industry empowered by AI than only self-driving vehicles (TradingView, 2022).

Artificial Intelligence has found many applications for public transportation authorities. With the use of advanced models, mass transit agencies are able to design and develop optimal route networks that maximize ridership and minimize road congestion. On top of that, AI can accurately predict passenger flows throughout the day, allowing to roll out more vehicles on the road or tracks when needed, making them less crowded and offering more pleasurable experience (Abduljabbar et al., 2019).

One might think that it is easy to solve traffic issues simply by building more lanes. Unfortunately, this statement is very far away from the truth. Firstly, expanding physical infrastructure is extremely costly and in most cases just infeasible in dense urban areas. Secondly, road infrastructure is an example of a fascinating economic phenomenon known as induced demand. In simplest words, each added lane incentivizes additional drivers to go on the road. Thus, in the short term, traffic congestion might be improved, but in the longer term it always ends at least as bad as before (Lee, Klein and Camus, 1999).

This is where data and AI comes in, seen as the most efficient way to combat traffic congestion with the current state of technology. It turns out that infrastructure elements we take for granted are much more technologically advanced than one might think. Take traffic lights as an example. Data gathered from cameras and sensors at the intersections is fed to algorithms which can in turn improve timing plans for traffic lights (Abduljabbar et al., 2019). That improves the traffic flow and limits congestion – without adding any additional lanes.

Last but not least, AI serves as a backbone for Automatic Incident Detection (AID) systems. With the use of cameras and radars, these systems can detect unusual situations on the road in seconds, allowing qualified operators to spot incidents quickly and send emergency services if needed. Those systems are also supported by smartphones, which can detect incidents with accelerometers and acoustic data. Research shows that AID can reduce the fatality rate on the roads by 6%, meaning it actually helps to save human lives (White, et al., 1999).

Automatic Incident Detection – principle of operation

After all, AI is not only about self-driving vehicles. Insights from data are actively used in other aspects of transportation, allowing for more efficient public transport systems, reduced traffic and improved safety on the roads.

References

Abduljabbar, R., Dia, H., Liyanage, S. and Bagloee, S.A. (2019). Applications of Artificial Intelligence in Transport: An Overview. Sustainability, [online] 11(1), p.189. doi:10.3390/su11010189.

Lee, D.B., Klein, L.A. and Camus, G. (1999). Induced Traffic and Induced Demand. Transportation Research Record: Journal of the Transportation Research Board, 1659(1), pp.68–75. doi:10.3141/1659-09.

TradingView. (2022). Stock Screener — Search and Filter Stocks. [online] Available at:https://www.tradingview.com/screener/.

White, J., Thompson, C., Turner, H., Dougherty, B. and Schmidt, D.C. (2011). WreckWatch: Automatic Traffic Accident Detection and Notification with Smartphones. Mobile Networks and Applications, 16(3), pp.285–303. doi:10.1007/s11036-011-0304-8.

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