Exploring Blockchain for Trustful Collaborations between Immigrants and Governments

Chiang, Charles; Betanzos, Eber; Savage, Saiph

doi:10.1145/3170427.3188660

Cited by 17 publications

(13 citation statements)

References 9 publications

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“…Additionally, to build more trust and participation on crowd markets, it might also be worth to explore transparent interfaces that can inform the different actor of a marketplace just how much each actor is being fair and respectful of others' values [11]. Future work could explore other ways of recruiting Super Turkers and eliciting information from them, e.g., via video recordings or interviews [60].…”

Section: Discussionmentioning

confidence: 99%

Becoming the Super Turker: Increasing Wages via a Strategy from High Earning Workers

Savage,

Chiang,

Saito

et al. 2020

Preprint

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Crowd markets have traditionally limited workers by not providing transparency information concerning which tasks pay fairly or which requesters are unreliable. Researchers believe that a key reason why crowd workers earn low wages is due to this lack of transparency. As a result, tools have been developed to provide more transparency within crowd markets to help workers. However, while most workers use these tools, they still earn less than minimum wage. We argue that the missing element is guidance on how to use transparency information. In this paper, we explore how novice workers can improve their earnings by following the transparency criteria of Super Turkers, i.e., crowd workers who earn higher salaries on Amazon Mechanical Turk (MTurk). We believe that Super Turkers have developed effective processes for using transparency information. Therefore, by having novices follow a Super Turker criteria (one that is simple and popular among Super Turkers), we can help novices increase their wages. For this purpose, we: (i) conducted a survey and data analysis to computationally identify a simple yet common criteria that Super Turkers use for handling transparency tools; (ii) deployed a two-week field experiment with novices who followed this Super Turker criteria to find better work on MTurk. Novices in our study viewed over 25,000 tasks by 1,394 requesters. We found that novices who utilized this Super Turkers' criteria earned better wages than other novices. Our results highlight that tool development to support crowd workers should be paired with educational opportunities that teach workers how to effectively use the tools and their related metrics (e.g., transparency values). We finish with design recommendations for empowering crowd workers to earn higher salaries.

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Section: Discussionmentioning

confidence: 99%

Becoming the Super Turker: Increasing Wages via a Strategy from High Earning Workers

Savage,

Chiang,

Saito

et al. 2020

Preprint

Self Cite

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“…In the future, we would also like to explore using Crowd Coach to improve workers' personal skills for more complex professions such as CTOs, managers, or computer engineers. We also plan to explore the benefits of these type of crowd coach systems to facilitate skill development in rural communities where experts might be more scarce [2,21].…”

Section: Discussion and Future Workmentioning

confidence: 99%

Crowd Coach

Chiang

Kasunic

Savage

2018

Proc. ACM Hum.-Comput. Interact.

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Traditional employment usually provides mechanisms for workers to improve their skills to access better opportunities. However, crowd work platforms like Amazon Mechanical Turk (AMT) generally do not support skill development (i.e., becoming faster and better at work). While researchers have started to tackle this problem, most solutions are dependent on experts or requesters willing to help. However, requesters generally lack the necessary knowledge, and experts are rare and expensive. To further facilitate crowd workers' skill growth, we present Crowd Coach, a system that enables workers to receive peer coaching while on the job. We conduct a field experiment and real world deployment to study Crowd Coach in the wild. Hundreds of workers used Crowd Coach in a variety of tasks, including writing, doing surveys, and labeling images. We find that Crowd Coach enhances workers' speed without sacrificing their work quality, especially in audio transcription tasks. We posit that peer coaching systems hold potential for better supporting crowd workers' skill development while on the job. We finish with design implications from our research.

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“…The author also highlighted the capability of integration of blockchain technology for other services such as finance and taxation. Chiang et al [136] presented a blockchain and the smart contract integrated system to build the trust between immigrants and the government. The authors introduced ChainGov, a collaborative decentralized platform for immigrants, governments, and other institutions that can inform each collaborative individual about the flow of money as well as real time visibility of all transactions.…”

Section: Public Servicesmentioning

confidence: 99%

Survey on blockchain based smart contracts: Applications, opportunities and challenges

Hewa

Ylianttila

Liyanage

2021

Journal of Network and Computer Applications

274

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Blockchain is one of the disruptive technical innovation in the recent computing paradigm. Many applications already notoriously hard and complex are fortunate to ameliorate the service with the blessings of blockchain and smart contracts. The decentralized and autonomous execution with in-built transparency of blockchain based smart contracts revolutionize most of the applications with optimum and effective functionality. The paper explores the significant applications which already benefited from the smart contracts. We also highlight the future potential of the blockchain based smart contracts in these applications perspective.

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Exploring Blockchain for Trustful Collaborations between Immigrants and Governments

Cited by 17 publications

References 9 publications

Becoming the Super Turker: Increasing Wages via a Strategy from High Earning Workers

Becoming the Super Turker: Increasing Wages via a Strategy from High Earning Workers

Crowd Coach

Survey on blockchain based smart contracts: Applications, opportunities and challenges

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