Data economy

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A data economy is a global digital ecosystem in which data is gathered, organized, and exchanged by a network of companies, individuals, and institutions to create economic value. [1] [2] The raw data is collected by a variety of factors, including search engines, social media websites, online vendors, brick and mortar vendors, payment gateways, software as a service (SaaS) purveyors, and an increasing number of firms deploying connected devices on the Internet of Things (IoT). [3] Once collected, this data is typically passed on to individuals or firms, often for a fee. In the United States, the Consumer Financial Protection Bureau and other agencies have developed early models to regulate the data economy. [4] : 531–32 

Contents

Storing and securing collected data represent a significant portion of the data economy. [5]

Data economy categories

Big data economy

Big data is defined as the algorithm-based analysis of large-scale, distinct digital data for purposes of prediction, measurement, and governance. [6] [7]

This involves processing vast amounts of information from various sources, like social media, sensors, or online transactions, using advanced computer programs (algorithms). These algorithms help uncover patterns, trends, and insights that would be impossible to identify manually, enabling applications such as predicting consumer behavior or optimizing city traffic systems.

Data barter

Data barter occurs when goods or services are exchanged for customer data, typically at a zero monetary price. This phenomenon is common in digital services such as free apps, where the value of the data collected can be substantial. Data barter may not be captured by traditional GDP measures, leading to potential underestimation of economic activity. [8]

Partial data barter

In the process of economic transactions, firms acquire data about customers: the goods they purchased, the time at which they shopped or perhaps a means of payment, zip code or operating system. This data is valuable to firms. Firms that value such data should have an extra incentive do more transactions to gather more data. To do more transactions, a firm needs to lower its price or offer a higher-quality product at the same price, to induce more customers to come. Profit maximization dictates that firms that value data should offer customers lower prices (per unit of quality or quantity). This decline in the price, which is compensated for by the transfer of valuable data, is referred to as partial data barter. [8] [9]

Human-driven data economy

The human-driven data economy is a fair and functioning data economy in which data is controlled and used fairly and ethically in a human-oriented manner. [10] [11] The human-driven data economy is linked to the MyData Movement and is a human-centered approach to personal data management. [12]

This means that individuals have the ability to decide how their personal information is used and shared, ensuring transparency and accountability. It also aims to create systems where data contributes to societal benefits without compromising individual rights.

Personal data economy

The personal data economy is created by individuals using personal data, which people supply either directly or indirectly. Consumers become suppliers and controllers. [13] [14]

Algorithm economy

In an algorithm economy, companies and individuals can buy, sell, trade, or donate individual algorithms or apps pieces, by leveraging dedicated marketplaces. [15] [16] [17]

Transition to data economy

Market size

The size of the EU data economy was estimated to be more than €285 billion in 2015, representing over 1.94% of the EU GDP. Key sectors in the data economy either are or are on the way to becoming data-driven. For example, the manufacturing, agriculture, automotive, smart living environments, telecommunications, healthcare, and pharma industries are at the core of the data economy. [1]

Benefits

Management of personal information makes everyday life easier and adds to well-being. A unified procedure opens up opportunities for user-oriented innovations and business activities.

Individuals have control over the data concerning themselves. Individuals can actively define the services and the conditions under which their personal information is used. The service providers worthy of people's trust can also get access to significantly more extensive and varied data e-services.

Challenges

Approaches to data breaches are problematic. Challenging issues include compensation to victims, incentives for enterprises to invest in data security, and uncertainties for corporations about regulatory burdens and litigation risks. [18] Furthermore, data portability might decrease interest in innovations. [1]

Regulation

The regulation of the data economy is closely linked to privacy. [2] The present approach is flexibility, finding a balance between protecting privacy and allowing citizens to decide for themselves. The European Union GDPR regulation is one cornerstone of this new regulatory framework. [19] [20] A new paradigm for data governance is needed, with data ethics as a central component in all regulatory reforms. [21]

Criticism

The data economy raises concerns about regulatory uncertainties and incoherence, privacy, ethics, the loss of control of data, and the ownership of data and related rights. [22] [23] [24] Mathematical models and algorithms based on them are too often opaque, unregulated, and incontestable. [25]

Some concerns have been raised about internet companies controlling the flow of data and using it to gain power. [26]

The critiques expressed in the 2012 General Data Protection Regulation (GDPR) draft of the European Commission have now led to concrete regulations:

“This is why it is time to build a stronger and more coherent data protection framework in the EU, backed by strong enforcement that will allow the digital economy to develop across the internal market, put individuals in control of their own data and reinforce legal and practical certainty for economic operators and public authorities.” [27]

See also

References

  1. 1 2 3 "Data Market Study 2021-2023. First report on policy conclusions". European Commission. 7 May 2021. Retrieved 7 August 2023.
  2. 1 2 Sestino, Andrea; Kahlawi, Adham; De Mauro, Andrea (2 August 2023). "Decoding the data economy: a literature review of its impact on business, society and digital transformation". European Journal of Innovation Management. doi:10.1108/EJIM-01-2023-0078. S2CID   260405973.
  3. ↑ Chamberlin, Bill. "The Data Economy: 2016 Horizonwatch Trend Brief". Horizon Watch. IBM Expert Network. Retrieved 20 August 2018.
  4. ↑ Van Loo, Rory (2018-07-01). "Technology Regulation by Default: Platforms, Privacy, and the CFPB". Georgetown Law Technology Review. 2 (2): 531.
  5. ↑ Information Technology and Innovation Foundation (2017). Post-Hearing Written Submission Nigel Cory Trade Policy Analyst Before the United States International Trade Commission Investigation No. 332-56 Global Digital Trade I: Market Opportunities and Key Foreign Trade Restrictions [PDF file]. Retrieved from http://www2.itif.org/2017-usitc-global-digital-trade.pdf
  6. ↑ Flyverbom, Mikkel; Madsen, Anders Koed (January 2015). Sorting data out – unpacking big data value chains and algorithmic knowledge production. doi:10.4135/9781412985871. ISBN   9780803972377.{{cite book}}: |journal= ignored (help)
  7. ↑ Satell, Greg. "5 Things Managers Should Know about Big Data Economy". Forbes . Retrieved 7 September 2018.
  8. 1 2 Baley, Isaac; Veldkamp, Laura (2025). The data economy: tools and applications. Princeton: Princeton University Press. ISBN   978-0-691-25672-6.
  9. ↑ Baley, Isaac; Veldkamp, Laura (April 17, 2024). "The partial data barter trades of the digital economy". Brookings.
  10. ↑ "Human-Driven Data Economy". Sitra. Retrieved 7 September 2018.
  11. ↑ "Prepare for a new human-driven data economy HealthTech Wire". HealthTech Wire HIMMS Europe. May 23, 2018. Retrieved 7 September 2018.
  12. ↑ Dehaye, Paul-Olivier (December 21, 2017). "PersonalData.IO helps you get access to your personal data". Open Knowledge International Blog. Retrieved 7 September 2018.
  13. ↑ Syrjänen, Tuomas (January 24, 2018). "The Rise of the Personal Data Economy". GreenBook Blog. Retrieved 7 September 2018.
  14. ↑ Personal Data: The Emergence of a New Asset Class (PDF). World Economic Forum. January 2011. p. 40. Retrieved 7 September 2018.
  15. ↑ "What is the Algorithm Economy". Techopedia. 4 October 2017. Retrieved 7 September 2018.
  16. ↑ Kumar, Abhishek; Finley, Benjamin; Braud, Tristan; Tarkoma, Sasu; Hui, Pan (2020). "Marketplace for AI Models". arXiv: 2003.01593 [cs.CY].
  17. ↑ Ezrachi, Ariel; Stucke, Maurice E. (2019). Virtual Competition: The Promise and Perils of the Algorithm-Driven Economy. Cambridge: Harvard University Press. ISBN   9780674241589.
  18. ↑ Daly, Angela (2018). "The introduction of data breach notification legislation in Australia: A comparative view" (PDF). Computer Law & Security Review. 34 (3): 477–495. doi:10.1016/J.CLSR.2018.01.005. S2CID   67358435.
  19. ↑ Davies, Jamie (August 2018). "It turns out regulating the data economy is really hard". Telecoms news. Retrieved 27 August 2018.
  20. ↑ Abate, Serafino (13 August 2018). "Is the data economy self-healing, or should economic regulation be considered?". GSMA. Retrieved 27 August 2018.
  21. ↑ Maya, Uppaluru (April 16, 2018). "The U.S. Needs a New Paradigm for Data Governance". Harvard Business Review. Harward Business Review. Retrieved 7 September 2018.
  22. ↑ Wendehorst, Christiane; Cohen, Neil; Weise, Steve (August 25, 2017). "Feasibility Study ALI-ELI Principles for a Data Economy" (PDF). European Law Institute. Retrieved 20 August 2018.[ permanent dead link ]
  23. ↑ Crabtree, Andy; Lodge, Tom; Colley, James; Greenhalgh, Chris; Mortier, Richard; Haddadi, Hamed (November 2016). "Enabling the new economic actor: data protection, the digital economy, and the Databox". Personal and Ubiquitous Computing. 20 (6): 947–957. doi: 10.1007/s00779-016-0939-3 . hdl: 10044/1/52734 .
  24. ↑ Tene, Omer; Polonetsky, Jules (April 2013). "Big Data for All: Privacy and User Control in the Age of Analytics". Northwestern Journal of Technology and Intellectual Property. 11 (5). Retrieved 20 August 2018.
  25. ↑ O'Neil, Cathy (September 6, 2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown Publishing Group.
  26. ↑ "The world's most valuable resource is no longer oil, but data". The Economist. Retrieved 2018-11-20.
  27. ↑ "Proposal for a regulation of the European Parliament and the Council on the protection of individuals with regard to the processing of personal data and on the free movement of such data (General Data Protection Regulation GDPR). COM(2012) 11 final" (PDF). European Parliament. Retrieved 20 August 2018.

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