Synthetic data

Author:

Patel Preeti1ORCID

Affiliation:

1. London Metropolitan University, UK

Abstract

The rise of data-driven businesses poses a number of significant challenges for contemporary organisations. These include legal and ethical considerations arising from the use of personal data, the growing challenges of information security, and the difficulty managing the volume of data generated in business transactions of different kinds. The exponential growth of data continues unabated with global data volumes reaching 181 zettabytes by 2025, and with 90% of the world’s data generated in the last two years alone. This massive growth can be mainly attributed to data gathered by Internet of Things (IoT) and related sensory devices, in addition to data generated through the human use of digital tools and applications. Given this abundance of real-world data, in what context could synthetic data be necessary? This paper highlights the growing organisational use of synthetic data and explores where and how it can be optimally used. It examines the ethical aspects of synthetic data usage, the need to garner public perception and acceptance, and the key aspects of traceability, accountability and risk mitigation.

Publisher

SAGE Publications

Subject

Economics, Econometrics and Finance (miscellaneous),Business, Management and Accounting (miscellaneous),Business and International Management

Reference19 articles.

1. ACM (2021), Companies Beef Up AI Models with Synthetic Data, The Wall Street Journal, available at: https://cacm.acm.org/news/254385-companies-beef-up-ai-models-with-synthetic-data/fulltext (accessed 10 October 2023)

2. Ambrosio J (2022) How Waymo is using ML to Build a Scalable, Autonomous Driver, Google Waymo, available at: https://exchange.scale.com/public/blogs/how-ml-waymo-building-scalable-autonomous-driver-dmitri-dolgov (accessed 10 October 2023)

3. Barth A (2022) Amazon Sagemaker Ground Truth Now Supports Synthetic Data Generation, AWS News Blog, available at: https://aws.amazon.com/blogs/aws/new-amazon-sagemaker-ground-truth-now-supports-synthetic-data-generation/ (accessed 10 October 2023)

4. FCA (2022), Synthetic Data to Support Financial Services Innovation, Financial Conduct Authority, available at: https://www.fca.org.uk/publication/call-for-input/synthetic-data-to-support-financial-services-innovation.pdf (accessed 10 October 2023)

5. Harnessing the power of synthetic data in healthcare: innovation, application, and privacy

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3