Momentum Builds for a ‘Data Labor Movement’
The abuse of social media data highlighted this week by two days of media-trained testimony by Facebook founder Mark Zuckerberg shines a spotlight on the privacy tradeoffs inherent in the widespread use of convenient, addictive applications.
If Apple co-founder Steve Wozniak is correct in saying we users are Facebook’s “product,” supplying all our personal data and reaping few if any of the profits, then part of the coming regulation of social media should include compensating us for our labor. Wozniak, who also has a product he would like to sell, trashed the social media giant by asserting that Facebook’s “profits are all based on the user’s info, but the users get none of the profits back.”
The data privacy upheaval and assertions that it is promoting economic inequality are seeding a nascent data labor movement in which social media giants like Facebook (NASDAQ: FB) would compensate users for their personal data. Part of the reason, a new book on digital markets argues, is that all that posting and “Like”-ing is uncompensated work.
“Data is something that is useful to companies in producing products that we all like,” said Glen Weyl, co-author of Radical Markets: Uprooting Capitalism and Democracy for a Just Society. Interviewed this week on NPR’s Morning Edition, Wyl continued: Data is “incredibly intimate, and its belongs powerfully to us. So, all those traits sound a lot to me like labor.”
And that labor in the form of tweeting an Instagram-ing adds value to social media company’s products, prompting the Yale University economist Wyl and others to argue that users should get a cut of the hefty profits.
What we get in return for relinquishing our privacy, of course, is convenience and the ability to watch instructional videos, find a restaurant and the fastest route to it. What YouTube, Yelp and Google Maps (NASDAQ: GOOGL) get in return is far more valuable, personal data that is quickly becoming the coin of the realm. Wyl told NPR: “I want to see companies compete, and say to people, ‘Look, you shouldn’t be taken advantage of. We will pay you a fair price for your data.’
“I want to see people get aware—cyber ‘woke’,” Wyl added.
As data becomes more valuable to the economy, Wyl, who also works as a researcher at Microsoft (NASDAQ: MSFT), estimates our data should be worth about $1,000 per social media user per year.
Wyl and co-author Eric Posner’s advocacy of a data labor movement is part of a larger thesis about the profound impact of data on the economy and how wealth tends to accumulate in behemoths like Facebook rather than their product: us. Hence, they argue that a data labor movement and other mechanisms for “expanding the scope of markets” will help reduce economic inequality while restoring economic growth.
If big personal data is the future, they maintain, all of us deserve a share of the profits.
November 20, 2019
- Cloudera Announces Enhanced Partner Program
- Starburst Raises $22M in Series A Financing
- Grafana Labs Announces General Availability of Loki
- TigerGraph Selected to Strengthen Fraud Detection and Credit Risk Assessment
- DDN Acquires Western Digital’s IntelliFlash NVMe, Hybrid Flash and Predictive Analytics Enterprise Business Unit
- MOSAiC Data Now Available in ARM Data Center
- NetApp and Google Cloud Advance Strategic Partnership to Drive Innovation in the Cloud
- Survey: Data Strategy Holds the Secret to Customer Loyalty in Financial Services
- Kinetica Active Analytics Platform and RAPIDS Now Available on Oracle Cloud Infrastructure
- Core Scientific Now Provides NetApp ONTAP AI Infrastructure-as-a-Service
- Information Builders Achieves AWS Data and Analytics Competency Status
November 19, 2019
- Google Cloud Launches BigQuery Reservations
- Igneous DataProtect Now Supports Microsoft Azure Blob Storage and is Available in Azure Marketplace
- Striim Announces Incremental Data Capture from Google Cloud Spanner
- Science and Technology Facilities Council Selects Spectra Logic Tape Library to Process and Preserve Scientific Research Data
- HyperMobile Tech Aims to Significantly Boost Business Productivity for Users on the Go
- Report Finds New Data Architecture Key to Future of Pharma R&D
- Cirrascale Cloud Services Announces Availability of Graphcore IPU Servers and Cloud Instances for Machine Intelligence Workflows
- AntemetA Selects Cloudian Object Storage for Sovereign Cloud Offering
- Aerospike Raises $32M Equity Round
Most Read Features
- Deep Learning Has Hit a Wall, Intel’s Rao Says
- Big Data File Formats Demystified
- Why Every Python Developer Will Love Ray
- How to Build a Better Machine Learning Pipeline
- Hadoop Has Failed Us, Tech Experts Say
- 10 Big Data Trends to Watch in 2019
- Kafka Transforming Into 'Event Streaming Database'
- Why Knowledge Graphs Are Foundational to Artificial Intelligence
- Beyond BI: Looker Seeks Bigger Role for Data
- What’s the Difference Between AI, ML, Deep Learning, and Active Learning?
- More Features…
Most Read News In Brief
- Apache Arrow Takes ‘Flight’ with Big Data Net
- HPE Acquires MapR
- Scala Gets Its Notebook with Netflix's Polynote
- California's New Data Privacy Law Takes Effect in 2020
- Global DataSphere to Hit 175 Zettabytes by 2025, IDC Says
- IBM Adds AI to Planning Analytics
- Mobile Coding is a Thing
- Inside Fortnite's Massive Data Analytics Pipeline
- OmniSci 'Hitting Its Stride,' CEO Says
- Microsoft Aims for Data Analytics Unification with 'Synapse'
- More News In Brief…
Most Read This Just In
- DataCamp Unveils Mobile Coding Courses for Data Science Learning-On-the-Go
- Igneous DataProtect Now Supports Google Cloud Platform Storage
- ScyllaDB Announces Performance Record, Hits 1,000,000,000 RPS
- Hewlett Packard Enterprise Redefines Mission-Critical Storage with New Platform Designed for the Intelligence Era
- Snowflake, Next Pathway Partner to Accelerate Migration from Legacy Data Warehouses
- CockroachDB 19.2 Enables Enterprise to Build Global Applications with Strong Performance
- Neo4j Introduces Neo4J Aura, a Graph Database in the Cloud
- GridGain and Azul Systems Collaborate to Enable Java for Low-Latency Use Cases at Massive Scale
- NIST Releases Final Version of ‘Big Data’ Framework
- Unravel Data Launches Performance Management and Cloud Migration Assessment Solution for Google Cloud Dataproc
- More This Just In…
January 26, 2020 - January 28, 2020Austin TX United States