Enterprise AI Analysis
Surrendering to Powerlessness: Governing Personal Data Flows in Generative AI
Personal data flows across digital technologies integrated into people's lives and relationships. Increasingly, these technologies include Generative AI. (How) should personal data flow into and out of GenAI models? We investigate how people experience personal data collection in GenAI ecosystems and unpack the enablers and barriers to governing their data. We focus on personal data collection by Meta, specifically Instagram, in line with their recent policy update on processing user data to train GenAI models. We conducted semi-structured interviews with 20 Latin American Instagram users, based in Europe and Latin America. We discussed the acceptability of their data flowing in and out of GenAI models through different scenarios. Our results interrogate power dynamics in data collection, the (inter)personal nature of data, and the multiple unknowns concerning data and their algorithmic derivatives. We pose provocations around feelings of powerlessness, re-framing (inter)personal data, and encountering unknown data and algorithms through design.
Authors: Alejandra Gómez Ortega (Stockholm University), Hosana Morales Ornelas (Delft University of Technology), Uğur Genç (Delft University of Technology)
Key Findings at a Glance
Understand the immediate implications of personal data governance in Generative AI for your enterprise strategy.
0
Users Unaware of AI Data Use
0
Unaware of Opt-Out Rights
0
Participants Interviewed
0
Generative Insights for Governance
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
The 'Small Boat' Analogy: Navigating Powerlessness
Participants equated navigating Meta's policies to being 'in the middle of the sea in a storm and you find a small boat.' Despite high probability of the boat failing, it's 'better to get in and try to save yourself in the small boat than not to get in and drown in the storm.' This sentiment captures the essence of surrendering to powerlessness, highlighting the lack of capacity to act differently and the pervasive nature of Meta's products in daily life.
This illustrates the critical need for enterprises to provide clear, actionable, and user-centric data governance frameworks that acknowledge user agency.
80%
of users unaware of personal data use for AI training, highlighting a significant transparency gap.
Meta's GenAI Data Flow
User's Information (Training Data)
→
User's Inputs to Meta's AI
→
Meta's AI Outputs
→
Data Retention
| Dimension | Acceptable | Unacceptable |
|---|---|---|
| Identifiability |
|
|
| Privacy |
|
|
| Specificity |
|
|
| Labor |
|
|
| Category | Participants in LATAM (N=10) | Participants in the EU (N=10) |
|---|---|---|
| Prior Knowledge (Meta's Data Collection) | 2/10 | 2/10 |
| Prior Knowledge (Privacy Policy Update) | 1/10 | 3/10 |
| Opting-Out (Prior to Interview) | 0/10 | 1/10 |
| Opting-Out (During Interview) | 7/10 | 6/10 |
Shifting Power: Data Activism Strategies
The paper proposes three strategies for individuals to leverage their data and shift power imbalances with tech giants: Opt-Out Strikes (actively withdrawing consent), Relational Data Poisoning (contributing harmful or altered data to prevent non-consensual use), and Conscious Data Labor (transferring data to platforms where value can be derived or monetized). These approaches aim to empower individuals beyond passive acceptance, offering avenues for reclaiming agency in a GenAI-driven world.
Calculate Your Potential AI Impact
Estimate the efficiency gains and cost savings your enterprise could achieve with a tailored AI implementation strategy.
Potential Annual Savings
$0
Hours Reclaimed Annually
0
Your Enterprise AI Implementation Roadmap
A structured approach to integrating advanced AI into your business, from strategy to sustainable growth.
Strategic Assessment & Planning
Comprehensive analysis of current workflows, identification of AI opportunities, and development of a tailored implementation roadmap aligned with your business objectives.
Data Governance & Infrastructure Setup
Establishing robust data privacy protocols, preparing and integrating existing datasets, and setting up scalable AI infrastructure to support model development and deployment.
Custom Model Development & Training
Designing, developing, and training bespoke AI models using your enterprise data, with continuous iteration and refinement for optimal performance and ethical considerations.
Integration & Deployment
Seamless integration of AI models into your existing systems and applications, followed by careful deployment and monitoring to ensure smooth operation and minimal disruption.
Performance Monitoring & Optimization
Ongoing monitoring of AI model performance, regular updates, and continuous optimization to adapt to evolving business needs and maximize long-term ROI.
Ready to Navigate the Future of AI?
Schedule a free consultation with our AI specialists to discuss how these insights apply to your enterprise and how we can tailor a powerful, ethical AI strategy for you.
Ready to Get Started?
Book Your Free Consultation.
Let's Discuss Your AI Strategy!
Lets Discuss Your Needs
Select a Date
Sun
Mon
Tue
Wed
Thu
Fri
Sat