The Shift in Data Collection and Management by Tech and Public Companies
Many data- and AI-centric technology and public companies increasingly recognize that personal data is becoming more of a liability than an asset.
In the US and now globally, personal data collected from electronic interactions is often traded without genuine informed consent. Companies are growing wary of technologies and business models that exploit rather than enhance user experiences and personalization. As a result, industry executives and board directors are reassessing their use of third-party cookies and emphasizing safety-by-design principles to avoid ethical issues later.
Why now? What’s changed?
There are several reasons technology and public companies are rethinking their collection and use of personal data:
Public Awareness: Increasing public awareness of data privacy issues, highlighted by high-profile breaches, has fueled consumer demands for transparency and control, pushing companies to prioritize ethical data practices.
Technological Advancements: Advanced encryption methods and differential privacy enable companies to collect and use data to minimize privacy risks. Additionally, shifting consumer preferences towards privacy-focused products like Apple’s have compelled companies to reassess and often tighten their data practices to align with new legal, social, and market expectations.
AI has alerted users, particularly of generative AIs, to the risks of data leaking into large datasets used for training large language models (LLMs) and other applications. The ethical AI movement has raised awareness about these privacy issues caused by unregulated and open AI datasets, training, models, and applications.
Regulatory Compliance: Stricter data protection laws – such as the General Data Protection Regulation (GDPR) in the European Union and the California Consumer Privacy Act (CCPA) in the U.S. – impose stringent data collection, processing, and security rules. Companies are evaluating their data policies and practices and adapting to these laws to avoid heavy fines and legal issues.
Consumer Privacy Concerns: As public awareness of data privacy issues grows, consumers become more concerned about how their data is used. This shift in consumer sentiment pushes companies to adopt privacy-first policies to maintain trust and loyalty.
Competitive Differentiation: Companies are increasingly using privacy as a competitive differentiator. By promoting strong privacy protections, companies can distinguish themselves in markets where consumers are particularly privacy-conscious. A good example in the search engine space i DuckDuckGo, which has several products intended to help people protect their online privacy and recently gained market share.
Operational Risks and Costs: Managing vast amounts of personal data can be risky and costly, especially with the threat of data breaches. By minimizing data collection, companies can reduce the risk of data breaches and the associated financial and reputational damage.
Ethical Considerations: There's a growing recognition of the ethical implications of data collection and usage practices. Companies are considering the broader impact of their data practices on society and individual rights, leading to more ethical data practices.
The shift in how technology and public companies approach personal data collection and use reflects broader changes in society, regulations, and technology. It's part of an evolving landscape that data- and AI-centric startups should be aware of.