White Paper
February 22, 2024
Rethinking Privacy in the AI Era: Policy Provocations for a Data-Centric World

Jennifer King, Caroline Meinhardt

Executive Summary

➜ In this paper, we present a series of arguments and predictions about how 
existing and future privacy and data protection regulation will impact the 
development and deployment of AI systems.

➜ Data is the foundation of all AI systems. Going forward, AI development will 
continue to increase developers’ hunger for training data, fueling an even 
greater race for data acquisition than we have already seen in past decades.

➜ Largely unrestrained data collection poses unique risks to privacy that 
extend beyond the individual level—they aggregate to pose societal-level harms 
that cannot be addressed through the exercise of individual data rights alone.

➜ While existing and proposed privacy legislation, grounded in the globally 
accepted Fair Information Practices (FIPs), implicitly regulate AI development, 
they are not sufficient to address the data acquisition race as well as the 
resulting individual and systemic privacy harms.

➜ Even legislation that contains explicit provisions on algorithmic 
decision-making and other forms of AI does not provide the data governance 
measures needed to meaningfully regulate the data used in AI systems.

➜ We present three suggestions for how to mitigate the risks to data privacy 
posed by the development and adoption of AI:

1. Denormalize data collection by default by shifting away from opt-out to 
opt-in data collection. Data collectors must facilitate true data minimization 
through “privacy by default” strategies and adopt technical standards and 
infrastructure for meaningful consent mechanisms.

2. Focus on the AI data supply chain to improve privacy and data protection. 
Ensuring dataset transparency and accountability across the entire life cycle 
must be a focus of any regulatory system that addresses data privacy.

3. Flip the script on the creation and management of personal data. 
Policymakers should support the development of new governance mechanisms and 
technical infrastructure (e.g., data intermediaries and data permissioning 
infrastructure) to support and automate the exercise of individual data rights 
and preferences.

https://hai.stanford.edu/white-paper-rethinking-privacy-ai-era-policy-provocations-data-centric-world
_______________________________________________
nexa mailing list
[email protected]
https://server-nexa.polito.it/cgi-bin/mailman/listinfo/nexa

Reply via email to