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Written by Adam Huenke
Having conducted intelligence collections and open-source intelligence (OSINT) for a combined 20 years, one of the most pressing issues today is how to effectively incorporate artificial intelligence (AI) into the intelligence cycle, particularly in the data collection phase. As the power and scope of AI expand, questions around the ethical use of publicly available data have taken center stage. One of the key concerns is how AI-enabled tools impact individual privacy when harvesting open-source information. That issue, and the broader challenge of balancing data collection with privacy rights, is the focus of this blog.
In a hyper-connected world, AI has transformed how security is conducted. From facial recognition to behavior prediction, AI's power stems largely from its ability to process enormous amounts of data, much of it drawn from OSINT. Governments, corporations, and cybersecurity entities increasingly rely on publicly accessible data to detect threats, monitor risks, and identify malicious actors. However, this convenience and efficiency come at a steep cost: the erosion of personal privacy. This tension lies at the heart of what is now known as the privacy paradox.
The privacy paradox refers to the inconsistency between people's desire for privacy and their online behavior. While individuals claim to care deeply about safeguarding their personal data, they often freely disclose it on social media, forums, and public platforms. The problem today is not just what we willingly post, but what AI and OSINT tools can infer from those breadcrumbs. What was once scattered and relatively harmless is now aggregated, contextualized, and monetized, often without consent or awareness.
AI + OSINT: When Public Data Becomes Deep Surveillance
AI has dramatically changed the rules of data engagement. With the ability to process and correlate data at scale, AI-enabled systems turn trivial details into highly accurate behavioral models. This amplification effect means that even innocuous public data can now fuel precision-targeted surveillance.
A January 2025 report from AI+ Info, titled "AI and OSINT: New Threats Ahead," explains how modern AI tools scrape and analyze everything from geotagged photos to old resumes. The data is then used to identify movement patterns, affiliations, and even potential future behavior. The report warns that this automation of inference has created "a level of personal visibility that exceeds traditional surveillance methods."
In this context, privacy doesn't just diminish, it disappears. The difference lies in scale and intent. Human investigators once had to spend hours correlating bits of data. AI does it in seconds, across millions of records, often without oversight or ethical guardrails.
Weaponizing the Public Domain
The problem isn't limited to state actors. Private companies are commercializing OSINT tools to sell intelligence profiles to law enforcement, marketers, and foreign governments. In a July 2024 investigative article for The Mackenzie Institute, journalist John P. Ruehl revealed how companies like Palantir and Babel Street are using open-source information for both military and commercial intelligence purposes. Ruehl writes, "The fusion of OSINT with machine learning enables a surveillance apparatus that’s no longer confined to authoritarian regimes, it's going mainstream."
This commodification of open data transforms it into a tool of mass profiling. For example, platforms that mine LinkedIn, Facebook, Reddit, or even GitHub can compile dossiers for everything from background checks to credit scoring, often without the individual’s knowledge or ability to contest the data.
Legal and Ethical Blind Spots
Current privacy laws are ill-equipped to deal with this new reality. According to Edward Millett and colleagues in their 2023 paper for the Security and Human Rights Monitor, international legal frameworks have failed to account for the "doctrinal gap" created by automated OSINT. Their research argues that while open-source data might be publicly available, its collection, aggregation, and repurposing by AI can still violate rights to privacy and data protection.
The authors warn that "mass open-source surveillance, even when seemingly legal, threatens the fundamental right to privacy if left unregulated." The same concern is echoed by a 2023 policy brief from About:Intel, which highlights the lack of oversight in automated OSINT deployments by Western intelligence agencies.
Striking the Balance: Security Without Sacrifice
None of this is to suggest that AI or OSINT are inherently harmful. They are powerful tools that have undeniably improved national security, cyber defense, and threat intelligence. But the unchecked deployment of these technologies poses existential questions for liberal democracies.
To navigate the privacy paradox, we must build systems that prioritize both security and individual rights. Here are four actionable solutions:
Conclusion: A New Social Contract
The privacy paradox is not just about our behavior; it is about our systems. AI and OSINT have the potential to enhance security in ways once thought impossible. But when left unchecked, they also risk turning societies into surveillance ecosystems where privacy is a myth.
To preserve our rights in an AI-driven age, we must demand greater transparency, stronger legal safeguards, and ethical data practices that recognize the blurred line between public and private. Open-source does not mean open season.
References:
- AI+ Info (2025). AI and OSINT: New Threats Ahead
- Ruehl, J. (2024). Open-source information fueling new age of war. The Mackenzie Institute.
- Millett, E., et al. (2023). Open-Source Intelligence, Armed Conflict, and the Rights to Privacy. Security and Human Rights Monitor.
- About:Intel. (2023). Privacy and Automated OSINT.
