Noah Miller, MJLST Staffer
The concept of widespread surveillance of public areas monitored by artificial intelligence (“AI”) may sound like it comes right out of a dystopian novel, but key investments by the Department of Homeland Security (“DHS”) could make this a reality. Under the Biden Administration, the U.S. has acted quickly and strategically to adopt artificial intelligence as a tool to realize national security objectives.[1] In furtherance of President Biden’s executive goals concerning AI, the Department of Homeland Security has been making investments in surveillance systems that utilize AI algorithms.
Despite the substantial interest in protecting national security, Patrick Toomey, deputy director of the ACLU National Security Project, has criticized the Biden administration for allowing national security agencies to “police themselves as they increasingly subject people in the United States to powerful new technologies.”[2] Notably, these investments have not been tailored towards high-security locations—like airports. Instead, these investments include surveillance in “soft targets”—high-traffic areas with limited security: “Examples include shopping areas, transit facilities, and open-air tourist attractions.”[3] Currently, due to the number of people required to review footage, surveilling most public areas is infeasible; however, emerging AI algorithms would allow for this work to be done automatically. While enhancing security protections in soft targets is a noble and possibly desirable initiative, the potential privacy ramifications of widespread autonomous AI surveillance are extreme. Current Fourth Amendment jurisprudence offers little resistance to this form of surveillance, and the DHS has both been developing this surveillance technology themselves and outsourcing these projects to private corporations.
To foster innovation to combat threats to soft targets, the DHS has created a center called Soft Target Engineering to Neutralize the Threat Reality (“SENTRY”).[4] Of the research areas at SENTRY, one area includes developing “real-time management of threat detection and mitigation.”[5] One project, in this research area, seeks to create AI algorithms that can detect threats in public and crowded areas.[6] Once the algorithm has detected a threat, the particular incident would be sent to a human for confirmation.[7] This would be a substantially more efficient form of surveillance than is currently widely available.
Along with the research conducted through SENTRY, DHS has been making investments in private companies to develop AI surveillance technologies through the Silicon Valley Innovation Program (“SVIP”).[8] Through the SVIP, the DHS has awarded three companies with funding to develop AI surveillance technologies that can detect “anomalous events via video feeds” to improve security in soft targets: Flux Tensor, Lauretta AI, and Analytical AI.[9] First, Flux Tensor currently has demo pilot-ready prototype video feeds that apply “flexible object detection algorithms” to track and pinpoint movements of interest.[10] The technology is used to distinguish human movements and actions from the environment—i.e. weather, glare, and camera movements.[11] Second, Lauretta AI is adjusting their established activity recognition AI to utilize “multiple data points per subject to minimize false alerts.”[12] The technology generates automated reports periodically of detected incidents that are categorized by their relative severity.[13] Third, Analytical AI is in the proof of concept demo phase with AI algorithms that can autonomously track objects in relation to people within a perimeter.[14] The company has already created algorithms that can screen for prohibited items and “on-person threats” (i.e. weapons).[15] All of these technologies are currently in early stages, so the DHS is unlikely to utilize these technologies in the imminent future.
Assuming these AI algorithms are effective and come to fruition, current Fourth Amendment protections seem insufficient to protect against rampant usage of AI surveillance in public areas. In Kyllo v. United States, the Court placed an important limit on law enforcement use of new technologies. The Court held that when new sense-enhancing technology, not in general public use, was utilized to obtain information from a constitutionally protected area, the use of the new technology constitutes a search.[16] Unlike in Kyllo, where the police used thermal imaging to obtain temperature levels on various areas of a house, people subject to AI surveillance in public areas would not be in constitutionally protected areas.[17] Being that people subject to this surveillance would be in public places, they would not have a reasonable expectation of privacy in their movements; therefore, this form of surveillance likely would not constitute a search under prominent Fourth Amendment search analysis.[18]
While the scope and accuracy of this new technology are still to be determined, policymakers and agencies need to implement proper safeguards and proceed cautiously. In the best scenario, this technology can keep citizens safe while mitigating the impact on the public’s privacy interests. In the worst scenario, this technology could effectively turn our public spaces into security checkpoints. Regardless of how relevant actors proceed, this new technology would likely result in at least some decline in the public’s privacy interests. Policymakers should not make a Faustian bargain for the sake of maintaining social order.
Notes
[1] See generally Joseph R. Biden Jr., Memorandum on Advancing the United States’ Leadership in Artificial Intelligence; Harnessing Artificial Intelligence to Fulfill National Security Objectives; and Fostering the Safety, Security, and Trustworthiness of Artificial Intelligence, The White House (Oct. 24, 2024), https://www.whitehouse.gov/briefing-room/presidential-actions/2024/10/24/memorandum-on-advancing-the-united-states-leadership-in-artificial-intelligence-harnessing-artificial-intelligence-to-fulfill-national-security-objectives-and-fostering-the-safety-security/ (explaining how the executive branch intends to utilize artificial intelligence in relation to national security).
[2] ACLU Warns that Biden-Harris Administration Rules on AI in National Security Lack Key Protections, ACLU (Oct. 24, 2024, 12:00 PM), https://www.aclu.org/press-releases/aclu-warns-that-biden-harris-administration-rules-on-ai-in-national-security-lack-key-protections.
[3] Jay Stanley, DHS Focus on “Soft Targets” Risks Out-of-Control Surveillance, ALCU (Oct. 24, 2024), https://www.aclu.org/news/privacy-technology/dhs-focus-on-soft-targets-risks-out-of-control-surveillance.
[4] See Overview, SENTRY, https://sentry.northeastern.edu/overview/#VSF.
[5] Real-Time Management of Threat Detection and Mitigation, SENTRY, https://sentry.northeastern.edu/research/ real-time-threat-detection-and-mitigation/.
[6] See An Artificial Intelligence-Driven Threat Detection and Real-Time Visualization System in Crowded Places, SENTRY, https://sentry.northeastern.edu/research-project/an-artificial-intelligence-driven-threat-detection-and-real-time-visualization-system-in-crowded-places/.
[7] See Id.
[8] See, e.g., SVIP Portfolio and Performers, DHS, https://www.dhs.gov/science-and-technology/svip-portfolio.
[9] Id.
[10] See Securing Soft Targets, DHS, https://www.dhs.gov/science-and-technology/securing-soft-targets.
[11] See pFlux Technology, Flux Tensor, https://fluxtensor.com/technology/.
[12] See Securing Soft Targets, supra note 10.
[13] See Security, Lauretta AI, https://lauretta.io/technologies/security/.
[14] See Securing Soft Targets, supra note 10.
[15] See Technology, Analytical AI, https://www.analyticalai.com/technology.
[16] Kyllo v. United States, 533 U.S. 27, 33 (2001).
[17] Cf. Id.
[18] See generally, Katz v. United States, 389 U.S. 347, 361 (1967) (Harlan, J., concurring) (explaining the test for whether someone may rely on an expectation of privacy).