In a significant shift in its advertising policies, Google has adopted a more lenient stance towards fingerprinting, effective from February 2025. This change allows advertisers to track users across various digital platforms, including connected TVs (CTVs) and game consoles, by creating unique digital fingerprints linked to individual devices. Google attributes its updated approach to advancements in Privacy Enhancing Technologies (PETs), asserting that these technologies make device tracking more secure than in the past. However, its reversal on fingerprinting has incited concerns among industry professionals regarding privacy issues, particularly in areas with stringent data regulations.
Fingerprinting is a method of user identification that combines various signals and identifiers, such as IP addresses, to track users across different browsers and devices. It is commonly used for ad targeting, fraud detection, and cross-session tracking. Unlike cookies, which can be easily deleted by users, fingerprinting operates mainly at the server level, making it a persistent tracking mechanism that poses privacy challenges. Web-based fingerprinting usually employs JavaScript and HTTP requests to capture user signals, while mobile apps leverage software development kits (SDKs) to gather data directly from users’ devices.
In the light of its new ad policy, Google has positioned itself to capitalize on the growing CTV sector, where it has historically lagged compared to competitors. This strategic move may indicate a shift in how the company views fingerprinting—once marginalized—now perceived as vital for maintaining competitiveness in emerging ad spaces. Nevertheless, this appears to be in contradiction with Google’s previous attempts to curb fingerprinting, particularly with its ongoing initiatives like the Privacy Sandbox, which aims to mask IP addresses in third-party contexts to prevent unconsented tracking.
Critics assert that this increased reliance on fingerprinting raises significant ethical concerns. Since personal data used in advertising is subject to user consent, Google’s decision to embrace fingerprinting without stringent oversight can lead to inadvertent breaches of privacy. Moreover, while fingerprinting may serve as a tool for fraud detection, the lack of transparency about how data is collected and shared remains a pressing issue. Regulatory bodies and major tech entities like Apple continue to scrutinize the implications of fingerprinting, further complicating the landscape for advertisers and tech companies alike.
At the same time, in a report by GlobalData, 74% of businesses expressed concerns regarding the privacy and data integrity risks associated with artificial intelligence (AI), inhibiting its broader adoption. Furthermore, 59% of the businesses reported a lack of confidence in integrating AI within their organizations, with only 21% noting high or very high adoption levels. This hesitancy is reflected in the distrust around third-party AI tools due to perceived weaknesses in data safeguarding practices.
GlobalData’s report suggests that the failure of proprietary AI models to ensure transparency in data protection poses a major obstacle to wider adoption. This concern is further emphasized by a Cisco study on DeepSeek R1, a language model that demonstrated a 100% attack success rate against harmful prompts, indicating severe vulnerabilities in its security mechanisms. In stark contrast, leading LLMs like Meta’s Llama 3.1 and OpenAI’s ChatGPT-4o had significantly lower attack success rates of 96% and 86%, respectively. GlobalData highlights that these findings may deter businesses from implementing generative AI solutions due to reputational risks associated with deploying potentially harmful AI systems.
Despite these apprehensions, GlobalData is optimistic about the future of AI investment, emphasizing the practicality of reinforcement learning—a technique in which AI agents learn optimal decision-making based on feedback. However, as the landscape evolves, companies must remain vigilant in assessing their vendors’ use of fingerprinting and AI systems to maintain compliance with emerging data privacy laws.
As Google navigates its approach to fingerprinting amidst increasing scrutiny of digital tracking practices, it is imperative for advertisers and tech providers to grasp the implications of these changes thoroughly. While the quest for effective data-driven advertising continues, the overarching challenge will remain: balancing innovation and privacy in an increasingly interconnected digital world. Fingerprinting may offer potential advantages, but questions surrounding ethical practices must not be sidelined in the pursuit of competitive advantage.
