By Manish Sinha, Founder & CTO, PatSeer
The rise in digital platforms and the seamless exchange of information has brought attention to the importance of safeguarding trademarks and copyrighted content. As a result, protecting Intellectual Property (IP) rights has become increasingly complex. However, Artificial Intelligence (AI) offers hope in addressing these challenges. With the AI market expected to grow to $515.31 billion by 2023, its applications in various domains, including intellectual property protection, are becoming more evident.
In today’s world, where the digitalisation of content and commerce is the norm, the role of Artificial Intelligence (AI) in intellectual property protection has become increasingly vital. Stakeholders are integrating AI solutions to address IP infringements. Online marketplaces are adopting AI systems to combat the rising risk of unauthorised reproduction of copyrighted materials. The globalisation of commerce has also heightened cross-border intellectual property challenges, and for brand owners, a thorough search is required to be run across local marketplaces present in each country of interest.
The rapid increase in technological advancements and its corresponding rise in global patent filings have complicated the patent landscape similarly, although global patent databases such as PatSeer undertake the heavy lifting of aggregating worldwide data, translating it, and making it available through a unified search interface, making the task a bit easier.
Faced with these challenges, the use of AI technologies has emerged as a promising solution to strengthen IP protection strategies.
AI-Powered Search and Monitoring Systems:
Redefining Detection Capabilities for Trademark and Copyright Owners Detection capabilities in intellectual property enforcement have been redefined by AI-powered monitoring systems. These innovative systems can perform automated searches and monitoring over vast amounts of online data, such as websites, social media, and online marketplaces. They further employ AI computer vision algorithms to detect logos, trademarks, and other visual elements, efficiently flagging unauthorised use of trademarks in the images and multimedia content present on the web. Research studies have validated the effectiveness of AI-driven tools and technologies in improving the efficiency of identifying potential infringements, underscoring the crucial role played by AI in enhancing detection accuracy.
The adoption of AI algorithms for identifying infringements has significantly influenced the evolution of enforcement tactics. AI-driven detection agents are now integral components of anti-IP infringement strategies, reflecting the widespread recognition of their effectiveness.
In a recent example, a leading e-commerce platform employed ML algorithms to identify trademark infringements precisely. The system was trained to analyse global listings and segregate images uploaded by sellers, utilising existing databases that encompass registered logos, brands, and product designs, among other identity markers. This screening process enabled the system to flag products with similar intellectual designs, and upon infringement detection, the AI and ML systems triggered takedown requests by alerting relevant bodies to take necessary action. Swift response measures reduced the impact infringements could have on original products and content consumption.
In the software industry, AI-based pattern recognition techniques are used in source code analysis tools to detect potential copyright violations in software. To achieve this, a machine learning model is first created on the code for the company’s software, and this is then used for pattern recognition on the target software to identify areas of overlap. Companies also use such tools to detect if any open-source code has been copied into their product’s code.
AI-Driven Analytics:
Empowering Global Enforcement Strategies AI-driven analytics helps take monitoring a step towards enforcement. AI tools can analyse large datasets of existing IP infringements to identify trends, emerging threats, and potential hotspots, and this information helps brand owners develop better enforcement strategies. AI-driven predictive analytics allows insights into potential future trademark violation risks that can further be used for risk assessment or setting up preemptive measures. An additional advantage here is that these solutions transcend boundaries and can analyse global datasets, enabling IP enforcement beyond a single country. Global dataset availability combined with integrated AI analysis facilitates collaborative efforts and aids in navigating international legal landscapes for effective cross-border enforcement.
Generative AI tools further help automate certain aspects of the enforcement process. For instance, AI tools can send cease and desist notices or prepare legal action drafts, thereby speeding up the task of enforcement itself.
Human Expertise and AI:
Optimising Decision-Making With the increasing use of AI in trademark or copyright enforcement, it is important to note that while AI can be a valuable time and cost-saving tool, it may not be perfect, and human oversight is usually necessary to review and validate the final set of results before taking action.
The right mix of human expertise with AI is important for accurate and efficient decision-making in these activities and is necessary for navigating complex IP infringement cases.
Addressing Challenges and Ethical Considerations in AI-Driven Enforcement
AI-driven enforcement encounters persistent challenges, such as potential biases in algorithms and the delicate balance between enforcement and free expression.
To mitigate biases, industry leaders focus on creating diverse and representative datasets for algorithmic training, but the risk of bias is difficult to eliminate, especially in models that are self-learning. Ongoing debates also revolve around the ethical implications of AI in IP enforcement. However, the evolving landscape of AI displays promising trends, including predictive modelling for the preemptive identification of infringement patterns and the integration of emerging technologies.
Concerns regarding privacy implications and transparency in decision-making persist, highlighting the need for human supervision to ensure the ethical use of AI in IP protection.
AI has made a transformative impact on intellectual property enforcement strategies to adapt to the digital era. Collaborative efforts between AI technologies, legal professionals, and policymakers are essential for effective IP protection. As AI continues to evolve, its role in reshaping enforcement strategies will remain profound, ushering in an era marked by enhanced precision, adaptability, and efficiency.
