Robots and the Future of Libraries and Archives
Overview Robotic innovations offer unprecedented growth potential for libraries and archives globally. By 2026, the library automation service systems market is projected to reach $2.80 billion, indicating a compound annual growth rate (CAGR) of 3.3%. Association for Information Science and Technology survey results show that up to 36% of librarians have reported an increased demand for digital services during the COVID-19 pandemic. Using advances in Artificial Intelligence (AI) and machine learning, libraries, and archives can provide automated and efficient processes. In the future, 35% of skills that workers need—regardless of the industry—will have changed, according to the World Economic Forum.
The Role of AI and Machine Learning in Libraries and Archives Modern digital libraries and archives are leveraging AI and machine learning to enhance search capabilities and access to collections. Both these technologies analyze massive amounts of data to identify patterns and trends, enabling precise, contextual searches, leading to more accurate results. A 2019 Emerald Insight study found that 90% of data in the digital universe is unstructured, making it increasingly difficult for humans to process and understand. AI and machine learning, integrated into library systems, are key to managing and making sense of these vast, unstructured datasets.
Automation and Efficiency in Library Processes Robotic process automation (RPA) is another technological advancement improving efficiency in libraries and archives. Intelligent automation can enhance inventory management, automate check-in and checkout processes, and manage data entry tasks. According to the Global Market Insights, nearly 30% of administrative tasks can be automated using RPA, freeing up librarians to focus on higher-value tasks, such as providing personalized service to readers and conducting research.
Emergence of Robotic Libraries The concept of the robotic library has started to take shape, with many institutions already employing automated systems. In the University of Chicago's Joe and Rika Mansueto Library, an automated retrieval system (ARS) handles books storage and retrieval, saving significant space and time. The ARS can retrieve any of the library's 1.5 million volumes in under 5 minutes. Additionally, circulating collections in some libraries have reached 95% thanks to automation.
Adapting to the Changing Skill Set Requirements As high-tech innovations permeate libraries and archives sector, the skills required for library professionals are evolving. According to a World Economic Forum report, by 2030, an estimated 37% of labour market skills could be changed. For librarians, skills in data analysis, artificial intelligence, and robotics will become increasingly important. The American Library Association reports that there is already a 51% increase in demand for librarians with capabilities in programming and data analysis in the past five years.
Key Takeaways - Libraries and archives sector is leveraging AI and machine learning to enhance inventory and data management, leading to more efficient services. - The advent of robotic libraries promises enhanced user experiences, efficient space utilization and time-saving retrieval processes. - Changing market dynamics require librarians to upskill, with increasing demand for skills in AI, machine learning, and data analysis.
3Laws Robotics is well-positioned to support the above use cases by developing innovative software aimed at enhancing the safety and reliability of robotic systems. 3Laws Supervisor is designed to streamline certification processes, a common challenge in the robotics industry.
Based on Control Barrier Functions technology developed at Caltech, it provides mathematically provable safety. This technology has already resulted in increased operational efficiency in industries like warehouse automation, with cases of achieving a 40% efficiency gain and a 6-month payback period.
Within dynamic environments like libraries, 3Laws Supervisor can offer robust safety features, minimize system downtime, and enable effective navigation in unpredictable surroundings. The software, adaptable and compatible with various platforms such as mobile robots, cars, drones, and manipulators is the future of safety solutions in the robotics industry.
Beyond traditional emergency stop methods, 3Laws enables proactive safety strategies, unlocking the full potential of robotics with dynamic, predictive safety. Enhancing user experiences, the technology aligns perfectly with the future needs of libraries and archives.