Abstract: High quality, trustworthy data can help organizations build strategies, capture value, increase the potential of automation and enable insightful and fast decision-making. Data could change the cities we inhabit through real-time solutions to challenges such as traffic congestion, air quality, energy distribution and monitoring. Data could enable us to be more effective, efficient, sustainable. Data is already changing the world one industry at a time. Despite this potential, research shows that as few as 10 per cent of companies are attempting to put data and artificial intelligence to work across their businesses. Some industries such as telecommunications, automotive and financial services are doing relatively well catching up with the level of maturity seen in information and communication technologies, while others such as health care, education, government, and construction are still not close to realizing the full potential of data. Adopting data-oriented approaches is a destination, yet one cannot reach that point without taking the journey. This journey requires companies to curate, collect, assess, operationalize, analyze, visualize and algorithmize data. The process can be long, and new skill sets and perspectives are necessary – as well as investment – for a successful application. However, the opportunities are as limitless as the change is inevitable. Data is often referred to as “the new oil”. I always found this metaphor a bit scary. Today we are, on one hand, grateful for the changes that oil fueled. Yet on the other hand, one of the world’s biggest struggles today is waste from this revolution – the climate change. Now that we are at the beginning of a new era, which many call the fourth industrial revolution, it is vital to understand how data-related decisions of today can affect the future and minimize waste from the start. Therefore, it is essential to acquire the fundamentals of data, know how it will be useful for our industry and learn the lessons of other industries to avoid repeating their mistakes. To this end, our strategy should be not only collecting data but collecting the right amount of data for the right purpose, instead of collecting data without a well-defined objective. This requires companies to ask important questions, put initial data management plans in action and continuously check the quality of the data. To enable sustainable, optimized decisions we need not only our data but also data from others. Thus, discussions on how to integrate and share data are more important than ever. If the traditional companies which could benefit most from data and artificial intelligence want to be able to compete, profit and help to build a sustainable world, the decision makers must start embracing data, hire the right people and put in place the required policies to gather the correct data, make it accessible and assess its quality. Only in this way will our industry be in a position to truly take advantage of the next industrial revolution.
Date and Time: : April 8, 2021, 14:00-15:00
Short bio: Dr. Didem Gürdür Broo is an experienced researcher who is trained as a computer scientist. She holds MSc in computer science and PhD degree in mechatronics. Currently, she is a research associate at the University of Cambridge. She is with the Center for Smart Infrastructure, Laing O'Rourke Centre for Construction and Technology, and the Center of Digital Built Britain. Her current research interest is on data science for cyber-physical systems such as collaborative robots, autonomous vehicles and smart cities. She strongly advocates the importance of transdisciplinary, collaborative research. Her research focuses on blending systems thinking, future studies and design thinking approaches to develop methods, methodologies and implementations for the purpose of overcoming interoperability, complexity and sustainability challenges related to cyber-physical systems. Dr. Didem Gürdür has been granted prestigious Marie Skłodowska-Curie Global Fellowship to conduct research on her own project on human-centred and sustainable cyber-physical systems at Stanford University starting from September 2021. She has been granted IEEE Senior Membership due to her significant performance and excellence over the last five years. She is a data champion of the University of Cambridge, a member of European AI Alliance, and Women in AI Ethics. She actively contributes to the discussions of all aspects of data, artificial intelligence and their impact on the society.