(Feb News) 3 June 2025 - On Tuesday, the Faculty of Economics and Business, Universitas Airlangga officially opened The 9th International Conference and Ph.D. Colloquium for Economics and Business (9th ICEB). The international conference which lasted for two days brought together academics, researchers, and practitioners from various countries in a strategic discussion forum on global issues in the fields of economics and business.
One of the sessions that attracted the attention of participants was scientific material themed "Building a Sustainable Digital Economy" delivered by Professor Pedro R Palos Sanchez. In his presentation, he raised a visionary approach to the future of digital technology that emphasized the sustainability, social justice, and strengthening global ethical policies.
In his presentation, Professor Pedro R Palos Sanchez explained that machine learning (machine learning) is the main foundation of digital intelligence that allows computers to learn from data and improve performance without explicit programs. This is different from the traditional AI system because Machine Learning is able to adapt based on experience through the training process and data testing.
He said that this technology can be utilized in various fields, such as satellite observation, anomalous detection, natural disaster predictions, climate change, and greenhouse gas emissions. For example, the Machine Learning system is able to identify deforestation patterns and help mitigate the impact of climate change through large data analysis (big data).
Professor Pedro R Palos Sanchez stressed that this technology has been applied in satellite images to detect deforestation patterns, climate change, and greenhouse gas emissions, and is used in smart grid systems, smart buildings, and smart transportation that support the circular economy in various countries. "Machine learning allows the system to develop independently through experience, not only based on fixed instructions from traditional programming," he said.
In real practice, the research team collaborated with Ecosia - an environmentally friendly seeker engine - which planted around 1,000 trees for every one million searches, of which 80% of them were superior plant species. In addition, the use of drones, spectral photogrammetry, and cloud computing are also discussed as a solution in monitoring forest and land fires in real-time. According to him, "By utilizing large data, we can advance water conservation, references, and management of environmental resources efficiently."
Professor Pedro also underlined important challenges, such as digital access inequality-only 27% of the population in developing developing countries, compared to 36% in developed countries-as well as issues of privacy and bias algorithms. Regulatory efforts, such as Artificial Intelligence Act in Europe, are very important to ensure the use of large data still respect individual rights and minimize systemic discrimination.
As a further step, Professor Pedro R Palos Sanchez encouraged the need for inclusive policies and education that combined machine learning and digital technology for all communities. He stressed that the future of the digital economy must be built on the foundation of global cooperation between sectors, equal digital infrastructure, and strong ethical standards. "Digital technology is not just an efficiency tool, but a motorbike of sustainable sociological changes," he concluded.
