I focus on developing evidence-based policies on the contribution of science, technology and industry to well-being and sustainable growth. My activities cover a broad range of topics, including industry and globalisation, innovation and entrepreneurship, scientific R&D and emerging technologies.
Rapid urbanization is leading to smarter cities that improve the lives of citizens through technology. A smart city is a framework, predominantly composed of Information and Communication Technologies (ICT), to develop, deploy, and promote sustainable development practices to address growing urbanization challenges.
Fintech is a portmanteau of the terms “finance” and “technology” and refers to any business that uses technology to enhance or automate financial services and processes. From mobile banking and insurance to cryptocurrency and investment apps, FinTech has broad applications and intense competition at global stage.
Artificial intelligence (AI) AI is the capability of machines to imitate intelligent human behavior, and perform tasks that normally require humans. Machine learning (ML) is a subset of AI that gives computers the ability to learn without being explicitly programmed.
Governance is the systems and processes that ensure the overall effectiveness of an entity – whether a business, government or multilateral institution. Data governance is a system for defining who within an organization has authority and control over data assets and how those data assets may be used.
Sustainability is based on a simple principle: Everything that we need for our survival and well-being depends, either directly or indirectly, on our natural environment. To pursue sustainability is to create and maintain the conditions under which humans and nature can exist in productive harmony.
Decentralization is the process of dispersing decision-making governance closer to the people or citizen. It includes the dispersal of administration or governance in sectors or areas like management science, political science, education, sociology and health care. Decentralization is also possible in the dispersal of population and employment.
The current mode of governance and development where national economies compete through building stronger innovation systems while the major economic players operate at the global level is unsustainable. Equally unsustainable is to put innovation policies exclusively at the service of economic growth and competitiveness, ignoring broader societal and environmental concerns.
Innovation policy needs to become transformative, transnational, and decentralized. The more decentralized a system is, the more it relies on lateral relationships, and the less it can rely on command or force.
The movements are a key actor both in the functioning and in the socio-political transformations of contemporary democracies toward collective yet decentralized societies. They themselves are undergoing profound changes as a result of the proliferation of practices associated with technology and power. As a result, new forms of construction, consensus, and collective intelligence emerge.
Data Science
To build a framework for operational analytics. To theorize, analyze and contribute to the construction of technopolitical autonomy, that is, relationships with and through technologies that promote new forms of freedom and creativity, both personal and collective. To examine distributed architecture technologies that allow users to retain full control over their data and the technologies they use, while promoting truly democratic and peer-to-peer collaborative economy models.
Political Science
To study the mechanisms involved and the methods used by different actors in the construction of public and political discourses. To build a framework and a digital infrastructure for participatory democracy. To analyze the limits, risks and possibilities of politics today. To build alternatives that allow us to advance towards a network society. To interrogate and build upon economic proposals for a collective yet decentralized society.
Cognitive Science
To understand causes. To represent more complex theories of decision making. To use a blend of artificial intelligence, neural networks, machine learning, natural language processing, sentiment analysis and contextual awareness. To design and implement the algorithms capable of solving problems. To analyze a situation effectively and revolutionize the current and legacy systems.
Interdisciplinary Science
To analyze biodiversity; improve access to safe drinking water; promote the responsible management of biotechnologies, drugs, and environmental resources; and ensure the ethical collection, management, and interpretation of data. And to build a global movement dedicated to reimagining the foundation of democracy and markets.
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