The challenge of generating new value for the data economy

GMV y el reto de impulsar el nuevo valor de la economía del dato

In our current context, data is the focal point of the major transformations that are taking place in our society as a result of applying new digital technologies. For this reason, it will be impossible for any digital economy to become fully established and compete globally unless it has a solid data economy. This is why our goal in Spain, and in Europe as a whole, is to create a single market for data, where both personal and non-personal data, including sensitive business data, will be secure, so that companies can be given access to high-quality industry data as a way to drive growth and create value.

At the AMETIC Artificial Intelligence Summit 2023, José Carlos Baquero, GMV’s Manager of Artificial Intelligence and Big Data, participated in a session entitled “The new value of the data economy”, where he explained the benefits and key elements of combining data spaces and artificial intelligence (AI). He also discussed other subjects such as the associated regulations and mechanisms needed to ensure that data can flow with security and privacy, and some of the obstacles that will have to be overcome when implementing data spaces.

To put all of this in context, it is estimated that about 45 TB of data were needed just to train the ChatGPT 3 model. Much of that data is taken from information existing on the Internet, which in itself presents challenges in relation to safeguarding privacy and intellectual property. This is a fact that highlights the need for federated governance of data ecosystems, such as data spaces, to allow sharing of data in a secure and controlled manner. The aim is to grow the data economy in a sustainable way, in the context of increasing demands for data for AI systems and the challenges related to privacy and intellectual property.

At GMV, we know that data spaces, together with AI, have the potential to drive the data economy, by allowing secure and controlled sharing of data. In turn, this will generate business opportunities and economic growth. Data spaces also facilitate data interoperability, including at the semantic level. This is done by adopting a standardized architecture model, which makes it easier to understand and use data in different contexts, for a variety of applications. For example, as part of the AgrarIA project, we are working on developing and implementing a data space for the agriculture industry. The aim is to produce a single platform that combines a variety of cross-cutting technologies, which can be put to a variety of uses across the food and agriculture value chain: production, transformation, and distribution. These data spaces will allow for voluntary sharing of data, under a system of common governance and security mechanisms, as a way to make the food and agriculture industries more technological, innovative, and sustainable.

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