algoritmos

In the policies promoted by the European Union, an intimate connection between artificial intelligence and open data has been considered. In this regard, as we highlighted, open data is essential for the proper functioning of artificial intelligence, since the algorithms must be fed by data whose quality and availability is essential for its continuous improvement, as well as to audit its correct operation.

Artificial intelligence entails an increase in the sophistication of data processing, since it requires greater precision, updating and quality, which, on the other hand, must be obtained from very diverse sources to increase the quality of the algorithms results. Likewise, an added difficulty is the fact that processing is carried out in an automated way and must offer precise answers immediately to face changing circumstances. Therefore, a dynamic perspective that justifies the need for data -not only to be offered in open and machine-readable format, but also with the highest levels of precision and disaggregation- is needed.

This requirement acquires a special importance as regards the accessibility of the data generated by the public sector, undoubtedly one of the main sources for algorithms due to both the large number of available data sets and the special interest of the subjects, especially public services. In this regard, apart from the need to overcome the inadequacies of the current legal framework regarding the limited scope of the obligations imposed on public entities, it is convenient to assess what extent the legal conditions in which data are offered serve to streamline the development of applications based on artificial intelligence.

Thus, in the first place, article 5.3 of the Law states categorically that "public sector administrations and organizations may not be required to maintain the production and storage of a certain type of document focused on its reuse". Taking into account this legal forecast, the aforementioned entities can rely on the absence of an obligation to guarantee the supply of data indefinitely. Also in the limitation of liability contemplated by some provisions when stating that the use of the data will be carried out under the responsibility and risk of the users or reuser agents or, even, the exoneration for any error or omission that is determined by the incorrectness of the data itself. However, it is an interpretation whose effective scope in each specific case has to be contrasted with the demanding European regulation related to the scope of the obligations and the protection channels, in particular after the reform that took place in the year 2013.

Beyond an approach based on strict regulatory compliance from a restrictive interpretation, the truth is that the need to offer open data policies for the public sector to meet the unique demands of artificial intelligence requires a proactive approach. In this sense, the interaction between public and private subjects in contexts of systematic data measurements and collection, continuously updated from generalized connections - as is the case of smart city initiatives - places us in front of a technological scenario where active contractual management policies acquire a special importance in order to overcome the barriers and legal difficulties for its opening. In fact, municipal public services are often provided by private parties that are outside the reuse regulations and, in addition, data are not always obtained from services or objects managed by public entities; even in spite of the general interest underlying in areas such as electricity supply, the provision of telephony and electronic communications services, or even financial services.

For this reason, the initiative launched by the European Union in 2017 acquires a singular importance from the perspective of artificial intelligence, since it aims to overcome a large part of the legal restrictions currently in place for data opening. In the same sense, the Spanish Strategy of R & D in Artificial Intelligence, recently presented by the Ministry of Science, Innovation and Universities, considers as one of its priorities the development of a digital data ecosystem whose measures include the need to guarantee an optimal use of open data, as well as the creation of a National Data Institute in charge of the governance of the data coming from the different levels of the Public Administration. Likewise, in line with the European initiative previously referred, among other measures, there is a need to expand the sharing obligations of up to certain private entities and scientific data, which would undoubtedly have a relevant impact on the better functioning of the algorithms.

The technological singularity that Artificial Intelligence poses requires, without a doubt, an adequate ethical and legal framework that allows facing the challenges that it entails. The new Directive on open data and reuse of public sector information recently approved by the European Parliament will be a strong impulse for artificial intelligence, as this initiative will expand both the obligated parties and the type of data that will have to be available. Undoubtedly a certainly relevant measure, which will be followed by many others within the framework of the European Union's strategy on Artificial Intelligence, one of whose main premises is to ensure an adequate regulatory framework to facilitate technological innovation based on respect for fundamental rights and the ethical principles.

Content prepared by Julián Valero, professor at the University of Murcia and Coordinator of the Research Group "Innovation, Law and Technology" (iDerTec).

Contents and points of view expressed in this publication are the exclusive responsibility of its author.

Betterplace is a technology company specializing in Location Intelligence, whose technology extracts and analyzes business information that, combined with public and private data, helps users to optimize time and resources in their day-to-day business. In his own words: "we turn tables into maps to guide decision-making".

The amount of data we generate does not stop growing. 90% of the data created in the history of humanity were produced during the last year and a 40% annual growth is estimated for the next decade. These figures highlight the importance of data in today's economy and society. The data provide us with knowledge, which facilitate to make the right decisions at the right time.

To optimize the advantages that the use of data can bring to our day to day, an increasing number of organizations and companies are implementing new technologies that help to improve their management and obtain greater value. The report New trends and challenges in the data world analyzes some of these technological and social trends that are revolutionizing the world of data. These technologies are big data and artificial intelligence, decision algorithms, internet of things and blockchain.

The following are some of the main conclusions of the report:

Big Data and Artificial Intelligence

• What is it? The analysis of large volumes of data, from different sources and with different formats, in real time, acquires a new dimension combined with artificial intelligence technologies, which apply reason guidelines to data.
• What are its advantages? Thanks to these technologies, companies and organizations can better understand the current and future functioning of their environment, and face the challenges at the right time. The combination of Artificial Intelligence and Big Data can boost economic growth, respond to citizens needs and optimize public services. In addition, it can contribute to the strengthening of democracy.
• What are its challenges? The lack of talent with the necessary skills, the limitation in current infrastructures and the privacy protection are the main challenges that organizations have to face when implementing a Big Data initiative.

The decision algorithms

• What is it? These are automated agents capable of extracting value from a large volume of data in an agile and efficient way, facilitating automatic decision making.
• What are its advantages? Decision algorithms allow more efficient, transparent and equitable decision making.
• What are its challenges? Among the challenges faced by people in charge of algorithms management is ensuring the quality and availability of data through controls and audits, as well as ensuring their integrity, ethics and independence.

Internet of Things

• What is it?  When we talk about Internet of Things (IoT) we refer to a network of connected objects, by wireless or cable, capable of generating data without human intervention.
• What are its advantages? IoT facilitates processes automation and provides new and multiple forms of interaction that contribute to improving universality and accessibility to services.
• What are its challenges? The main inhibitors of IoT are security and privacy, interoperability and the need for new infrastructures. It is also important to bear in mind that IoT can contribute to increasing the existing gap between different social classes according to their possibilities of data and services access.

Blockchain

• What is it? Blockchain is a distributed database that controls the transfer of digital information. That is, a kind of account book where the records are encrypted and interleaved, so change in one of the blocks affects the others.
• What are its advantages? Its main advantage is the security and privacy of information, the integrity, the sustainability, the transparency and the (quasi) anonymity. This will allow us to transform our political system and enable profound social changes.
• What are its challenges?
• The lack of qualified talent, the regulatory changes, the electronic security of citizens and the limits on institutions ability to adapt the new enviroment are the main challenges highlighted in the report.

Thanks to Big Data and artificial intelligence, decision algorithms, Internet of Things or Blockchain, organizations and companies can extract the necessary value from the data, which will help them to improve services and products for citizens. Although these four technologies are still in a phase of incipient adoption, they are expected to grow rapidly over the next few years, once the above-mentioned challenges are overcome - if you want to delve into these challenges you can read the report New trends and challenges in the world of data.

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