Context – Artificial-Intelligence.bz

Context in South Tyrol

In the province of Bolzano (South Tyrol) industrial and economic activities are in various sectors, including agriculture, automotive, energy production and distribution, manufacturing, construction, tourism, commerce and services. The production of customised, diverse, and serial products is supported by digital innovations, allowing for faster reactions to market changes and a more efficient organisation of the production process. The European Commission states that Smart Processing’s cornerstones are Artificial Intelligence, Internet of Things, Modelling and Simulation, Cloud Computing, and Big Data analysis. The digitisation of the economy and society represents a fundamental change that extends beyond the IT sector and affects traditional sectors as well. The abundance of available data (Big Data) not only increases efficiency, but also fosters the creation of new digital business models among companies. In the coming decades, radical advances and innovations in deep learning, computer vision, natural language processing, and robotics will change various fields of science and business, such as healthcare or enterprise data management.

In the Smart Specialisation Strategy (RIS3), the Autonomous Province of South Tyrol foresees the promotion and support of four main specialisation areas: Automation-Automotive and Smart Processing, Food and Life Science, Alpine Technologies, and Green Technologies. Transversal to the above specialisation areas, a number of strategic themes for South Tyrol have been identified as Big Data, Computer Vision, Natural Language Processing, Process Mining, Data Lakes and Data Redundancy, Cybersecurity, Education 4.0, Artificial Intelligence and Deep Learning, Predictive Analytics and Maintenance, and Business Analytics for Business Performance. Our laboratory is mostly focussed on the goals of the specific Smart Processing specialisation area, which for the next strategic period include increasing efficiency and sustainability, creating uniform data management, developing tools for data-driven process optimisation, digitising business processes, fostering cooperation between users and technology providers in South Tyrol, supporting start-ups and spin-offs, and creating technical knowledge.

In the context of the Digital Innovation Hub (DIH) of South Tyrol, the following strategic actions are being planned to establish the digital backbone to enable smart green regions by 2030: Internet of Things (IoT) and Data Collection, Open Data Hub for Data Sharing and Community, Artificial Intelligence and Data Processing.

Important research centres and local institutions contribute to create a research network that is vibrant, open and collaborative. These include: UniBZ, NOI Tech Park, EURAC, Covision Lab, Fraunhofer Italia, Laimburg Research Centre.

Context in Europe

The European approach to AI is based mainly on two documents, the “AI Act“ (2021) and the “Coordinated Plan on AI“ (2018, 2021), which provide a framework of principles and aims to promote a range of European efforts in developing AI excellence and innovation, while guaranteeing trust, safety and fundamental rights. The AI Act is the world’s first proposal for a legal framework regulating specific uses of AI while the Coordinated Plan on AI brings forward strategic alignment, policy action and acceleration of investment.

More specifically, the “Coordinated Plan on AI” is a strategic document developed by the European Commission that outlines a framework for the development and deployment of AI in the European Union. The plan represents the EU’s commitment to shaping the development of AI in a way that benefits society and fosters innovation and competitiveness. The plan focuses on three key areas of action: increasing investment in AI, fostering AI adoption and deployment, and ensuring that the development and deployment of AI is done in a manner that is human-centric and ethical. The plan proposes a range of actions, including increased investment in research and innovation, the development of a European AI ecosystem, the establishment of a European AI governance framework, and the promotion of digital skills and education. The plan also highlights, according to the so-called “quadruple helix approach” (https://op.europa.eu/en/publication-detail/-/publication/6e54c161-36a9-11e6-a825-01aa75ed71a1), the importance of collaboration between member governement, industry, academia, and civil society to ensure that the EU remains at the forefront of AI development while maintaining a high level of ethical and societal standards.

Moreover, the document “White Paper on Artificial Intelligence: A European approach to excellence and trust” (2020) outlines the European strategy for developing and deploying AI in a way that is both excellent and trustworthy. The white paper identifies three main pillars of action for the European Union: 1) fostering an ecosystem of excellence for AI, 2) ensuring an ecosystem of trust for AI, and 3) creating an enabling environment for the development and deployment of AI. To achieve the first pillar, the European Union intends to invest in research and innovation, encourage the development of AI skills and talents, and foster the growth of startups and SMEs. The second pillar focuses on ensuring that AI is used in a responsible and ethical way, protecting fundamental rights and values, and ensuring safety and security. The third pillar aims to create a regulatory framework that is flexible and innovation-friendly, while still addressing the potential risks and challenges of AI.

The white paper also includes a series of proposals for future EU legislation on AI, including the creation of a legal framework for high-risk AI applications, the establishment of a European AI board to oversee the development and deployment of AI, and the development of an EU-wide system of testing and certification for AI technologies.

Through the Horizon Europe and Digital Europe programs, the Commission plans to invest €1 billion per year in AI. With a total of €134 billion at its disposal, the Recovery and Resilience Facility has the potential to foster and transform digital innovation, enabling Europe to achieve its ambitions and establish itself as a dominant player in creating innovative and reliable AI solutions.

The AI laboratory is a member of the Confederation of Laboratories for Artificial Intelligence Research in Europe (CLAIRE). CLAIRE seeks to strengthen European excellence in AI research and innovation with a pan-European coordination approach. Its member groups and organisations are committed to working together towards realising an European excellence in AI. The document “Claire Vision: Toward a European Common Approach for AI” is a report commissioned by the European Commission’s Directorate-General for Communications Networks, Content and Technology. It aims to provide a common vision for the development of AI in Europe and identify key challenges and opportunities for policymakers, businesses, and society as a whole (see also “CLAIRE: A European Vision for AI“, 2018).

The report highlights the importance of AI in driving economic growth, social progress, and scientific discovery. However, it also acknowledges the potential risks associated with the development and deployment of AI, such as the impact on employment, privacy, and security. To address these challenges, the report proposes a set of guiding principles and key actions for policymakers and stakeholders, including the following aspects:

a human-centric approach that respects human rights, diversity, and inclusion;
trustworthy AI to ensure that AI systems are transparent, explainable, and accountable, and that they operate within ethical and legal boundaries;
a knowledge-based approach that promotes research and innovation in AI and fosters collaboration between academia, industry, and government;
a level playing field to ensure that European businesses have access to data, talent, and investment to compete with other global players;
international cooperation to promote a global dialogue on AI governance and establishing partnerships with other countries and regions.

The report also identifies several priority application areas for AI development in Europe, including healthcare, energy, transport, and agriculture. It highlights the potential benefits of AI in these sectors, such as improving efficiency, reducing costs, and promoting responsible and sustainable innovation processes.

The report emphasises the need for a coordinated and comprehensive approach to AI development and governance in Europe. It calls for a partnership between policymakers, industry, academia, and civil society to ensure that AI is designed, implemented and used in a way that benefits all European citizen.

Finally, it is worth mentioning that in the “A European strategy for data. Communication from the Commission to the European parliament, the council, the European economic and social committee and the committee of the regions” (2020), it is clearly stated that in the period 2021-2027, the Commission will invest in a High Impact Project on European data spaces and federated cloud infrastructures. The project will fund infrastructures, data-sharing tools, architectures and governance mechanisms for thriving data-sharing and, specifically, Artificial Intelligence ecosystems. The foreseen investment for the establishment of EU-wide common, interoperable data spaces in strategic sectors will bring together private actors with public support to develop common platforms offering access to a large diversity of cloud services for secure data storage and sharing as well as applications ranging from AI to simulation, modelling, digital twins and high performance computing (HPC) resources. In the conclusions, this strategic document highlights the fact that the EU’s technological future depends on whether it manages to harness its strengths and seize the opportunities offered by the ever-increasing production and use of data. A European way for handling data will ensure that more data becomes available for addressing societal challenges and for use in the economy, while respecting and promoting our European shared values.

Context in Italy

The “National Strategy for Artificial Intelligence (AI) – Italy 2020” is a document that outlines the country’s plan to develop and implement AI technologies in various sectors. Here are the main points of the document.

Vision: The Italian government aims to establish the country as a leader in AI research, development, and application. The goal is to create a “human-centric” approach to AI that focuses on improving the quality of life for citizens and creating sustainable economic growth.
Challenges: The document identifies several challenges that need to be addressed to achieve the vision. These include developing a skilled workforce, establishing a supportive regulatory framework, creating partnerships between public and private sectors, and ensuring ethical and responsible use of AI.
Priorities: The strategy identifies four priority areas for investment and development of AI technologies: healthcare, security, environment and climate change, and cultural heritage. These sectors were chosen based on their potential for high impact and positive societal benefits.
Objectives: The strategy sets out several objectives for each priority area, including the development of new AI applications, the integration of AI with existing technologies, and the promotion of research and innovation. The document also emphasises the importance of international collaboration and standardisation to ensure interoperability and avoid fragmentation.
Implementation: The strategy outlines a roadmap for implementation that includes the establishment of a national AI task force, the creation of a dedicated funding program, and the promotion of public-private partnerships. The document also highlights the need for public awareness and education initiatives to promote understanding and acceptance of AI technology.

The “National Strategy for Artificial Intelligence – Italy 2020” aims to position Italy as a key player in the global AI landscape, while promoting responsible and ethical use of AI technology for the benefit of society.

In March 2016, the Agency for Digital Italy (AGID) created the “AI-Gov: Artificial Intelligence at the service of the citizen” task force to study how dissemination of Artificial Intelligence solutions and technologies can affect the evolution of public services to improve the relationship between public administration and citizens. In March 2018, in collaboration with the Italian Association for Artificial Intelligence (AIxIA), published the “Artificial Intelligence at the service of citizens” white paper aiming at analysing the impact of Artificial Intelligence (AI) in the Italian society and, more specifically, in the Public Administration, in order to promote digital transformation in sectors like healthcare, education and judiciary systems, public employment, security and management. The main objective of that document is to facilitate the adoption of these technologies in the Italian Public Administration, to improve services to citizens and businesses, thus giving a decisive impulse to innovation, the proper functioning of the economy and, more generally, to progress in daily life. Among the critical challenges that must be faced to integrate Artificial Intelligence in public sectors in a profitable way, the document highlights the following:

the ethical challenge, formulated as the need to strongly affirm the anthropocentric principle stating that Artificial Intelligence is always at the service of the citizen and not vice versa.
The technological challenge stressing the need to work on personalisation and adaptivity to ensure that data and algorithms at our disposal can be increasingly more effective in allowing us to operate individually in some specific areas of our daily life.
The development of dedicated skills in the age of Artificial Intelligence.
The availability, quality and interoperability of data. In this context, the linked open data of public bodies, it is written in the document, must be retrieved and filtered by means of semantic technologies and shared ontologies, not only for interoperability reasons, but also as a way to ensure equal and non-discriminatory access to anyone wishing to use it.
The legal challenge is phrased in the document as the necessity to reconcile the principle of transparency of administrative acts and procedures or the protection of personal data with the right to privacy. The white paper addresses these issues and provides some technical solutions that are also included in the European Regulation on the protection of personal data (GDPR).
The adoption of AI technology in the public sector challenge to improve the relationship between the State, citizens and businesses. In order to address this challenge, the white paper underlines the importance of training public employees, particularly officials and managers, on the functioning, benefits, as well as ethical and technical implications on the use of AI technologies in the public sector.
The seventh challenge is about preventing inequalities in the field of education and training, health and disability, knowledge and human rights. To this aim, the Public Administration must pay great attention to the development of inclusive, accessible, transparent, not discriminatory and free from bias solutions.
The measurement of the impact of AI technology, from the point of view of both citizens and institutions, is also listed among the challenges that need to be addressed. Emphasis is placed here on the necessity to conduct both multidisciplinary quantitative and qualitative research: the impact of technology on citizens and institutions has indeed different facets, including economic, technical, social, cultural, psychological and anthropological factors.
The last challenge analysed in the white paper is called “the human being“. The document suggests the need to create a public discourse around AI, starting from the assumption that both citizens and institutions should be aware of the significant importance of these tools. On this respect, the document introduces experiments that have been proposed in the fields of design, arts, psychology, anthropology and sociology that can close the gap between research, industry, and society.

The “Consorzio Interuniversitario Nazionale per l’Informatica” (CINI) was born in the year 1989 with the mission of promoting and coordinating scientific activities of research and technological transfer, both basic and applicative, in several fields of Computer Science and Computer Engineering. Currently, the CINI Consortium involves 1,300+ professors of both Computer Science and Computer Engineering, belonging to 39 public universities.
In the year 2018, the Consortium gave birth to the “Laboratory of Artificial Intelligence and Intelligent Systems” (AIIS) with the main aim of creating the bases for an effective Italian ecosystem of artificial intelligence, collecting all the expertise and national excellences aiming to highlight and strengthen the scientific and technological role of Italy in Europe and in the world. Among the targets of the lab there are the following:

to strengthen the Italian Research: establish a connection among the Italian scientific excellences in all the AI and smart systems fields. AIIS aims to monitor the Italian research in the AI and supervise the progresses in the theory and engineering of smart systems, either in terms of capacity of research and technological transfer.
To endorse the Italian role in the world: it means pushing the Italian strategic role in all the European and international ventures to support the national and European investments in Technology and Research.
To help the Italian IT industry promoting the technological transfer from the research to the entrepreneurship through innovative start-up and new business activities, engaging small and medium sized companies with AI products as strategical assets, supporting the Italian industrial stakeholder without IT assets (Automotive, Fashion, Manufacturing, Agrifood Industry, Space) in their growth.
To support the Italian Society in facing the challenges the AI is introducing to our lifestyles: health, ageing and wellness technologies, education and instruction up to humanistic and cultural disciplines.
To promote AI solutions to the Public Administrations for the new services to the citizens.
To introduce a deeper awareness of the AI technologies application risks, even on ethics and social aspects, data security, national security, malevolent use, dual-use.
To monitor the Italian resource to develop the AI technology in the present and in the future, engaging the High Performance Computing resource managers to define the strength of the Italian infrastructure.

The AI laboratory is one of the affiliate node of the AIIS lab.

The Italian Association for Artificial Intelligence (AIxIA) is a non-profit scientific association founded in 1988 with the aim of promoting the research and dissemination of the techniques related to Artificial Intelligence.
The Association aims at increasing the knowledge of Artificial Intelligence, fostering its teaching, and promoting both theoretical and applied research in the field through seminars, targeted initiatives and sponsorship of events. Within the Association there exist a number of working groups focused on specific research topics. Eleven working groups are active at the moment, focusing on the following areas: agent and multi-agent systems, AI and ageing, AI and cybersecurity, augmentation in AI, knowledge representation and automated reasoning, machine learning and data mining, natural language processing, AI and robotics, economic paradigms and strategic reasoning, AI for healthcare, AI for cultural heritage. Currently, the association has over 1000 members and it is part of the European Association for Artificial Intelligence (EurAI, formerly known as ECCAI). The EurAI was founded in 1982 as a representative organisation of the European AI community, with the aim of promoting the study, research and application of Artificial Intelligence in Europe.

Traditionally, scholars of the laboratory (from full to assistant professor and researchers) are also members of the AIxIA and contribute with their research and community-oriented activities to the achievement of the overall association objectives.

Context in the global economy

In the present-day business landscape, data and analytics play a crucial role in enhancing decision-making outcomes for businesses of all kinds, including macro, micro, real-time, cyclical, strategic, tactical, and operational decisions. In addition to improving decision-making, data and analytics can also uncover new questions and innovative solutions to business challenges and opportunities that leaders may not have previously considered.

According to Gartner and Deloitte‘s 2022 predictions, significant advancements in AI and data management are expected to emerge from corporate research labs, academia, and open-source communities. As machine learning techniques become more common and supported by system integrators and vendors, organisations are becoming more receptive to exploring them. However, even though machine and deep learning systems are becoming more prevalent in decision-making, their lack of explainability makes their decisions untrustworthy for many enterprises. Semantic-based approaches, such as knowledge graphs and ontologies, can address this limitation by providing a knowledge level to data modelling, making it easier to connect all knowledge sources within a company and allowing AI technologies to surpass traditional machine learning. With the changing market conditions, product digitalisation, and increased complexity and customisation, companies need advanced data interaction, which can be facilitated by semantic technologies and data literacy. Data literacy is defined as the ability to read, write, and communicate data in context; it requires an understanding and a specification of the semantics of data sources and constructs, analytical methods and techniques applied and the ability to describe the use-case application and resulting value. These technologies can automate processes like data structuring, text analysis, and data model merging, as well as integrate structured and unstructured data, clean up data, and enrich it based on reasoning.

According to Gartner‘s predictions, the utilisation of semantic and knowledge graph technologies in data and analytics innovations is set to increase from 10% in 2021 to 80% by 2025. The adoption of knowledge graphs is being driven by various factors, such as the ever-increasing amount of data being generated and collected, the necessity to comprehend it, and its integration into artificial intelligence and machine learning. The structured data and context provided by semantic annotations, knowledge graphs, and ontologies can significantly benefit these technologies.
Starting from the assumption that knowledge is every company’s most valuable asset, which remains scattered across different systems and human minds,

Similarly, in “Wisdom of Enterprise Knowledge Graphs” (2019) Deloitte indicates the creation of knowledge graph with semantic description of information context as the instrument to allow users to access machine-readable representation of complex interdependencies the form real-world model of the knowledge domain. Knowledge graphs, as it is stressed in the document conclusions, integrate knowledge and data across the whole enterprise, support complex decisions and efficiently helps in revealing the origin of correlation: knowledge graphs are at the foundations of AI technologies “that are more intelligent than artificial”.