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Digital Agenda: Overview

Artificial Intelligence

Data and artificial intelligence (AI) can help find solutions to many of society’s problems, from health to farming, from security to manufacturing.

This can only be achieved if technology is developed and used in ways that earns peoples’ trust. Therefore, an EU strategic framework based on fundamental values will give citizens the confidence to accept AI-based solutions, while encouraging businesses to develop them.

© European Commission, 2020

Video of Artificial Intelligence

EU strategic framework

Citizens:

Businesses:

  • machinery
  • transport
  • cybersecurity
  • farming
  • the green and circular economy
  • healthcare
  • high-value added sectors like fashion and tourism

Governments:

  • reduce the costs of providing services (transport, education, energy and waste management)
  • improve the sustainability of products
  • equip law enforcement authorities with appropriate tools to ensure the security of citizens, with proper safeguards to respect their rights and freedoms

Promoting excellence in AI & Building Trust

A European approach to excellence and trust as it is proposed by the White Paper

  • Working with Member States: actions for closer and more efficient cooperation between Member States, and the Commission in key areas, such as research, investment, market uptake, skills and talent, data and international cooperation
  • Focusing the efforts of the research and innovation community: create more synergies and networks between the multiple European research centers on AI and to align their efforts to improve excellence, retain and attract the best researchers and develop the best technology
  • Strong focus on skills to fill competence shortages:
  • The updated Digital Education Action Plan will help make better use of data and AI-based technologies such as learning and predictive analytics with the aim to improve education and training systems and make them fit for the digital age
  • Developing the skills necessary to work in AI and upskilling the workforce to become fit for the AI-led transformation will be a priority of the revised Coordinated Plan on AI to be developed with Member States
  • Establish and support through the advanced skills pillar of the Digital Europe Programme networks of leading universities and higher education institutes to attract the best professors and scientists and offer world-leading masters programmes in AI
  • Focus on SMEs: the Digital Innovation Hubs and the AI-on-demand platform should be strengthened further and foster collaboration between SMEs. The Digital Europe Programme will be instrumental in achieving this.
  • Partnership with the private sector: a broad-based public private partnership, and securing the commitment of the top management of companies though the programme of Horizon Europe
  • Promoting the adoption of AI by the public sector: The Commission will initiate open and transparent sector dialogues giving priority to healthcare, rural administrations and public service operators in order to present an action plan to facilitate development, experimentation and adoption
  • Securing access to data and computing infrastructures
  • International aspects: the EU recognises that important work on AI is ingoing in other multilateral fora, including the Council of Europe, the United Nations Educational Scientific and Cultural Organization (UNESCO), the Organisation for Economic Co-operation and Development’s (OECD), the World Trade Organisation and the International Telecommunications Union (ITU)

                                                                             Visit AI Watch to monitor the development, uptake and impact of Artificial Intelligence for Europe

Examples

AI examples in our lives:

Online shopping and advertising: Artificial intelligence is widely used to provide personalised recommendations to people, based for example on their previous searches and purchases or other online behaviour. AI is hugely important in commerce: optimising products, planning inventory, logistics etc.

Web search: Search engines learn from the vast input of data, provided by their users to provide relevant search results.

Digital personal assistants: Smartphones use AI to provide services that are as relevant and personalised as possible. Virtual assistants answering questions, providing recommendations and helping organise daily routines have become ubiquitous.

Machine translations: Language translation software, either based on written or spoken text, relies on artificial intelligence to provide and improve translations. This also applies to functions such as automated subtitling.

Smart homes, cities and infrastructure: Smart thermostats learn from our behaviour to save energy, while developers of smart cities hope to regulate traffic to improve connectivity and reduce traffic jams.

Cars: While self-driving vehicles are not yet standard, cars already use AI-powered safety functions. The EU has for example helped to fund VI-DAS, automated sensors that detect possible dangerous situations and accidents.

Cybersecurity: AI systems can help recognise and fight cyberattacks and other cyber threats based on the continuous input of data, recognising patterns and backtracking the attacks.

Artificial intelligence against Covid-19: In the case of Covid-19, AI has been used in thermal imaging in airports and elsewhere. In medicine it can help recognise infection from computerised tomography lung scans. It has also been used to provide data to track the spread of the disease.

Fighting disinformation: Certain AI applications can detect fake news and disinformation by mining social media information, looking for words that are sensational or alarming and identifying which online sources are deemed authoritative.

Guidelines for trustworthy AI

Seven key requirements that AI applications should respect to be considered trustworthy

1. Human agency and oversight: They should act as enablers to a flourishing and equitable society by supporting human agency and fundamental rights, and not decrease, limit or misguide human autonomy. The overall wellbeing of the user should be central to the system's functionality.

2. Technical robustness and safety: AI systems need to be reliable, secure enough to be resilient against both overt attacks and more subtle attempts to manipulate data or algorithms themselves, and they must ensure a fall-back plan in case of problems.

3. Privacy and Data Governance: It will allow individuals to trust the data processing, it must be ensured that they have full control over their own data, and that data concerning them will not be used to harm or discriminate against them.

4. Transparency: It is important to log and document both the decisions made by the systems, as well as the entire process that yielded the decisions.

5. Diversity, non-discrimination and fairness: AI systems should consider the whole range of human abilities, skills and requirements, and ensure accessibility through a universal design approach to strive to achieve equal access for persons with disabilities.

6. Societal and environmental well-being: Sustainability and ecological responsibility of AI systems should hence be encouraged.

7. Accountability: Mechanisms should be put in place to ensure responsibility and accountability for AI systems and their outcomes, both before and after their implementation.

 

Artificial Intelligence in figures

© European Commission, 2020