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
Citizens:
Businesses:
Governments:
A European approach to excellence and trust as it is proposed by the White Paper
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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.
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.
© European Commission, 2020