AI and digitalisation
What is artificial intelligence?
Various definitions of artificial intelligence (AI) exist, both globally and within Europe. Both the Council of Europe Framework Convention on AI, Human Rights, Democracy and the Rule of Law and the European Union’s Artificial Intelligence Act (AI Act) propose similar definitions.
The Council of Europe Framework Convention defines an AI system as:
a machine-based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations or decisions that may influence physical or virtual environments. Different artificial intelligence systems vary in their levels of autonomy and adaptiveness after deployment.
The EU AI Act definition states that:
[an] ‘AI system’ means a machine-based system that is designed to operate with varying levels of autonomy and that may exhibit adaptiveness after deployment, and that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments.
One concern when it comes to defining what counts as AI is whether certain degrees of autonomy are required for a system to count as an AI system. Related to that, the current focus on foundation models such as ChatGPT has raised questions on how it should be regulated. This is due to the fact that unlike AI systems that are used for specific purposes (for example, deciding on loans, predictive policing, a music recommendation algorithm), foundation models can generate high quality texts and images. These products can then have multiple downstream uses alongside potential emergent harms, such as wide-scale misinformation, that are hard to foresee and predict in advance.
Despite the lack of clarity over definitions, the main concern that has arisen relates to machine learning. This is a sub-type of artificial intelligence that can automatically learn and improve from experience, namely from the data it has been trained on and which it continually encounters. Machine learning systems can identify patterns and correlations which can be used for prediction, recommendations or decision making.Â
What is digitalisation?
Digitalisation, also known as digital transformation, refers to the use of digital technologies to transform various aspects of business, society, or other domains. It is the process of using digital technologies to convert analogue or physical assets, processes, or information into digital formats with the aim of improving efficiency, productivity, and innovation. It is not just about using digital tools, but it is about fundamentally rethinking and reshaping traditional approaches to meet the changing demands of the digital age.
How are AI and digitalisation linked?
Artificial intelligence and digitalisation are closely linked and often complement each other. AI systems have the capacity to:
Accelerate digitalisation
For example, via automation technologies
Enhance the effectiveness and efficiency of digital transformation efforts
For example, via data analysis and insights, personalisation and an enhanced customer experience
Optimise digitalisation strategies
For example, via predictive capabilities
The integration of AI and digitalisation empowers businesses and organisations to leverage the capabilities of AI technologies within their digital systems and processes. Â
Both AI and digitalisation bring many new opportunities in a world where technology is playing an ever-increasing role, but they also pose many new challenges and concerns. It is therefore more important than ever to adequately regulate these practices, especially from a human rights perspective. Â
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