Sustainable AI

Artificial Intelligence (AI) has an inseparable relationship with sustainability. Using AI, we can work more efficiently, better predict and anticipate future developments, and encourage sustainable choices. At the same time, AI also has a downside: consider its ecological footprint and the risk of bias. That is why it is important to develop and apply AI in a sustainable manner.

Three pillars

Within the Faculty of Social Sciences, we conduct extensive research and provide education on sustainable AI. We approach sustainable AI from several different perspectives:

Technology

We develop energy-efficient AI systems inspired by the human brain. Examples include neuromorphic computing models that can perform complex calculations using significantly less energy than traditional computers.

Behaviour

AI can support people in making more informed choices. In healthcare, for instance, decision-support systems can help weigh treatment options based on effectiveness, cost, and quality of life.

Critical-Reflective

We also study the societal downsides of AI: from energy consumption and working conditions to privacy and the use of training data. In addition, we reflect on how AI shapes our understanding of human intelligence.

Highlights

Johan Kwisthout, hoogleraar Probabilistic Graphical Models

Sustainable AI for decision support

14 February 2025 News item

Artificial intelligence has transformed many aspects of our lives, from healthcare to decision-making. But how can we ensure that AI is used responsibly and sustainably? This question was at the heart of Professor Johan Kwisthout’s inaugural lecture.

A collage that merges circuit board patterns with textile motifs in a grid-like background of alternating black, grey, and white. Two hand-drawn arms are on each side of the image, positioned as if gently pulling on thin, white strings that cross the image diagonally. The hands appear soft and somewhat translucent, contrasting with the rigid lines of the circuit board patterns behind them.

Critical AI Literacy (CAIL)

Research

The Critical AI Literacy (CAIL) project provides new scientific insights and innovative ways of thinking based on expert critical perspectives on AI in science and society.