Regulating Socio-Technical Change
Technology is playing an ever more invasive role in all walks of life. But regulation often lags behind the speed of technology development. We study how we can integrate new technology in society through regulation in such a way that everybody benefits.
The impact of socio-technical change on law and regulation manifests itself in two ways. The first is when new technologies change the way we live or create new risks. We ask questions about how the existing legal and regulatory framework can be adapted to deal with these changes. For example, how is healthcare to be regulated when the patient interacts with a computer program? How to we handle cybercrimes and cybersecurity risks? The second impact is that new technologies, like artificial intelligence, increasingly allow for decisions to be made by machines instead of humans. If regulation is by technology, how do we ensure that this regulation is fair and that it does not fail us?
The research program Regulating Socio-Technical Change is conducted in three clusters:
- Governance: focusing on the relationship between power and technology and what the role of law and institutions in this new space is;
- Fundamental rights and technology: focusing on privacy and data protection, cybercrime and cybersecurity and the relationship between AI and fundamental rights;
- Competition & innovation: focusing on the challenges of regulating digital and energy markets.
Questions on rather than queries to ChatGPT: “Now is the time to make fundamental choices”
Some of the projects:
A framework for Data Justice on the global level
Places and populations that were previously digitally invisible are now part of a ‘data revolution’ that is being hailed as a transformative tool for human and economic development.
MEGAMIND: AI and regulation in the electricity system
MEGAMIND focuses on the so-called edges of the electricity system: the distribution networks and the electricity producing and consuming devices connected to them.
Handbook on non-discriminating algorithms
Algorithms are used increasingly frequently for risk-based operations and automated decision-making. However, this approach carries a great risk, especially with machine-learning systems, namely, that it is no longer clear how the decision-making takes place.
The right to be let alone by yourself
Veni - Bart van de Sloot: Can privacy be reconceptualised so that it also provides protection from, and the possibility to integrate narrative-disruptive information about oneself and if so, what would it entail?
THESEUS: Make patching happen
This research project aims to empower organizations to patch (i.e. resolve) cybersecurity vulnerabilities much faster, more efficiently and with less risk.