A few weeks ago, during a conference on artificial intelligence for science, someone in the audience asked a very common question. The framing was familiar because it appears almost systematically whenever new technologies are discussed: “AI is a tool and like any tool, it can be used for good or bad. So how do we make sure it is used responsibly?”

The more I work on responsible research and innovation, the more I encounter the same paradox: we keep asking innovators to become more responsible while organizing innovation systems in ways that make it increasingly difficult for them to choose their path.

European research funding increasingly asks projects to demonstrate societal impact. In principle, this is a good thing. For years, research and innovation systems have been criticized for their distance from major societal and environmental challenges, and for the way scientific excellence was often evaluated independently from broader consequences.

Deep Tech startups are often presented as key actors in the ecological transition. However, the environmental and societal impact of Deep Tech startups is rarely addressed seriously during the early stages of technological development.

For a long time, research evaluation was primarily organized around scientific excellence. The central questions were relatively clear: Is the science robust? Is it novel? Can it advance knowledge? Eventually, additional criteria such as publication metrics, patents, technology transfer became increasingly important. But the overall logic remained largely the same: research produced knowledge first, and societal effects would follow later. This is progressively changing.

Your research institute has just published the latest figures on its research transfer strategy! You observe the number of patents filed and start-ups created with pride. Then you remember the climate crisis, growing social divisions and the recent health crisis. Doubt assails you.

What are contemporary promises worth? At a time when the 6th report of the IPCC has been released and when many announcements will rain – “pledges” and other commitments on the part of industrial groups and governments – the question is burning.

If social entrepreneurship remains largely absent from the places where technologies are shaped, it is tempting to see this as a gap to fill: a matter of awareness, incentives, or better collaboration. This reading is convenient. It is also misleading.

Should researchers be “engaged” with societal issues? This question comes up regularly in public debates, often with an underlying concern: that science might become activist or ideological, or lose its supposed neutrality.

Racism is a structural phenomenon, and technological development, though perceived as a neutral space, is far from being exempt from it.