A neuroscientific perspective on human–AI interaction
In their recent contribution, Rossi et al. 2026 address human–AI interaction from a neuroscientific and philosophical standpoint. The authors start from a well established principle in neuroscience, namely that brain plasticity is activity and time dependent. Cognitive functions, like motor or perceptual ones, follow a use it or lose it logic. When engagement decreases, neural circuits tend to weaken over time.
Against this background, the authors raise a crucial question. What happens when a growing share of everyday cognitive tasks is delegated to AI systems. Drawing on theories of synaptic plasticity and metaplasticity, they hypothesize that different styles of interaction with AI may lead to very different long term outcomes. Passive and uncritical acceptance of AI outputs may reduce neural activation and contribute to cognitive erosion. Active and reflective engagement, by contrast, may sustain or even enhance learning and critical thinking.
From cognitive offloading to agency erosion
The article situates this discussion within the broader literature on cognitive offloading. Delegating tasks to external tools is not new. However, the scale and pervasiveness of contemporary AI systems introduce a qualitative shift. According to Rossi et al. 2026, the risk is not limited to reduced effort or weaker problem solving skills. More profoundly, excessive reliance on AI may erode personal agency and responsibility.
This concern becomes especially salient when AI outputs are treated as answers rather than as suggestions to be evaluated. Large language models do not operate on meaning or values. They generate statistically plausible results without understanding their implications. When humans stop questioning these results, responsibility silently shifts away from the human agent, with potential consequences for ethical judgement and autonomy.
The 3R principle: Results, Responses, Responsibility
To address these risks, Rossi et al. 2026 introduce the 3R principle. The first distinction is between results and responses. AI systems can produce results, but these results do not automatically constitute meaningful responses. A response, the authors argue, only emerges when a human agent interprets the output, evaluates its consequences and situates it within a value framework.
The third and most important R is responsibility. Responsibility cannot be externalized to AI systems because it presupposes intentionality, value choice and accountability. These dimensions remain irreducibly human. By making responsibility explicit, the 3R principle functions as a form of cognitive hygiene, reminding users that meaning and agency require active engagement rather than passive consumption of AI generated content.
Implications for digital sustainability
The relevance of this perspective extends beyond neuroscience. From a digital sustainability standpoint, the article highlights a dimension that is often overlooked. Sustainable digital transformation is not only about energy efficiency or environmental impact. It is also about preserving human cognitive capacities, critical thinking and agency in the long term.
By framing human–AI interaction as a factor that shapes brain plasticity, Rossi, Fraccaro and Manzotti invite policymakers, educators and organizations to rethink how AI tools are introduced and used. Education, in particular, plays a central role. Encouraging students to question, verify and contextualize AI outputs may help prevent cognitive erosion while still benefiting from technological support.
Why this contribution matters now
Published at a moment when generative AI is rapidly becoming embedded in daily life, The brain side of human-AI interaction in the long term offers a timely and conceptually rigorous contribution to ongoing debates. Its value lies not in providing definitive empirical answers, but in articulating a clear framework that connects neuroscience, ethics and digital sustainability.
For researchers and practitioners interested in the long term human implications of AI, the 3R principle provides a useful lens. It shifts the focus from what AI can do to how humans choose to interact with it. In doing so, it reinforces a core message of digital sustainability. Technological progress remains sustainable only if it supports, rather than undermines, human agency, meaning making and cognitive health.
Full Article:
nature.com