Human-AI Coevolution

Dino Pedreschi, Luca Pappalardo, Emanuele Ferragina, Ricardo Baeza-Yates,
Albert-László Barabási et al.

Artificial Intelligence
Available online November 13th, in Open Access

https://doi.org/10.1016/j.artint.2024.104244

An international team of AI, social, and complexity scientists - including Emanuele Ferragina - work paves the way for a new field of research, merging artificial intelligence and complexity science to understand how the continuous interaction between humans and algorithms can profoundly transform social dynamics.

In a world where algorithms and recommendation systems increasingly guide daily decisions, this paper explores how these processes influence human behaviors, creating a “feedback loop” in which individual choices and automated suggestions reinforce each other. This loop generates complex and often unpredictable effects that evade traditional models of human-machine interaction.

The paper lays the groundwork for studying human-AI coevolution as a phenomenon with crucial ethical and social implications. Through an interdisciplinary approach, the team emphasizes the importance of a new cross-disciplinary perspective to address the challenges of coevolution, presenting concrete examples of human-AI ecosystems. The authors also highlight the need for new regulatory and policy tools to monitor and manage the feedback loop that governs digital interactions.

“The feedback loop between humans and AI,” says Dino Pedreschi, Professor of Computer Science at the University of Pisa, “creates unprecedented forms of interaction, with recommendation systems deeply influencing our preferences. The complexity of this ecosystem is constantly growing, as each interaction adds new levels of complexity and data to analyze.”

“If we want to understand the real impact of AI on our society,” adds Luca Pappalardo, researcher at CNR and professor at Scuola Normale Superiore in Pisa, “we need to reinterpret our understanding of complex systems in light of this continuous feedback between humans and algorithms.”

Finally, Emanuele Ferragina, Professor of Sociology at Sciences Po - CRIS, underscores the urgency of addressing legal and policy barriers: “To fully understand human-AI coevolution, we need greater transparency from major online platforms. Initiatives such as the EU’s Digital Services Act can make a difference, but it’s also essential to ensure an equitable distribution of ‘recommendation tools’ in a more competitive market.”

This study sparks a fundamental debate, inviting us to rethink the relationship between AI and society and to shape a future where humans and artificial intelligence can coevolve consciously and responsibly.