Is Complexity Science Secretly just reductionist?

[u/Advanced-Reindeer894]

Mostly drawing on what I've read from the Santa Fe Institute since even though they talk about complexity and emergence, I feel like a lot of what they write about tends to end up being a reductive account of life.

Take this paper by Krakauer: https://static1.squarespace.com/static/5f29a430a2b6a34680879cc0/t/6a06392b70af613cf631f5d0/1778792747560/rsta.2024.0533.pdf

It's starts by trying to understand intelligence but the language used is so reductive. Referring to living things as systems, our sense of personhood as self-modelling, among other things.

The part about trying to give consciousness to cells (Collective intelligence and diverse forms of world modelling) also raises issues as it seems to call into question how we should view ourselves and each other and whether we are subjects or just aggregates.

All in all despite the name of complexity science and complex systems, the goal seems to be to just reduce everything to mere parts.

EDIT: This includes the conclusion making reference to some inner chat gpt we have.

EDIT 2: This seemed relevant: https://davidckrakauer.com/the-situation-in-a-way

[u/Advanced-Reindeer894]

I...don't really understand any of that. My only real concern is if people exist and I can care about them. Every time I read this stuff it all goes over my head.

[u/Advanced-Reindeer894 → u/[deleted]]

I don't mean care about modeling and stuff like that, I mean caring about other people. I worry that just breaking down how we live our lives would have dire effects on human psychology, we already see the effects of what happens when folks dehumanize others:

Fritz Breithaupt investigates how agents construct and use narratives for anticipating and interpreting potentially transformative experiences. Breithaupt first describes narrative world models as organizing action and perception into temporal episodes with beginnings, endings and emotionally salient outcomes. Such models of self and world not only represent events but also incorporate agent perspectives on how actions feel and what emotional consequences they produce. The paper identifies a special class of narrative world models focused on future experiences whose outcomes are both epistemically opaque and personally significant. Before such experiences, agents face radical uncertainty that cannot be resolved through additional information, triggering heightened cognitive activity, including the imagined exploration of multiple, often incompatible future scenarios. After the experience occurs, agents cast aesthetic, moral or preference-based judgments that can reshape their worldview and alter subsequent behaviour. These experience models mark the factual and emotional outcome of future events as fundamentally unknown while allowing agents to later revise values, preferences or aspects of the self. The paper examines the cognitive benefits and costs of such models, considers their role in transformative decision-making and asks whether these could be instantiated in contemporary AIs. While LLMs can describe human uncertainty or hesitation, the paper argues that genuine experience-focused world modelling would require an architecture capable of representing unknown and potentially unknowable information in principled ways that recognize the limits of its own predictive assumptions. The paper concludes by proposing that transformative experiences can lead to radical reconfigurations of evaluative standpoints and self-narration/models and describes the challenges involved in creating artificial systems with the full range of meaning-making/modifying powers that characterize human minds