As Artificial Intelligence (AI) becomes increasingly integrated into our
lives, the need for new norms is urgent. However, AI evolves at a much faster
pace than the characteristic time of norm formation, posing an unprecedented
challenge to our societies. This paper examines possible criticalities of the
processes of norm formation surrounding AI. Thus, it focuses on how new norms
can be established, rather than on what these norms should be. It distinguishes
different scenarios based on the centralisation or decentralisation of the norm
formation process, analysing the cases where new norms are shaped by formal
authorities, informal institutions, or emerge spontaneously in a bottom-up
fashion. On the latter point, the paper reports a conversation with ChatGPT in
which the LLM discusses some of the emerging norms it has observed. Far from
seeking exhaustiveness, this article aims to offer readers interpretive tools
to understand society's response to the growing pervasiveness of AI. An outlook
on how AI could influence the formation of future social norms emphasises the
importance for open societies to anchor their formal deliberation process in an
open, inclusive, and transparent public discourse.

人工智能的快速发展对新规范形成过程构成了前所未有的挑战，本文探讨了围绕人工智能形成新规范的可能关键问题，研究中央集权或分散化规范形成过程的不同情景，并报告了与 ChatGPT 的对话中观察到的一些新兴规范，旨在提供解读工具以了解社会对人工智能不断渗透的反应，并强调了开放社会在形成未来社会规范时将其正式论述过程锚定在开放、包容和透明的公众讨论中的重要性。

塑造 AI 的新规范

Shaping New Norms for AI

Representation and control of the dynamics of stigmergic substances used by
bio-inspired approaches is a challenge when applied to robotics. In order to
overcome this challenge, this work proposes a model to coordinate swarms of
robots based on the virtualisation and control of these substances in a local
scope. The model presents a new pheromone modelling, which enables the
decentralisation and asynchronicity of navigation decisions. Each robot
maintains an independent virtual pheromone map, which is continuously updated
with the robot's deposits and pheromone evaporation. Moreover, the individual
pheromone map is also updated by aggregating information from other robots that
are exploring nearby areas. Thus, individual and independent maps replace the
need of a centralising agent that controls and distributes the pheromone
information, which is not always practicable. Pheromone information propagation
is inspired by ants' vibroacoustic communication, which, in turn, is
characterised as an indirect communication through a type of gossip protocol.
The proposed model was evaluated through an agent simulation software,
implemented by the authors, and in the Webots platform. Experiments were
carried out to validate the model in different environments, with different
shapes and sizes, as well as varying the number of robots. The analysis of the
results has shown that the model was able to perform the coordination of the
swarm, and the robots have exhibited an expressive performance executing the
surveillance task.

本论文提出了一种基于分布式模型的虚拟荷尔蒙建模的群体机器人协同方案，通过实现机器人之间的信息交互和知识共享，实现了机器人的分散化和异步化协同，以及高效地完成了目标监视任务。

PheroCom 基于虚拟信息素和振动声通信的分散异步群体机器人协调

PheroCom: Decentralised and asynchronous swarm robotics coordination based on virtual pheromone and vibroacoustic communication

The exponential growth of the blockchain size has become a major contributing
factor that hinders the decentralisation of blockchain and its potential
implementations in data-heavy applications. In this paper, we propose segment
blockchain, an approach that segmentises blockchain and enables nodes to only
store a copy of one blockchain segment. We use \emph{PoW} as a membership
threshold to limit the number of nodes taken by an Adversary---the Adversary
can only gain at most $n/2$ of nodes in a network of $n$ nodes when it has
$50\%$ of the calculation power in the system (the Nakamoto blockchain security
threshold). A segment blockchain system fails when an Adversary stores all
copies of a segment, because the Adversary can then leave the system, causing a
permanent loss of the segment. We theoretically prove that segment blockchain
can sustain a $(AD/n)^m$ failure probability when the Adversary has no more
than $AD$ number of nodes and every segment is stored by $m$ number of nodes.
The storage requirement is mostly shrunken compared to the traditional design
and therefore making the blockchain more suitable for data-heavy applications.

本文提出了基于分段的区块链方法，该方法使节点只需存储一个区块链段，并基于工作量证明限制节点数，从而缩减存储需求并解决现有区块链的去中心化和大数据应用问题。