This position paper discusses the benefits of longitudinal behavioural research with customised AI tools for exploring the opportunities and risks of synthetic relationships. Synthetic relationships are defined as "continuing associations between humans and AI tools that interact with one another wherein the AI tool(s) influence(s) humans' thoughts, feelings, and/or actions." (Starke et al., 2024). These relationships can potentially improve health, education, and the workplace, but they also bring the risk of subtle manipulation and privacy and autonomy concerns. To harness the opportunities of synthetic relationships and mitigate their risks, we outline a methodological approach that complements existing findings. We propose longitudinal research designs with self-assembled AI agents that enable the integration of detailed behavioural and self-reported data.

It's Monday morning and you're in Hong Kong having coffee with your new boss, a virtual robot powered by artificial intelligence. Meanwhile, your digital clone is attending another meeting on your behalf, taking notes that you'll review later, but you're actually working from your bedroom in Rio de Janeiro. It may sound straight out of a science fiction novel, but this is the future of work promised by the metaverse and by NetDragon, a Chinese company that recently appointed an AI-powered virtual humanoid robot as the rotating CEO of its flagship subsidiary, Fujian NetDragon Websoft. The metaverse, often dubbed the next version of the Internet, promises a 3D virtual world that people enter via virtual reality (VR) and augmented reality (AR) headsets to do business, hang out and play games through their virtual avatars or holograms. NetDragon Websoft, the Chinese gaming company which has gained a reputation with games such as Eudemons Online, Heroes Evolved, Conquer Online and Under Oath, is betting heavily on this new digital world and its related technologies.

The 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJACI-ECAI 2022) took place from 23-29 July, in Vienna. The title of her talk was "Engineering sociality and collaboration in AI systems". Robots are widely used in industrial settings, but what happens when they enter our everyday world, and, specifically, social situations? Ana believes that social robots, chatbots and social agents have the potential to change the way we interact with technology. She envisages a hybrid society where humans and AI systems work in tandem.

The 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJACI-ECAI 2022) took place from 23-29 July, in Vienna. In this post, we continue our round-up of the invited talks, summarising the presentation by Ana Paiva, University of Lisbon and INESC-ID. The title of her talk was "Engineering sociality and collaboration in AI systems". Robots are widely used in industrial settings, but what happens when they enter our everyday world, and, specifically, social situations? Ana believes that social robots, chatbots and social agents have the potential to change the way we interact with technology.

This paper describes a social robotic game player that is able to successfully play a team card game called Sueca. The question we will address in this paper is: how can we build a social robot player that is able to balance its ability to play the card game with natural and social behaviours towards its partner and its opponents. The first challenge we faced concerned the development of a competent artificial player for a hidden information game, whose time constraint is the average human decision time. To accomplish this requirement, the Perfect Information Monte Carlo (PIMC) algorithm was used. Further, we have performed an analysis of this algorithm's possible parametrizations for games trees that cannot be fully explored in a reasonable amount of time with a MinMax search.

I present arguments against the hypothesis put forward by Silver, Singh, Precup, and Sutton ( https://www.sciencedirect.com/science/article/pii/S0004370221000862 ) : reward maximization is not enough to explain many activities associated with natural and artificial intelligence including knowledge, learning, perception, social intelligence, evolution, language, generalisation and imitation. I show such reductio ad lucrum has its intellectual origins in the political economy of Homo economicus and substantially overlaps with the radical version of behaviourism. I show why the reinforcement learning paradigm, despite its demonstrable usefulness in some practical application, is an incomplete framework for intelligence -- natural and artificial. Complexities of intelligent behaviour are not simply second-order complications on top of reward maximisation. This fact has profound implications for the development of practically usable, smart, safe and robust artificially intelligent agents.

It's often said that men and women's brains work so differently that one sex is from Venus and the other is from Mars. Well now a new study supports this hypothesis after finding 1,000 genes that are much more active in one gender than the other. It looked into how male and female mouse brains differ by probing areas that are known to program'rating, dating, mating and hating' behaviours. The behaviours -- for example, male mice's quick determination of a stranger's sex, females' receptivity to mating, and maternal protectiveness -- help the animals reproduce and their offspring survive. These differences are also likely reflected in the brains of men and women, the researchers from Stanford Medicine said.

Valve's Team Fortress 2 (TF2) is a vastly popular online first-person shooter (FPS) with a fanbase and support that stems back a decade. It's rare that a FPS continues to carry such a strong community. However, it's fair to say that TF2 has continued to evolve as a platform, with significant changes to this weird and eclectic shooter since its original launch back in 2007. But it's not the game itself I'm interested in today -- given that I typically talk about the AI that works behind the scenes. Rather, I'm going to talk about at its community.

In a world-first, scientists have genetically engineered ants to lack their sense of smell, affecting the animals' ability to communicate. Scientists used the controversial CRISPR technology to disrupt the ants' ability to communicate, forage or compete to be a queen, as their antennae and brain circuits failed to fully develop. While the system has not yet been tested in humans, the researchers believe that it could one day be used to treat conditions that affect social communication, including schizophrenia and depression. In a world-first, scientists have genetically engineered ants to lack their sense of smell, affecting the animals' ability to communicate Crispr technology precisely changes small parts of genetic code. Unlike other gene-silencing tools, the Crispr system targets the genome's source material and permanently turns off genes at the DNA level.

Robots raise all kinds of concerns. They could steal our jobs, as some experts think. And if artificial intelligence grows, it might even be tempted to enslave us, or to annihilate the whole of humanity. Robots are strange creatures, and not only for these frequently invoked reasons. We have good cause to be a little worried about these machines. Imagine that you are visiting the Quai Branly-Jacques Chirac, a museum in Paris dedicated to anthropology and ethnology.