Social BRIDGES Archive

You're welcome to browse through the archive of our past conferences.

We do our best to keep the materials online and accessible to inquiring minds from all over the world.

 

Social BRIDGES 1: Society, psychology and behaviour during and post COVID-19 lockdown (22-24 July 2020)

The present COVID-19 pandemic is challenging each of us and society in unique ways. One positive outcome, however, is the extraordinary effort being made to try and bridge the physical gap as a result of lockdown measures. So too in academia, where international teams of researchers from universities and institutes across the globe are collaborating to try better understand the effect of self-isolation and distancing during the current COVID-19 pandemic.

The two-day virtual exchange event on 22-24 July 2020 provided news from up-to-date research investigating how society, behaviour and psychology are being affected by the COVID-19 pandemic.
Studies about the disruptive energies of the pandemic and the collective worldwide steps into the new normal were presented in three main sections: individual behaviour during and after lockdown;
doing things together during and after lockdown; mental health care: challenges and proposed solutions.

Social BRIDGES 2: Alignment in groups, networks and teams (18-20 November, 2020)

In this event, the second in our series of social BRIDGES e-conferences, we present an interdisciplinary forum where researchers in social psychology, sports psychology, philosophy, and neuroscience come together to discuss how and why we become aligned with others in body and mind. For our purposes, alignment can capture everything from how footballers and dancers physically coordinate to create movement patterns that score goals and enchant audiences but also how groups of individuals collectively make decisions or act together as one. During this three-day virtual event on November 18-20, 2020, we have done our best to answer questions like:

- Are two (or more heads) always better than one?
- What are the best computational methods for describing the ways individuals coordinate?
- Are we talking about the same phenomenon when we describe alignment in crowds, musicians or a team of football players?
- How is alignment in humans special or can we learn something from fish?
What stops us from becoming aligned with others?

Social BRIDGES 3: The near-future of AI: How will humans and AI interact in 5 years? (21-23 April, 2021)

Theme 1
AI beyond tools: Cooperating and competing with artificial non-human agents

When computer scientists develop a machine-learning application or even an AI system, they do so to solve a specific problem: driving a car, recognising faces, or finding game-winning strategies. In these circumstances AI systems are nothing more than tools. We, the users of machines, have goals and machines are there to help us meet them. But when it comes to human-AI cooperative contexts, should we treat AI as more than tools and when is it beneficial or even necessary to include a ‘human-in-the-loop’?

Examples of research questions:
- How does the make-up of human and non-human groups change how we coordinate our actions?
- Will we trust, expose ourselves to risk, and cooperate with artificial agents as much as we do with fellow humans?
- What challenges do we face in ensuring that the introduction of AI systems into our society is as smooth and efficient as possible?
- Are there obstacles to our cooperation with machines and are there ways to overcome them?
- How to foster our trust in AI systems? Are there reasons not to trust them? Can these worries be overcome and how?
- We want AI systems and their use to be unconditionally benevolent, explainable, and fully transparent. Is that achievable? Are there contexts in which we would not want that?

Theme 2
Extending the senses: Learning and perceiving in human and non-human agents

Given adequate training data and time to learn, current machine learning applications can rival human performance. However, while the performance outputs like in visual object recognition are comparable, the underlying sensory processing is not. Machine learning performance is stifled when objects are rotated or some pixels are altered, whereas human perception is vulnerable to optical illusions. Here, we discuss the similarities and differences in learning and perceiving in human and non-human agents.

Examples of research questions:
- Can we couple artificial sensors and computation with human perception?
- Should we think of, and can we design AI perception to be like human perception?
- Can human perception and cognition be enhanced with the use of smart technologies?
- Can we use AI technologies to apply our senses in contexts in which we have not used them before?

Theme 3
Robots like us: Machines that look and think like humans

While this could be the sequel to Ian McEwan’s ‘Machines like me’, here we want to turn our attention to issues of embodied cognition: Are these robots capable of social interaction? Possible application areas of robotic AI systems involve care-homes, the military and the modern workforce. But should we use them for this purpose and, if so, what should we be thinking about as we do so?

Examples of research questions:
- Do robots have to think and look like us for us to be able to coordinate actions effectively?
- Why and when do we (want to) anthropomorphize machines?
- Is it enough for us to believe that machines are similar to us in order for us to trust and welcome their use, or do we have to know that they are in fact similar to us too?
- In human-machine interaction, can we nudge people into believing that they interact with someone “like” them? Are there contexts in which we should or should not do that?