Research
Research
we are interested in interactionsHumans interact with each other – and soon with AI – to share information and make decisions. Our lab investigates the cognitive and neurobiological basis of interactive decision making. We use behavioural psychological testing, functional and structural brain imaging and psychopharmacology techniques to understand human interactive behaviour.
Human-AI Interaction
Autonomous interactive AI is already present in our lives. This presence will increase very quickly, very soon. This will create a hybrid society in which humans have to invent the new norms of social interaction as new situations arise. Many such situations will not have evolutionary precedents. Take for example, a self-driving VW that is […]
Human-AI Interaction
Autonomous interactive AI is already present in our lives. This presence will increase very quickly, very soon. This will create a hybrid society in which humans have to invent the new norms of social interaction as new situations arise. Many such situations will not have evolutionary precedents. Take for example, a self-driving VW that is equipped with capacity to coordinate with and access the distributed collective memory of all other VWs on the street. To human drivers, this will be a completely new situation.
We have recently started to study the interactions between human agents and autonomous AI. We ask questions such as:
- what will be social norms (e.g., the rules of politeness) in the future society where human and AI agents will interact with each other as equals with diverging interests and preferences?
- How will humans interact with AI-powered decision support systems that, for example, will help a doctor in their diagnosis and practice?
- And in such case, if a medical malpractice occurs, who (the human or the AI) will be held responsible for the consequences?
These and similar questions are abundant around us now and will only increase in number and urgency in near future. We have so far has shown that humans do not adhere to social norms such as reciprocity and fairness when interacting with AI compared to interacting with other humans.
In a paper just accepted, we have shown the brain mechanisms involved in such human-specific normative conformity (Mahmoodi et al PLoS Bio, in press). Cognitive neuroscience can make a useful contribution to the transition from our current human-only social frame to the future, human-AI hybrid society. One of our recent research papers on this topic was published in 2021 and has been extensively featured in the international media such as NYTimes, Süddeutsche Zeitung, Deutschland Funk Radio, Swiss radio SRF.
Shared responsibility in collective decisions
Contradictory maxims such as “two heads are better than one” and “too many cooks spoil the broth” raise the question WHY people engage in collective decisions. We propose that an overlooked and very important reason to join collectives is sharing responsibility for decision outcomes. Sharing responsibility with others protects individuals from possible negative consequences of […]
Shared responsibility in collective decisions
Contradictory maxims such as “two heads are better than one” and “too many cooks spoil the broth” raise the question WHY people engage in collective decisions. We propose that an overlooked and very important reason to join collectives is sharing responsibility for decision outcomes. Sharing responsibility with others protects individuals from possible negative consequences of difficult and uncertain decisions by reducing regret, punishment and stress.
Motives to join a collective decision can relate to the decision process itself and its anticipated outcome. These motives include improving outcomes (combining effort and pooling intelligence, underlined); social inclusion and normative needs (in italic); and critically for us: shared responsibility (in bold). Of course, an important question is how all these different factors interact or add up to motivate people to engage in a collective decision.
We are currently running behavioral (online and in the lab) and neuroimaging experiments inspired from neuroeconomics and social psychology to empirically address questions related to this framework, for example:
- On regret: Do people anticipate less regret when deciding in group? Does experienced regret influence the choice to play alone or in a group? Is the group protected from negative consequences of costly decisions?
- On punishment: Do people violate norms more easily if they are part of a group because of the sharing of responsibility? Is punishment reduced for an individual in a collective structure?
- Neural basis of shared responsibility: using magnetoencephalography (MEG), we investigate the cognitive and neural basis of shared responsibility during collective decisions, from the moment participants are informed they are part of a group to the moment they make a collective decision, to the moment they process the outcome.
We explain our proposed framework in detail in our new perspective paper (El Zein, Bahrami & Hertwig, Nature Human Behaviour). The paper is openly accessible to pubic but in case you could not find it Marwa for a copy.
What happens in the brain of an influencer
We live in the age of persuasion. From the outcomes of political campaigns to our stand on issues such as global warming, immigration crisis and taxation, the fate of the most critical issues in our public life depends on persuaders working to influence public opinion. The research on social influence has been dominated by the motivation to understand the mind of the targets of influence (e.g. consumers, voters) in order to exert even more influence on them. Far less is known about the cognitive and neurobiological underpinnings of the source of the influenc
What happens in the brain of an influencer
We live in the age of persuasion. From the outcomes of political campaigns to our stand on issues such as global warming, immigration crisis and taxation, the fate of the most critical issues in our public life depends on persuaders working to influence public opinion. The research on social influence has been dominated by the motivation to understand the mind of the targets of influence (e.g. consumers, voters) in order to exert even more influence on them. Far less is known about the cognitive and neurobiological underpinnings of the source of the influence (e.g. spin doctors, financial advisers, pundits etc).
We investigate the workings of the minds of the advisers and persuaders, asking:
- What are the psychological and cognitive of attempting to influence others? We investigate the mental processes behind the formulation of strategic advising that is aimed not only at benefiting the client but also ensuring the consultant’s influence. The psychological theory providing the framework of our research is portrayed in comic story displayed below:
- What are the neural substrates of strategic advising? Can we identify the neuronal implementations of the cognitive processes mentioned in 1-1 in the human brain? Are these neuronal substrates predictive of the inter-individual differences we observe in people’s advising behaviour? We use functional and structural brain imaging (MRI) to address these questions.
- Is it possible to cast consultancy as a game theoretic problem between rival consultants who compete for influence over a common client? We use this approach to search for and draw the optimal strategies for consulting that maximise the consultant’s influence over their client in the long run.
How do we make decisions together with others?
What is the cognitive, computational and psychological basis of success and failure of collective decision making? Joaquin Navajas employs computational modelling and behavioural psychology to address this problem. Our lab has a long standing collaboration with the Gatsby Computational Neuroscience Unit in developing the math of interactive decision making.
How do we make decisions together with others?
What is the cognitive, computational and psychological basis of success and failure of collective decision making? To answer this question we employ computational modelling and behavioural psychology. Our lab has a long standing collaboration with the Gatsby Computational Neuroscience Unit in developing the math of interactive decision making.
- For example, in this paper, we ask what computational principles underlie the idiosyncratic variations in how people communicate their uncertainty to one another?
How does the referee integrate his opinion with those of his assistants to make a decision?
- Here in this paper, we have asked what information individuals communicate to one another when making joint decisions? What kind of decision rule(s) do they apply to the communicated information?
- How do people learn to cooperate with each other? In collaborations with the University of Oxfordand Tehran University we developed dynamic models of how individuals learn to calibrate their opinion against those of their peers in order for the group to do best.