Multiscale Computation and Dynamic Attention in Biological and Artificial Intelligence
Biological and artificial intelligence (AI) are often defined by their capacity to achieve a hierarchy of short-term and long-term goals that require incorporating information over time and space at both local and global scales. More advanced forms of this capacity involve the adaptive modulation of integration across scales, which resolve computational inefficiency and explore-exploit dilemmas at the same time. Research in neuroscience and AI have both made progress towards understanding architectures that achieve this. The use and development of multiscale innovations in robotic agents, game AI, and natural language processing (NLP) are pushing the boundaries of AI achievements. By juxtaposing biological and artificial intelligence, the present work underscores the critical importance of multiscale processing to general intelligence, as well as highlighting innovations and differences between the future of biological and artificial intelligence.
Does it pay to bet on your favourite to win? Evidence on experienced utility from the 2018 FIFA World Cup experiment
Using the 2018 FIFA World Cup as the setting for this exploratory study, the authors found substantial reluctance among England supporters to bet against the success of the England football team in the tournament. This decision not to offset a potential loss through hedging did not pay off in people's happiness following an England win. However, it was associated with a sharp decrease in people's happiness following an England loss, which was a similar experience among subjects who were randomly assigned to bet for an England win. Post-match happiness was relatively more stable among those who chose to hedge or were randomly allocated to hedge. We conclude that people do not hedge enough partly because they tend to overestimate the expected diagnostic cost of betting against their social identity, while underestimate the negative emotional impact from betting on their favourite to win when they did not win.
A Negotiation in Middlemarch
In this paper Professor Daniel Read and Professor Thomas Hills, analyse a negotiation drawn from George Eliot’s great novel Middlemarch: A story of provincial life. Using a case within the novel, we discuss a wide range of negotiation principles. This case provides insights into the importance of the prenegotiation, the role of preparation, empathy and the fostering of relationships (even when you would prefer not to), and the problems of focusing on one’s own BATNA rather than your counterparts’. The paper concludes with six key negotiation lessons for the fictional negotiator (and for us), with a brief account of how both fictional and “non-fictional” negotiations can contribute to our understanding of how to learn about and improve negotiation practice.
Partial liquidation under reference-dependent preferences
Can a multiple optimal stopping model aid investors in selling a divisible asset position?
Investors have Sshaped reference-dependent preferences whereby utility is defined over gains and losses relative to a reference level, and is concave over gains and convex over losses. In this paper the authors found that in contrast to the extant literature, investors may partially liquidate the asset at distinct price thresholds above the reference level.
Nonbelieved memories in the false memory archive
The False Memory Archive is a unique art collection which contains hundreds of false memory reports submitted by members of the general population to analyse these reports. In this paper the authors examined whether some of the memories reported in these submissions were better described as nonbelieved memories (NBMs). Furthermore, the researchers investigated the reasons for why people decided that their memory was false and assessed the verification strategies that people used to validate their mental representation.
A Nudgeathon for sexual health: co-designing HIV prevention strategies using behavioural economics
How can we achieve the UNAIDS goal to end the HIV/AIDS epidemic as a public health threat by 2030?
To achieve the UNAIDS goal to end the HIV/AIDS epidemic as a public health threat by 2030, action is needed to optimise the uptake of HIV testing and effective HIV prevention technologies, such as pre-exposure prophylaxis (PrEP) medication and treatment as prevention (TasP). Although significant gains in this area have been achieved globally, there is still a need to rethink how we target difficult-to-reach subpopulations.
In this Nudgeathon Associate Professor Dr Jason Ong, Research Fellow at the Melbourne Sexual Health Clinic, Monash University and Professor Daniel Read, Professor of Behavioural Science at the Warwick Business School are leading a team to investigate how successes in behavioural change from other disciplines may help to address the issue of controlling HIV using behavioural economics.
The Effect of Self-Awareness on Dishonesty
What is the relationship between dishonesty and self awareness? Can this realtionshbe explained by cognitive dissonnace?
In this working paper Ceren Beng¨u C¸ ıbık and our newest academic lead Professor Daniel Sgroi explore the relationship between self-awareness and dishonesty in a preregistered experiment with 1,260 subjects. By varying vary the level of awareness of subjects’ own past dishonesty and exploring the impact on behaviour in tasks that include the scope to lie: results showed that We find that in single-person non-interactive tasks, self-awareness of dishonesty helps to lower dishonesty in the future. However, in tasks that are competitive in nature becoming more aware of past dishonesty raises the likelihood of dishonesty. In this thought provoking paper, results showed when and why pointing out those who have been (dis)honest in the past can be an effective way to induce honesty in the future and when it might back-fire badly. It perhaps also shed some light on perceived increases in dishonesty in politics, the media and everyday life.
Measuring National Happiness with Music
Professor Daniel Sgroi and Dr Anthony Tuckwell, working with computer scientists Dr Alessandro Ragano and Dr Emmanouil Benetos create a new measure of national life satisfaction based on the emotional content of a country’s most popular songs. Using machine learning to detect the valence of the UK’s chart-topping song of each year since the 1970s, they show that it is very effective at predicting the leading survey-based measure of life satisfaction. Moreover they find that music is better able to predict life satisfaction than a recently-proposed measure of happiness based on the happiness enshrined within words (a method pioneered by Professors Thomas Hills, Daniel Sgroi and co-authors and published in Nature Human Behaviour in 2019). Our results have implications for the role of music in society, confirming the place of music as a “language of the emotions” and building on the use of language as a practical measure of public sentiment.
Artificial Intelligence (AI) can detect low-glucose levels
A new technique developed by researchers at the University of Warwick uses the latest findings of Artificial Intelligence to detect hypoglycaemic events from raw ECG signals, via wearable sensors.
How do consumers respond to missing (and deliberately withheld) information?
New research by Sunita Sah and Daniel Read (Warwick) investigates whether people understand that if others (marketers or politicians) withhold information from them, its likely to be bad news for the person from whom the information is being withheld. The short answer is that to a large degree people do not understand this. Useful to know the next time you come to restaurant that has not posted its hygiene rating on the door.
Why don't people stand up to dictatorships?
Professor Nick Chater asks why people don't rise up against dictatorial regimes.
Memory is damaged by air pollution, researchers find
A study of 34,000 people by Warwick researchers finds our memory is significantly affected by pollution.
Reading the past like an open book - researchers use text to measure two hundred years of happiness
Scientists from Warwick have discovered the year we were at our happiest. Our national happiness levels of previous centuries (1820-2009) measured for the first time.
Data science tackles some of society's biggest issues
Services for homeless people could be improved greatly through the use of data science, thanks to the UK's inaugural 12-week Data Science for Social Good (DSSG) programme.