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.

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.

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.

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.

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.

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.

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.

Daniel Read presents new ideas on how to nudge people into thinking more of the future when making choices that extend into it.