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The traffic assignment problem aims to predict driver route choice, and is typically applied in the assessment of road schemes. The authors have previously published an SUE (Stochastic User Equilibrium) assignment algorithm, i.e. one which models variation in driver perception, and cost variation due to congestion. The algorithm works by minimising a function given by Sheffi and Powell (1982); in this paper the three terms of the function are investigated separately, and the possibility explored of constructing more sophisticated versions of the SUE algorithm.

This paper is designed to seek out the everyday narratives of copyright. To find these narratives, I analyze the comments section of websites where users can post their reactions to copyright-related stories. I argue that understanding how people who are not legal scholars frame the use of copyright as they discuss sharing, owning, and controlling the copy is a good place to begin to develop a sense for the everyday life of copyright law.

Most scholarly and governmental discussions about artificial intelligence (AI) today focus on a country’s technological competitiveness and try to identify how this supposedly new technological capability will improve productivity. Some discussions look at AI ethics. But AI is more than a technological advancement. It is a social question and requires philosophical inquiry. The producers of AI who are software engineers and designers, and software users who are human resource professionals and managers, unconsciously as well as consciously project direct forms of intelligence onto machines themselves, without considering in any depth the practical implications of this when weighed against human actual or perceived intelligences. Neither do they think about the relations of production that are required for the development and production of AI and its capabilities, where data-producing human workers are expected not only to accept the intelligences of machines, now called ‘smart machines’, but also to endure particularly difficult working conditions for bodies and minds in the process of creating and expanding the datasets that are required for the development of AI itself. This chapter asks, who is the smart worker today and how does she contribute to AI through her quantified, but embodied labour?

By the end of this chapter, you should be able to demonstrate an understanding of:

How sustainability messages have diffused into mainstream discourse?

The role of behavioural economics, specifically nudge theory, in encouraging sustainable behaviours.

The visual elements in marketing that support nudge theory.

How businesses are aligning with consumer concern for sustainability to illustrate their ‘wokeness’ to social issues.