Suchergebnisse

A government's response to increasing incidence of lifestyle-related illnesses, such as obesity, has been to encourage people to cook for themselves. The healthiness of home cooking will, nevertheless, depend on what people cook and how they cook it. In this article, one common source of cooking inspiration—Internet-sourced recipes—is investigated in depth. The energy and macronutrient content of 5,237 main meal recipes from the food website Allrecipes.com are compared with those of 100 main meal recipes from five bestselling cookery books from popular celebrity chefs and 100 ready meals from the three leading UK supermarkets. The comparison is made using nutritional guidelines published by the World Health Organization and the UK Food Standards Agency. The main conclusions drawn from our analyses are that Internet recipes sourced from Allrecipes.com are less healthy than TV chef recipes and ready meals from leading UK supermarkets. Only 6 out of 5,237 Internet recipes fully complied with the WHO recommendations. Internet recipes were more likely to meet the WHO guidelines for protein than other classes of meal (10.88 v 7% (TV), p < 0.01; 10.86 v 9% (ready), p < 0.01). However, the Internet recipes were less likely to meet the criteria for fat (14.28 v 24 (TV) v 37% (ready); p < 0.01), saturated fat (25.05 v 33 (TV) v 34% (ready); p < 0.01), and fiber (compared to ready meals 16.50 v 56%; p < 0.01). More Internet recipes met the criteria for sodium density than ready meals (19.63 v 4%; p < 0.01), but fewer than the TV chef meals (19.32 v 36%; p < 0.01). For sugar, no differences between Internet recipes and TV chef recipes were observed (81.1 v 81% (TV); p = 0.86), although Internet recipes were less likely to meet the sugar criteria than ready meals (81.1 v 83% (ready); p < 0.01). Repeating the analyses for each year of available data shows that the results are very stable over time.

AbstractThe last two decades have witnessed major disruptions to the traditional media industry as a result of technological breakthroughs. New opportunities and challenges continue to arise, most recently as a result of the rapid advance and adoption of artificial intelligence technologies. On the one hand, the broad adoption of these technologies may introduce new opportunities for diversifying media offerings, fighting disinformation, and advancing data-driven journalism. On the other hand, techniques such as algorithmic content selection and user personalization can introduce risks and societal threats. The challenge of balancing these opportunities and benefits against their potential for negative impacts underscores the need for more research in responsible media technology. In this paper, we first describe the major challenges—both for societies and the media industry—that come with modern media technology. We then outline various places in the media production and dissemination chain, where research gaps exist, where better technical approaches are needed, and where technology must be designed in a way that can effectively support responsible editorial processes and principles. We argue that a comprehensive approach to research in responsible media technology, leveraging an interdisciplinary approach and a close cooperation between the media industry and academic institutions, is urgently needed.

AbstractReading or viewing recommendations are a common feature on modern media sites. What is shown to consumers as recommendations is nowadays often automatically determined by AI algorithms, typically with the goal of helping consumers discover relevant content more easily. However, the highlighting or filtering of information that comes with such recommendations may lead to undesired effects on consumers or even society, for example, when an algorithm leads to the creation of filter bubbles or amplifies the spread of misinformation. These well-documented phenomena create a need for improved mechanisms for responsible media recommendation, which avoid such negative effects of recommender systems. In this research note, we review the threats and challenges that may result from the use of automated media recommendation technology, and we outline possible steps to mitigate such undesired societal effects in the future.