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Police issue warning over 'stupid and dangerous' TikTok trend that sees teens using AI to pretend a homeless person has broken into their house

Daily Mail - Science & tech

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Analysing the Needs of Homeless People Using Feature Selection and Mining Association Rules

Alcalde-Llergo, José M., García-Martínez, Carlos, Vaquero-Abellán, Manuel, Aparicio-Martínez, Pilar, Yeguas-Bolívar, Enrique

arXiv.org Artificial Intelligence

Homelessness is a social and health problem with great repercussions in Europe. Many non-governmental organisations help homeless people by collecting and analysing large amounts of information about them. However, these tasks are not always easy to perform, and hinder other of the organisations duties. The SINTECH project was created to tackle this issue proposing two different tools: a mobile application to quickly and easily collect data; and a software based on artificial intelligence which obtains interesting information from the collected data. The first one has been distributed to some Spanish organisations which are using it to conduct surveys of homeless people. The second tool implements different feature selection and association rules mining methods. These artificial intelligence techniques have allowed us to identify the most relevant features and some interesting association rules from previously collected homeless data.


Being smarter means you are more likely to use stereotypes

Daily Mail - Science & tech

People with higher cognitive abilities are often better able to spot patterns in the world around them, allowing them to excel in a wide range of tasks, from learning languages to recognizing faces. But, in some situations, even being intelligent has its drawbacks. A new study has found that these people are more likely to stereotype others based on the patterns they detect, potentially leading to negative consequences as they perpetuate social biases. A new study found that people with higher cognitive abilities are more likely to stereotype others. In the study, the researchers manipulated image-description pairings so that the faces with particular features were linked to negative stereotypes.


Households, The Homeless and Slums Towards a Standard for Representing City Shelter Open Data

Wang, Yetian (University of Toronto) | Fox, Mark S. (University of Toronto)

AAAI Conferences

In order to compare and analyse open data across cities, standard representations or ontologies have to be created. This paper defines a shelter ontology that includes concepts of shelters, slums, households and homelessness. The design of the ontology is based upon the data requirements of ISO 37120. ISO 37120 defines 100 indicators to measure and compare city performance. There are three shelter-themed indicators defined, namely 15.1 Percentage of city population living in slums, 15.2 Number of homeless per 100 000 population, and 15.3 Percentage of households that exist without registered legal titles. This ontology enables both the representation of the ISO 37120 Shelter theme indicators' definitions, and a city's indicator values and supporting data. This enables the analysis of city indicators by intelligent agents.