Reducing fall risk with combined motor and cognitive training in elderly fallers

Background. Falling is a major clinical problem in elderly people, demanding effective solutions. At present, the only effective intervention is motor training of balance and strength. Executive function-based training (EFt) might be effective at preventing falls according to evidence showing a relationship between executive functions and gait abnormalities. The aim was to assess the effectiveness of a motor and a cognitive treatment developed within the EU co-funded project I-DONT-FALL. Methods. In a sample of 481 elderly people at risk of falls recruited in this multicenter randomised controlled trial, the effectiveness of a motor treatment (pure motor or mixed with EFt) of 24 one-hour sessions delivered through an i-Walker with a non-motor treatment (pure EFt or control condition) was evaluated. Similarly, a 24 one-hour session cognitive treatment (pure EFt or mixed with motor training), delivered through a touch-screen computer was compared with a non-cognitive treatment (pure motor or control condition). Results. Motor treatment, particularly when mixed with EFt, reduced significantly fear of falling (F(1,478) = 6.786, p = 0.009) although to a limited extent (ES -0.25) restricted to the period after intervention. Conclusions. This study suggests the effectiveness of motor treatment empowered by EFt in reducing fear of falling.Peer ReviewedPostprint (published version

Signs for Ethical AI: A Route Towards Transparency

Artificial Intelligence (AI) has recently raised to the point where it has a direct impact on the daily life of billions of people. This is the result of its application to sectors like finance, health, digital entertainment, transportation, security and advertisement. Today, AI fuels some of the most significant economic and research institutions in the world, and the impact of AI in the near future seems difficult to predict or even bound. In contrast to all this power, society remains mostly ignorant of the capabilities, requirements and standard practices of AI today. Society is becoming aware of the dangers that come with that ignorance, and is rightfully asking for solutions. To address this need, improving on current practices of interaction between people and AI systems, we propose a transparency scheme to be implemented on any AI system open to the public. The scheme is based on two main pillars: Data Privacy and AI Transparency. The first recognizes the relevance of data for AI and is supported by GDPR, the most important legislation on the topic. The second considers aspects of AI transparency yet to be regulated: AI capacity, purpose and source. Lacking legislation to build upon, we design this pillar based on fundamental ethical principles. For each of the two pillars, we define a three-level display. The first level is based on visual signs, inspired by traffic signs managing the interaction between people and cars, and designed for quick and universal interpretability. The second level uses a factsheet system, providing further detail while still abstracting the subject. The last level provides access to all available details. After detailing and exemplifying the proposed transparency scheme, we define a set of principles for creating transparent by design software, to be used during the integration of AI components on user-oriented services.Comment: 27 pages, 7 figures, 1 tabl

Social Network Analysis and the illusion of gender neutral organisations

This thesis uses tools and measures emerging social network analysis to study whether organisations are gender neutral. (...) We will be using the same data as these authors as Scandinavian countries and, specially, Norway are quite advanced in implementing equality policies. Equality strategies have been seen as potential ways to counteract the strong patterns of occupational sex segregation, both from governments, policymakers as well as researchers. We will focus only in the data referred to the corporate Boards of Directors (BODs). The complete data description of the data is given in x4.1. In particular, we do believe that social network analysis will be a useful to help to answer some relevant questions as: 1. Which will be the influence of women in society after the implementation of gender equality policies? 2. Do relations among BODs members will change? 3. Are mandatory gender quotas on corporate boards good policies

Investing in AI for social good: an analysis of European national strategies

Artificial Intelligence (AI) has become a driving force in modern research, industry and public administration and the European Union (EU) is embracing this technology with a view to creating societal, as well as economic, value. This effort has been shared by EU Member States which were all encouraged to develop their own national AI strategies outlining policies and investment levels. This study focuses on how EU Member States are approaching the promise to develop and use AI for the good of society through the lens of their national AI strategies. In particular, we aim to investigate how European countries are investing in AI and to what extent the stated plans contribute to the good of people and society as a whole. Our contribution consists of three parts: (i) a conceptualization of AI for social good highlighting the role of AI policy, in particular, the one put forward by the European Commission (EC); (ii) a qualitative analysis of 15 European national strategies mapping investment plans and suggesting their relation to the social good (iii) a reflection on the current status of investments in socially good AI and possible steps to move forward. Our study suggests that while European national strategies incorporate money allocations in the sphere of AI for social good (e.g. education), there is a broader variety of underestimated actions (e.g. multidisciplinary approach in STEM curricula and dialogue among stakeholders) that can boost the European commitment to sustainable and responsible AI innovation.The authors are supported by the project A European AI On Demand Platform and Ecosystem (AI4EU) H2020-ICT-26 #825619. The views expressed in this paper are not necessarily those of the consortium AI4EU. The authors would also thank Sinem Aslan and Chiara Bissolo for their support in the quantitative overview and qualitative analysis respectively.Peer ReviewedPostprint (published version

Automatic classification of gait patterns using a smart rollator and the BOSS model

Nowadays, the risk of falling in older adults is a major concern due to the severe consequences it brings to socio-economic and public health systems. Some pathologies cause mobility problems in the aged population, leading them to fall and, thus, reduce their autonomy. Other implications of ageing involve having different gait patterns and walking speed. In this paper, a non-invasive framework is proposed to study gait in elder people using data collected by a smart rollator, the i-Walker. The analysis presented in this article uses a feature extraction method and a spectral embedding to represent the information and Bayesian clustering for the knowledge discovery. The algorithm considers raw data from the i-Walker sensors along with the calculated walking speed of each individual, which has been already used in clinical studies to assess physical and cognitive status of older adults. The results obtained demonstrate that the proposed analysis has the potential to separate in clusters the people of the two groups of interest: young people and geriatric.Peer ReviewedPostprint (author's final draft

European Strategy on AI: Are we truly fostering social good?

Artificial intelligence (AI) is already part of our daily lives and is playing a key role in defining the economic and social shape of the future. In 2018, the European Commission introduced its AI strategy able to compete in the next years with world powers such as China and US, but relying on the respect of European values and fundamental rights. As a result, most of the Member States have published their own National Strategy with the aim to work on a coordinated plan for Europe. In this paper, we present an ongoing study on how European countries are approaching the field of Artificial Intelligence, with its promises and risks, through the lens of their national AI strategies. In particular, we aim to investigate how European countries are investing in AI and to what extent the stated plans can contribute to the benefit of the whole society. This paper reports the main findings of a qualitative analysis of the investment plans reported in 15 European National StrategiesComment: 6 pages, 1 figures, submitted at IJCAI 2020 Workshop on AI for Social Goo

Health recommender system design in the context of CAREGIVERSPRO-MMD project

CAREGIVERSPRO-MMD an EU H2020 funded project aims to build a digital platform focusing on people living with dementia and their caregivers, offering a selection of advanced, individually tailored services enabling them to live well in the community for as long as possible. This paper provides an outline of a health recommender system designed in the context of the project to provide tailored interventions to caregivers and people living with dementia.Peer ReviewedPostprint (published version

The digital revolution in the urban water cycle and its ethical–political implications: a critical perspective

The development and application of new forms of automation and monitoring, data mining, and the use of AI data sources and knowledge management tools in the water sector has been compared to a ‘digital revolution’. The state-of-the-art literature has analysed this transformation from predominantly technical and positive perspectives, emphasising the benefits of digitalisation in the water sector. Meanwhile, there is a conspicuous lack of critical literature on this topic. To bridge this gap, the paper advances a critical overview of the state-of-the art scholarship on water digitalisation, looking at the sociopolitical and ethical concerns these technologies generate. We did this by analysing relevant AI applications at each of the three levels of the UWC: technical, operational, and sociopolitical. By drawing on the precepts of urban political ecology, we propose a hydrosocial approach to the so-called ‘digital water ‘, which aims to overcome the one-sidedness of the technocratic and/or positive approaches to this issue. Thus, the contribution of this article is a new theoretical framework which can be operationalised in order to analyse the ethical–political implications of the deployment of AI in urban water management. From the overview of opportunities and concerns presented in this paper, it emerges that a hydrosocial approach to digital water management is timely and necessary. The proposed framework envisions AI as a force in the service of the human right to water, the implementation of which needs to be (1) critical, in that it takes into consideration gender, race, class, and other sources of discrimination and orients algorithms according to key principles and values; (2) democratic and participatory, i.e., it combines a concern for efficiency with sensitivity to issues of fairness or justice; and (3) interdisciplinary, meaning that it integrates social sciences and natural sciences from the outset in all applications.Peer ReviewedPostprint (published version