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In response to an increasingly ageing world population, the World Health Organization has recently proposed a new framework – called Healthy Ageing – to better cater to older adults’ life needs and desires. This framework calls for transdisciplinary approaches to answer the challenges and opportunities posed by an ageing society. Following this framework, it is argued that the first step to accomplishing the goals of Healthy Ageing is to address the existing biases and stereotypes in the language used for addressing ageing issues. In this paper, we propose a series of linguistic guidelines that can help improve the lexicon used to talk about ageing in design research and practice, by countering many subconscious ageist biases and stereotypes. Ageism, especially in its implicit form, is a pervasive negative force that can affect not only design practitioners and researchers but also older adults, who often use ageist language to describe themselves. The proposed guidelines would also help the “false friends” of ageing people, who may be using apparently innocuous words, terminology, and remarks to refer to ageing, without perhaps realising the underlying ageist attitudes and stereotypes hidden in their used language. Overall, we aim to foster a change in design researchers’ and practitioners’ perspective on ageing, by paving the way for a transdisciplinary discourse on designing for ageing, which could then be further expanded and explored to eliminate ageism in design.

Despite a rapidly ageing world population, ageism – particularly in its implicit form – is widespread in society. In this article, we propose that a paradigm shift is needed in how we approach ageing-related design research and practice in areas such as assistive technologies. We also put forward the idea of using the Healthy Ageing (HA) framework of the WHO as the basis for new lines actions that can be taken by design researchers and practitioners to address implicit ageism in society through their work.

The email communication system is threatened by unsolicited commercial email aka spam. In response, spam filters have been deployed widely to help reduce the amount of spam users have to cope with. This paper describes work towards helping users better understand the often complex decision making that is spam filtering. An investigation of a number of popular web-based email services suggests that the filtering process is typically implemented as a black box allowing very little user involvement. In order to explore how we could help users understand how spam filters work and how they assess messages we conducted a number of user experiments using a simulated email interface providing richer spam filtering information than the webmail interfaces we investigated. Feedback indicates that additional information provided by the interface would be welcome and suggests to further investigate ways to involve users in the filtering process.

The email communication system is threatened by unsolicited commercial email aka spam. In response, spam filters have been deployed widely to help reduce the amount of spam users have to cope with. This paper describes work towards helping users better understand the often complex decision making that is spam filtering. An investigation of a number of popular web-based email services suggests that the filtering process is typically implemented as a black box allowing very little user involvement. In order to explore how we could help users understand how spam filters work and how they assess messages we conducted a number of user experiments using a simulated email interface providing richer spam filtering information than the webmail interfaces we investigated. Feedback indicates that additional information provided by the interface would be welcome and suggests to further investigate ways to involve users in the filtering process.