Towards a Learning Architecture to Support Social Scaffolding for an Artificially Intelligent Disability Assistant

In the last decade novel sensing technologies enabled development of applications that help individuals with chronic diseases monitor their health and activities. These applications often generate large volumes of data that need to be processed and analyzed. At the same time, many of these applications target non-professionals and individuals of advanced age and low educational level. These users may find the data collected by the applications challenging and overwhelming, rather than helpful, and may require additional assistance in interpreting it. In this paper we discuss two different approaches to designing computing applications that not only collect the relevant health and wellness data but also find creative ways to engage individuals in the analysis and assist with interpretation of the data. These approaches include visualization of data using simple real world imagery and metaphors, and social scaffolding mechanisms that help novices learn by observing and imitating experts. We present example applications that utilize both of these approaches and discuss their relative strengths and limitations.

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Moral Responsibility and the Social Dynamics of Power and Oppression

10.1093/oso/9780190609610.003.0003 ◽

2018 ◽

Author(s):

Catriona Mackenzie

Keyword(s):

Moral Responsibility ◽

Sustained Attention ◽

Social Dynamics ◽

Social Power ◽

Interpersonal Dynamics ◽

The Social ◽

Social Scaffolding

This chapter argues that moral responsibility theorists who take seriously the social scaffolding of agency and the interpersonal dynamics at the heart of our practices need to pay more sustained attention to the effects of social power and oppression. David Shoemaker’s tripartite distinction between attributability, answerability, and accountability is used to develop this argument. The aim of Shoemaker’s distinction is to explicate how impairments of capacity with respect to one or more of these dimensions affect agents’ eligibility for moral responsibility ascriptions. In this chapter the tripartite distinction is used to tease out the various ways that moral responsibility ascriptions and practices are entangled with social dynamics of power, thereby affecting persons’ statuses as morally responsible agents. The chapter concludes by considering the implications of the argument for Strawsonian theories and justifications.

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Interpreting Health and Wellness Information

Auto-Identification and Ubiquitous Computing Applications ◽

10.4018/978-1-60566-298-5.ch005 ◽

2010 ◽

pp. 74-90 ◽

Cited By ~ 1

Author(s):

Lena Mamykina ◽

Elizabeth Mynatt

Keyword(s):

Chronic Diseases ◽

Real World ◽

Educational Level ◽

Advanced Age ◽

Health And Wellness ◽

Visualization Of Data ◽

Social Scaffolding

In the last decade, novel sensing technologies enabled development of applications that help individuals with chronic diseases monitor their health and activities. These applications can generate large volumes of data that need to be processed and analyzed. At the same time, many of these applications are designed for non-professional use by individuals of advanced age and low educational level. These users may find the data collected by the applications challenging and overwhelming, rather than helpful, and may require additional assistance in interpreting it. In this chapter, we discuss two different approaches to designing computing applications that not only collect the relevant health and wellness data but also find creative ways to engage individuals in the analysis and assist with interpretation of the data. These approaches include visualization of data using simple real world imagery and metaphors, and social scaffolding mechanisms that help novices learn by observing and imitating experts. We present example applications that utilize both of these approaches and discuss their relative strengths and limitations.

Download Full-text