Towards an Ethical Framework for the Design and Development of
Inclusive Home-based Smart Technology for Older Adults and People
with Disabilities
Emma Murphy
, Damian Gordon
, Brian Keegan
, Julie Doyle
, Ioannis Stavrakakis
and Dympna O’Sullivan
ASCNet Research Group, School of Computer Science, Technological University Dublin, Dublin 7, Ireland
Netwell CASALA, Dundalk Institute of Technology, Dundalk, Co. Louth, Ireland
Keywords: Digital Ethics, Digital Health, Older Adults, People with Disabilities, Human Centred Design, Co-creation.
Abstract: Unique ethical, privacy and safety implications arise for people who are reliant on home-based smart
technology due to health conditions or disabilities. In this position paper we highlight a need for a reflective,
inclusive ethical framework that encompasses the life cycle of smart home technology design. We present
key ethical considerations in the design, development and deployment of smart home-based technology for
older adults and people with disabilities. Using ethical theories, human-centred design and personas we
explore how some of these critical issues can be addressed. Finally, we propose a novel ethical framework for
the development of inclusive home-based smart technology which combines these key considerations with
existing models of design.
The planning, design, development and
implementation of home-based smart technology to
enhance the quality of life of a particular individual is
a complex and evolving challenge, and these
complexities can be amplified when end users are
older or have a disability. Unique ethical, privacy and
safety implications arise for people who are reliant on
technology due to health conditions or disabilities.
The aim of home-based smart technology is to
provide utility to an end user by enhancing their
independence and improving quality of life, but if
attention has not also been paid to ethical and privacy
issues, the end user can have difficult and unfair
choices to make.
While ethical approaches have been applied to
particular aspects and phases of smart home-based
technology design and evaluation there is a need for
a practical ethical framework that spans the
technology life cycle and that can address the specific
requirements of people with sensory, physical or
cognitive impairments. In this position paper, we
argue human-centred design and participatory
techniques must form part of a larger multi
stakeholder ethical framework for the design of
inclusive smart spaces for older people and people
with disabilities.
Home-based smart technology encourages
independent living at home with the support of smart
technologies. Specialised assistive devices,
Murphy, E., Gordon, D., Keegan, B., Doyle, J., Stavrakakis, I. and O’Sullivan, D.
Towards an Ethical Framework for the Design and Development of Inclusive Home-based Smart Technology for Older Adults and People with Disabilities.
DOI: 10.5220/0010879900003123
In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 5: HEALTHINF, pages 614-622
ISBN: 978-989-758-552-4; ISSN: 2184-4305
2022 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
smartphone or tablet based applications, on-body or
passive sensing technology can be used to increase,
maintain, or improve the functional capabilities of
older adults or individuals with disabilities. Feedback
and information from monitoring technology can be
relayed to occupants or shared with informal
caregivers to aid with decision making about a
person's health and wellbeing.
Challenges in the development of inclusive smart
technology include how to develop understandable
and usable technologies so that they meet individual
variations in needs and abilities so that they help to
maintain autonomy, provide meaningful activities,
address the emotional state of individuals and
promote social inclusion (Nunes, 2015). Moreover,
there is a great variety within these user groups, such
as differences in demographics (e.g., socioeconomic
status) and personality, but also due to the diversity
of specific conditions, each with different
behavioural, cognitive, and emotional consequences.
It is, therefore, vital to have extensive insight into the
dynamic needs, wishes, and abilities of these user
groups and a reiterated theme in the literature is the
essential requirement to involve older adults or
individuals with disabilities in identifying which
needs technologies should meet as well as in the
development and evaluation of such technology
(Jovanovic, 2021; Mannheim, 2019; Cesta, 2018;
Elers, 2018). A review of the literature has
highlighted the following as ethical considerations
when developing smart assistive technologies.
Informed Consent.
The pervasive nature of some smart devices raises
issues of technological understanding and consent. In
addition, older adults or persons with specific
disabilities might have a reduced or even
compromised ability to decide for themselves about
the use of smart technology (O’Connor, 2017).
Smart devices gather a broad spectrum of data about
their users, ranging from in-application activity to
communications to movement and location data.
Combined with their pervasive nature, data can be
collected and used in ways that are not always clear
to end users (O’Connor, 2017; Gochoo, 2021).
Security in smart spaces refers to securing the IoT
devices and the networks they're connected to. This
involves physical security as well as security of the
data from intrusion and cyber attacks. Users need to
trust in these devices and that their data is secured
(Karale, 2021). Choosing the right technology to fit
the requirements is crucial in avoiding over or
unnecessary surveillance. For example when it comes
to security, a motion sensing device may be sufficient
in place of a camera to determine if a busy path is
clear of traffic to ensure safe passage.
Technology should be designed to accommodate
existing living patterns and should offer users control
and influence over their lives and well-being
(FakhrHosseini, 2019).
Ensuring the safety of older adults and persons with
disabilities is crucial to their independence and
quality of life. From a technology standpoint, safety
and technological reliability are highly coupled and it
is important that evaluations of smart technologies are
not limited to testing in laboratory settings designed
to simulate potential end user environments rather
than more complex real world environments (Pigini,
Data Accuracy.
The accuracy of data collected in smart spaces
depends on a number of factors including the
reliability of the device, device configuration or
placement, device misuse or misunderstanding.
Smart sensors can also generate false positives and
inferences, recommendations and predictions based
on inaccurate data will contain errors (Aramendi
Data Sharing.
Data collected via smart technologies is often shared
with manufacturers and third parties. This can be for
varied purposes, to help the manufacturer to improve
the product or to aggregate data for analytics and
insights. Older adults or persons with disabilities may
wish to share data with formal or informal caregivers
but they should have control over how and with
whom their own data is shared (Doyle et al., 2015).
Data management policies should be available and
accessible (Mocrii, 2018).
Transparency and Trust.
Transparency enables end users to understand the
smart system. It incorporates previous factors such as
privacy and data management and ensuring that these
are well understood by those using the system.
Transparency is important at both the device and
system levels (Yao, 2019). Understanding how the
data is stored and managed is essential for trust of
Towards an Ethical Framework for the Design and Development of Inclusive Home-based Smart Technology for Older Adults and People
with Disabilities
system and data Doyle et al. (2015). To trust decisions
computed by smart systems, users need to know how
that system arrives at its conclusions and
recommendations. Trust is related to data accuracy
and transparency above and explanation below
(Cannizzaro, 2020).
Existing approaches to explanations for smart
systems are tailored more towards interpretations that
are more suitable for modelers and less for technically
inexperienced users. The majority of smart systems
do not incorporate explanation capabilities (Nikou,
Immersive technology requires immersive data to
understand the environment and the individual. This
means allowing technology access to our personal
spaces. This can be intrusive if not done correctly and
tailored for the cohort. Passive, low impact, low
visibility, low maintenance and high reliability
should be considered as high priority requirements
when dealing with older adults and people with
disabilities. These requirements have a cost trade off
over disposable low cost IoT devices.
It is accepted that end users make trade-offs when
using smart technology, for example, data privacy for
functionality (Singh et al., 2016) or increased
autonomy, security over privacy for better
surveillance, increased functionality or better
displays for less explanations or usability for
complexity. We argue that these trade-offs should not
be inevitable, particularly for persons who are reliant
on technology. We posit that an ethical, user driven
framework incorporating a design-driven approach
can reduce or eliminate these trade-offs by better
understanding the needs and requirements of end
In terms of ethical frameworks, individual ethical
theories place different weight on the importance of
intentions versus outcomes in evaluating actions.
Deontology emphasises the intention to act in
accordance with our duties (intentions), and believes
the consequences of our actions have no ethical
relevance. The utilitarian view is that everyone's
interests have equal weight, and as form of
consequentialism, judges actions by their results or
outcomes. Virtue ethics becomes increasingly
popular in philosophy of technology, for example,
Vallor (2016) has argued that virtue ethics with its
focus on choices that aim at the ‘good life' is ideally
suited for managing complex, novel, and
unpredictable moral landscapes, just the kind of
landscape that today’s emerging technologies
present. Value Sensitive Design (Friedman, 2013),
defined as “a theoretically grounded approach to the
design of technology that accounts for human values
in a principled and comprehensive manner
throughout the design process” could be considered
an example of Vallor’s (2016) application of virtue
ethics to technology.
It is fair to say that the software engineering
process has traditionally been driven by a more
utilitarian approach by focusing on outcomes in terms
of the development of commercial products or
services. But a blind spot for intentions has led to
many high profile ethical technology failures where
software has displayed unintended consequences
(e.g. biases or privacy violations) or been used in a
different and unethical manner from that for which is
was originally designed (e.g. data harvesting
applications embedded in social media or facial
recognition technology used for commercial purposes
when it had originally been developed for law and
order purposes). The recent emphasis on data
management and governance and high profile data
breaches have led to high level data management
frameworks incorporating ethics, for example the UK
Department for Digital, Culture, Media & Sport
(2020) formulated an ethics framework in its National
Data Strategy.
Figure 1: Framework to assess individual invasiveness of
the outcome of data processing vs. societal value (O’Keefe
and O’Brien, 2018).
At lower levels, frameworks such as that by O’Keefe
and O’Brien (2018) (Figure 1 and Table 1) offer
organisations a practical guide to implementing data
ethics. These frameworks have tended to follow the
traditional trajectory in software engineering by
focusing more on outcomes than intentions. Recent
welcome developments have shifted the emphasis
HEALTHINF 2022 - 15th International Conference on Health Informatics
Table 1: First Principles Ethical Test (O’Keefe and
O’Brien, 2018).
First Principles Ethical Test:
“Does the outcome of your design/algorithm/process
outcome contribute positively to ‘the good’, or positive
preservation of human rights?” (O'Keefe and O’Brien,
Does it preserve or enhance human dignity?
Does it preserve the autonomy of the human?
Is the processing necessary and proportionate?
Does it uphold the common good?
from outcomes to intentions to reduce blind spots in
technology development, for example Consequence
Scanning is an Agile approach that fits within an
iterative development cycle and encourages
organisations to consider the potential consequences
of their product or service on people, communities
and the planet (Brown, 2019).
Research projects involving human participants
undergo ethical assessments and more recently data
protection impact assessments that are built on some
of the outcome-focused ethical frameworks presented
above but typically these occur at the end of the
technology design phase. This point of ethical
evaluation is usually late in the development of the
technology or research project and focus on the
impact of the system as designed on the research
participants. At this point, it is arguably too late for
researchers to consider questions such as “should this
technology ever have been developed in the first
place?”. We argue that a framework is required that
allows us to reflect on ethical issues - those related to
both intentions and outcomes - at challenge points
throughout the technology life cycle.
Most technology lifecycle models involve a user
requirements phase, for example the incorporation of
use cases as part of purpose and process
specifications within a practical IoT design
methodology (Bahga and Madisetti, 2021). However
it can be difficult to capture the complex requirements
involved in designing home-based smart technology
for older adults and people with disabilities without
involving them directly in the process.
Human-centred participatory approaches to
technology that involve end users at every stage of the
design process from requirements gathering to
prototype design and iterative development are not
novel. Design thinking, first proposed in 1969
(Simon, 1969) as a three step process is most
commonly applied to technology using the five stage
user centred, iterative design model developed by the
Hasso-Plattner Institute of Design at Stanford
University (see figure 2).
Figure 2: Five stages of Design Thinking (Hasso Plattner
Institute of Design, 2010).
However, we need to acknowledge that even
when a user-centred approach such as design thinking
is adopted, designs can still be technology-led or
driven by researchers rather than end users (Rogers
and Marsden, 2013) due to practical constraints such
as meeting requirements of funders or commercial
technology partners involved in the design. The
tensions between the requirements of relevant
stakeholders and a genuine user centred approach are
important to acknowledge for a holistic ethical
approach to design.
There are multiple stakeholders involved in the
creation, implementation and deployment of home-
based smart technology for health and wellbeing.
Social models of research and care for older adults
and people with disabilities have progressed
participatory approaches to technology design and
have led to more inclusive approaches to the entire
research process. There is a growing body of research
exploring ethnographic methodologies for a co-
researcher approach in the areas of developing age-
friendly concepts, (Buffel, 2015; Egan et al., 2014)
and disability research (Cappelen and Andersson,
2021). Rather than passively taking part in a task or
design phase, research participants can be viewed as
partners in the entire research lifecycle, with a focus
on conceptual issues of identity, participation and
support networks (Carroll and Rosson, 2013). It
should be acknowledged that some applications of
participatory approaches to technology design have
been critiqued as having a narrow interpretation of
ethnographic methods as a requirements gathering
exercise and have ignored core insights of
ethnographic inquiry, such as the relationship
between researcher and subject (Dourish, 2006). An
honest understanding of the relationship is crucial to
being able to evaluate ethical risk through the entire
design lifecycle.
A further criticism of Human Centred Design has
been the perception that the latest technology
Towards an Ethical Framework for the Design and Development of Inclusive Home-based Smart Technology for Older Adults and People
with Disabilities
advancements may not be utilised with a user driven
approach (Norman, 2005). This critique highlights
the need to involve multistakeholder design teams
that involve technology experts co-designing with
end users so that technological capabilities are well
matched to user needs. Furthermore human centred
does not preclude innovative technology designs. For
example recent state-of-the-art IoT environments
have explored how systems can be more human
centric by incorporating contextual elements that
have meaning for users such as time and space based
on proxemic interactions (Calderon, et al., 2016).
Personas are a useful tool in a human centred design
approach to understand and communicate user needs
and requirements. If designers want to test potential
solutions, but don’t have continuous access to the
end-users, they can create fictional characters that can
be used to represent a collection of the kinds of people
who could be using that potential solution, called
personas (Cooper, et al., 2014). Although some
researchers have criticised the use of personas by
pointing out that real customers are preferable to the
use of personas, there are many cases where this is not
possible, so personas are an effective, if somewhat
inferior, alternative (Salminen, et al., 2018). Studies
such as Long (2009) have shown that personas can
result in many benefits, including: more usable
designs, more user-centred discussions, and more
effective communication in design teams.
In this case, we have developed personas for this
process for design ideation to help create stories that
bring to life the existing data, theory and literature
(Gordon, et al., 2013) to help to understand and
communicate the key ethical issues presented above.
The two personas are as follows:
John Neat
John is a software
developer and has a
good understanding
of data flow and
privacy issues. John
has low vision and is
a wheelchair user.
John relies on various smart devices for daily
activities. He has concerns regarding the data
management for some of the commercial devices that he
uses. As a software developer he is well aware that even
if the creator of an application is very scrupulous about
their own data management, the application will
invariably use third-party libraries whose data
management policies may be impossible to
determine. For example he is concerned with how his
voice recordings for his voice assistant are stored and
shared with third party companies. However despite his
concerns, this is the only device that is accessible and so
he needs to make a difficult decision between his daily
activities and his personal privacy.
John is married to Judy, and they have two teenage
children, Gloria and Edward, who also use the family
smart speaker, which again, John is concerned that this
data will be shared, and that marketing companies will
have an extensive profile about his children before they
even become adults.
Mary Noble
Mary is a retired
Mathematics teacher,
and keeps up to date
with the national maths
curriculum so that she
can try to take the state
exams each year, she
feels this helps her to
monitor her cognitive
Mary has been diagnosed with a Mild Cognitive
Impairment that may be the early stages of dementia. She
has high blood pressure, high cholesterol and type II
diabetes that she manages with medication. Mary has an
old fashioned large keyed flip phone that she uses for
making calls. Her children recently gave her an iPad which
gathered dust for a while but her neighbour Kathleen
showed her how to use a great app called Rekall that has
a collection of puzzles, a diarying feature that she uses
with her neighbour, and a calendar feature that reminds
her of key events during the day, and during the week.
Mary has recently joined a research project that
involves her using a prototype of a smart pill box that
helps her to manage her complex medication routine and
is linked to an app on her iPad and alerts her when
something is wrong in relation to her medication dosage,
timing or frequency. Her daughter and neighbour
Kathleen are also sent alerts. Her pharmacist is also part
of the study and the system updates him when she needs
a medication refill.
HEALTHINF 2022 - 15th International Conference on Health Informatics
Mary is enjoying taking part in the research and while
she finds the technology useful, she does not fully
understand how her data is used in the project. She enjoys
the regular meetings with the research team when they
call to her house to interview her about the technology.
She is anxious that she will not be able to answer their
questions or use the technology if her memory
In the first persona, John Neat, we have tried to
synthesise the unique ethical and privacy implications
that arise for people who are reliant on a device or
technology due to health conditions or disabilities.
Accessibility requirements can generate unique
challenges and lack of choice that can pose difficult
choices for individuals and create an unfair trade-off
between personal ethical concerns with benefits to
health and everyday quality of life. In this persona,
John has to balance his independence through the use
of a voice assistant and the risk to privacy of his
family. We have tried to visualise this trade-off using
a matrix based on the O’Keefe and O’Brien (2018)
model presented in figure 1 but this time considering
the utility of a technology vs. the ethical risk posed
(see figure 3).
Figure 3: Considering the trade-off between utility and
ethical risk that is particularly relevant to older adults and
people with disabilities.
In the second persona we describe a smart pill
dispenser that sends alerts to the end user and their
network of care. We tried to highlight in this persona
the challenges that need to be addressed when a
research participant has low digital literacy which
will affect her use of the devices but her
understanding of the data flow and data management
within the research project. If these are not accessible
and controllable by the user, there are ethical risks
around autonomy and consent for the research and
related technology. Mary also has a cognitive
impairment that may worsen over time and this also
highlights that there can be ethical risks for the
sustainability of a system that is designed to support
a person at a point in time but may become redundant
if their situation, health or capabilities change.
Finally, we tried to illustrate the importance of the
relationship between a researcher and participants in
studies that deploy home-based smart technologies.
Participants like Mary may enjoy the social aspects of
being part of a research project and the effects of this
need to be considered after the technology is
withdrawn and a study ends. The relationships
between participants, their networks of care,
researchers, technology designers need to be
considered in the design of any research project that
involves home-based smart technology.
This research proposes a new ethical framework, that
we have entitled the 5D Framework, for the
development of inclusive home-based smart
technology by combining the research presented
above with aspects of the five-phase design thinking
model proposed by the Hasso-Plattner Institute of
Design (, at Stanford, USA (Apiyanti and
Dewi, 2019), as well as elements of the UK Design
Council’s Double Diamond Model (Howard, et al.,
Crucially, the Framework emphasises that the
user is at the heart of the entire framework - they must
be the co-designers of the system; in combination
with the OKeefe and OBrien ethics model and the
practical application of ethics in value-sensitive
design (Friedman, 2013), these two dimensions are
present in all five stages of the framework. The
Design Team are a team of participants that include
the end-user, as well as experts in technology and
relevant health domain i.e. clinicians, occupational
therapists, physiotherapists etc.
In Appendices A and B we have presented two
checksheets that can be used as prompts for system
developers with some of the key ethics issues that are
important for these systems, echoing themes
identified in Section 2, as well as the O’Keefe and
O’Brien (2018) Framework and in value-sensitive
design (Friedman, 2013). The checksheet in
Appendix A focuses on data-level ethical
considerations, and the one in Appendix B focuses on
system-level issues. The 5D Framework is as follows:
1. Discover
In this stage the full Design Team must begin a two-
way dialogue with the end-user (and other parties) in
a thoughtful manner to understand their needs. If
Towards an Ethical Framework for the Design and Development of Inclusive Home-based Smart Technology for Older Adults and People
with Disabilities
they cannot locate any end-users, they should use
personas such as those provided in Section 5.
They may use techniques from Software
Engineering, including Requirements Gathering and
Knowledge Elicitation (Sommerville, 2015), and the
IoT design methodology from Bahga and Madisetti
They may use design and research techniques
including interviews, ethnographical diarying, and
shadowing (Creswell, 2021).
From an ethics perspective, the three main ethical
theories from Section 3 (Deontology, Utilitarianism,
and Virtue ethics) need to be considered.
Assess potential benefit and harm for every
stakeholder group as proposed in (Friedman, 2013)
Basic research ethics protocols must also be used,
adhering to standard policies and codes, and it would
be expected to undergo a formal ethics approval.
2. Define
In this stage the full Design Team are trying to
encapsulate their findings from the Discover Stage
into a series of models, noting key challenges (pinch
points and pain points) as well as existing
affordances. Again, the end-user is a core member of
the Design Team, and they are both the subject of
the design, and the architect of the solutions. For the
times they are not available, the personas can be
They may use techniques from Software
Engineering, including Use Case Diagrams and Data
Flow Diagrams (Sommerville, 2015) and the IoT
design methodology from Bahga and Madisetti
They may use design techniques such as MindMaps
(or Spider Diagrams) and Gap Analysis to help
clarify their thinking (Buzan and Griffiths, 2013).
They may also refer to Assistive Technology models
such as the HAAT (Human, Activity, Assistive
Technology) and the TAM (Technology Acceptance
Model) (Cook, et al., 2020).
From an ethics perspective, the O’Keefe and
O’Brien (2018) Framework (looking at Dignity,
Autonomy, Necessity, and Good)
3. Develop
In this stage the full Design Team are working on
identifying a range of potential approaches to
addressing the issues identified in the two previous
stages. Again, the end-user will be a vital force in
the stage.
They may use techniques from Software
Engineering including Paper Prototyping and
“Wizard of Oz” Prototyping (Sommerville, 2015), as
well as the two personas, and the IoT design
methodology from Bahga and Madisetti (2014)
They may use design techniques such as the Six
Thinking Hats and Ishikawa Diagrams (Michalko,
A research ethics review should be conducted at this
point to ensure that none of the proposed solutions
diverge significantly from the formal ethics
This is likely to be the most iterative and
cyclical stage.
4. Deliver
In this stage the full Design Team are selecting a
single potential solution from those developed in the
previous stage, and it is vital that the end-user is
asked and listened to, as well as using personas
where needed.
They may use techniques from Software
Engineering including Vertical and Horizontal
Prototyping (Sommerville, 2015).
They may use design techniques including User
Stories and Storyboards (Sommerville, 2015),
Personas, Empathy Maps (Hasso Plattner Institute of
Design, 2010)
The ethics checksheets in Appendices A and B
should be discussed in meetings and reflected on
carefully. The team may also consider undertaking a
Data Protection Impact Assessment at this stage
(Bieker, 2016).
5. Determine
In this stage the full Design Team are testing the
effectiveness of their solution. The system is
deployed and the team are determining what aspects
of the system work well, and which are not fully
serving their purpose. This section includes
considerations relating to maintenance and
They may use techniques from Software
Engineering including User Acceptance Testing and
Performance Testing (Sommerville, 2015).
They may use design techniques such as group-
based roleplay and the Think-Aloud Protocol
(Norman, 1986).
They may use educational techniques such as
Reflective Practice and Metacognitive Strategies
(Gravells and Simpson, 2014).
The ethics checksheets in Appendices A and B are
crucial at this stage of the process. They must also
consider undertaking a Data Protection Impact
Assessment at this stage (Bieker, 2016). as well as
the O’Keefe and O’Brien (2018) First Principle Test.
A research ethics review should also be done at this
point to make sure no research ethics violations have
occurred. All team members must consider if there
are any lingering ethical issues that need to be
The development of inclusive home-based smart
technology presents many unique ethical challenges,
HEALTHINF 2022 - 15th International Conference on Health Informatics
and when this is allied with these systems being
developed for older adults and people with
disabilities, the ethical concerns and considerations
grow significantly. In this paper we have outlined a
framework for navigating some of these ethical issues
using a range of techniques from Software
Engineering, Education, and Research Methods to
produce a coherent new ethics driven approach that
we have entitled “The 5D Framework” that puts the
user at the heart of the process.
The authors gratefully acknowledge the support of the
Erasmus+ programme of the European Union. The
European Commission's support for the production of
this publication does not constitute an endorsement of
the contents, which reflect the views only of the
authors, and the Commission cannot be held
responsible for any use which may be made of the
information contained therein. This material is based
upon works supported by the Science Foundation
Ireland under Grant No. 19/FFP/6917.
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Appendix A: SmartTech Data-Level Ethics Checksheet.
Appendix B: SmartTech System-Level Ethics Checksheet.
HEALTHINF 2022 - 15th International Conference on Health Informatics