**10.4 Personalisation and role of AI**

*Security and Privacy From a Legal, Ethical, and Technical Perspective*

Arguably, as demonstrated in this research, we can define an ethically aligned design in relation to several key concepts. This includes (1) human role, (2) human benefit, (3) rights, (4) progress and (5) well-being. These concepts provide struc-

A key theme of this research has been about defining the purpose and role of new driving assistance technologies. As designers we decide what ethical guidelines AI in autonomous vehicles will follow. The analysis of relevant health literature and TILDA data has identified specific conditions that impact on older adult driving ability [66]. As such, it has provided an empirical basis for addressing ethical dilemmas around whether full automation is an appropriate solution to effectively managing the conflict between two goals—namely, (1) promoting driver persistence and (2) ensuring road safety. It is argued that the three levels of driver assistance represent an ethically aligned solution to enabling older drivers to continue driving, even if there is a risk of a serious accident given their medical background. Evidently, some medical conditions do not negatively impact on safe driving. However, there are other conditions that pose challenges to safe driving, and others still that make it unsafe to drive. The proposed solution is designed to directly address this fact—to promote driver persistence and enablement in these

turing principles to guide the design of new driving assistance systems.

different circumstances, albeit while simultaneously maintaining safety.

**10.3 Design problem and ethical vision: enablement and positive ageing**

The design problem—prolonging safe driving for older adults is framed in relation to a philosophy of 'enablement' and positive models of ageing. Crucially, the proposed vision of 'technology progress' in closely intertwined with concepts of progress from a societal values perspective. The proposed co-pilot system is premised on concepts of successful/positive ageing and self-efficacy. The system seeks to normalise ageing, and not treat ageing as a 'problem' or 'disease'. The driving solution (i.e. car, sensor system, co-pilot and human machine interface) is designed to optimise the abilities and participation of older adults. That is, it recognises what older adults can do as opposed to focusing on declining capacities. Further, the co-pilot is conceptualised as a means/intervention to ensure that older adults drive safely and for longer. The proposed technology supports continued and safe driving for all adults, including those adults at risk of limiting their driving and/or giving up when there is no medical/physical

Arguably, existing high automation approaches do not support positive ageing. Crucially, 'technology progress' in closely intertwined with concepts of progress from a societal values perspective. New assisted driving solutions provide an opportunity to change/improve the lived experience of older adults, particularly in relation to autonomy and social participation. Enabling driver persistence is an issue

Human benefit is an important goal of A/IS, as is respect for human rights. In terms of rights, this includes the rights of (1) older adult drivers and (2) other road users and pedestrians who may be negatively affected by older adult driving challenges and specifically, health events such as strokes and heart attacks. The specification of benefits is not straightforward. People benefit differently. Also, benefits are not always equal for all people, as driving system that benefits older adults must also benefit other road users and pedestrians. In this way, the proposed system must be verifiably safe and secure. We must ensure the safety of all drivers and pedestrians. Benefits in relation to older adult mobility must not outweigh safety concerns (i.e. we cannot address benefit from a narrow perspective/prioritise

**38**

one stakeholder).

reason for doing so.

for all of society, not just older adults.

Many negative driving experiences are linked to frustrations with the vehicle not being configured for the driver. Drivers are highly diverse in terms of size, strength, angle of vision and experience of different vehicles. Older drivers present even greater diversity when limitations of movement, hearing, eyesight, memory emerge. It is argued that personalisation is central to fostering a positive driver experience. For example, vehicle sensors can be used to detect which driver is driving and to adjust the vehicle parameters accordingly (i.e. angle of mirrors, steering wheel, seat, etc.). Moreover, personalisation offers an enormous opportunity to ensure that task support and multimodal feedback is configured according to knowledge of the particular driver's ability (including sensory ability), driving routines and routes and typical challenges/errors.

A human-centric and ethically aligned design philosophy necessitates continuous learning on the behalf of the assistance system (i.e. including AI/machine learning). If the assistance system can learn about those situations and tasks that prove challenging and/or stressful for the older adult driver (i.e. driving in traffic, poor visibility, changing lanes, parking and so forth, etc.), then it can tailor the task support that it provides to the driver. This tailored task support is predictive/intelligent, ensuring that the driver persists in challenging driving situations, while also enjoying their drive.
