Scoping Study On The Emerging Use Of Artificial .

3y ago
57 Views
2 Downloads
1,014.38 KB
66 Pages
Last View : 8d ago
Last Download : 6m ago
Upload by : Philip Renner
Transcription

1Scoping study on the emerging use ofArtificial Intelligence (AI) and roboticsin social careFinal ReportMay 2018Written by Consilium Research & ConsultancyScoping study on the emerging use of Artificial Intelligence (AI) and robotics in social care

2Published by Skills for CareScoping study on the emerging use of Artificial Intelligence (AI) and robotics in social carePublished by Skills for Care, West Gate, 6 Grace Street, Leeds LS1 2RP www.skillsforcare.org.uk Skills for Care 2018Reference no. WP2.1a6-CON-17001Scoping study on the emerging use of Artificial Intelligence (AI) and robotics in social care

3Copies of this work may be made for non-commercial distribution to aid social care workforcedevelopment. Any other copying requires the permission of Skills for Care.Skills for Care is the employer-led strategic body for workforce development in social care for adults inEngland. It is part of the sector skills council, Skills for Care and Development.This work was researched and compiled by Consilium Research and Consultancy Ltd.Scoping study on the emerging use of Artificial Intelligence (AI) and robotics in social care

4Table of contentsAcknowledgements . 4Executive summary . 51.Introduction . 142.Overview of research methods. 15Rapid evidence review . 15Sector consultations . 153.Context . 174.Key findings from the research. 19Presenting a typology of AI and robotic technologies. 20Evidence of effectiveness . 32Current limitations of AI and robotic systems . 37Ethical considerations. 39Workforce implications . 425.Gaps in the evidence base . 47Routes to market . 47Understanding user experience . 49Future training needs. 516.Conclusions and recommendations . 54Conclusions . 54Recommendations. 567.Appendices . 58List of references . 58List of stakeholder consultations . 62Rapid evidence review approach . 63AcknowledgementsSkills for Care and Consilium Ltd would like to thank the range of individuals andorganisations within the fields of robotics, local government, academia and socialcare who supported this scoping study and gave up their time to speak withmembers of the research team. Their time and support is greatly appreciated.Scoping study on the emerging use of Artificial Intelligence (AI) and robotics in social care

5Executive summaryIntroductionConsilium Research and Consultancy (Consilium) was commissioned in March 2018by Skills for Care to undertake a scoping study on the emerging use of ArtificialIntelligence (AI) and robotics in adult social care. The purpose of the scoping study isto: Examine the existing international literature in the context of AI and robotics andtheir uses in adult social care;Explore what is currently happening in the context of AI and robotics and theiruses in adult social care focusing on the UK but including internationalexamples; andOutline workforce issues that might arise as the use of AI and robotics in adultsocial care begins to grow.Overview of research methodsThis scoping study has incorporated a rapid evidence review of existing publishedliterature on the potential for and use of AI and robotics within adult social care andengaged a range of individuals and organisations within the fields of robotics, localgovernment, academia and social care.ContextThe adult social care sector in England continues to face a range of challenges withgrowing unmet care need with estimates showing that showing that 1.2 millionpeople are not receiving the help they need, an increase of 18% on last year. Whilstthere is a recognised need to invest more in social care in the coming yearstechnology could also have an important role to play in supporting the care workforceand improving care outcomes. However, there is recognition that technology is notyet being used to its full potential with calls for increased investment in technology tosupport caring as part of the UK government’s industrial strategy.Presenting a typology of AI and robotic technologiesThis rapid evidence review has highlighted a wide range of AI and robotictechnologies that have been piloted or are in use within social care either within theUK or, more commonly, internationally. Much of the research focuses on the role oftechnology in supporting older people, albeit the applications have transferable valuefor a wider range of people who use care services.Scoping study on the emerging use of Artificial Intelligence (AI) and robotics in social care

6A common theme identified in the review was a lack of information on the extent towhich the different AI and robotic technologies had moved beyond the prototype andtesting phase. Several authors provide a clear distinction between physicallyassistive robots (PARs) and socially assistive robots (SARs), distinguishing betweenthe intellectual and physical needs of people in different phases of late life.PARs have been developed to perform discreet tasks including lifting and carrying tosupport people who use care services. Whilst some PARs have been designed tooperate independently from the care workforce others have been designed tosupport the care workforce to undertake physical tasks associated with performingtheir care role. Given the significant safety challenges and requirements surroundingthe design and use of PARs, the evidence review suggests that there are currently alimited number of robots either in development or being used within social care.Socially assistive robotics aims to endow robots with the ability to help peoplethrough individual non-contact assistance in convalescence, rehabilitation, trainingand education. SARs can be categorised into two operational groups, namely‘service robots’ which are tasked with aiding activities of daily living and ‘companionrobots’ which are more generally associated with improving the psychological statusand overall well-being of its users.Cognitive Assistance Robots (CARs) is another emerging area work in usingSARS to support users to perform cognitive tasks with potential to support peoplewith dementia, Alzheimer’s disease and other cognitive impairments.Some of the AI and robotic technologies are focusing on enabling social careemployers to respond more effectively to questions or concerns raised by carers andpatients, by using chatbots as part of their customer interface. These have thepotential to aid carers and people who use care services to monitor and self-managetheir care and identify at an early stage behaviours or symptoms that may requireprofessional intervention and support.Also, within the field of AI and robotics are technologies, care coordination aids,that aim to support social care employers in making logistic and efficiencyimprovements to the delivery of care services whilst also improving communicationbetween social care employers, carers, the care workforce and people who use careservices.One area which has been highlighted within stakeholder consultations is the futureuse of AI and ‘machine learning’ within social care. Machine learning is the set oftechniques and tools that allow computers to ‘think’ by creating mathematicalalgorithms based on accumulated data.Scoping study on the emerging use of Artificial Intelligence (AI) and robotics in social care

7Machine learning offers the potential for AI and robotic technologies to draw on datacollected through sensors and social interaction to learn offline and on the job thusimproving the quality of care provided.Given the predicted growth in data produced by new technologies such as smartsensors in homes and telemedicine robots, machine learning may offer a system ofturning data into intelligence which in turn can ensure care plans are regularlyupdated to enable human care workers or assistive robots to intervene proactively ina range of assistive scenarios, such as medicine adherence, nutrition andrehabilitation support, as well as social engagement.Evidence of effectivenessThe evidence base demonstrating the effectiveness of AI and robotics in supportingcare provision is relatively under-developed and characterised by research that islimited due to methodological issues. This is in part because many of the AI androbotic technologies have yet to move from concept and early prototype stage towider application within the adult social care sector. Much of the evidence basetherefore presents commentary on the future potential for the use of AI and roboticswithin social care whilst highlighting a need for more in-depth studies. The exceptionis the use of Cognitive Assistance Robots where there is good evidence of their usein the adult social care sector in the UK.Current limitations of AI and robotic systemsAcknowledged barriers for growing the use of AI and robotic systems include costand a lack of understanding or even antipathy within the sector to their introduction,which in turn limits the opportunity to evidence their contribution to supporting thecare workforce and improving outcomes for people who use care services.Gaps in the evidence baseA notable gap in the evidence base relates to any assessment of the routes tomarket for the range of assistive robots that have been developed and piloted overthe last decade. The literature on the development of assistive robots is dominatedby technological papers with little consideration of how such devices might becommercialised for a mass market at a price that is affordable for older people andtheir families as well as public services and care insurers.The lack of evidence or reports on effective routes to market for AI and roboticshighlights a need for greater dialogue between technology companies and roboticdevelopers, social care employers, carers and people who use care services. A lackof effective dialogue is likely to perpetuate challenges in ensuring greater adoptionand use of AI and robotic technologies across the social care sector.Scoping study on the emerging use of Artificial Intelligence (AI) and robotics in social care

8Another notable absence in the evidence base relates to achieving a greaterunderstanding of the user experience and user acceptance of AI and robotictechnologies. The evidence base highlights a need to better understand older adults'lived experiences with SARs to create the possibility of using an approach thatembeds technological innovation into the care practice itself. Further evidence istherefore required from a wider roll-out of SARs to support the develop of modelsand approaching for better integrating the use of AI and robotics within the everydayprocess of providing care.Workforce implicationsThere is limited published evidence on the current or future role for the social careworkforce in using AI and robotics as part of their care provision. This perhapsreflects the lack of involvement of the care workforce in collaborating with technologycompanies and robotic developers to design and shape AI and robotic systems to fitwith the realities and practicalities of providing care.Some commentators forecast rising unemployment as labour is substituted for AIenabled robots and machines, whilst others foresee a transformation in the type ofemployment available with the creation of new jobs compensating for those thatwere lost and the prospect of robotics and AI augmenting existing roles and enablinghumans to achieve more than they could on their own.The literature around the use of AI and robotics in social care largely mirrors thesediffering views with some framing the debate as ‘humans versus machines’ whilstothers suggest that the implications are likely to be far subtler with AI and roboticsproviding support for tasks within jobs.Consultations with AI and robotics sector representatives undertaken for this scopingstudy have emphasised that the main hurdle to overcome initially is in terms ofcultural change and addressing the reluctance and scepticism from the careworkforce on the ability of AI and robotics to assist them in their role rather thanbeing a threat to their jobs.Part of challenge is that few professional learning and training programmes in socialcare practice, social work or elder care offer students the opportunity to explore andintegrate awareness of the technologies currently and in the future deployable incare settings. They do not provide students with sufficient opportunities to developcritical awareness of human robot interaction.Scoping study on the emerging use of Artificial Intelligence (AI) and robotics in social care

9This suggests that staff at all levels, including those in initial training, need greaterclarity on the current and potential scope for AI and robotics to add value to theircare roles. Further work is required to bring together key stakeholders from roboticdevelopers and social care employers (and through them the care workforce andpeople who use care services) to explore and promote the use of AI and robotics insocial care and the role of the workforce in embracing and using new technologies.Stakeholders also outlined a range of factors required to support the introduction ofAI and robotics in social care including the required protocols and policies to informcommissioning, maintenance, CPD and training, risk management protocols andclarification of the scope of the role of AI and robotics in social care.Future training needsAlthough this study has uncovered little published research, discussions with a rangeof stakeholders as part of this study have highlighted a range of potential trainingneeds for the social care workforce linked to an increased use of AI and robotics.Unsurprisingly the focus of any training is likely to be influenced by the design andintended purpose of the AI and robotic technology, the needs of the person in receiptof care and the care setting.A further area likely to require training for the future workforce is in interpreting thedata collated by AI and robotic systems. However, not all workforce implicationssurrounding the increased use of AI and robotics will be technology focused orrequire digital skills competency with research studies highlight the contribution thatAI and robotic technologies can play in freeing up frontline care staff to focus onmore human tasks such as providing emotional and social support for people whouse care services.The proliferation of AI and robotic systems over the past decade is likely to continue,however to realise their potential to support the social care sector further work isrequired to ensure user acceptance and use. As such there is likely to be a futurerole for the care workforce in encouraging and facilitating people who use careservices to use AI and robotic technologies that can support them to liveindependently and manage their health needs.Scoping study on the emerging use of Artificial Intelligence (AI) and robotics in social care

10ConclusionsWhilst several research studies demonstrate the potential of AI and robotics tosupport the delivery of care, there is a recognised need to produce strongerevidence through more robust trials and pilots. Where evidence of impact has beenpresented, to date these have focused mainly on the impacts on people who usecare and support services with less attention paid to the impact on the careworkforce (including formal and informal carers). Given that a significant proportionof the technology remains at the concept or prototype phase there appears to belittle practical evidence of the use of AI and robotics within the social care sector inEngland.There is a need to draw together a clearer picture of the existing use of AI androbotic technologies within the social care sector and to review their routes tomarket. Further work is also required to explore the future potential use of machinelearning within adult social care and how this could be built into PAR and SARtechnologies.To date the research suggests there has been an insufficient focus on adopting userled design within the development process and little opportunity for social careemployers and the care workforce to influence the development of new technologiesat a concept stage. This needs to be addressed to ensure that new AI and robotictechnologies can support the practical, everyday challenges facing the workforce indelivering care.The lack of research focusing specifically on the workforce implications of anincreased use of AI and robotics highlights an area that needs to be addressed. Theevidence base highlights a consensus that AI and robotics will not replace theworkforce but will likely provide support for tasks within jobs. As such more work isrequired to map out the future training and development needs of the care workforceto ensure that the opportunities presented by AI and robotic technologies can berealised.Stronger collaboration can also help to explore how existing smart technologies suchas home hubs, smartphones, computer tablets and smart sensors can be used toimprove the quality and efficiency of care delivery which may assist the process ofadoption within the social care sector. More research is needed to determinewhether these everyday technologies can help to challenge and change theperceptions of the care workforce on the contribution and value of AI and robotics insupport their care role and improving outcomes for people who use care services.Scoping study on the emerging use of Artificial Intelligence (AI) and robotics in social care

11RecommendationsA small number of recommendations are provided below based on the key themesand learning outlined in this scoping report.Skills for Care The findings of this scoping report need t

Scoping study on the emerging use of Artificial Intelligence (AI) and robotics in social care A common theme identified in the review was a lack of information on the extent to which the different AI and robotic technologies had moved beyond the prototype and

Related Documents:

May 02, 2018 · D. Program Evaluation ͟The organization has provided a description of the framework for how each program will be evaluated. The framework should include all the elements below: ͟The evaluation methods are cost-effective for the organization ͟Quantitative and qualitative data is being collected (at Basics tier, data collection must have begun)

Silat is a combative art of self-defense and survival rooted from Matay archipelago. It was traced at thé early of Langkasuka Kingdom (2nd century CE) till thé reign of Melaka (Malaysia) Sultanate era (13th century). Silat has now evolved to become part of social culture and tradition with thé appearance of a fine physical and spiritual .

A2 The Scoping Requirements of Directives 85/337/EEC and 97/11/EC A3 Implementation of Scoping in the EU A3.1 Mandatory and Voluntary Scoping Systems A3.2 Scoping Reports and Opinions A3.3 Scoping Consultations PART B PRACTICAL GUIDANCE ON SCOPING B1 Introduction B2 Use of the Guidance B3 Scoping Procedures

Dr. Sunita Bharatwal** Dr. Pawan Garga*** Abstract Customer satisfaction is derived from thè functionalities and values, a product or Service can provide. The current study aims to segregate thè dimensions of ordine Service quality and gather insights on its impact on web shopping. The trends of purchases have

On an exceptional basis, Member States may request UNESCO to provide thé candidates with access to thé platform so they can complète thé form by themselves. Thèse requests must be addressed to esd rize unesco. or by 15 A ril 2021 UNESCO will provide thé nomineewith accessto thé platform via their émail address.

̶The leading indicator of employee engagement is based on the quality of the relationship between employee and supervisor Empower your managers! ̶Help them understand the impact on the organization ̶Share important changes, plan options, tasks, and deadlines ̶Provide key messages and talking points ̶Prepare them to answer employee questions

Chính Văn.- Còn đức Thế tôn thì tuệ giác cực kỳ trong sạch 8: hiện hành bất nhị 9, đạt đến vô tướng 10, đứng vào chỗ đứng của các đức Thế tôn 11, thể hiện tính bình đẳng của các Ngài, đến chỗ không còn chướng ngại 12, giáo pháp không thể khuynh đảo, tâm thức không bị cản trở, cái được

Le genou de Lucy. Odile Jacob. 1999. Coppens Y. Pré-textes. L’homme préhistorique en morceaux. Eds Odile Jacob. 2011. Costentin J., Delaveau P. Café, thé, chocolat, les bons effets sur le cerveau et pour le corps. Editions Odile Jacob. 2010. Crawford M., Marsh D. The driving force : food in human evolution and the future.