Co-creating Humanistic AI AgeTech to Support Dynamic Care Ecosystems: A Preliminary Guiding Model.

As society rapidly digitizes, successful aging necessitates using technology for health and social care and social engagement. Technologies aimed to support older adults (e.g., smart homes, assistive robots, wheelchairs) are increasingly applying artificial intelligence (AI), and thereby creating ethical challenges to technology development and use. The international debate on AI ethics focuses on implications to society (e.g., bias, equity) and to individuals (e.g., privacy, consent). The relational nature of care, however, warrants a humanistic lens to examine how "AI AgeTech" will shape, and be shaped by, social networks or care ecosystems in terms of their care actors (i.e., older adults, care partners, service providers); inter-actor relations (e.g., care decision-making) and relationships (e.g., social, professional); and evolving care arrangements. For instance, if an older adult's reduced functioning leads actors to renegotiate their risk tolerances and care routines, smart homes or robots become more than tools that actors configure; they become semi-autonomous actors, in themselves, with the potential to influence functioning and interpersonal relationships. As an experientially-diverse, transdisciplinary working group of older adults, care partners, researchers, clinicians, and entrepreneurs, we co-constructed intersectional care experiences, to guide technology research, development, and use. Our synthesis contributes a preliminary guiding model for AI AgeTech innovation that delineates humanistic attributes, values, and design orientations, and captures the ethical, sociological, and technological nuances of dynamic care ecosystems. Our visual probes and recommended tools and techniques offer researchers, developers/innovators, and care actors concrete ways of using this model to promote successful aging in AI-enabled futures.

Designing the User Interface of a Nitroglycerin Dose Titration Decision Support System: User-Centered Design Study.

BACKGROUND: Nurses adjust intravenous nitroglycerin infusions to provide acute relief for angina by manually increasing or decreasing the dosage. However, titration can pose challenges, as excessively high doses can lead to hypotension, and low doses may result in inadequate pain relief. Clinical decision support systems (CDSSs) that predict changes in blood pressure for nitroglycerin dose adjustments may assist nurses with titration. OBJECTIVE: This study aimed to design a user interface for a CDSS for nitroglycerin dose titration (Nitroglycerin Dose Titration Decision Support System [nitro DSS]). METHODS: A user-centered design (UCD) approach, consisting of an initial qualitative study with semistructured interviews to identify design specifications for prototype development, was used. This was followed by three iterative rounds of usability testing. Nurses with experience titrating nitroglycerin infusions in coronary care units participated. RESULTS: A total of 20 nurses participated, including 7 during the qualitative study and 15 during usability testing (2 nurses participated in both phases). Analysis of the qualitative data revealed four themes for the interface design to be (1) clear and consistent, (2) vigilant, (3) interoperable, and (4) reliable. The major elements of the final prototype included a feature for viewing the predicted and actual blood pressure over time to determine the reliability of the predictions, a drop-down option to report patient side effects, a feature to report reasons for not accepting the prediction, and a visual alert indicating any systolic blood pressure predictions below 90 mm Hg. Nurses' ratings on the questionnaires indicated excellent usability and acceptability of the final nitro DSS prototype. CONCLUSION: This study successfully applied a UCD approach to collaborate with nurses in developing a user interface for the nitro DSS that supports the clinical decision-making of nurses titrating nitroglycerin.

User Perception of Smart Home Surveillance Among Adults Aged 50 Years and Older: Scoping Review.

BACKGROUND: Smart home technology (SHT) can be useful for aging in place or health-related purposes. However, surveillance studies have highlighted ethical issues with SHTs, including user privacy, security, and autonomy. OBJECTIVE: As digital technology is most often designed for younger adults, this review summarizes perceptions of SHTs among users aged 50 years and older to explore their understanding of privacy, the purpose of data collection, risks and benefits, and safety. METHODS: Through an integrative review, we explored community-dwelling adults' (aged 50 years and older) perceptions of SHTs based on research questions under 4 nonmutually exclusive themes: privacy, the purpose of data collection, risk and benefits, and safety. We searched 1860 titles and abstracts from Ovid MEDLINE, Ovid Embase, Cochrane Database of Systematic Reviews, and Cochrane Central Register of Controlled Trials, Scopus, Web of Science Core Collection, and IEEE Xplore or IET Electronic Library, resulting in 15 included studies. RESULTS: The 15 studies explored user perception of smart speakers, motion sensors, or home monitoring systems. A total of 13 (87%) studies discussed user privacy concerns regarding data collection and access. A total of 4 (27%) studies explored user knowledge of data collection purposes, 7 (47%) studies featured risk-related concerns such as data breaches and third-party misuse alongside benefits such as convenience, and 9 (60%) studies reported user enthusiasm about the potential for home safety. CONCLUSIONS: Due to the growing size of aging populations and advances in technological capabilities, regulators and designers should focus on user concerns by supporting higher levels of agency regarding data collection, use, and disclosure and by bolstering organizational accountability. This way, relevant privacy regulation and SHT design can better support user safety while diminishing potential risks to privacy, security, autonomy, or discriminatory outcomes.

Predicting Blood Pressure After Nitroglycerin Infusion Dose Titration in Critical Care Units: A Multicenter Retrospective Study.

Critical care nurses use physiological indicators, such as blood pressure, to guide their decision-making regarding the titration of nitroglycerin infusions. A retrospective study was conducted to determine the accuracy of systolic blood pressure predictions during nitroglycerin infusions. Data were extracted from the publicly accessible eICU program database. The accuracy of a linear model, least absolute shrinkage and selection operator, ridge regression, and a stacked ensemble model trained using the AutoGluon-Tabular framework were investigated. A persistence model, where the future value in a time series is predicted as equal to its preceding value, was used as the baseline comparison for model accuracy. Internal-external validation was used to examine if heterogeneity among hospitals could contribute to model performance. The sample consisted of 827 patients and 2541 nitroglycerin dose titrations with corresponding systolic blood pressure measurements. The root-mean-square error on the test set for the stacked ensemble model developed using the AutoGluon-Tabular framework was the lowest of all models at 15.3 mm Hg, equating to a 22% improvement against the baseline. Internal-external validation revealed consistent accuracy across hospitals. Further studies are needed to determine the impact of using systolic blood pressure predictions to inform nurses' clinical decision-making regarding nitroglycerin infusion titration in critical care.

Parent and clinician perceptions and recommendations on a pediatric cancer pain management app: A qualitative co-design study.

Pain is one of the most prevalent and burdensome pediatric cancer symptoms for young children and their families. A significant proportion of pain episodes are experienced in environments where management options are limited, including at home. Digital innovations such as apps may have positive impacts on pain outcomes for young children in these environments. Our overall aim is to co-design such an app and the objective of this study was to explore the perceptions of children's parents about app utility, needed system features, and challenges. We recruited parents of young children with cancer and multidisciplinary pediatric oncology clinicians from two pediatric cancer care centers to participate in audio-recorded, semi-structured, co-design interviews. We conducted interviews structured around technology acceptance and family caregiving theories until data saturation was reached. Audio-recordings were then transcribed, coded, and analyzed using thematic analysis. Forty-two participants took part in the process. Participants endorsed the concept of an app as a useful, safe, and convenient way to engage caregivers in managing their young child's pain. Overall, the app was valued as a means to provide real-time, multimodal informational and procedural pain support to parents, while also reducing the emotional burden of pain care. Recommendations for intervention design included accessibility-focused features, comprehensive symptom tracking, and embedded scientific- and clinically-sound symptom assessments and management advice. Predicted challenges to app use included the workload burden it may place on parents and clinicians. The insights gathered will inform the design principles of our future childhood cancer pain digital research.

Researched Apps Used in Dementia Care for People Living With Dementia and Their Informal Caregivers: Systematic Review on App Features, Security, and Usability.

BACKGROUND: Studies have shown that mobile apps have the potential to serve as nonpharmacological interventions for dementia care, improving the quality of life of people living with dementia and their informal caregivers. However, little is known about the needs for and privacy aspects of these mobile apps in dementia care. OBJECTIVE: This review seeks to understand the landscape of existing mobile apps in dementia care for people living with dementia and their caregivers with respect to app features, usability testing, privacy, and security. METHODS: ACM Digital Library, Cochrane Central Register of Controlled Trials, Compendex, Embase, Inspec, Ovid MEDLINE, PsycINFO, and Scopus were searched. Studies were included if they included people with dementia living in the community, their informal caregivers, or both; focused on apps in dementia care using smartphones or tablet computers; and covered usability evaluation of the app. Records were independently screened, and 2 reviewers extracted the data. The Centre for Evidence-Based Medicine critical appraisal tool and Mixed Methods Appraisal Tool were used to assess the risk of bias in the included studies. Thematic synthesis was used, and the findings were summarized and tabulated based on each research aim. RESULTS: Overall, 44 studies were included in this review, with 39 (89%) published after 2015. In total, 50 apps were included in the study, with more apps developed for people living with dementia as end users compared with caregivers. Most studies (27/44, 61%) used tablet computers. The most common app feature was cognitive stimulation. This review presented 9 app usability themes: user interface, physical considerations, screen size, interaction challenges, meeting user needs, lack of self-awareness of app needs, stigma, technological inexperience, and technical support. In total, 5 methods (questionnaires, interviews, observations, logging, and focus groups) were used to evaluate usability. There was little focus on the privacy and security aspects, including data transfer and protection, of mobile apps for people living with dementia. CONCLUSIONS: The limitations of this review include 1 reviewer conducting the full-text screening, its restriction to studies published in English, and the exclusion of apps that lacked empirical usability testing. As a result, there may be an incomplete representation of the available apps in the field of dementia care. However, this review highlights significant concerns related to the usability, privacy, and security of existing mobile apps for people living with dementia and their caregivers. The findings of this review provide a valuable framework to guide app developers and researchers in the areas of privacy policy development, app development strategies, and the importance of conducting thorough usability testing for their apps. By considering these factors, future work in this field can be advanced to enhance the quality and effectiveness of dementia care apps. TRIAL REGISTRATION: PROSPERO CRD42020216141; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=216141. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1159/000514838.

A New Age of Health Promotion: The Use of Digital Infographics in Nursing Education.

ABSTRACT: The COVID-19 pandemic has shifted how nursing education and information are delivered, with many classes being moved to an online platform. This opened opportunities to find creative ways to engage students. As a result, an entirely online infographic assignment for final-year baccalaureate nursing students was created. The focus of this assignment was to engage students to identify important health issues, consider multilevel solutions, and communicate information to relevant stakeholders using visual storytelling for maximum impact.

Evaluating knowledge and attitudes scales for the care of older adults among nursing students in Ghana.

BACKGROUND: Understanding nursing students' knowledge about and attitudes toward older adults' using context-specific survey instruments can help to identify and design effective learning and teaching materials to improve the care for persons 60 years and above. However, there are no validated instruments to examine nursing students' knowledge and attitudes toward the care for older adults in the African context. The study aimed to evaluate the items on the Knowledge about Older Patients Quiz and Kogan's Attitudes towards Old People Scale suitable for the African context. METHODS: A cross-sectional study was conducted using second-and third-year nursing students from two public Nursing Training Institutions in Ghana. Using Sahin's rule of sample size estimate of at least 150 participants for unidimensional dichotomous scales, 170 nursing students were recruited to participate after an information session in their classrooms. Data were collected from December 2019-March 2020 using the Knowledge about Older Patients Quiz and Kogan's Attitudes Towards Old People Scale. Item response theory was employed to evaluate the Knowledge about Older Patients Quiz difficulty level and discrimination indices. Corrected item-to-total correlation analysis was conducted for Kogan's Attitudes towards Old People Scale. The internal consistency for both scales was examined. RESULTS: Of the 170 participants, 169 returned completed surveys. The mean age of participants was 21 years (SD = 3.7), and (54%) were female. Of the 30-items of the Knowledge about Older Patients Quiz, seven items were very difficult for most students to choose the correct response, and one was easy, as most of the students chose the correct response. Although 22 items demonstrated appropriate difficulty level, discrimination indices were used to select the final 15- items that discriminated moderately between upper and lower 25% performing students. The Kuder-Richardson-20 reliability was. 0.30, which was low. Considering Kogan's Attitudes towards Old People scale, 10-items were removed following negative and low corrected item-to-total correlation and a high Alpha coefficient if items were deleted. The final 22-items had a Cronbach alpha coefficient of 0.65, which was moderately satisfactory. CONCLUSION: Evaluation of the scales demonstrated essential content validity and moderate internal consistency for the context of our study. Further research should focus on ongoing context-specific refinement of the survey instruments to measure nursing students' knowledge about and attitudes toward caring for older adults in the African context.

The effectiveness and cost-effectiveness of clinical fracture-risk assessment tools in reducing future osteoporotic fractures among older adults: a structured scoping review.

This scoping review described the use, effectiveness, and cost-effectiveness of clinical fracture-risk assessment tools to prevent future osteoporotic fractures among older adults. Results show that the screening was not superior in preventing all osteoporosis-related fractures to usual care. However, it positively influenced participants' perspectives on osteoporosis, may have reduced hip fractures, and seemed cost-effective. PURPOSE: We aim to provide a synopsis of the evidence about the use of clinical fracture-risk assessment tools to influence health outcomes, including reducing future osteoporotic fractures and their cost-effectiveness. METHODS: We followed the guidelines of Arksey and O'Malley and their modifications. A comprehensive search strategy was created to search CINAHL, Medline, and Embase databases until June 29, 2021, with no restrictions. We critically appraised the quality of all included studies. RESULTS: Fourteen studies were included in the review after screening 2484 titles and 68 full-text articles. Four randomized controlled trials investigated the effectiveness of clinical fracture-risk assessment tools in reducing all fractures among older women. Using those assessment tools did not show a statistically significant reduction in osteoporotic fracture risk compared to usual care; however, additional analyses of two of these trials showed a trend toward reducing hip fractures, and the results might be clinically significant. Four studies tested the impact of screening programs on other health outcomes, and participants reported positive results. Eight simulation studies estimated the cost-effectiveness of using these tools to screen for fractures, with the majority showing significant potential savings. CONCLUSION: According to the available evidence to date, using clinical fracture-risk assessment screening tools was not more effective than usual care in preventing all osteoporosis-related fractures. However, using those screening tools positively influenced women's perspectives on osteoporosis, may have reduced hip fracture risk, and could potentially be cost-effective. This is a relatively new research area where additional studies are needed.

"We've All Lost So Much": The Long-Term Care Home Experiences of Essential Family Caregivers During COVID-19.

BACKGROUND: During the coronavirus (COVID-19) pandemic, long-term care homes (LTCHs) imposed visitor restrictions that prevented essential family caregivers (EFCs) from entering the homes. Under these policies, EFCs had to engage in virtual, window, and outdoor visits, prior to the re-initiation of indoor visits. OBJECTIVE: To understand EFCs' visitation experiences with LTCH residents during COVID-19. METHODS: Seven virtual focus groups with EFCs were conducted and analysed using a thematic approach. FINDINGS: Six themes were identified: (a) inconsistent and poor communication; (b) lack of staffing and resources; (c) increasing discord between EFCs and staff during COVID-19; (d) shock related to reunification; (e) lack of a person-centred or family-centred approach; and, (f) EFC and resident relationships as collateral damage. DISCUSSION: Our findings reflect how EFCs' visitation experiences were affected by factors at the individual, LTCH, and health-system levels. Future sectoral responses and visitation guidelines should recognize EFCs as an integral part of the care team.

Real-time location systems technology in the care of older adults with cognitive impairment living in residential care: A scoping review.

Introduction: There has been growing interest in using real-time location systems (RTLS) in residential care settings. This technology has clinical applications for locating residents within a care unit and as a nurse call system, and can also be used to gather information about movement, location, and activity over time. RTLS thus provides health data to track markers of health and wellbeing and augment healthcare decisions. To date, no reviews have examined the potential use of RTLS data in caring for older adults with cognitive impairment living in a residential care setting. Objective: This scoping review aims to explore the use of data from real-time locating systems (RTLS) technology to inform clinical measures and augment healthcare decision-making in the care of older adults with cognitive impairment who live in residential care settings. Methods: Embase (Ovid), CINAHL (EBSCO), APA PsycINFO (Ovid) and IEEE Xplore databases were searched for published English-language articles that reported the results of studies that investigated RTLS technologies in persons aged 50 years or older with cognitive impairment who were living in a residential care setting. Included studies were summarized, compared and synthesized according to the study outcomes. Results: A total of 27 studies were included. RTLS data were used to assess activity levels, characterization of wandering, cognition, social interaction, and to monitor a resident's health and wellbeing. These RTLS-based measures were not consistently validated against clinical measurements or clinically important outcomes, and no studies have examined their effectiveness or impact on decision-making. Conclusion: This scoping review describes how data from RTLS technology has been used to support clinical care of older adults with dementia. Research efforts have progressed from using the data to track activity levels to, most recently, using the data to inform clinical decision-making and as a predictor of delirium. Future studies are needed to validate RTLS-based health indices and examine how these indices can be used to inform decision-making.

Evolving with technology: Machine learning as an opportunity for operating room nurses to improve surgical care-A commentary.

AIMS: To describe machine learning applications in an operating room setting, raise awareness of the lack of nursing inclusion on machine learning algorithm development, and show how operating room nurses can co-create this new technology. BACKGROUND: Operating room nurses and managers perform anticipatory work on a daily basis to manage intrinsic and extrinsic factors that can cause surgical delays. EVALUATION: Recent literature on machine learning and its potential use in operating room settings was reviewed along with literature on the role of the nurse in co-creating novel technology. KEY ISSUE: Machine learning technology is rapidly evolving and being created for the operating room environment to improve patient safety and flow. Operating room nurses and managers are not being included in the development of machine learning algorithms, meaning products may be created that are not usable for all members of the surgical team. CONCLUSION: This commentary highlights the ways machine learning effectively assists nurses and nursing managers, suggesting a pathway forward for surgical nursing as co-creators and implementers. IMPLICATION FOR NURSING MANAGEMENT: Nursing managers will be exposed to machine learning programmes in the near future and need to understand the benefits they have for patient safety and patient flow.

Ageism and Artificial Intelligence: Protocol for a Scoping Review.

BACKGROUND: Artificial intelligence (AI) has emerged as a major driver of technological development in the 21st century, yet little attention has been paid to algorithmic biases toward older adults. OBJECTIVE: This paper documents the search strategy and process for a scoping review exploring how age-related bias is encoded or amplified in AI systems as well as the corresponding legal and ethical implications. METHODS: The scoping review follows a 6-stage methodology framework developed by Arksey and O'Malley. The search strategy has been established in 6 databases. We will investigate the legal implications of ageism in AI by searching grey literature databases, targeted websites, and popular search engines and using an iterative search strategy. Studies meet the inclusion criteria if they are in English, peer-reviewed, available electronically in full text, and meet one of the following two additional criteria: (1) include "bias" related to AI in any application (eg, facial recognition) and (2) discuss bias related to the concept of old age or ageism. At least two reviewers will independently conduct the title, abstract, and full-text screening. Search results will be reported using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) reporting guideline. We will chart data on a structured form and conduct a thematic analysis to highlight the societal, legal, and ethical implications reported in the literature. RESULTS: The database searches resulted in 7595 records when the searches were piloted in November 2021. The scoping review will be completed by December 2022. CONCLUSIONS: The findings will provide interdisciplinary insights into the extent of age-related bias in AI systems. The results will contribute foundational knowledge that can encourage multisectoral cooperation to ensure that AI is developed and deployed in a manner consistent with ethical values and human rights legislation as it relates to an older and aging population. We will publish the review findings in peer-reviewed journals and disseminate the key results with stakeholders via workshops and webinars. TRIAL REGISTRATION: OSF Registries AMG5P; https://osf.io/amg5p. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/33211.

Who's in the House? Staffing in Long-Term Care Homes Before and During COVID-19 Pandemic.

Critical gaps exist in our knowledge on how best to provide quality person-centered care to long-term care (LTC) home residents which is closely tied to not knowing what the ideal staff is complement in the home. A survey was created on staffing in LTC homes before and during the COVID-19 pandemic to determine how the staff complement changed. Perspectives were garnered from researchers, clinicians, and policy experts in eight countries and the data provides a first approximation of staffing before and during the pandemic. Five broad categories of staff working in LTC homes were as follows: (1) those responsible for personal and support care, (2) nursing care, (3) medical care, (4) rehabilitation and recreational care, and (5) others. There is limited availability of data related to measuring staff complement in the home and those with similar roles had different titles making it difficult to compare between countries. Nevertheless, the survey results highlight that some categories of staff were either absent or deemed non-essential during the pandemic. We require standardized high-quality workforce data to design better decision-making tools for staffing and planning, which are in line with the complex care needs of the residents and prevent precarious work conditions for staff.

"It's the worst thing I've ever been put through in my life": the trauma experienced by essential family caregivers of loved ones in long-term care during the COVID-19 pandemic in Canada.

BACKGROUND: Essential family caregivers (EFCs) of relatives living in long-term care homes (LTCHs) experienced restricted access to their relatives due to COVID-19 visitation policies. Residents' experiences of separation have been widely documented; yet, few have focused on EFCs' traumatic experiences during the pandemic. Objective: This study aims to explore the EFCs' trauma of being locked out of LTCHs and unable to visit their loved ones in-person during COVID-19. METHODS: Seven online focus groups with a total of 30 EFCs from Ontario and British Columbia, Canada were conducted as part of a larger mixed-method study. We used an inductive approach to thematic analysis to understand the lived experiences of trauma. RESULTS: Four trauma-related themes emerged: 1) trauma from prolonged separation from loved ones; 2) trauma from uncompassionate interactions with the LTCH's staff and administrators; 3) trauma from the inability to provide care to loved ones, and 4) trauma from experiencing prolonged powerlessness and helplessness. DISCUSSION: The EFCs experienced a collective trauma that deeply impacted their relationships with their relatives as well as their perception of the LTC system. Experiences endured by EFCs highlighted policy and practice changes, including the need for trauma-centred approaches to repair relational damage and post-pandemic decision-making that collaborates with EFCs.

Poor and Lost Connections: Essential Family Caregivers' Experiences Using Technology with Family Living in Long-Term Care Homes during COVID-19.

Background: Long-term care homes (LTCHs) restricted essential family caregivers' (EFCs) visitations during COVID-19, and virtual visits using technology were used. Objective: To understand EFCs' virtual visitations experiences during COVID-19 in two Canadian provinces. Methods: Seven focus groups were conducted with EFCs. Thematic analysis was used to identify themes at micro, meso, and macro levels. Results: Four themes were found: 1) a lack of technology and infrastructure; 2) barriers to scheduling visitations; 3) unsuitable technology implementation; and 4) inability of technology to adapt to residents' needs. Discussion: Virtual visitations showcased a confluence of micro, meso, and macro factors that, in some cases, negatively impacted the EFCs, residents, and the relationship between EFCs and residents. Structural and home inequities within and beyond the LTCH impacted the quality of technology-based visitations, underscoring the need to support technology infrastructure and training to ensure residents are able to maintain relationships during visitation bans. Conclusion: EFCs' experiences of technology-based visitations were impacted by structural vulnerabilities of the LTCH sector.

Effects of Exergaming on Physical and Cognitive Outcomes of Older Adults Living in Long-Term Care Homes: A Systematic Review.

BACKGROUND: Aging is often associated with increasing functional decline as measured by deterioration in mobility and activities of daily living. Older adults (OAs) living in residential long-term care (LTC) homes in particular may not engage in regular physical exercise, significantly increasing their risk of further cognitive and functional decline. Exergaming may hold promise for OAs by combining exercise and technology-based gaming systems, but evidence for its use in LTC is unknown. METHODS: A systematic review was conducted to summarize the effects of exergaming interventions on physical, cognitive, and quality of life (QoL) outcomes for OAs (>65 years of age) living in LTC. RESULTS: Twenty-one studies involving 657 OAs living in LTC met the inclusion criteria. Most studies were associated with a high risk of bias and many used uncontrolled designs and small samples. Across studies, exergame interventions were associated with preliminary benefits relative to control conditions on standardized measures of physical outcomes (e.g., Timed Up & Go, 5-meter gait speed). No consistent effects were found for cognitive and QoL outcomes. CONCLUSIONS: Exergames might be a promising intervention to benefit the physical health of OAs (>65 years) living in LTC, but more research is required to determine the effects of exergaming on physical health, as well as cognitive and QoL outcomes. More specifically, larger and more methodologically robust evaluations are needed.

Digital Ageism: Challenges and Opportunities in Artificial Intelligence for Older Adults.

Artificial intelligence (AI) and machine learning are changing our world through their impact on sectors including health care, education, employment, finance, and law. AI systems are developed using data that reflect the implicit and explicit biases of society, and there are significant concerns about how the predictive models in AI systems amplify inequity, privilege, and power in society. The widespread applications of AI have led to mainstream discourse about how AI systems are perpetuating racism, sexism, and classism; yet, concerns about ageism have been largely absent in the AI bias literature. Given the globally aging population and proliferation of AI, there is a need to critically examine the presence of age-related bias in AI systems. This forum article discusses ageism in AI systems and introduces a conceptual model that outlines intersecting pathways of technology development that can produce and reinforce digital ageism in AI systems. We also describe the broader ethical and legal implications and considerations for future directions in digital ageism research to advance knowledge in the field and deepen our understanding of how ageism in AI is fostered by broader cycles of injustice.