A Framework for Artificial Intelligence Applications in the Healthcare Revenue Management Cycle

There is a lack of understanding of specific risks and benefits associated with AI/RPA implementations in healthcare revenue cycle settings. Healthcare companies are confronted with stricter regulations and billing requirements, underpayments, and more significant delays in receiving payments. Despite the continued interest of practitioners, revenue cycle management has not received much attention in research. Revenue cycle management is defined as the process of identifying, collecting, and managing the practice’s revenue from payers based on the services provided.This dissertation provided contributions to both areas, as mentioned above. To accomplish this, a semi-structured interview was distributed to healthcare executives. The semi-structured interview data obtained from each participant underwent a triangulation process to determine the validity of responses aligned with the extant literature. Data triangulation ensured further that significant themes found in the interview data answered the central research questions. The study focused on how the broader issues related to AI/RPA integration into revenue cycle management will affect individual organizations. These findings also presented multiple views of the technology’s potential benefits, limitations, and risk management strategies to address its associative threats. The triangulation of the responses and current literature helped develop a theoretical framework that may be applied to a healthcare organization in an effort to migrate from their current revenue management technique to one that includes the use of AI/ML/RPA as a means of future cost control and revenue boost

The Impact of Artificial Intelligence on Workers’ Skills: Upskilling and Reskilling in Organisations

Aim/Purpose This paper aims to investigate the recent developments in research and practice on the transformation of professional skills by artificial intelligence (AI) and to identify solutions to the challenges that arise. Background The implementation of AI in various organisational sectors has the potential to automate tasks that are currently performed by humans or to reduce cognitive workload. While this can lead to increased productivity and efficiency, these rapid changes have significant implications for organisations and workers, as AI can also be perceived as leading to job losses. Successfully adapting to this transformation will lead companies and institutions to new working and organisational models, which requires implementing measures and strategies to upskill or reskill workers. Organisations, therefore, face considerable challenges such as guiding employees towards the change process, dealing with the cost of training, and ensuring fairness and inclusion posed by age, gender, and cultural diversity. Methodology A narrative review has been conducted to analyse research and practice on the impact of AI on human skills in organisations. Contribution This work contributes to the body of knowledge by examining recent trends in research and practice on how AI will transform professional skills and workplaces, highlighting the crucial role played by transversal skills and identifying strategies that can support organisations and guide workers toward the upskilling and reskilling challenges. Findings This work found that introducing AI in organisations combines many organisational strategies simultaneously. First, it is critical to map the transversal skills needed by workers to mitigate the current skills gap within the workplace. Secondly, organisations can help workers identify the skills required for AI adoption, improve current skills, and develop new skills. In addition, the findings show that companies need to implement processes to support workers by providing ad hoc training and development opportunities to ensure that workers’ attitudes and mental models towards AI are open and ready for the changing labour market and its related challenges. Recommendation for Researchers AI is a complex and multifaceted field that encompasses a wide range of disciplines, including computer science, mathematics, engineering, and behavioural and social sciences. Researchers should take a transdisciplinary approach to enable the integration of knowledge and perspectives from different fields that are essential to understanding the full range of implications and applications of AI. Future Research Further research is needed to understand the impact of AI on human skills and the role of soft skills in the adoption of AI in organisations. Future studies should also consider the challenges presented by Industry 5.0, which is likely to involve the integration of new technologies and automation on an even greater scale

Co-designing MOOCs with CoDe-Graph

As MOOCs have become a standard format of online learning, it is increasingly important to design courses that ft the needs and contexts of the targeted learners. One way to do so is by actively designing with the subject experts, instructors, and other stakeholders. Within the context of designing MOOCs for disadvantaged groups in Southeast Asia, we explore the three-phase process of co-design. We present a graphical modeling language, CoDe-Graph, which can be used to facilitate the co-design process. We examine how diverse groups of experts provide feedback on design elements and create a com mon understanding using shared artifacts. Four case studies illustrate how the tool can be used by co-design teams to create and visualize custom MOOC designs

Smart city : How smart is it actually?

The global megatrends of population growth and fast urbanisation are negatively impacting the life in the cities. Smart city is the high-level concept by which the cities try to address the need to improve their social, economic and environmental sustainability. This thesis studies how the smart city concept is defined, what are the underlying hypotheses and assumptions on which the smart city research is based on, what are the latest results and innovations of the smart city research, how the smart city initiatives are meeting their objectives, and how the hypotheses and assumptions may vary between the smart city initiatives. The objective of this study is to critically review the smart city research paradigm to find possible pitfalls, conflicting results and topics for further study and improvement. This research is conducted as a traditional critical literature review, covering the current academic literature on the smart city topic, the websites presenting the smart city initiatives around the world, and the latest popular literature for contrasting views. A qualitative comparison of the smart city initiatives in selected cities – Helsinki, Singapore and London – complements the literature review. The research strategy in this study approximates the grounded theory, utilising inductive reasoning to generate arguments and conclusions about the form, validity and future of the smart city. This study produced the following key findings: there are many different and overlapping definitions of smart city; the smart city development is mostly seen as the responsibility of smart ICT implementations, while simultaneously demanding for a more focused human viewpoint; the smart city initiatives form complex, multidisciplinary platforms that require holistic evaluation; the current evaluation methods and rankings of the smart cities vary considerably, making the evaluation of the success of the smart cities difficult; some of the existing smart city elements and proposed solutions are ineffective or even counterproductive for the smart city objectives. The main conclusions of this study were that the complex nature of the smart city initiatives and the conflicts and interdependencies of the smart city objectives are not fully addressed in the current smart city research, and that the current smart city research is not adequately multidisciplinary in nature. For the future, this research argues for the increased utilisation of research methods used in information systems science for their ability to address socio-technical and multidisciplinary problems. Also, the need for a future research on the efficacy of the multidisciplinary research of smart cities is identified.Väestönkasvu, siitä aiheutuva muuttoliike ja nopea kaupungistuminen ovat maailmanlaajuisia megatrendejä, jotka usein vaikuttavat kielteisesti elämisen ja asumisen laatuun kaupungeissa. Älykaupunki on ylemmän tason konsepti, jonka avulla kaupungit yrittävät muokata sosiaalista, taloudellista ja ympäristönsä kehitystä kestävämmälle pohjalle. Tässä tutkielmassa tarkastellaan, miten älykaupungin konsepti on määritelty, mitkä ovat ne taustaolettamukset ja perusteet, joiden varaan älykaupunkien tieteellinen tutkimus pohjautuu, mitkä ovat älykaupunkitutkimuksen viimeisimmät tulokset ja innovaatiot, miten älykaupunkihankkeet saavuttavat tavoitteensa ja miten niiden perusteet ja taustaolettamukset vaihtelevat älykaupunkien välillä. Tämän tutkimuksen tavoitteena on kriittisesti tarkastella älykaupunkien tutkimusparadigmaa ja löytää mahdollisia sudenkuoppia sekä ristiriitaisia tutkimusaiheita ja -tuloksia, joita voitaisiin käyttää älykaupunkien jatkotutkimukseen ja -kehittämiseen tulevaisuudessa. Tämä tutkimus on toteutettu perinteisenä kriittisenä kirjallisuustutkimuksena. Lähdeaineistona on käytetty älykaupunkien viimeisimpiä akateemisia tutkimustuloksia ja julkaisuja, älykaupunkihankkeiden omia nettisivustoja ympäri maailman sekä kontrastin vuoksi myös viimeisimpiä populaarin lähdekirjallisuuden käsittelemiä aiheita ja ilmiöitä. Kirjallisuustutkimusta on täydennetty kvalitatiivisella älykaupunkivertailulla, jossa Helsingin, Singaporen ja Lontoon älykaupunkihankkeita on vertailtu keskenään. Työn tutkimusstrategia muistuttaa ankkuroitua teoriaa, jossa induktiivisen päättelyn avulla pyritään lähdeaineistosta löytämään ja luomaan väitteitä, perusteluja ja johtopäätöksiä älykaupunkien muodosta, olemassaolon oikeellisuudesta ja tulevaisuudesta. Tutkimuksessa havaittiin seuraavat pääkohdat: älykaupunki voidaan määritellä usealla, myöskin samanaikaisesti päällekkäisellä tavalla; älykaupunkien kehittäminen nähdään yleensä tieto- ja viestintäteknologisten innovaatioiden kehittämisenä, vaikka samanaikaisesti usein vaaditaan myös inhimillisemmän näkökulman korostamista; älykaupunkihankkeet muodostavat monitahoisia, monia tieteenaloja koskettavia alustoja, jotka vaativat nykyistä kokonaisvaltaisempaa tarkastelua ja arvi-ointia; nykyiset älykaupunkien menestyksen mittarit ja arviointitavat vaihtelevat huomattavasti, jolloin älykaupunkien älykkyyden ja onnistumisen yhteismitallinen arviointi on vaikeaa; jotkut havaituista älykaupunkien ominaisuuksista ja ratkaisuista ovat tehottomia tai jopa kielteisesti älykaupunkien tavoitteisiin vaikuttavia. Tässä tutkimuksessa päädyttiin seuraaviin johtopäätöksiin: älykaupunkihankkeiden monimutkaisen ja ristiriitaisen luonteen takia nykyinen älykaupunkitutkimus- ja kehitys ei täysin pysty vastaamaan näiden ristiriitaisuuksien ja keskinäisriippuvuuksien tuomiin haasteisiin; nykyinen älykaupunkitutkimus ei myöskään ole tieteellisesti riittävän monialaista. Tämän tutkimuksen pohjalta voidaan suositella, että tulevaisuudessa älykaupunkien kehitys voisi pohjautua enemmän tietojärjestelmätieteiden tutkimusmetodologioiden hyödyntämiseen, jolloin älykaupunkien vaatimat sosiotekniset ja monitieteelliset näkökulmat saataisiin paremmin havaittua, katettua ja arvioitua tutkimustuloksissa. Tulevaisuudessa tarvitaan myös tutkimusta siitä, kuinka tehokkaasti monitieteellinen älykaupunkitutkimus onnistuu

Statement, July 1983

Statement Magazine of Morehead State University from July of 1983

Uberising the Urban. Labour, Infrastructure and Big Data in the Actually Existing Smart City of Toronto

This thesis explores how Uber reformats the urban and vice versa. Rather than taking for granted Uber’s success in remoulding the emerging ‘smart city’ in its own image, Uberising the Urban pays close attention to the contradictory, variegated and far from frictionless encounters between Uberisation and urbanisation. The thesis is particularly interested in those neuralgic points of contact where the abstract logics of Uber’s business model – its vectors of data extraction, labour exploitation and platform expansion – hit the urban ground of existing social and physical geographies. The Uberisation of the urban – such is this thesis’s main argument – does not take place in a material and social void; it unfolds in, with and against the dense social and material thickness of existing urban space. This argument is deepened in three case studies. Zooming in from different angles, these case studies show how the vectors of Uberisation have come up against the multiscalar and variously uneven urban grounds of the actually existing smart city of Toronto. While the first case study provides a detailed discussion of the conflictive processes leading up to the legalisation of Uber in Toronto and the parallel ‘regulated deregulation’ of the city’s taxi-cum-ridehail market, the second case study tackles the next subsequent ‘stage’ of Uberisation in Toronto: the proliferation of various public-private ridehail partnerships (PPRPs) between Uber and Lyft on the one hand and local and regional transit agencies in the GTA on the other. The third case study is concerned with Uber’s self-driving car programme and, in particular, the invasive practices of data extraction that Uber has implemented in Toronto – turning the city into a real-life urban data reservoir for the development of its self-driving software. A conclusion, shedding light on a potential reconfiguration of Uber towards more socially emancipatory ends, rounds out the dissertation

Holistic Approach for Authoring Immersive and Smart Environments for the Integration in Engineering Education

Die vierte industrielle Revolution und der rasante technologische Fortschritt stellen die etablierten Bildungsstrukturen und traditionellen Bildungspraktiken in Frage. Besonders in der Ingenieurausbildung erfordert das lebenslange Lernen, dass man sein Wissen und seine Fähigkeiten ständig verbessern muss, um auf dem Arbeitsmarkt wettbewerbsfähig zu sein. Es besteht die Notwendigkeit eines Paradigmenwechsels in der Bildung und Ausbildung hin zu neuen Technologien wie virtueller Realität und künstlicher Intelligenz. Die Einbeziehung dieser Technologien in ein Bildungsprogramm ist jedoch nicht so einfach wie die Investition in neue Geräte oder Software. Es müssen neue Bildungsprogramme geschaffen oder alte von Grund auf umgestaltet werden. Dabei handelt es sich um komplexe und umfangreiche Prozesse, die Entscheidungsfindung, Design und Entwicklung umfassen. Diese sind mit erheblichen Herausforderungen verbunden, die die Überwindung vieler Hindernisse erfordert. Diese Arbeit stellt eine Methodologie vor, die sich mit den Herausforderungen der Nutzung von Virtueller Realität und Künstlicher Intelligenz als Schlüsseltechnologien in der Ingenieurausbildung befasst. Die Methodologie hat zum Ziel, die Hauptakteure anzuleiten, um den Lernprozess zu verbessern, sowie neuartige und effiziente Lernerfahrungen zu ermöglichen. Da jedes Bildungsprogramm einzigartig ist, folgt die Methodik einem ganzheitlichen Ansatz, um die Erstellung maßgeschneiderter Kurse oder Ausbildungen zu unterstützen. Zu diesem Zweck werden die Wechselwirkung zwischen verschiedenen Aspekten berücksichtigt. Diese werden in den drei Ebenen - Bildung, Technologie und Management zusammengefasst. Die Methodik betont den Einfluss der Technologien auf die Unterrichtsgestaltung und die Managementprozesse. Sie liefert Methoden zur Entscheidungsfindung auf der Grundlage einer umfassenden pädagogischen, technologischen und wirtschaftlichen Analyse. Darüber hinaus unterstützt sie den Prozess der didaktischen Gestaltung durch eine umfassende Kategorisierung der Vor- und Nachteile immersiver Lernumgebungen und zeigt auf, welche ihrer Eigenschaften den Lernprozess verbessern können. Ein besonderer Schwerpunkt liegt auf der systematischen Gestaltung immersiver Systeme und der effizienten Erstellung immersiver Anwendungen unter Verwendung von Methoden aus dem Bereich der künstlichen Intelligenz. Es werden vier Anwendungsfälle mit verschiedenen Ausbildungsprogrammen vorgestellt, um die Methodik zu validieren. Jedes Bildungsprogramm hat seine eigenen Ziele und in Kombination decken sie die Validierung aller Ebenen der Methodik ab. Die Methodik wurde iterativ mit jedem Validierungsprojekt weiterentwickelt und verbessert. Die Ergebnisse zeigen, dass die Methodik zuverlässig und auf viele Szenarien sowie auf die meisten Bildungsstufen und Bereiche übertragbar ist. Durch die Anwendung der in dieser Arbeit vorgestellten Methoden können Interessengruppen immersiven Technologien effektiv und effizient in ihre Unterrichtspraxis integrieren. Darüber hinaus können sie auf der Grundlage der vorgeschlagenen Ansätze Aufwand, Zeit und Kosten für die Planung, Entwicklung und Wartung der immersiven Systeme sparen. Die Technologie verlagert die Rolle des Lehrenden in eine Moderatorrolle. Außerdem bekommen die Lehrkräfte die Möglichkeit die Lernenden individuell zu unterstützen und sich auf deren kognitive Fähigkeiten höherer Ordnung zu konzentrieren. Als Hauptergebnis erhalten die Lernenden eine angemessene, qualitativ hochwertige und zeitgemäße Ausbildung, die sie qualifizierter, erfolgreicher und zufriedener macht