Development Of Ai Tools For Making Sense Of Future Complex Intelligent Systems

Artificial intelligence (AI) is increasingly introduced into many systems that modern society rely on and is often portrayed as a savior that can contribute to finding solutions to societal challenges e.g., social, and ecological sustainability. Many of these systems can be classified as complex systems, with interdependencies, emergent behaviors and a diversity of actors involved. As AI is increasingly introduced into these systems, we witness a transformation from complex systems into complex intelligent systems. At the same time caution is invoked toward the risks of AI regarding e.g., biases and loss of control as more tasks are transferred to AI. Hence, the introduction of AI into complex systems is associated with uncertainties around management of AI initiatives and their influence on future systems. Challenges like this can affect many different functions and professions and thus need to be understood collectively. The aim of this thesis is to examine how the actors’ prospective collective sensemaking processes in developing complex systems are affected by AI introduction. Previous research within complex systems literature shows important aspects regarding sensemaking of the system and situations within operations of complex systems. However, sensemaking in the development process of complex systems has been less studied. By examining the introduction of AI in complex systems development this thesis explores collective prospective sensemaking processes in the development of complex intelligent systems. To study an emerging phenomenon like AI introduction in complex systems, an explorative case study was found suitable. The case chosen for the study was a cross-organizational development project of an AI-tool based on Machine Learning for planning of energy systems to be used in the urban planning process of new city districts. This setting revealed plenty prospective and collective sensemaking occasions around AI introduction and exhibited continuous engagement in prospective collective sensemaking relating to the development of the AI tool and the imagined use of the AI tool in the system, which have been reported in the two appended papers. The first paper showed misalignment between actors’ sensemaking processes that alternated between seeking and disengaging behaviors. It also identified the use of boundary objects to retain disengaged actors and raised considerations around the level of detail of the boundary objects in relation to the sensemaking behaviors. The second paper identified dependencies between near- and distant-sensemaking loops that highlight challenges to connect retrospective insights with prospective imaginations by action in the present. In the creation of complex intelligent systems, human involvement seems inevitable, and the second paper exposes how AI can augment human cognition and organizational capabilities for creative imagination around possible and desirable distant-future scenarios. This thesis extends previous research on prospective and collective sensemaking in the development process of complex intelligent systems by presenting a framework of near and distant future sensemaking and internal and external complexity. This provided new insights of how knowledge flows over system levels and how to use boundary objects throughout such projects. Insight that can be useful for management of purposeful AI introduction in complex systems and society. Moreover, it contributes with an empirical case of AI introduction in complex systems to the innovation management literature. Artificiell intelligens (AI) integreras alltmer i de system som vårt moderna samhälle vilar på och framställs ofta som en viktig faktor för att lösa de utmaningar som samhället står inför, till exempel social och ekologisk hållbarhet. Många av dessa system kan definieras som komplexa system, med ömsesidiga beroenden, oförutsedda beteenden och en mångfald av inblandade aktörer. När AI introduceras i sådana system kan vi skönja en transformation från komplexa system till komplexa intelligenta system. Samtidigt påtalas ofta riskerna med AI avseende till exempel partiskhet och minskad kontroll när uppgifter tas över av AI. Införandet av AI i samhällskritiska system förknippas därmed med osäkerheter kring hanteringen av AI-initiativ och dess påverkan på framtiden. Detta leder till utmaningar som berör många olika funktioner och professioner och därmed behöver förstås kollektivt. Syftet med avhandlingen är att undersöka aktörernas framtidsorienterade, gemensamma, meningsskapande processer under utveckling av komplexa system och hur de påverkas av introduktionen av AI. Tidigare forskning inom komplexa system har visat på viktiga aspekter gällande människors förståelse av systemet och situationer framförallt inom driften av komplexa system. Meningsskapande i utvecklingsprocessen av komplexa system har dock hittills inte uppmärksammats i samma utsträckning. Genom att undersöka introduktionen av AI i utvecklingen av komplexa system utforskar denna avhandling kollektiva, framåtblickande, meningsskapande processer inom utvecklingen av komplexa intelligenta system. För studier av ett framväxande fenomen som AI-introduktion i komplexa system ansågs en explorativ fallstudie lämplig. Det valda fallet var ett utvecklingsprojekt av ett AI-verktyg baserat på maskininlärning med syfte att användas i planeringen av energisystem inom stadsplaneringsprocessen av nya stadsdelar och hade flera medverkande organisationer. Fallet visade på flera framtidsorienterade och gemensamma meningsskapande situationer kring AI-introduktion. Därmed synliggjordes de medverkandes kontinuerliga deltagande i framåtblickande gemensamt meningsskapande relaterat till utvecklingen av AI-verktyget och dess tänkta användningen i systemet, vilket rapporterats i de två bilagda artiklarna. Den första artikeln visade att de meningsskapande processerna var ur fas mellan aktörerna, vilka växlade mellan sökande och oengagerade beteenden, och att användningen av gränsöverskridande objekt med rätt detaljnivå kan involvera oengagerade aktörer. Den andra artikeln identifierade beroenden mellan olika meningsskapande cykler, närliggande respektive avlägsen framtid, vilket belyser utmaningar med att koppla tillbakablickande insikter till framåtblickande föreställningar om systemet genom handling i nuet. Vid skapande av komplexa intelligenta system framstår mänsklig inblandning som oundviklig, och den andra artikeln belyser även hur AI kan förstärka mänsklig kognition och organisatoriska förmågor för att främja kreativ föreställningsförmåga kring möjliga och önskvärda scenarier av en avlägsen framtid. Avhandlingen bidrar genom att bredda tidigare forskning om framtidsorienterat och kollektivt meningsskapande i utvecklingsprocessen av komplexa intelligenta system genom att presentera ett ramverk av närliggande och avlägset framåtblickande och intern och extern komplexitet. Det visar på nya insikter om hur kunskap flödar över systemnivåer och gränsöverskridande objekt kan användas under sådana utvecklingsprojekt. Sådana insikter kan vara praktiskt användbara för en välgrundad AI-introduktion i komplexa system och i samhället i stort. Dessutom bidrar den med en empirisk fallstudie av resan mot AI-introduktion i komplexa system till litteraturen inom innovationsledning.

Industrial robots, self-driving cars, customer-service chatbots and Google’s algorithmic predictions have brought the topic of artificial intelligence into public debate. Why is AI the source of such intense controversy and what are its economic, political, social and cultural consequences? Tracing the changing fortunes of artificial intelligence, Elliott develops a systematic account of how automated intelligent machines impact different spheres and aspects of public and private life. Among the issues discussed are the automation of workforces, surveillance capitalism, warfare and lethal autonomous weapons, the spread of racist robots and the automation of social inequalities. Elliott also considers the decisive role of AI in confronting global risks and social futures, including global pandemics such as COVID-19, and how smart algorithms are impacting the search for energy security and combating climate change. Making Sense of AI provides a judiciously comprehensive account of artificial intelligence for those with little or no previous knowledge of the topic. It will be an invaluable book both for students in the social sciences and humanities and for general readers.

In recent years, our world has experienced a profound shift and progression in available computing and knowledge sharing innovations. These emerging advancements have developed at a rapid pace, disseminating into and affecting numerous aspects of contemporary society. This has created a pivotal need for an innovative compendium encompassing the latest trends, concepts, and issues surrounding this relevant discipline area. During the past 15 years, the Encyclopedia of Information Science and Technology has become recognized as one of the landmark sources of the latest knowledge and discoveries in this discipline. The Encyclopedia of Information Science and Technology, Fourth Edition is a 10-volume set which includes 705 original and previously unpublished research articles covering a full range of perspectives, applications, and techniques contributed by thousands of experts and researchers from around the globe. This authoritative encyclopedia is an all-encompassing, well-established reference source that is ideally designed to disseminate the most forward-thinking and diverse research findings. With critical perspectives on the impact of information science management and new technologies in modern settings, including but not limited to computer science, education, healthcare, government, engineering, business, and natural and physical sciences, it is a pivotal and relevant source of knowledge that will benefit every professional within the field of information science and technology and is an invaluable addition to every academic and corporate library.

Companies that don't use AI to their advantage will soon be left behind. Artificial intelligence and machine learning will drive a massive reshaping of the economy and society. What should you and your company be doing right now to ensure that your business is poised for success? These articles by AI experts and consultants will help you understand today's essential thinking on what AI is capable of now, how to adopt it in your organization, and how the technology is likely to evolve in the near future. Artificial Intelligence: The Insights You Need from Harvard Business Review will help you spearhead important conversations, get going on the right AI initiatives for your company, and capitalize on the opportunity of the machine intelligence revolution. Catch up on current topics and deepen your understanding of them with the Insights You Need series from Harvard Business Review. Featuring some of HBR's best and most recent thinking, Insights You Need titles are both a primer on today's most pressing issues and an extension of the conversation, with interesting research, interviews, case studies, and practical ideas to help you explore how a particular issue will impact your company and what it will mean for you and your business.

This book constitutes the refereed proceedings of the 22nd IFIP WG 6.11 Conference on e-Business, e-Services and e-Society, I3E 2023, held in Curitiba, Brazil, during November 9–11, 2023. The 29 full papers and 2 short papers presented in this volume were carefully reviewed and selected from 68 submissions. The contributions were organized in topical sections as follows: Artificial Intelligence and Algorithm; Digital Transformation and New Technologies; and Sustainable Technologies and Smart Cities.

Artificial intelligence (AI) may be the most beneficial technological development of the twenty-first century.Media hype and raised expectations for results, however, have clouded understanding of the true nature of AI—including its limitations and potential. AI at War provides a balanced and practical understanding of applying AI to national security and warfighting professionals as well as a wide array of other readers. Although the themes and findings of the chapters are relevant across the U.S. Department of Defense, to include all Services, the Joint Staff and defense agencies as well as allied and partner ministries of defense, this book is a case study of warfighting functions in the Naval Services—the U.S. Navy and U.S. Marine Corps. Sam J. Tangredi and George Galdorisi bring together over thirty experts, ranging from former DOD officials and retired flag officers to scientists and active duty junior officers. These contributors present views on a vast spectrum of subjects pertaining to the implementation of AI in modern warfare, including strategy, policy, doctrine, weapons, and ethical concerns.

In recent years a vast literature has been produced on the feasibility of Artificial Intelligence (AI). The topic most frequently discussed is the concept of intelligence, with efforts to demonstrate that it is or is not transferable to the computer. Only rarely has attention been focused on the concept of the artificial per se in order to clarify what kind, depth and scope of performance (including intelligence) it could support. Apart from the classic book by H.A. Simon, The Sciences of the Artificial, published in 1969, no serious attempt has been made to define a conceptual frame for understanding the intimate nature of intelligent machines independently of its claimed or denied human-like features. The general aim of this book is to discuss, from different points of view, what we are losing and what we are gaining from the artificial, particularly from AI, when we abandon the original anthropomorphic pretension. There is necessarily a need for analysis of the history of AI and the limits of its plausibility in reproducing the human mind. In addition, the papers presented here aim at redefining the epistemology and the possible targets of the AI discipline, raising problems, and proposing solutions, which should be understood as typical of the artificial rather than of an information-based conception of man.