Search results for "Tekoäly"

showing 10 items of 188 documents

Time for AI (Ethics) maturity model is now

2021

Publisher Copyright: Copyright © 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). There appears to be a common agreement that ethical concerns are of high importance when it comes to systems equipped with some sort of Artificial Intelligence (AI). Demands for ethical AI are declared from all directions. As a response, in recent years, public bodies, governments, and universities have rushed in to provide a set of principles to be considered when AI based systems are designed and used. We have learned, however, that high-level principles do not turn easily into actionable advice for practitioners. Hence, also companie…

FOS: Computer and information sciencesjärjestelmäsuunnitteluComputer Science - Computers and SocietytoimintaohjeetComputingMethodologies_PATTERNRECOGNITIONComputers and Society (cs.CY)tekoälyetiikkaeettisyysohjelmistokehitys113 Computer and information sciencesGeneralLiterature_MISCELLANEOUS
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Governance of Ethical and Trustworthy Al Systems: Research Gaps in the ECCOLA Method

2021

Advances in machine learning (ML) technologies have greatly improved Artificial Intelligence (AI) systems. As a result, AI systems have become ubiquitous, with their application prevalent in virtually all sectors. However, AI systems have prompted ethical concerns, especially as their usage crosses boundaries in sensitive areas such as healthcare, transportation, and security. As a result, users are calling for better AI governance practices in ethical AI systems. Therefore, AI development methods are encouraged to foster these practices. This research analyzes the ECCOLA method for developing ethical and trustworthy AI systems to determine if it enables AI governance in development process…

FOS: Computer and information sciencesjärjestelmäsuunnitteluKnowledge managementAl governanceComputingMilieux_LEGALASPECTSOFCOMPUTINGtekoälyGeneralLiterature_MISCELLANEOUSData governanceComputer Science - Computers and SocietyAlComputers and Society (cs.CY)Health careInformation governanceEthicsbusiness.industryCorporate governanceeettisyysECCOLAMLComputingMethodologies_PATTERNRECOGNITIONTrustworthinessluottamusEthical concernsEthical AIetiikkabusinessAi systems2021 IEEE 29th International Requirements Engineering Conference Workshops (REW)
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Implementing AI Ethics in Practice: An Empirical Evaluation of the RESOLVEDD Strategy

2020

As Artificial Intelligence (AI) systems exert a growing influence on society, real-life incidents begin to underline the importance of AI Ethics. Though calls for more ethical AI systems have been voiced by scholars and the general public alike, few empirical studies on the topic exist. Similarly, few tools and methods designed for implementing AI ethics into practice currently exist. To provide empirical data into this on-going discussion, we empirically evaluate an existing method from the field of business ethics, the RESOLVEDD strategy, in the context of ethical system development. We evaluated RESOLVEDD by means of a multiple case study of five student projects where its use was given …

FOS: Computer and information sciencesjärjestelmäsuunnitteluUnderlineComputingMilieux_THECOMPUTINGPROFESSIONethical toolContext (language use)Ai ethicstekoälykäytäntöartificial intelligenceethicsField (computer science)developer commitmentComputer Science - Computers and SocietyEmpirical researchdesign methodsComputers and Society (cs.CY)Key (cryptography)RESOLVEDDEngineering ethicsBusiness ethicsetiikkaDesign methodsPsychology
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ECCOLA : a Method for Implementing Ethically Aligned AI Systems

2020

Various recent Artificial Intelligence (AI) system failures, some of which have made the global headlines, have highlighted issues in these systems. These failures have resulted in calls for more ethical AI systems that better take into account their effects on various stakeholders. However, implementing AI ethics into practice is still an on-going challenge. High-level guidelines for doing so exist, devised by governments and private organizations alike, but lack practicality for developers. To address this issue, in this paper, we present a method for implementing AI ethics. The method, ECCOLA, has been iteratively developed using a cyclical action design research approach. The method aim…

FOS: Computer and information sciencesjärjestelmäsuunnitteluimplementingManagement scienceComputer science020207 software engineering02 engineering and technologyAi ethicstekoälyethicsGeneralLiterature_MISCELLANEOUSComputer Science - Computers and SocietyAI ethicsArtificial Intelligence020204 information systemsComputers and Society (cs.CY)suunnittelumenetelmät0202 electrical engineering electronic engineering information engineeringmethodAction design researchetiikkaAi systems
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Continuous experimentation on artificial intelligence software : a research agenda

2020

Moving from experiments to industrial level AI software development requires a shift from understanding AI/ ML model attributes as a standalone experiment to know-how integrating and operating AI models in a large-scale software system. It is a growing demand for adopting state-of-the-art software engineering paradigms into AI development, so that the development efforts can be aligned with business strategies in a lean and fast-paced manner. We describe AI development as an “unknown unknown” problem where both business needs and AI models evolve over time. We describe a holistic view of an iterative, continuous approach to develop industrial AI software basing on business goals, requiremen…

Focus (computing)Future studiesComputer sciencebusiness.industrysoftwareContinuous experimentationohjelmistotuotantoSoftware development020207 software engineeringArtificial intelligence software02 engineering and technologytekoälytutkimustoimintaartificial intelligenceGeneralLiterature_MISCELLANEOUSEngineering managementBusiness goalsSoftwareComputingMethodologies_PATTERNRECOGNITION020204 information systems0202 electrical engineering electronic engineering information engineeringSoftware systembusinessohjelmistokehitys
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Lost People : How National AI-Strategies Paying Attention to Users

2021

Abstract. This paper focuses on how major national strategies call attention to the human dimensions of artificial intelligence (AI). All intelligent technologies using AI are constructed for people as either active users or as relatively passive target persons. Thus, human properties and human research should have an important role in developing future AI systems. In these development strategies, it is interesting to pay attention to the underlying intuitive assumptions and tacit commitments. This issue is especially interesting when we think about what governmental working groups say about people and their changing lives in their strategies. The traditional stances adopted in writing nati…

Focus (computing)Knowledge managementbusiness.industrysocial transformationtekoälyGeneralLiterature_MISCELLANEOUSteknologiapolitiikkaComputingMethodologies_PATTERNRECOGNITIONSocial transformationHuman researchyhteiskunnallinen muutosbusinessPsychologykehitysstrategiatAI-strategieshuman factorsAi systemsinhimilliset tekijät
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Go-tekoälyjen toteutusratkaisuja

2009

Go tarjoaa tekoälytutkijoille jatkuvasti uusia haasteita ja tapoja testata ideoitaan. Toistaiseksi ei ole vielä onnistuttu kehittämään tekoälyä, jota ihminen ei voisi voittaa, mutta yrityksiä on monenlaisia. Yksinkertaisista säännöistä huolimatta go on hyvin strateginen ja taktinen peli ja gon ratkaisemista pidetään yleisenä tavoitteena tekoälytutkimuksessa.       

GNU GotekoälymenetelmätGoFuegotekoäly
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Data Analytics in Healthcare: A Tertiary Study

2022

AbstractThe field of healthcare has seen a rapid increase in the applications of data analytics during the last decades. By utilizing different data analytic solutions, healthcare areas such as medical image analysis, disease recognition, outbreak monitoring, and clinical decision support have been automated to various degrees. Consequently, the intersection of healthcare and data analytics has received scientific attention to the point of numerous secondary studies. We analyze studies on healthcare data analytics, and provide a wide overview of the subject. This is a tertiary study, i.e., a systematic review of systematic reviews. We identified 45 systematic secondary studies on data analy…

General Computer ScienceComputer Networks and Communicationsterveydenhuoltodata-analytiikkahealthcaredata miningtekoälyartificial intelligenceComputer Graphics and Computer-Aided DesignComputer Science Applicationsmachine learningkoneoppiminendataComputational Theory and Mathematicsbig dataArtificial Intelligencetiedonlouhintadata analyticsSN Computer Science
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Explainable Student Agency Analytics

2021

Several studies have shown that complex nonlinear learning analytics (LA) techniques outperform the traditional ones. However, the actual integration of these techniques in automatic LA systems remains rare because they are generally presumed to be opaque. At the same time, the current reviews on LA in higher education point out that LA should be more grounded to the learning science with actual linkage to teachers and pedagogical planning. In this study, we aim to address these two challenges. First, we discuss different techniques that open up the decision-making process of complex techniques and how they can be integrated in LA tools. More precisely, we present various global and local e…

General Computer ScienceHigher educationComputer scienceProcess (engineering)päätöksentekoLearning analyticstekoälyoppimisanalytiikkadecision makingkorkeakouluopetusData modelingAgency (sociology)ComputingMilieux_COMPUTERSANDEDUCATIONGeneral Materials ScienceElectrical and Electronic Engineeringexplainable artificial intelligenceopiskelijatPoint (typography)business.industrypalauteGeneral EngineeringtoimijuusoppimisalustatData scienceLearning sciencesTK1-9971Analyticshigher educationkorkeakouluopiskelustudent agencyElectrical engineering. Electronics. Nuclear engineeringExplainable artificial intelligencebusinessarviointiIEEE Access
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Artificial General Intelligence vs. Industry 4.0 : Do They Need Each Other?

2022

Artificial Intelligence (AI) is known to be a driving force behind the Industry 4.0. Nowadays the current hype on development and industrial adoption of the AI systems is mostly associated with the deep learning, i.e., with the abilities of the AI to perform various specific cognitive activities better than humans do. However, what about the Artificial General Intelligence (AGI), associated with the generic ability of a machine to perform consciously any task that a human can? Do we have many samples of the AGI research adopted by Industry 4.0 and used for smart manufacturing? In this paper, we report the systematic mapping study regarding the AGI-related papers (published during the five-y…

Google distancesystematic mapping studyälytekniikkatekoälyteollisuusIndustry 4.0Artificial general intelligence
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