Generative AI

Business & Information Systems Engineering, Journal Year: 2023, Volume and Issue: 66(1), P. 111 - 126

Published: Sept. 12, 2023

The term "generative AI" refers to computational techniques that are capable of generating seemingly new, meaningful content such as text, images, or audio from training data. widespread diffusion this technology with examples Dall-E 2, GPT-4, and Copilot is currently revolutionizing the way we work communicate each other. In article, provide a conceptualization generative AI an entity in socio-technical systems models, systems, applications. Based on that, introduce limitations current agenda for Business & Information Systems Engineering (BISE) research. Different previous works, focus context information and, end, discuss several opportunities challenges unique BISE community make suggestions impactful directions

Language: Английский

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Generative artificial intelligence

Electronic Markets, Journal Year: 2023, Volume and Issue: 33(1)

Published: Dec. 1, 2023

Abstract Recent developments in the field of artificial intelligence (AI) have enabled new paradigms machine processing, shifting from data-driven, discriminative AI tasks toward sophisticated, creative through generative AI. Leveraging deep models, is capable producing novel and realistic content across a broad spectrum (e.g., texts, images, or programming code) for various domains based on basic user prompts. In this article, we offer comprehensive overview fundamentals with its underpinning concepts prospects. We provide conceptual introduction to relevant terms techniques, outline inherent properties that constitute AI, elaborate potentials challenges. underline necessity researchers practitioners comprehend distinctive characteristics order harness potential while mitigating risks contribute principal understanding.

Language: Английский

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Crafting the techno-functional blocks for Metaverse - A review and research agenda

International Journal of Information Management Data Insights, Journal Year: 2024, Volume and Issue: 4(1), P. 100213 - 100213

Published: Jan. 14, 2024

The "Metaverse," a term popularized by Neal Stephenson's novel Snow Crash, has been discussed in the science fiction community for decades, but technological advancements have only recently made it reality. Metaverse is an all-encompassing, interconnected virtual environment where users can freely communicate with one another and digital content. This article examines how various technologies, primarily Virtual Reality (VR) Augmented (AR), contributed to development of (AR). These innovations revolutionized way we interact media enabling us genuine, realistic experiences. In addition, examine technologies that make possible construct fully realized, functional world. Among these are recent advances artificial intelligence (AI), cryptocurrencies, spatial peripheral computing, other fields. Our research investigates advantages disadvantages as well they may influence future Metaverse. Furthermore, explores darker aspects Metaverse, particularly emergence "dark verse," which underscores potential organized illicit activities within Internet due insufficient oversight governance

Language: Английский

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Broadening the perspective for sustainable artificial intelligence: sustainability criteria and indicators for Artificial Intelligence systems

Current Opinion in Environmental Sustainability, Journal Year: 2024, Volume and Issue: 66, P. 101411 - 101411

Published: Jan. 8, 2024

The increased use of Artificial intelligence systems (AI systems) is associated with multifaceted social, environmental, and economic consequences. These include nontransparent decision-making processes, discrimination, increasing inequalities, rising energy consumption greenhouse gas emissions in AI model development application, an concentration power. By considering the multidimensionality sustainability, this paper takes steps toward substantiating call for overarching perspective on 'sustainable AI.' It presents Sustainability Criteria Indicators Intelligence Systems (SCAIS) Framework, assessment framework that contains a set 19 sustainability criteria sustainable 67 indicators are based results critical literature review, expert workshops. Its interdisciplinary approach contributes unique holistic to facilitate structure discourse AI. Further, it provides concrete lays foundation developing standards tools support conscious application systems.

Language: Английский

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Generative AI as a transformative force for innovation: a review of opportunities, applications and challenges

European Journal of Innovation Management, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 1, 2024

Purpose This study examines the existing literature on generative artificial intelligence (Gen AI) and its impact across many sectors. analysis explores potential, applications, challenges of Gen AI in driving innovation creativity generating ideas. Design/methodology/approach The adopts a comprehensive review approach, carefully assessing current scientific articles published from 2022 to 2024. trends insights derived research. Findings indicates that has significant potential augment human processes as collaborative partner. However, it is imperative prioritize responsible development ethical frameworks order effectively tackle biases, privacy concerns, other challenges. significantly transforming business models, processes, value propositions several industries, but with varying degrees effect. indicate also despite theory-driven approach investigating AI's creative innovative cutting-edge applications research prioritizes examining possibilities models. Research limitations/implications Although this offers picture great possibilities, concurrently underlines necessity for deep knowledge nuances fully harness capabilities. findings continuous exploration efforts are required address assure implementation. Therefore, more needed enhancing human-AI collaboration defining norms varied circumstances. Originality/value presents relevant transformational an catalyst. It emphasizes major issues integration.

Language: Английский

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Strategic Green Alliances: Integrating Green Dynamic Capabilities, AI, and Electronic Entrepreneurial Innovation for Sustainability

Sustainable Futures, Journal Year: 2025, Volume and Issue: unknown, P. 100433 - 100433

Published: Jan. 1, 2025

Language: Английский

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Generative AI

SSRN Electronic Journal, Journal Year: 2023, Volume and Issue: unknown

Published: Jan. 1, 2023

The term "generative AI'' refers to computational techniques that are capable of generating seemingly new, meaningful content such as text, images, or audio from training data. widespread diffusion this technology with examples Dall-E 2, GPT-4, and Copilot is currently revolutionizing the way we work communicate each other. In article, provide a conceptualization generative AI an entity in socio-technical systems models, systems, applications. Based on that, introduce limitations current agenda for Business & Information Systems Engineering (BISE) research. Different previous works, focus context information and, end, discuss several opportunities challenges unique BISE community make suggestions impactful directions

Language: Английский

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Comparing the Ideation Quality of Humans With Generative Artificial Intelligence

IEEE Engineering Management Review, Journal Year: 2024, Volume and Issue: 52(2), P. 153 - 164

Published: Jan. 12, 2024

Traditionally, ideating new product innovations is primarily the responsibility of marketers, engineers, and designers. However, a rapidly growing interest lies in leveraging generative artificial intelligence (AI) to brainstorm service ideas. This study conducts comparative analysis ideas generated by human professionals an AI system. The results blind expert evaluation show that AI-generated score significantly higher novelty customer benefit, while their feasibility scores are similar those Overall, comprise majority top-performing ideas, human-generated scored lower than expected. executive's emotional cognitive reactions were measured during check for potential biases showed no differences between idea groups. These findings suggest that, under certain circumstances, companies can benefit from integrating into traditional idea-generation processes.

Language: Английский

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AI for social good and the corporate capture of global development

Information Technology for Development, Journal Year: 2024, Volume and Issue: 30(4), P. 626 - 643

Published: Feb. 16, 2024

This article focuses on the AI for Social Good (AI4SG) movement, which aims to leverage Artificial Intelligence (AI) and Machine Learning (ML) achieve United Nations Sustainable Development Goals (UN SDGs). It argues that, through AI4SG, Big Tech is attempting advance AI-driven technosolutionism within development policy scholarly space creating new opportunities rent extraction. The situates history of ICT4D. also highlights contiguity AI4SG with so-called 4th Industrial Revolution (4IR), a framework that places other digital innovations at center national international industrial agendas. By exploring how has attempted depoliticize datafication, we thus suggest 4IR are mutually reinforcing discourses serve purpose depoliticizing arena by bestowing legitimacy authority reshape spaces epistemic infrastructures while inserting themselves, an unprecedented degree, between citizen (data) state (development policy).

Language: Английский

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Artificial Intelligence for Sign Language Translation – A Design Science Research Study

Communications of the Association for Information Systems, Journal Year: 2023, Volume and Issue: 53(1), P. 42 - 64

Published: Jan. 1, 2023

Although our digitalized society is able to foster social inclusion and integration, there are still numerous communities suffering from inequality. This also the case with deaf people. About 750,000 people in European Union over 4 million United States face daily challenges terms of communication participation. occurs not only leisure activities but also, more importantly, emergency situations. To provide equal environments allow hearing handicaps communicate their native language, this paper presents an AI-based sign language translator. We adopted a transformer neural network capable analyzing 500 data points person’s gestures translate into text. have designed machine learning pipeline that enables translator evolve, build new datasets, train recognition models. As proof concept, we instantiated interpreter for call 200 phrases. The overall goal support inabilities by enabling them participate economic, social, political, cultural life.

Language: Английский

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