Economic Policy for Artificial Intelligence

Agrawal, Ajay; Gans, Joshua S.; Goldfarb, Avi

doi:10.3386/w24690

Cited by 92 publications

(29 citation statements)

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“…A range of terms such as "Machine Intelligence," "Intelligence Agents," "Intelligent Systems" and "Algorithms" also serve as labels for describing AI. Today, AI starting to become an essential feature of almost all industries [9] including education [22], healthcare [57], finance [3], transportation [11], agriculture [6], and manufacturing [32]. In these contexts, AI consists of a comprehensive set of training computers that aim to do tasks involving human intelligence.…”

Section: Ai From Science Fiction To Business Factmentioning

confidence: 99%

Re-thinking the Competitive Landscape of Artificial Intelligence

Alsheibani¹,

Messom²,

Cheung³

2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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Artificial Intelligence (AI) has emerged from its traditional domain of computer science research to be a management reality. This can be seen in the remarkable increase in the adoption of AI technology in organizations resulting in increased revenue, reduced costs and improved business efficiency [19]. Despite this trend, there are still many organizations that are facing the decision whether to adopt AI. Thus, to evaluate the adoption of AI at organizational-level, we draw on two-grounded theories:Technology-Organizations-Environment (TOE) framework and Diffusion of Innovation theory (DOI) to identify factors that influence the adoption of AI. Survey data collected from 208 large, mediumsized and small organizations in Australia is used to test the proposed framework. We offer a method of how examining AI over a set of organizations. Besides offering several important recommendations for AI adoption future directions for research in this area are also included in this paper.

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Section: Ai From Science Fiction To Business Factmentioning

confidence: 99%

Re-thinking the Competitive Landscape of Artificial Intelligence

Alsheibani¹,

Messom²,

Cheung³

2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…AI and Big Data are growing in importance in broader research fields that are often seen as foundational for entrepreneurship research, such as economics (Acemoglu and Restrepo 2018;Einav and Levin 2014), economic policy (Agrawal et al 2019), innovation (Aghion et al 2017), management (George et al 2014;Ransbotham et al 2017), and psychology (Kosinski et al 2016). Likewise, this data revolution is also disrupting application fields associated with entrepreneurship, including industry, business management, and innovation (Cockburn et al 2018).…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence and big data in entrepreneurship: a new era has begun

Obschonka¹,

2019

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While the disruptive potential of artificial intelligence (AI) and Big Data has been receiving growing attention and concern in a variety of research and application fields over the last few years, it has not received much scrutiny in contemporary entrepreneurship research so far. Here we present some reflections and a collection of papers on the role of AI and Big Data for this emerging area in the study and application of entrepreneurship research. While being mindful of the potentially overwhelming nature of the rapid progress in machine intelligence and other Big Data technologies for contemporary structures in entrepreneurship research, we put an emphasis on the reciprocity of the co-evolving fields of entrepreneurship research and practice. How can AI and Big Data contribute to a productive transformation of the research field and the real-world phenomena (e.g., "smart entrepreneurship")? We also discuss, however, ethical issues as well as challenges around a potential contradiction between entrepreneurial uncertainty and rule-driven AI rationality. The editorial gives researchers and practitioners orientation and showcases avenues and examples for concrete research in this field. At the same time, however, it is not unlikely that we will encounter unforeseeable and currently inexplicable developments in the field soon. We call on entrepreneurship scholars, educators, and practitioners to proactively prepare for future scenarios.

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“…[78] Medhi, S., B. Scholkopf and M. Hirsch (2017), "EnhanceNet: Single image super-resolution through automated texture synthesis", arXiv 1612.07919, https://arxiv.org/abs/1612.07919. [97] MIT (2018), "Cybersecurity's insidious new threat: Workforce stress", MIT Technology Review, 7 August, https://www.technologyreview.com/s/611727/cybersecuritys-insidious-new-threatworkforce-stress/. [92] O'Dwyer, R. (2018), Algorithms are making the same mistakes assessing credit scores that humans did a century ago, Quartz, 14 May, https://qz.com/1276781/algorithms-are-makingthe-same-mistakes-assessing-credit-scores-that-humans-did-a-century-ago/.…”

Section: Vr For Training Ai Systemsmentioning

confidence: 99%

“…As jobs change, so will the skills required of workers (OECD, 2017 [96]; Acemoglu and Restrepo, 2018 [97]; Brynjolfsson and Mitchell, 2017[98]). The present subsection outlines a few possible repercussions of AI on skills, noting this is a rapidly evolving area where evidence-based analytical work is only beginning.…”

Section: Skills To Use Aimentioning

confidence: 99%

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Artificial Intelligence in Society (Summary in German)

2019

Künstliche Intelligenz in Der Gesellschaft

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You can copy, download or print OECD content for your own use, and you can include excerpts from OECD publications, databases and multimedia products in your own documents, presentations, blogs, websites and teaching materials, provided that suitable acknowledgement of OECD as source and copyright owner is given. All requests for public or commercial use and translation rights should be submitted to rights@oecd.org. Requests for permission to photocopy portions of this material for public or commercial use shall be addressed directly to the Copyright Clearance Center (CCC) at info@copyright.com or the Centre français d'exploitation du droit de copie (CFC) at contact@cfcopies.com.Preface Artificial intelligence (AI) is reshaping economies, promising to generate productivity gains, improve efficiency and lower costs. It contributes to better lives and helps people make better predictions and more informed decisions. These technologies, however, are still in their infancy, and there remains much promise for AI to address global challenges and promote innovation and growth. As AI's impacts permeate our societies, its transformational power must be put at the service of people and the planet.At the same time, AI is also fuelling anxieties and ethical concerns. There are questions about the trustworthiness of AI systems, including the dangers of codifying and reinforcing existing biases, such as those related to gender and race, or of infringing on human rights and values, such as privacy. Concerns are growing about AI systems exacerbating inequality, climate change, market concentration and the digital divide. No single country or actor has all the answers to these challenges. We therefore need international co-operation and multistakeholder responses to guide the development and use of AI for the wider good.This book, Artificial Intelligence in Society, examines the AI landscape and highlights key policy questions. Its goal is to help build a shared understanding of AI in the present and near term, and to encourage a broad dialogue on important policy issues, such as labour market developments and upskilling for the digital age; privacy; accountability of AIpowered decisions; and the responsibility, security and safety questions that AI generates.The book draws on the work of the AI group of experts at the OECD, formed in 2018 to scope principles to facilitate innovation, adoption and trust in AI. Their debates inspired the OECD Recommendation of the Council on Artificial Intelligence -the first intergovernmental standard on AI -adopted by all OECD members and by several partner countries on 22 May 2019. This work emphasises the need for international co-operation to shape a policy environment that fosters trust in and adoption of AI.Looking ahead, we must progress together on AI-related technical, ethical and legal issues, in order to foster the alignment of standards and codes of conduct while ensuring the interoperability of laws and regulations. This is urgent, given the speed of developments and the breadth of a...

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Economic Policy for Artificial Intelligence

Cited by 92 publications

References 0 publications

Re-thinking the Competitive Landscape of Artificial Intelligence

Re-thinking the Competitive Landscape of Artificial Intelligence

Artificial intelligence and big data in entrepreneurship: a new era has begun

Artificial Intelligence in Society (Summary in German)

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