Artificial Intelligence Factory, Data Risk, and VCs’ Mediation: The Case of ByteDance, an AI-Powered Startup

The AI factory is an effective way of managing artificial intelligence (AI) processes, enabling broad AI deployment in a firm. The purpose of this study is to explore the role of the AI factory in an entrepreneurship context. How do AI-powered startups leverage AI to grow, and manage data risks? What is the role of venture capitalists in this process? We answer these research questions by conducting an in-depth study of an AI-powered startup: ByteDance. Our study extends both AI and entrepreneurship literature by showing that AI-powered startups adopt the AI factory approach to optimize scale, scope, and learning. Our discussion also emphasizes the critical role played by venture capitalists in assisting AI-powered startups in building AI factories and in reducing data risk.

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Smart Technology for Smart Response During Pandemic Times

10.4018/978-1-6684-3509-0.ch013 ◽

2022 ◽

pp. 261-278

Keyword(s):

Artificial Intelligence ◽

Social Media ◽

Big Data ◽

Smart City ◽

Critical Role ◽

Communication Strategy ◽

Smart Technology ◽

Information And Communication ◽

Remote Learning

The formal response to COVID-19 through ICT is presented with a focus on testing COVID-19, ICTs and tracking COVID-19, ICTs and COVID-19 treatment, and policies and strategies. The chapter highlights the critical role of ICTs and e-government for technologies to fight coronavirus. It covers delivery of remote learning, ICT trends, artificial intelligence (AI), and big data in fighting the pandemic, in addition to social media application for awareness of citizens such as emergencies, protection, and pandemic news. The notion of developing an information and communication strategy for redesigning smart city transformation in a pandemic is highlighted.

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Chief information officers’ perceptions about artificial intelligence

First Monday ◽

10.5210/fm.v26i1.10648 ◽

2020 ◽

Author(s):

J. Ignacio Criado ◽

Rodrigo Sandoval-Almazan ◽

David Valle-Cruz ◽

Edgar A. Ruvalcaba-Gómez

Keyword(s):

Artificial Intelligence ◽

Public Sector ◽

Three Dimensions ◽

Chief Information Officers ◽

The Public ◽

Design And Implementation ◽

Challenges And Opportunities ◽

Research Questions ◽

State And Local

This article presents a study about artificial intelligence (AI) policy based on the perceptions, expectations, and challenges/opportunities given by chief information officers (CIOs). In general, publications about AI in the public sector relies on experiences, cases, ideas, and results from the private sector. Our study stands out from the need of defining a distinctive approach to AI in the public sector, gathering primary (and comparative) data from different countries, and assessing the key role of CIOs to frame federal/national AI policies and strategies. This article reports three research questions, including three dimensions of analysis: (1) perceptions regarding to the concept of AI in the public sector; (2) expectations about the development of AI in the public sector; and, (3) challenges and opportunities of AI in the public sector. This exploratory study presents the results of a survey administered to federal/national ministerial government CIOs in ministries of Mexico and Spain. Our descriptive statistical (and exploratory) analysis provides an overall approach to our dimensions, exploratory answering the research questions of the study. Our data supports the existence of different governance models and policy priorities in different countries. Also, these results might inform research in this same area and will help senior officials to assess the national AI policies actually in process of design and implementation in different national/federal, regional/state, and local/municipal contexts.

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A study of artificial intelligence on employee performance and work engagement: the moderating role of change leadership

International Journal of Manpower ◽

10.1108/ijm-07-2021-0423 ◽

2022 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Dewie Tri Wijayati ◽

Zainur Rahman ◽

A’rasy Fahrullah ◽

Muhammad Fajar Wahyudi Rahman ◽

Ika Diyah Candra Arifah ◽

...

Keyword(s):

Artificial Intelligence ◽

Work Engagement ◽

Employee Performance ◽

Critical Role ◽

Change Leadership ◽

Equation Modeling ◽

Research Approach ◽

Content Type ◽

Rapid Changes

PurposeThis paper aims to explore employee perceptions of companies engaged in services and banking of the role of change leadership on the application of artificial intelligence (AI) that will impact the performance and work engagement in conditions that are experiencing rapid changes.Design/methodology/approachThis study has used a quantitative research approach, and data analysis uses an approach structural equation modeling (SEM) supported by program computer software AMOS 22.0. A total of 357 respondents were involved in this study, but only 254 were qualified. In this study, the respondent is an employee of companies engaged in the services and banking sector in the East Java, Indonesia region.FindingsThe results reveal that AI has a significant positive effect on employee performance and work engagement. Change leadership positively moderates the influence of AI on employee performance and work engagement.Originality/valueThe development of this model has a novelty by including the moderating variable of the role of change leadership because, in conditions that are experiencing rapid changes, the role of leaders is essential. After all, leaders are decision-makers in the organization. The development of this concept focuses on studies of companies engaged in services and banking. Employee performance is an essential determinant in the organization because it will improve organizational performance. In addition, the application of AI in organizations will experience turmoil, so that the critical role of leaders is needed to achieve success with employee work engagement.

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A Digital Tale of Two Cities—Observing the Dynamics of the Artificial Intelligence Ecosystems in Berlin and Sydney

Sustainability ◽

10.3390/su131910564 ◽

2021 ◽

Vol 13 (19) ◽

pp. 10564

Author(s):

Thorsten Lammers ◽

Dilek Cetindamar ◽

Maren Borkert

Keyword(s):

Artificial Intelligence ◽

Knowledge Spillovers ◽

Critical Role ◽

Secondary Data ◽

Knowledge Bases ◽

Digital Innovation ◽

Knowledge Practices ◽

Two Cities ◽

Spillover Theory

In entrepreneurial ecosystems (EEs), geographical and contextual factors play a big role in shaping the knowledge bases for digital innovation. While cities around the world compete to be perceived as successful “tech startup hubs”, proactive urban strategies are needed to create knowledge spillovers into EEs. This study explores the evolution of artificial intelligence (AI) knowledge practices in the EEs of Berlin and Sydney by using knowledge-spillover theory of entrepreneurship. The study utilizes a bibliometric analysis of secondary data in combination with exploratory stakeholder interviews conducted for both cities. Findings underline the critical role of experimental knowledge in driving the momentum of the EEs and the supporting role of policies imprinting knowledge practices. The paper shows how the dynamics of EEs can be explored empirically and raises awareness of the role of specialised and integrated policies in determining a city’s overall success in building EEs.

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The Practice of UN Treaty-Making concerning Science

The Oxford Handbook of United Nations Treaties ◽

10.1093/law/9780190947842.003.0019 ◽

2019 ◽

pp. 320-338

Author(s):

Sam Johnston

Keyword(s):

Climate Change ◽

Artificial Intelligence ◽

Synthetic Biology ◽

New Technologies ◽

Social Economic ◽

Critical Role ◽

Applied Science ◽

Global Commons ◽

Institutional Expectations

This chapter describes the growing influence of science in UN treaties, which centers around four main roles; scientific influence in the treaty-making process, promoting access to existing science, supporting research, and managing the threats posed by science. It also highlights the challenges UN treaties face in using science such as; resolving the tensions that exist between pure and applied science; maintaining science’s role as a peaceful activity in the global commons; ensuring that scientific input is not lost among the increasing complex and crowded nature of treaty-making; ensuring that science is more inclusive, holistic, and balanced; and improving its relevance while retaining its credibility. The UN will also need to use science to respond to new and emerging areas such as managing new technologies including nanotechnologies, synthetic biology, or artificial intelligence, or new threats such as cyberwarfare and security. Failures of science in predicting and managing threats from climate change, epidemics, and nuclear disasters have revealed the uncertainties underlying many of its areas of practice and has demonstrated the critical role that social, economic, and institutional expectations play. Recognizing that science is not neutral or objective is an important step in addressing the key shortcomings facing the role of science in UN treaties. Determining what measures need to be taken to balance social and economic influences is another important side of this challenge. Reconciling these enduring challenges will be increasingly important in all areas where UN treaty-making processes and science intersect.

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The Role of the SLP in Autism Spectrum Disorder Screening and Assessment

Perspectives on Language Learning and Education ◽

10.1044/lle15.2.50 ◽

2008 ◽

Vol 15 (2) ◽

pp. 50-59 ◽

Cited By ~ 1

Author(s):

Amy Philofsky

Keyword(s):

Language Development ◽

Critical Role ◽

Children With Autism ◽

Autism Spectrum ◽

Children With Asd ◽

Prevalence Estimates ◽

Notable Increase ◽

Screening Assessment ◽

Critical Components

AbstractRecent prevalence estimates for autism have been alarming as a function of the notable increase. Speech-language pathologists play a critical role in screening, assessment and intervention for children with autism. This article reviews signs that may be indicative of autism at different stages of language development, and discusses the importance of several psychometric properties—sensitivity and specificity—in utilizing screening measures for children with autism. Critical components of assessment for children with autism are reviewed. This article concludes with examples of intervention targets for children with ASD at various levels of language development.

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