SENSEMAKING IN AI-BASED DIGITAL INNOVATIONS: INSIGHTS FROM A MANUFACTURING CASE STUDY

Organizations strive to innovate with Artificial Intelligence (AI) to tap new value potentials and outperform their competition. However, despite the enormous expectations associated with AI, incorporating the latter induces novel uncertainties and can even result in business value destruction. Therefore, organizations innovating with AI must manage these AI-induced uncertainties in their sensemaking process. Drawing on an exploratory case study, we investigate organizational sensemaking in two AI-based digital innovation projects at a globally leading automotive manufacturer. We account for the properties by which AI differs from traditional information systems and carve out how distinct AI properties unfold in AI-based digital innovations. We deduce four AI sensemaking mechanisms (i.e., cognition, interaction, regulation, and concretization) to understand better how AI challenges digital innovation endeavors in organizations

Market Share, R&D Cooperation, and EU Competition Policy

Current EU policy exempts horizontal R&D agreements from antitrust con- cerns when the combined market shares of participants are low enough. This paper argues that existing theory does not support limiting the exemption to low market shares. This is done by introducing a set of non-innovating outside firms to the standard framework to assess what link might exist between the market share of innovating firms and the product market benefits of cooperation. With R&D output choices, the market share criterion, while it rules out the most socially harmful R&D cooperation agreements, also hinders the most beneficial ones. With R&D input choices, cooperation may actually be desirable in concentrated industries, and harmful in more competitive ones. If R&D cooperation does have anti-competitive effects in product markets, it seems that these are therefore best addressed by other tools than market share criteria.R&D; Cooperation; Competition; Regulation

Towards Value Creation with Artificial Intelligence in Healthcare: A Qualitative Study on User Requirements

In recent years, artificial intelligence (AI) has emerged as a promising technology for healthcare. As a result, incumbents and startups entering the healthcare market with AI-enabled products need to explore the user requirements of medical professionals to enable reliable and satisfactory solutions. To overcome barriers and channel AI for value creation, we examine how startups and incumbents in the healthcare industry are innovating their business models to create value with AI. We conducted a qualitative interview study in which we investigate medical professionals from a provider perspective and representatives of medical companies. In the first round of data collection, we developed a holistic view of the specific requirements for AI-enabled medical devices in radiology (organizational, regulatory, product, communicative, and financial). In the second round, we plan to explore how companies can respond to the previously identified requirements through business model innovation and identified risks. We contribute to research and practice

How to Blend Journalistic Expertise with Artificial Intelligence for Research and Verifying News Stories

The use of AI technology can help to automate news verification workflows, while significantly innovating journalism practices. However, most existing systems are designed in isolation without interactive collaboration with journalists. ‘DMINR’ project aims to bring humans-at-the-center of AI loop for developing a powerful tool that is sympathetic to the way journalists work. In this paper, we attempt to understand how AI can shape journalists’ practices and, crucially, be shaped by them; we aim to design human-centred AI tool that works in synergy with journalists’ practices and strike a useful balance between human and machine intelligence. In this paper, we conducted a Co-design workshop to inform the design of the ‘DMINR’ system. Based on the findings, we outline the main challenges for designing AI systems in the context of journalism, that can serve as a resource for Human-AI interaction design

Artificial Intelligence: Too Fragile to Fight?

The article of record may be found at https://www.usni.org/magazines/proceedings/2022/february/artificial-intelligence-too-fragile-fightInformation Warfare Essay Contest - First PrizeArtificial intelligence (Al) has become the technical focal point for advancing naval and Department of Defense (DoD) capabilities. Secretary of the Navy Carlos Del Toro listed AI first among his priorities for innovating U.S. naval forces. Chief of Naval Operations Admiral Michael Gilday listed it as his top priority during his Senate confirmation hearing. This focus is appropriate: ai/ offers many promising breakthroughs in battlefield capability and agility in decision making. Yet, the proposed advances come with substantial risk: automation-including AI- has persistent, critical vulnerabilities that must be thoroughly understood and adequately addressed if defense applications are to remain resilient and effective.Booz Allen Hamilito

The role of inter-organizational collaboration within innovation strategies: towards a portfolio approach.

Within the innovation literature, inter-organizational collaboration is being advanced as instrumental for improving the innovative performance of firms. In addition inter-organizational collaboration can be instrumental for addressing the multiple requirements innovation strategies entail. At the same time - large scale - empirical evidence for such a relation is scarce. Within this paper we examine whether evidence can be found for the idea that inter-organizational collaboration supports the effectiveness of innovation strategies. Multivariate and Tobit analyses of data on Belgian manufacturing firms, collected by means of the CIS survey (n=221), reveals a positive relationship between inter-organizational collaboration and innovative performance. Moreover the findings reported here suggest the relevancy of adopting a portfolio approach towards inter-organizational collaboration.Data; Effectiveness; Firms; Innovation; Innovation strategy; Manufacturing; Performance; Portfolio; Requirements; Strategy; Time;

Establishing a communications-intensive network to resolve artificial intelligence issues within NASA's Space Station Freedom research centers community

MITRE Corporation's, A Review of Space Station Freedom Program Capabilities for the Development and Application of Advanced Automation, cites as a critical issue the following situation, extant at the NASA facilities visited in the course of preparing the review: The major issues noted with regard to design and research facilities deal with cooperative problem solving, technology transfer, and communication between these facilities. While the authors were visiting lab and test beds to collect information, personnel at many of these facilities were interested in any information they could collect on activities at other facilities. A formal means of gathering this information could not be identified by these personnel. While communication between some facilities was taking place or was planned, for technology transfer or coordination of schedules (e.g., for SADP demonstrations), poor communication between these facilities could lead to a lack of technical standards, duplication of effort, poorly defined interfaces, scheduling problems, and increased cost. Formal mechanisms by which effective communication and cooperative problem solving can take place, and information can be disseminated, must be defined. A solution is proposed for the communications aspects of the issues addressed above; and offered at the same time a solution which can prove effective in dealing with some of the problems being encountered with expertise being lost via retirement or defection to the private sector. The proffered recommendations are recognizably cost-effective and tap the rising sector of expert knowledge being produced by the American academic community

Technological Progress and the Distribution of Productivities across Sectors

This paper studies the impact of the process of technological change on the distribution of productivities and profits across sectors. We find that if technological progress affects high-tech and traditional sectors differently, the impact of changes in the determinants of economic growth may differ depending on which is the actual change. When an economy is growing faster due to an increase in the productivity of research or to a reduction of the taxes on capital accumulation, inequality will decrease. However, if faster growth is due to the presence of tax incentives to high technology sectors or to structural changes that allow a better absorption of externalities, inequality will increase.

Voluntary agreements and community development as CSR in innovation strategies

The present paper examines how an innovating firm decides between two forms of voluntary agreements (VA) in a context, where a non-governmental organization (NGO) rather than a regulator watches over citizens' interests. The innovation generates profit and consumer surplus as well as environmental damage. Corporate social responsibility (CSR) within the innovation process is considered in terms of a redistribution of profit towards community development, with or without additional abatement efforts via a VA. Bargaining between firm and NGO yields the amount allocated to community development. The model demonstrates that the firm's choice of VA hinges on the tradeoffs between appropriating the full innovation profit and paying a higher lump sum towards community development or sacrificing some of the innovation profit by lowering innovation effort, but gaining in terms of paying a lesser amount towards community development. CSR with abatement is unlikely in the case of radical innovations. There is also a clear divergence of interests between the firm, the NGO and the State for some parameter configurations, which are duly identified.Corporate social responsibility, voluntary agreements, community development, donations, innovation

Financial Innovation and Endogenous Growth

We model technological and financial innovation as reflecting the decisions of profit maximizing agents and explore the implications for economic growth. We start with a Schumpeterian endogenous growth model where entrepreneurs earn monopoly profits by inventing better goods and financiers arise to screen entrepeneurs. A novel feature of the model is that financiers also engage in the costly, risky, and potentially profitable process of innovation: Financiers can invent more effective processes for screening entrepreneurs. Every existing screening process, however, becomes less effective as technology advances. Consequently, technological innovation and, thus, economic growth stop unless financiers continually innovate. Historical observations and empirical evidence are more consistent with this dynamic model of financial innovation and endogenous growth than with existing models of financial development and growth.Invention, Economic Growth, Corporate Finance, Financial Institutions, Technological Change, Entrepreneurship.