Artificial intelligence and big data in entrepreneurship: a new era has begun
By M. Obschonka, David B. Audretsch. Small Business Economics, 2019
366 citations recorded by the source corpus.
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.
Subfields: Accounting, Management Information Systems, Management of Technology and Innovation
View Paper: https://www.semanticscholar.org/paper/6f8079bd861fba170331b748262dd06d56826213
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Citations in the corpus
- Artificial Intelligence and Entrepreneurship: Implications for Venture Creation in the Fourth Industrial Revolution (2020, methodology): “…negative consequences of new technological affordances such as AI, specifically by analyzing the implications of what we consider surprisingly hands-off governance approaches that operate largely on “blind trust” ( Obschonka & Audretsch, 2019 ) that an algorithm is functioning appropriately.”
- Emerging Technology and Business Model Innovation: The Case of Artificial Intelligence (2019, neutral): “contradiction between rule-driven AI rationality and innovation uncertainty [54] should not be ignored in future study.”