Barriers to AI Adoption in Indian Agriculture: An Initial Inquiry

Barriers to AI Adoption in Indian Agriculture: An Initial Inquiry

Asaf Tzachor
Copyright: © 2021 |Pages: 15
DOI: 10.4018/IJIDE.2021070103
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Greater adoption of artificial intelligence (AI) in Indian agriculture can contribute to regional and global food security. An examination of parameters that may prevent and postpone AI transfer, diffusion, and adoption is essential. However, little research on AI adoption barriers in Indian agriculture has been conducted. This paper attends to the gap. In order to recognize, categorize, and prioritize the most critical impediments to AI adoption in Indian agriculture, this paper draws on a participatory research design in which workshops were used as the main research methodology. Seven working groups of local experts identified five categories of constraints, covering 18 explicit adoption barriers. Two constraints in particular were recognized as most critical: lack of trust in technology among farmers and a language barrier compounded by high illiteracy rates and a digital divide. With an initial catalog of constraints, this paper aims to contribute to the actualization of AI in Indian agriculture and thereby to local and global food security.
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1. Introduction

Digitization, a process of representing information in discrete data units readable by machines, in combination with other machines that are able to store and transmit data, such as microprocessors and wireless communication technologies, gave rise to a global digital economy.

In this new economy, a convergence between computer technologies and communications technologies accelerates the creation, manipulation and dissemination of information, brings about changes in the structure and functioning of markets, transforms traditional production processes, improves productivity, and underpins new digital services (Brynjolfsson and Kahin, 2002:14; Ayres and Williams, 2004; Malecki and Moriset, 2007).

Several scholars have argued that the digital economy yields social dividends as well as economic. Enhanced connectivity among organizations increases the number of potential innovations in products, processes, and social institutions (Carlsson, 2004). “When connections change, so too does the structure of the system. When structure changes, the dynamic properties of the system change also. This changes the conditions under which connections exist; new ones may form, existing ones may […] become strengthened […] In essence, the defining characteristic of the modern economy is extremely rapid technological, organizational and institutional change, all embedded within broader patterns of social change” (Potts, 2000:2-4). These transitions are assumed to benefit society writ large, through innovations allowing greater access to healthcare services, education, finance and financial services, and the workforce, thereby reducing poverty, gender inequality and illness (Tapscott, 1996; Smith et al., 1999; Marker et al., 2002; Cecchini and Scott, 2003; Slater and Tacchi, 2004; Peitz and Waldfogel, 2012; Haluza and Jungwirth, 2015).

Indeed, evidences suggest that where computer technologies and communications technologies are actualized, social progress, welfare benefits and economic growth can be attained (Tapscott, 1996; Baily and Lawrence, 2001; Brynjolfsson and Kahin, 2002; Pilat, 2003; Sharma, 2005; Atkinson and McKay, 2007; Diewert et al., 2018). For example, a comprehensive literature review of empirical studies conducted by the Organization for Economic Co-operation and Development concluded that the productivity effect of computer and communication technologies is positive, significant and increasing overtime (Kretschmer, 2012).

However, the gains associated with the digital economy have not been experienced equally everywhere. Structural and institutional barriers to the utilization of computer and communications technologies have limited the expansion of the digital economy in many regions. As previously observed, a limited digital economy has detrimental implications for social development (e.g. Singh, 2010).

Since the emergence of the digital economy, impediments to the diffusion and adoption of computer and communications technologies has been a widely-explored area (e.g. Brotchie et al., 1991; Grimes, 1992; Ilbery et al., 1995; Berkeley et al., 1996; McMahon and Salant, 1999; Parker, 2000; Gillespie et al., 2001; Gibbs, 2001; Grimes, 2003; Chakpitak, 2018).

The main motivation underpinning these studies was to examine parameters that prevent the spread of the digital economy, in order to assist societies to remove these barriers and realize the full benefits of digital innovations. This motivation has anything but subsided.

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