Data obstacles and privacy concerns in artificial intelligence initiatives
Aslam, B., Karjaluoto, H., & Varmavuo, E. (2022). Data obstacles and privacy concerns in artificial intelligence initiatives. In O. Niininen (Ed.), Contemporary Issues in Digital Marketing (pp. 130-138). Routledge. https://doi.org/10.4324/9781003093909-16
Toimittajat
Päivämäärä
2022Oppiaine
Basic or discovery scholarshipDigitaalinen liiketoiminta ja talous (painoala)Digital marketing and CommunicationMarkkinointiHyvinvoinnin tutkimuksen yhteisöTyön ja johtamisen muuttuminen digitaalisessa ajassaBasic or discovery scholarshipDigital Business and Economy (focus area)Digital marketing and CommunicationMarketingSchool of WellbeingEmergent work in the digital eraTekijänoikeudet
© Authors, 2022
To become and remain competitive, many companies (especially large ones) are considering capitalising on data-based technologies, such as Artificial Intelligence (AI). However, whether these companies are structurally ready in terms of data collection and management remains unknown. This chapter discusses how privacy issues and reforms, such as the General Data and Protection Regulation (GDPR), affect companies’ AI initiatives and processes. For this purpose, we reviewed the relevant literature and collected empirical data using in-depth interviews with AI and data industry experts in five countries. Our main findings indicated that companies are lacking sound data collection and management practices. We also found that privacy should be at the centre of policies when implementing any data initiatives. Initiatives, such as the GDPR, are helping industries safeguard consumer privacy without causing problems for AI initiatives. Our study will bring clarity to business managers who want to capitalise on data-based AI technology and detail existing academic knowledge streams.
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Julkaisija
RoutledgeEmojulkaisun ISBN
978-0-367-55533-7Kuuluu julkaisuun
Contemporary Issues in Digital MarketingAsiasanat
Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/101686903
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