The data is from qualitative case study research into the implementation of the Rapid Recruitment project at Walmart, US, in 2020. One of the key elements of the rapid recruitment project was the use of a machine learning algorithm in the hiring system for hourly paid store-level associates (employees). The research involved semi-structured interviews with fourteen respondents with different roles and responsibilities in relation to the hiring process including: seven head office staff responsible for developing and implementing the system, five store-level managers and HR staff who used the system and two recently recruited employees. Interviews lasted 30 to 90 minutes and were conducted via video conferencing during the Covid-19 pandemic from September to December 2020. Interviews were supplemented with bi-weekly meetings with a business sponsor at the organisation and follow-up information gathered by email. Interviews were recorded and transcribed by the researchers. The interviews explored: recent changes to the hiring system, aims and objectives of the changes, the of motivations behind the changes, the development and implementation process, user adoption and perceptions of the new system and its effectiveness. The research found that the Rapid Recruitment project had largely been successful. Most users were using the new system as intended, the system had sped up the hiring process, enabled the organisation to hire greater numbers of staff during the increased demand due to the pandemic and the organisation reported that it had improved hiring outcomes (90-day turnover rates). However, not all users were confident in the new system or trusted the technology used, which in some cases meant that they were not using the system in the way intended, potentially undermining some of the objectives of the changes. Interview data could not be deposited to the archive because it was protected by a non-disclosure agreement (NDA) but research documents and metadata is deposited.The Digital Futures at Work Research Centre (Dig.IT) will establish itself as an essential resource for those wanting to understand how new digital technologies are profoundly reshaping the world of work. Digitalisation is a topical feature of contemporary debate. For evangelists, technology offers new opportunities for those seeking work and increased flexibility and autonomy for those in work. More pessimistic visions, in contrast, see a future where jobs are either destroyed by robots or degraded through increasingly precarious contracts and computerised monitoring. Take Uber as an example: the company claims it is creating opportunities for self-employed entrepreneurs; while workers' groups increasingly challenge such claims through legal means to improve their rights at work. While such positive and pessimistic scenarios abound of an increasingly fragmented, digitalised and flexible transformation of work across the globe, theoretical understanding of contemporary developments remains underdeveloped and systematic empirical analyses are lacking. We know, for example, that employers and governments are struggling to cope with and understand the pace and consequences of digital change, while individuals face new uncertainties over how to become and stay 'connected' in turbulent labour markets. Yet, we have no real understanding of what it means to be a 'connected worker' in an increasing 'connected' economy. Drawing resources from different academic fields of study, Dig.IT will provide an empirically innovative and international broad body of knowledge that will offer authoritative insights into the impact of digitalisation on the future of work. The Dig.IT centre will be jointly led by the Universities of Sussex and Leeds, supported by leading experts from Aberdeen, Cambridge, Manchester and Monash Universities. Its core research programme will cover four broad-ranging research themes. Theme one will set the conceptual and quantitative base for the centre's activities. Theme two involves a large-scale survey of Employers' Digital Practices at Work. Theme three involves qualitative research on employers' and employees' experiences of digitalisation at work across 4 sectors (Creative industries, Business Services, Consumer Services, Public Services). Theme 4 examines how the disconnected attempt to reconnect, through Public Employment Services, the growth of new types of self-employment, platform work and workers' responses to building new forms of voice and representation in an international context. Specific projects include: 1. The Impact of Digitalisation on Work and Employment -Conceptualising digital futures, historically, regionally and internationally -Comparative regulation of digital employment - Mapping regional and international trends of digital technology and work 2. Employers' Digital Practices at Work Survey 3. Employers' and employees' experiences of digital work across sectors -Changing management processes and practices -Workers' experiences of digital transformation 4. Reconnecting the disconnected: new channels of voice and representation - displaced workers, job search and the public employment service - self-employment, interest representation and voice Dig.IT will establish a Data Observatory on digital futures at work to promote our findings through an interactive website, report on a series of methodological seminars and new experimental methods and deliver extensive outreach activities. It will act as a one-platform library of resources at the forefront of research on digital work and will establish itself as a focal point for decision-makers across the policy spectrum, connecting with industrial strategy, employment and welfare policy. It will also manage an Innovation Fund designed to fund novel research ideas, from across the academic community as they emerge over the life course of the centre.

The research involved semi-structured interviews with fourteen respondents with different roles and responsibilities in relation to the hiring process including: seven head office staff responsible for developing and implementing the system, five store-level managers and HR staff who used the system and two recently recruited employees. Respondents were purposively sampled with the help of a business sponsor assigned by the organisation. Respondents were chosen because they were either key personnel in the development and implementation of the new hirings system, or because they were users of the system in stores from a broad range of markets (rural/urban, geographical range).