FRIEDRICH-EBERT-STIFTUNG – Artificial Intelligence and Auto­mation in Retail based ›events‹ in which consumers participate as spectators and shop simultaneously. Product visualisation applications can potentially help consumers make more confident choices and help reduce the number of returns, both for online and in-store purchases – assuming the technology functions accurately and is true to reality. Consumers are offered very substantial convenience by such augmented reality technolo­gies, avoiding both trips to stores and the bother of returning goods which do not look or fit as anticipated, although as with predictive marketing and other aspects of e-commerce this may also increase the risk of overconsumption. This is particularly useful for the sale of large goods like home fur­nishings which are expensive and difficult to return. Similarly, in-store AR-based content can be used as a marketing tool and can improve the customer experience. Both of which can have knock-on benefits for worker job security through increased sales, reduced costs and increased profitability. In addition, fraud and counterfeit detection can reduce losses for retailers. While these types of technology were seen as less contro­versial by focus group participants than some of the other applications discussed above, some concerns were men­tioned. First, while product visualisation can be developed for in-store or online use such systems arguably have more potential benefit for online retail as imaging software allows customers to ›try‹ clothes digitally online, enhancing the reach of e-commerce and enabling it to replicate some of the features of in-store retail. Furthermore, the cost of such systems and technical knowhow needed to develop them could price smaller retailers out of such developments in the short term. In addition, product visualisation systems could potentially reduce employee-customer interactions and the opportunities for staff to deploy customer service and sales skills, tasks which until now have been the reserve of human workers. Second, as with some of the applications discussed previously in this section, all of the applications in this section make use of cameras and generate video data, raising ethical questions about privacy and use of data. 12