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E-Discovery

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Ingezonden reactie op de (on)mogelijkheden van een Executive Information System.

Enterprise 2.0.

In the last decade, organizations have re-engineered their business processes and started using standard software solutions. Integration of structured data in relational databases has improved documentation of business transactions and increased data quality. But almost 90% of the information cannot be integrated in relational data bases. This amount of ‘unstructured’ information is exploding within the Enterprise 2.0. The use of social media tools to enhance collaboration, creates corporate blogs, wikis, forums, and other types of unstructured information. Structured and unstructured information are records, meant and used as evidence for policies, decisions, products, actions and transactions. Most stakeholders are making increasing demands for the trustworthiness of records for accountability reasons. In this age of evolving social media use, organizational chains, inter-organizational data warehouses and cloud computing, it is crucial for the Enterprise 2.0. that its policies, decisions, products, actions and transactions can be reliably reconstructed in context. Digital Archiving is a necessity for the Enterprise 2.0.: the reconstruction of the past depends on records and their meta data. Blogs, wikis, forums, etc., used for collaboration within the business processes of the organization, need to be documented for reconstruction in the future. Digital Archiving is a combination of three mechanisms: enterprise records management, organizational memory and records auditing. These mechanisms ensure that a digitized organization as the Enterprise 2.0. has a documented understanding of its past. In that way, it improves organizational accountability.

Leveraging data protection law for protecting workers’ fundamental right to health and safety in the workplace

The American company Amazon has made headlines several times for monitoring its workers in warehouses across Europe and beyond.1 What is new is that a national data protection authority has recently issued a substantial fine of €32 million to the e-commerce giant for breaching several provisions of the General Data Protection Regulation (gdpr) with its surveillance practices. On 27 December 2023, the Commission nationale de l’informatique et des libertés (cnil)—the French Data Protection Authority—determined that Amazon France Logistique infringed on, among others, Articles 6(1)(f) (principle of lawfulness) and 5(1)(c) (data minimization) gdpr by processing some of workers’ data collected by handheld scanner in the distribution centers of Lauwin-Planque and Montélimar.2 Scanners enable employees to perform direct tasks such as picking and scanning items while continuously collecting data on quality of work, productivity, and periods of inactivity.3 According to the company, this data processing is necessary for various purposes, including quality and safety in warehouse management, employee coaching and performance evaluation, and work planning.4 The cnil’s decision centers on data protection law, but its implications reach far beyond into workers’ fundamental right to health and safety at work. As noted in legal literature and policy documents, digital surveillance practices can have a significant impact on workers’ mental health and overall well-being.5 This commentary examines the cnil’s decision through the lens of European occupational health and safety (EU ohs). Its scope is limited to how the French authority has interpreted the data protection principle of lawfulness taking into account the impact of some of Amazon’s monitoring practices on workers’ fundamental right to health and safety.

Employers have a Duty of Beneficence to Design for Meaningful Work

Artificial intelligence-driven technology increasingly shapes work practices and, accordingly, employees’ opportunities for meaningful work (MW). In our paper, we identify five dimensions of MW: pursuing a purpose, social relationships, exercising skills and self-development, autonomy, self-esteem and recognition. Because MW is an important good, lacking opportunities for MW is a serious disadvantage. Therefore, we need to know to what extent employers have a duty to provide this good to their employees. We hold that employers have a duty of beneficence to design for opportunities for MW when implementing AI-technology in the workplace. We argue that this duty of beneficence is supported by the three major ethical theories, namely, Kantian ethics, consequentialism, and virtue ethics. We defend this duty against two objections, including the view that it is incompatible with the shareholder theory of the firm. We then employ the five dimensions of MW as our analytical lens to investigate how AI-based technological innovation in logistic warehouses has an impact, both positively and negatively, on MW, and illustrate that design for MW is feasible. We further support this practical feasibility with the help of insights from organizational psychology. We end by discussing how AI-based technology has an impact both on meaningful work (often seen as an aspirational goal) and decent work (generally seen as a matter of justice). Accordingly, ethical reflection on meaningful and decent work should become more integrated to do justice to how AI-technology inevitably shapes both simultaneously.

The role of robotization in work design

Robots are increasingly used in a variety of work environments, but surprisingly little attention has been paid to how robots change work. In this comparative case study, we explore how robotization changed the work design of order pickers and order packers in eight logistic warehouses. We found that all warehouses robotized tasks based on technological functionality to increase efficiency, which sometimes created jobs consisting of ‘left-over tasks’. Only two warehouses used a bottom-up approach, where employees were involved in the implementation and quality of work was considered important. Although the other warehouses did not, sometimes their work design still benefitted from robotization. The positive effects we identified are reduced physical and cognitive demands and opportunities for upskilling. Warehouses that lack attention to the quality of work may risk ending up with the negative effects for employees, such as simplification and intensification of work, and reduced autonomy. We propose that understanding the consequences of robots on work design supports HR professionals to help managing this transition by both giving relevant input on a strategic level about the importance of work design and advocating for employees and their involvement.