The rapid development of algorithms as a technological tool has created new opportunities for automating work processes and management functions, enabling workers to be managed remotely, writes Laura Bradshaw PhD, research lead for emerging technologies at IOSH.
Algorithms are machine-learning tools which underpin contemporary artificial intelligence (AI) systems. Organisations use them to help work processes, gather data, and track activity. Examples include using social media algorithms to track engagement and offering user-prescribed content based on relevance. However, there are also algorithms used in the physical world, such as in sensors in manufacturing companies, that motion capture and detect movement. In recent times for many of us, a large part of our working lives has been online, and algorithms have become normalised and tolerated by workers as part of the behaviour-tracking practice.
Psycho-Social Issues and Algorithmic Tracking
There is a general understanding in our daily lives that technology tracking tools can make life easier, and algorithmic tracking has become part of our working and non-working lives. Examples include restaurant suggestions, road traffic directions, and Netflix recommendations, which all use algorithmic tracking to offer personalised suggestions. However, digitalisation algorithms have developed at speed with the digital revolution now in full swing and with rapid changes in emerging technologies. Whereas previously, we used algorithms to monitor webpage clicks, visits and time spent on different content, which offered data insights for managers to decipher. More recently, a dark side of artificial intelligence has developed through the algorithmic management of people.
Algorithmic management can occur through keystroke tracking, webcam monitoring, sensor detection for activity time monitoring, sensory gloves, and wearables. All these algorithmic tracking tools can become intrusive workplace monitoring tools and change the power dynamics within the organisation. Algorithmic management can be used in HR to filter job applicants, in factories to fire inadequately fast warehouse workers. Practices such as this can cause algorithm aversion and cognitive complacency (Jarrahi t al, 2021). Furthermore, the negative implications associated with algorithmic tracking are the exacerbation of psychosocial issues, such as anxiety, depression, presenteeism and fear of not being constantly available. There are physical implications too; natural fight or flight responses are engineered in humans for moments of threat, we are not meant to be on state of alert for the duration of each working week. The rise in cortisol levels over time by tools that trigger psychosocial issues through intrusive workplace monitoring can also have negative physical impacts on blood pressure and stress levels.
While legislation is beginning to creep into place, organisations need to take responsibility for the wellbeing of their employees both mentally and physically
Algorithmic management is now evidenced in research to be a key psychosocial stressor in the workplace. Many companies use such tools under the umbrella of data gathering; the concern is what data is being collected unbeknown to the employees. Organisationally algorithmic tracking and the collection of big data can have broader repercussions, such as eroding organisational trust and culture through micro-management of employees. An anti-trust culture is a recipe for disaster for organisations of any size. Therefore, implementing and using these algorithms needs to be tightly regulated with safeguards to protect workers from micromanagement and workplace surveillance and monitoring. While legislation is beginning to creep into place, organisations need to take responsibility for the wellbeing of their employees both mentally and physically.
Work management platforms that monitor work tasks (including platform mediated gig work) may be helpful in a business planning sense but could also filter poor workers, separate those who are slower at tasks or those who submit work close to the deadline. These tracking performance indicators can cause stress and anxiety and could be used later in work disputes to build a picture of dissatisfaction of an employee the organisation would like to be rid of or block promotion. Furthermore, sensors that provide feedback data on factory floors can detect the time spent in the restrooms or how long people are idle from daily tasks.
Employees have the right to a healthy mind and body and although digital tools may be seen as an effective way of managing workers, it poses the question; Are algorithmic management tools the dark side of AI? Either way, this is an underworld where legislation is catching up fast, to shine a light on dubious practices and empower workers to more privacy and the right to disconnect.
Jarrahi, M. H., Newlands, G., Lee, M. K., Wolf, C. T., Kinder, E., & Sutherland, W. (2021). Algorithmic management in a work context. Big Data & Society, 8(2).
Laura Bradshaw PhD is research lead for emerging technologies at IOSH