This is vital. The first step for unions to start protecting workers’ data is to develop model clauses, based on the
10 Principles outlined by Uniglobal, to ensure workers, delegates and union representatives have access to and influence over the data collected about them.
All of these lifecycle stages have potential for collective bargaining claims. And the truth is that workers can only truly negotiate collectively in the face of data collection on individuals by corporations.
However, when it comes to worker data (and also their data as individuals, patients citizens and consumers), an enterprise by enterprise approach is not sufficient.
Many of the tech companies that provide data services to employers are massive, venture-capital funded multinational corporations (like Cisco, Microsoft, etc).
The employer may use the database provided by Cisco to manage its HR or workers data, but have almost no control over what Cisco does with it. Employers may just pump workers data into a massive “data warehouse” provided by Amazon or Google, with no consideration to the data policies of that tech provider.
Similarly, some employers are part of “group entities” (or franchises), where the company at the top of the foodchain is not the employer but nonetheless accesses and controls data created by its subordinate entities. The entity exercising that data control may not be the workers’ employer, and so an enterprise bargaining approach will/may not cover the top group entity.
The urgent next step: Workers Data Trusts
Conceptually, imagine that workers’ data is like superannuation. Unions can create a data trust – as a legal entity with trustees – and then negotiate with groups of employers on behalf of members and workers to gain control over the data of the beneficiaries of the trust (the workers).
Why do this?
Firstly, workers need to gain collective control over their own data.
Only unions understand this, and only unions are in a position to organise workers collectively to reassert workers’ control over their data.
The only way to balance the economic and social power of employers and tech giants is through collective institutions organised by unions.
Secondly, this is a familiar and effective model for unions and workers. The closest similar example is superannuation trusts managing money for members – there are also older models like Credit Unions – which are focused on creating a “collective system of rights and accountability, with legal standards upheld by a new class of representatives who act as fiduciaries for their members.” (
Link)
From a technological point of view, it is easy for a data trust to hold copies of the data created about or collected from their members. A data trust can then negotiate with employers and corporations on how the trust members’ data is used, analysed and accessed – and can alert members to how corporations use the data.
How the Trusts would work in practice
How would a Workers Data Trust work in practice? Well, there are lots of other kinds of data trusts already operating that give us an indication (most of them private, corporate trusts, but some are non-profit trusts – for example, Facebook has created a private non-charitable trust to manage some of the data it creates and stores, and as another example, many medical and scientific institutions create data trusts to store and govern data).
Here’s one way that a Workers Data Trust could operate.
A union (or group of unions) create a Workers Data Trust, where the union’s members would also be beneficiaries and members of the trust. The unions would then negotiate a legal agreement, deed or similar with an employer about the ownership of workers’ data. As part of the agreement, the employer would agree to vest ownership and control of its employees data with the trust. The Workers Data Trust would then set the terms, rules and conditions of the employer’s use of that data.
The data collected could include the workers’ personal and health information, HR information, time and motion data, geo-location data, shift and scheduling data, personal payroll data and biometric data (such as facial recognition).
The Trust’s conditions on data use by an employer could include: access to the data by the worker and their union representatives, restrictions on monetisation or sale of the data, limitations and rules in the use of business analytics, and the physical location of data storage.
Workers Data Trusts could also do what existing medical data trusts do, which is charge usage fees for access to data (the employer would pay the fee). This would enable the Trust to have the resources required to properly and securely manage the data.
When the worker moves to a new employer, the union and Trust would negotiate with the new employer. If there were multiple “industry” Workers Data Trusts, the worker could also shift their data from one Trust to another.
Conclusion
Workers data (as workers, and in other realms of their live) is being commodified and used to control them.
In the near future, the companies that invest in surveillance capitalism will be in an unassailably powerful position to control workers’ lives.
By establishing Workers Data Trusts now, unions can take a proactive step towards shaping data laws that will enable those trusts to have legal powers to represent members and ensure that control over data is held by workers, not corporations.
Just as unions led the creation of superannuation funds to act as long-term (and ultimately powerful) trustees for workers’ retirement savings, Workers Data Trusts will do the same for workers’ data.
Industry superannuation funds in Australia are some of the most powerful financial institutions. The foresight of the union leaders that created industry super funds in the 1980s and 90s led to the establishment of funds that have the potential to influence the corporate behaviour of even massive companies like AMP, Qantas or Wesfarmers.
Workers Data Trusts have the potential to exercise this kind of decisive influence and power – especially as creation, collection, use and analysis of data becomes more valuable.