This report is a facilitator’s guide to teaching forward. It is designed to support people interested in delivering trainings about the digitalisation of public services and work.

Each chapter in this report corresponds to one workshop. There are 6 workshops in total. We recommend that you organise 90-120 minute meetings or workshops with your members or colleagues. It is advisable to go through just one chapter per meeting.  

The chapters each contain useful information for you as a facilitator. They each end with a section called “Facilitator Material” which includes a facilitator’s guide with tips for holding the workshop as well as possible responses to the group work, links to PowerPoint slides, exercises for your participants, and for chapters 2-6 on tools and guides a video describing each tool.  

In addition to the first chapter, which is all about the foundational knowledge we need to have to negotiate on the digitalisation of work, each subsequent chapter is devoted to one of the tools or guides we have developed in PSI's Our Digital Future project.  

You can navigate through the different chapters using the Table of Contents.

For background information check out the Our Digital Future website, scroll down to Project Materials, choose your region, and read some of the Training Materials provided there.  

How to use this guide 

As the facilitator, you can use the text in the chapters as speaking notes, or you can copy some or all of it as reading material prior to the meeting/workshop. Use the provided slide decks as are or copy those you want to use. You can beneficially share the slide decks with participants before each workshop.  

In workshops 2-6, it is recommendable to ask the participants to open the tool and go through it with them. Lastly, you can share this guide with the participants who have been at all, or most, of the workshops. In this way they can teach forward too!  

While this report is intended to be broadly accessible, we recommend that the facilitator has a sound knowledge of the risks and opportunities associated with the digitalisation work and workers. This doesn’t mean, however, that you should know the answer to every question that participants may have. If you get stuck and can’t answer a question, tell the participants you will get back to them. Ask your PSI regional coordinator for help!

Workshop 1: The Fundamentals  

What we need to know about data and algorithms 

Before your union or members can begin to conduct collective bargaining or policy advocacy on the digitalisation of public services and work, they need to have a basic understanding of the core features of digitalisation: data and algorithms. In this chapter we will provide you with text and material to conduct a workshop or meeting on these foundational aspects of digitalisation.  

Data 

Data is any information that can be collected and stored. It can be numbers, text, images, or any other type of information. Data can be used to make decisions, solve problems, and understand the world around us. 

Data is being extracted from our actions and non-actions at a never-ending rate. Just think of your smartphone. It is a powerful computer that currently has 14 sensors in it. Apps can turn these sensors on, so they get access to, for example, your location, movement speed, your microphone, or camera. Mobile phones are powerful and handy, but they are also a surveillance apparatus like nothing else. They know where you are. But also, where you are not. They know whether you exercise, how often, doing what? Apps are gathering data, making statistical inferences (profiles) on you, and using all of that for advertising, but also ultimately for manipulation. The world that is offered to you, the advertisements you see, are algorithmically determined.  

Add to that all the information you are sending out there when you use your credit card for what, or what you don’t use it for. When you write something on social media, when you “like” a friend’s post and don’t like another, use government or private e-services of any kind, when you use your loyalty card to the shop or simply browse the internet.  

You are giving away data (information) that is used to profile and predict what type of consumer you are, what you most likely will vote, what type of worker you are, indeed who you are. These systems are obscure, hidden under the hood, surveilling you and predicting what you will do, should do, or what should be available to you and what shouldn’t.  

Think of all that data (picture it as a constant information flow you are knowingly or unknowingly giving away about yourself), and ask what influence it can, or might have, on your work and career? Maybe some of you have a social media profile. Now, data miners know your gender, age, what you do and don’t do, and also what skills/education/work experience you have. It is not difficult to put a profile together on the type of worker you are: investable or less so? 

It’s Not Just About You 

"I've done nothing wrong, so who cares if they take my data?"

If you can hear yourself say this, you are not alone. The thing is: this is not just about you. Your data says a lot about you, yes. But it can have a huge impact on the work and life opportunities of people similar to you, or the absolute opposite. This is due to so-called “inferences” and the role they play in predictive analysis.  

Statistics is the science of learning from experience, particularly experience that arrives a little bit at a time. Predictive analysis takes all the experiences extracted on your actions and non-actions, combines them with folks like you, or very different from you and churns them through powerful computational systems. The result is estimations on what you, and others like you or dissimilar to you, are likely to do in any given situation. Will your political affiliation change if you constantly are fed certain pieces of news – also fake news? Will your speed of work drop if you are working next to someone of this or that age, gender, or ethnicity? Will you buy organic food if you are shown certain advertisements? Research has shown that even when employers try to reach all audiences with a potential job advertisement, the audience is mediated by, for example, Facebook's algorithm. It is oftentimes that algorithm, rather than the employer’s, that decides whether you are a likely candidate, and should see the job announcement or not. 

Data at Work - Data is Power 

The data that is being extracted is essentially information about our private actions. It’s our data. Even in workplaces, the surveillance and monitoring of you as a worker that essentially creates data about you and what you do (and don’t do) is information about you. That the employer knows whether you are talking to a colleague, or are going to the bathroom 5 times, or spending time by browsing the internet or taking a break, and how they then use this data, is a question of power.  

The employer and the systems they use are creating numerous “facts” about you and your colleagues that can have a real-life influence on your work life, employment continuity and career opportunities. Did they ever ask you for permission? Did they even inform you about these systems? Do you know what data is being extracted and for what purposes? Does the employer sell datasets to the many data brokers out there? If they do, have they told you that information derived from your actions and non-actions is an additional income stream? Where does all of this leave your privacy rights? In Addendum 1: Data Rights – Additional Information we show how management typically extracts data from you.  

A result of this surveillance society and labour market is the unequal distribution of power. If we as workers do not know what data is extracted, for what purposes, where it is stored, who has access to it, and whether it gets sold on, we are essentially disempowered. If we additionally have few, if any, rights to edit or block the data and the inferences derived from them, we are essentially being objectified. Turned into mathematical equations that either deem us to be productive, or effective or not so.  

The thing is, whatever the “result” be it horribly wrong, or worthy of an explanation, can have very harsh, very real impacts on our work life, job and careers. This objectification, or as some call it, quantification of workers, is turning labour – both the individual worker as well as us all as a collective sum of the parts – into a commodity. 

Data can be collected from a variety of sources, including sensors, surveys, and social media. Once data is collected, it needs to be processed and analysed. This is where algorithms come in. 

Algorithms 

Algorithms are the sets of instructions that tell computers what to do with this data. They are used to process data, make decisions, and solve problems. Algorithms are used in a wide variety of applications, including computer programs, websites, and mobile apps. 

There are many different types of algorithms, each with its own purpose. Some common types of algorithms include sorting algorithms, search algorithms, and machine learning algorithms. 

"A set of rules in computer programming code, for solving a problem or performing a task"
Definition of an Algorithm

Think of an algorithm as a recipe. The algorithm is tasked to make the best tomato soup. It is instructed to cut 200 grams of onions, fry them off, add the garlic, then use 2 cans of tinned tomatoes. The result of the algorithm will be very different if you change the order of the instructions, for example if you fried the tomatoes and not the onions. If your ingredients are rotten you will still make a soup, but it will taste awful. This is what we call “garbage in, garbage out”. So if the data used is not representative of your culture, or is biased or incomplete, the outcome will be equally bad.

What counts here is:

• 1. The purpose of the system,

• 2. The data and the quality of the data,

• 3. the instructions

• 4. the order of those instructions.  

For you union reps, this can translate into a series of issues they should raise with management to hold them responsible and liable to the systems and tools they are deploying and the affects these can have on workers and members of the public.  

Example of an algorithmic system at work 

For example, let’s imagine an automated scheduling system for homecare workers.  

• Its purpose is to increase client numbers per worker 

• Its secondary purpose is to improve client satisfaction. 

• It extracts historical data from all the previous routes workers have taken relative to client locations and client satisfaction rates  

• In this order it has been instructed to match route optimization with client “preferences”  

This scheduling system could have several highly negative impacts on workers. Work will become more stressful as the number of clients per worker increases and/or the time allocated to each client decreases. Client “preferences” can lead to biases against less represented groups of homecare workers. In addition, workers who do not “match” client preferences might receive the least favourable working times as well as an increase in the percentage of more poorly clients (as they are assumed to be so poorly their satisfaction rate is less significant). Discrimination abounds! Unions must act! 

Facilitator Material 

Use the above text as speech notes for the introduction of the foundations of digital technologies. Recall that with this knowledge, your colleagues and members will be in a position to better understand where to set in to ensure that digital technologies do not harm workers. 

In addition, you can use these resources: 

1. Slide deck – this also includes an introduction to the digitalisation of public services. We have added some speech notes too!

2. Slides - design an algorithm exercise 

3. Design an algorithm - facilitator’s guide

Workshop 2: The Data Lifecycle at Work 

AN INTUITIVE TOOL TO SUPPORT POLICY or COLLECTIVE BARGAINING DEMANDS 

This is the first of two guides specifically related to data. The data lifecycle at work is all about the gathering, use, access and offboarding of data in the workplace. It is a helpful tool for workers as they begin to map what data is collected, from where and for what purpose(s). 

Download the Data Lifecycle at Work Guide

Negotiating the Data Lifecycle for Workers’ Collective Data Rights 

Workers’ data rights are in most data protection regulations across the world poorly protected. To bridge these legal gaps, unions could beneficially negotiate for workers’ collective data rights.  From the process of collecting data and the codetermination over the sources of these data, to how these data are analysed, for what purposes, and what the workers’ rights are to know about these inferences and edit them, to knowing under which jurisdiction the data is stored, which third parties have access to the data, to finally having a say over what happens to the data. Is it sold? To whom?  

Data Collection  

The data-collection phase covers internal and external collection tools, the sources of the data, whether shop stewards and workers have been informed about the intended tools and whether they have the right to rebut or reject them. Much data extraction is hidden from the worker (or citizen) and management must be held accountable. Negotiate here for clear agreements on the right to know what digital tools are being used, what data they are trained on and the sources of the data it extracts. 

Data Analysis 

In the data-analysis phase, unions must negotiate for rights regarding the inferences (the profiles, the statistical probabilities) drawn from the data. Such inferences can be used to determine schedules, wages (if linked to performance metrics) or, in human resources, whom to hire, promote or fire. They can be used to predict behaviour based on historic patterns, emotional and/or activity data.  

Access to the inferences is key to the empowerment of workers and indeed to human rights. Workers should have greater insight into, and access to, these inferences and rights to rectify, block or even delete them. Without these rights, there will be few checks and balances on management’s use of algorithmic systems or on data-generated discrimination and bias. 

Combined with the data collection phase, unions could here beneficially negotiate around the purposes of data collection and analysis. This includes determining the redlines for what the data collected can be used for, and what it can’t. 

Example: a union from the US has negotiated that location data from drivers collected to ensure their safety cannot be used in performance evaluations of said workers.  

Data Storage and Access 

The data-storage and access phase is important. It relates to the jurisdiction under which data is stored, but also to whether third parties have access to the workers’ data. Imagine here a public service that has outsourced the payroll to a private company. Here workers should negotiate what rights this third party has to (a) repurpose the data, and (b) sell it or combine it with other datasets and then sell it.  

The question of the jurisdiction under which the data is stored is important to determine the rights of workers over their data. Ask management! 

Data Offboarding 

Unions must also be vigilant in how employers remove employee data from their systems. This 'data offboarding' can include the sharing of data or the deletion of data. Unions should negotiate much better rights to know what is being off-boarded and to whom, with scope to object to or even block the process. Equally, unions should as a minimum have the right to request that data sets and inferences are deleted when their original purpose has been fulfilled. 

Example: A union in Ireland has successfully negotiated that the employer cannot sell any data sets that include workers’ personal data.  

With these rights, the worst harms inflicted upon workers would be avoided. At the same time, digital technologies could be designed and deployed to benefit both workers and employers. 

Facilitator Material 

Use the above text as speech notes when you introduce the data lifecycle. Here are additional resources. Download them all: 

1. Facilitator’s Guide to this workshop – this includes possible responses to the exercise. Discuss these with your participants 

2. Video introducing the Data Lifecycle at Work Guide

3. Slide deck – note the first slides which are specifically for workers inside the European Data Protection Regulation (the GDPR). Skip these if you are from outside the EU, or use them to discuss with participants what rights they have and what it would take to get the same ones as workers under the GDPR. Note that some of the slides have speaking notes too.  

4. Slides - Exercise on how to use the data lifecycle 

5. Additional background information on data at work 

Workshop 3: Data Rights Tool 

AN ONLINE, INTERACTIVE TOOL THAT BRINGS YOUR LEGAL RIGHTS TO YOU AS YOU MAP THE DIGITAL TECHNOLOGIES USED 

This workshop is quite specialised. It is mainly aimed at policy and legal staff as well as shop stewards who wish to learn about the data rights they have and use these to map and dissect the digital technologies at work and on this basis formulate bargaining or policy responses. As part of the entire set of workshops in this Guide, this workshop is shorter, as it mainly introduces the tool to participants who then can use it afterwards. 

The Data Rights Tool is the second tool concerned with data rights. It is an advanced, online and interactive tool that step-by-step brings data rights to you rather than you having to know all of the relevant articles in your data protection law. This tool requires time to complete. Currently the tool has been tailormade to workers in the GDPR zone and is more generic for the rest of the world.  This does NOT mean it is not relevant for all of you. Workers digital rights are currently poorly defined in most countries in the world and negotiating stronger protections is essential. Like our data life cycle at work guide, you can find lots of inspiration in the tool that will help you fill legal gaps and negotiate for stronger rights. 

Click here to access the Data Rights Tool
(online only, choose language in top right corner)

Contents of the tool 

The tool consists of 4 main parts each with subsections. It is accompanied by a worksheet, which is a spreadsheet template that step-by-step will help you, the shop stewards and union officers to log information about the digital tools and systems used in a workplace.  

Part 1: Getting to know what tools and systems are being used, incl. setting clear limits for invasive systems 

Part 2: Mapping the data sources and setting clear limits for what data management can extract. 

Part 3: Mapping automated decision-making and profiling and setting clear limits for what analyses/profiling is acceptable to the workers.  

Part 4: Determining whether 3rd parties have access to workers’ data and setting clear limits for what they can do with that data. 

How to use the tool 

As you progress through the tool, you will receive tips and ideas in addition to the concrete clauses you can use. You will be asked to check for certain rights in the data protection regulation in your area. Where legal rights exist, you will be nudged to use them. Where they don’t, you will receive ideas as to how you can bridge the gaps through your negotiations with management. 

It is a good idea to go through the tool in chronological order until you have become well acquainted with it. Early in the tool, you will be asked to open the worksheet. When you do, save a copy to your own device. Here is a short video (English only) that explains how to use the worksheet.

Note: the tool is detailed and aimed at supporting your negotiations on the various stages from data collection, analysis and 3rd party access and use of your data. It will take time to collect the necessary information from management, to map and apply the legal rights you might have, and to find out where you could set in in your negotiations to improve workers’ data rights.  

Facilitator Material 

1. Facilitator’s guide – follow that step by step 

2. Video presenting the Data Rights Tool  

3. Worksheet to help you log information

4. Slide deck 

5. Video presenting how to use the spreadsheet (English only) 

6. Key Terminology Factsheet - Negotiating Data Rights

Workshop 4: Co-Governing Algorithmic Systems 

USE THIS TOOL FOR HOLDING MANAGEMENT ACCOUNTABLE, RESPONSIBLE AND LIABLE FOR THE DIGITAL TOOLS THEY ARE DEPLOYING 

Strongly linked to workers’ data rights is the issue of having co-determination rights over the algorithmic tools and systems that management put in place to manage workers. Recall from workshop 1 the link between data and algorithms and the harms workers can be subjected to if digital technologies are not meaningfully and properly governed. 

This Workshop 4 is all about how workers and their union can hold management responsible, liable, and transparent in relation to the automated management systems they deploy. It aims towards establishing co-determination and governance rights. Note that the lessons in this workshop can apply to situations where workers need to use digital systems in their work towards the public.  

In the quest towards co-determination and governance, the Our Digital Future project has developed “The Co-Governance of Algorithmic Systems” guide. 

The guide consists of 7 themes and 19 questions for ensuring that management is held responsible, liable and in control of procured or in-house designed digital systems.  

Download the guide

Why is the guide important?  

Algorithmic systems include Artificial Intelligence, Deep Learning and Machine Learning tools, but importantly also relate to more basic systemic analysis conducted in spreadsheets, or data analysis systems. Common for all of them is that they rely on data inputs, and they create outputs that can be predictions, probabilities, comparisons. In other words, the outputs are judgements. 

In public services, many of these worker-management systems are private sector systems that the public services have licensed in or procured to third parties. This makes the co-governance even more important as it begs the questions:  

• who has determined the purpose of the systems, the instructions inside the systems and the data used?  

• Is it the deploying public service or the designers/vendors who control these systems and can determine any changes to them?  

• How do the contractual relations between developer and deployer impact worker’s rights and workers’ possibilities to demand change to them?  

• How can the experiences and needs of the workers and their reps be included in the governance of these digital technologies? 

 Introducing the 7 themes 

Whereas the co-governance guide’s themes and questions in no way are exhaustive, and demand some practice, not least in relation to how to react to managers’ responses, they are the most important questions to be asked. Here’s why: 

Transparency and Procurement Contracts 

• To address the fact that many workers/shop stewards express that they do not know what algorithmic systems are in their workplaces, these first questions are key to ensuring transparency.  

• Many of these systems are third party systems that the deploying organisation either licenses or buys the rights to use. Depending on the contract between developer/vendor and deployer, the rights to adjust the algorithm(s) can vary. Also, it is pertinent for workers to know who (developer/vendor and/or deployer) has access and control over the data extracted. 

Responsibility 

• It is clear that the introduction of algorithmic systems in workplaces is influencing managerial responsibilities. Many shop stewards report that it is unclear who they should turn to for answers and responses. Is it the local/central human resources department, or the IT department? Who is doing the impact assessments and governing the effects of the technologies. Workers have a right to know. 

Right of redress 

• Given the real and potential impacts of algorithmic systems on workers, workers must have the right to challenge actions and decisions based solely or partially on these systems.  

Data Protection and Rights 

• In line with Data Lifecycle at Work, workers should as a minimum have certain rights to know what data is collected, for what reasons and what happens to the data post extraction.  

However, workers must also have the right to co-determine and edit these data. 

Harms and Benefits 

• These questions relate very much to probing management for what assessments or audits they have conducted on these algorithmic systems. What remedies management have in place if unintentional or intentional harms are identified? 

Adjustments 

• This theme relates to theme 1 on transparency and procurement. It asks what rights management and workers have to amend the algorithms if harms or other adversarial impacts have been identified. This is pertinent in the cases where the deploying public service is using 3rd party systems. 

Co-governance 

• The last theme builds on the others by asking what mechanisms can be put in place so workers and management can co-govern algorithmic systems. Given that the managerial lines of responsibility can be far-removed from the affected workers, it is pertinent that those who have the closest contact to workers are party to the governance of these systems. 

This theme also addresses the question of whether management and workers have the necessary skills and knowledge to successfully co-govern algorithmic systems. There is a dangerous assumption in many governance models that management actually understands the potential impacts of the algorithmic systems they are deploying. Additional training for workers and managers will be needed. 

 How to use the guide 

Use the guide as you prepare to approach management on their use of algorithmic systems. Note down how you expect they will respond. When you begin to ask management these questions, you will most certainly find that they require time to answer. Digital systems are changing the division of responsibilities between various managerial roles such as human resources, IT departments, data protection officers and department heads. Alternatively, when you call for the meeting, you can require that these managers are present.  

When you get a response from management, check whether you find management’s response satisfactory. Push for more detail if you do not receive enough information.  

Facilitator Material 

Use the text above as an introduction, then show the following. Download all links: 

1. Workshop 4 facilitator’s guide. this includes possible responses to the exercise. Discuss these with your participants 

2. Video presenting the co-governance guide

3. Slide deck introducing the Co-governance guide and the 19 questions 

4. Exercise slides – for group work 

Workshop 5: The Digital Bargaining Hub 

A WORLD FIRST PUBLICLY ACCESSIBLE DATABASE OF BARGAINING CLAUSES, UNION GUIDANCE AND FRAMEWORK AGREEMENTS.  

The previous 4 workshops have all been concerned about supporting workers and their union as they understand, then dissect, map and query digital technologies at work. In workshop 4 we began formulating concrete collective bargaining clauses. This workshop is all about that. It is concerned with PSIs Digital Bargaining Hub - a resource to help unions meet the challenges of digitalisation head-on at the bargaining table.  

The Digital Bargaining Hub is the first online, free, publicly accessible, searchable database of real-world bargaining clauses, union guidance, and framework agreements on issues related to digitalisation.   

Click here to access the hub
(Online only, choose language above the title)

Navigating the hub 

The material in the hub has been compiled to help union negotiators and other bargaining team members identify language that they can bring to the table to strengthen workers’ rights in our current moment of technological transformation.  

 Clauses have been sorted into 8 themes, which can be seen on the left of the screen. Users can interact with the hub in three ways:  

1. Report view – This view provides a brief summary of each theme, why it’s important and view a handful of highlighted clauses taken from our database. 

2. Database view - In this view, Hub users can review our entire collection of clauses.  

3. Search function - The database is searchable by theme or by choosing clause type, union, country, sector, and more. This will return a list of the clauses relevant to the search parameters.  

Importantly, users can upload their own clauses and, in this way, keep the database as up-to-date and representative as possible.  

Facilitator Material 

Unlike the previous workshops that required some introduction, this workshop is all about doing! Download the facilitator notes for a good run through of how to conduct this workshop, including the group work exercises. Set aside 2 hours for this workshop – experience shows that the more time participants have to learn to use the hub and answer the scenario questions the better. 

Here are the materials you need: 

1. Facilitator guide this includes possible responses to the exercise. Discuss these with your participants 

2. Video introducing the hub

3. Slide deck – this includes speaker notes, so remember to look at these  

4. Group exercise slides 

Workshop 6: The Digital Impact Framework 

THIS ONLINE, INTERACTIVE TOOL WILL FACILITATE UNION TRANSFORMATION INTO THE DIGITAL AGE 

This last workshop is about PSIs Digital Impact Framework (DIF). It’s an online, interactive tool that is aimed at supporting a privacy-preserving, fundamental rights orientated union transformation. 

The DIF should be used by the group of union leaders or department teams who are seeking to implement digital strategies and use digital tools and systems to boost the union’s campaigning, organising and power.  

Click here to access the Digital impact Framework
(Choose language top right)

About the DIF 

The DIF has been developed with inspiration from existing digital or data maturity frameworks as week as the UK TUCs digital health check. It was created to support unions to take informed, critical decisions about the use of digital tools as well as to mainstream digital awareness across the union.  

Start the meeting by showing the video. It provides a brief description of how to use the DIF as well as one other very important feature: the DIF does not recommend concrete tools, nor does it draft specific policies or visions. Instead, the DIF tells participant what they would be doing if their digital impact score was higher. 

This means it is up to the participants to decide how they will increase their score. This includes defining the goal of their initiatives, setting progress milestones, deciding timelines and responsibilities.  

As is mentioned in the video, it is important that the leadership or department teams go through the DIF together. Reserve a 2-hour slot to do this.  

This is what participants should do: 

1. Go through the tool and on each dimension select 1 of the 5 possible responses. Select the response that most resembles their current level of impact. 

2. Discuss for each dimension why you are where you are, and what it would take to move up a level or two. 

3. When finished, download the pdf and date it. 

4. Now select one or two dimensions to work on over the next months. 

5. Determine project goals, milestones, and dedicate a responsible person to oversee the work. 

6. Reconvene as a group periodically to discuss progress.  

7. When the milestones have been reaved, retake the framework noticing how improvements on the selected dimensions can impact other dimensions. 

8. Chose new dimensions to work on 

9. Download and date. 

10. Repeat from step 4. 

Facilitator Material 

Use the above text as speech notes when you introduce the digital impact framework. Here are additional resources. Download all links: 

1. Workshop 6_facilitator guide DIF this includes possible responses to the exercise. Discuss these with your participants 

2. Video introducing the Digital Impact Framework

3. Slide deck including video 

4. Exercise slides - group discussions 

The training guide was kindly supported by Friedrich-Ebert-Stiftung and is made publicly available courtesy of Public Services International under an Attribution-NonCommercial-NoDerivatives Creative Commons Licence. 

Please attribute as:  "Teach Forward! A Facilitator’s Guide to Our Digital Future, Public Services International, 2023"   

​​References and other useful material