What is a fair minimum rate? Views from AI & The Humans

August 29, 2023 -

Hurray! New possibilities have been created to make collective (minimum) rate agreements for solo self-employed persons. We have read interesting legal perspectives in the other (highly readable!) contributions to this blog, concerning, for instance, their knock-on effects or wider relevance. It is now also time for some practical guidance for those who are starting their work with the new tools in the toolbox.

We may negotiate collectively … but how do we achieve fair rates? What is fair? What might it look like for professional groups for whom no objective footing has been created in the past or for professions that cannot easily be placed in a bigger picture relative to other functions in a sector or organisation? How do you price an activity that is part of a revenue model consisting of a mix of paid and unpaid activities, and which may or may not be intertwined with the sale of products and exploitation of rights? Complex questions, which will nonetheless require an answer if we are to achieve meaningful outcomes from collective bargaining for solo self-employed in the cultural and creative sectors.

The Dutch competition authority (ACM), initially one of the toughest kids on the block, had already presented a new and considerably friendlier view on collective bargaining for self-employed workers by the end of 2019. In this context, and in the wake of the turmoil surrounding Covid-19, the Kunstenbond has been able to gain experience with new approaches to reaching fair rates. This experience came somewhat earlier than in many other EU countries, for whom perspectives have now also changed in light of the European Commission guidelines published late in 2022.

This blog post offers some insight into the emerging outcomes of an extensive working process, involving a wide coalition of stakeholders in the creative sector in the Netherlands, consisting of several smaller groups, each made up of representatives of links in the value chain around a specific profession, that has each of them sought to arrive at a set of parameters for that professions that may be taken into account in order to determine a fair remuneration and establish a meaningful minimum valuation of work based on objective indicators. This painstaking work is intended to a be baseline for establishing fair working conditions across the sector and to make it sustainable in the future. The final outcome we aim to achieve will be a simple calculation tool for relevant professions in the sector. The methodology drew directly on the knowledge and lived experience of those working in the sector. For more complex sub-sectors, the work also involved starting from a limited number of professions which were described by a specialised agency. This description was based on detailed study, via interviews, of the work in practice involved in these professions. Discussions then proceeded with a view to establishing and weighting relevant criteria for determination of fair remuneration. And in all cases a specialised research bureau was appointed to do calculations and provide the working groups with mathematically, financial and socially correct justifications of the offered rates. Where, for example, a financial translation of differently valued hours of work required to perform a particular gig, and set against as realistic an estimate as possible of how many such gigs could be done in a full year when working full-time (all stemming from a survey of practitioners and other stakeholders), ultimately leads to a reasonable minimum fee for similar assignments.

So far the work of The Humans… however, to make it more exciting and to provide an interesting counterpoint to the analysis being developed, we decided to also simultaneously look at how AI would approach these same issues. This was also an opportunity to explore via comparison whether AI tools are already at a level to provide meaningful input to our deliberations and our professional practice as unions. The outcomes were certainly interesting and a representative sample is provided below. Some general trends were immediately clear. On the one hand, The Humans (mostly professionals who were directly and on a day-to-day basis involved in, or part of, the profession for which we wanted to establish fair rates), arrived at their model more searchingly, via exchange of views, and in the final result sometimes steered more emphatically towards simplicity where they could, or, on the contrary, embraced more complexity where more professions had to be contained in one and the same system. On the other hand, AI’s answer for the different professions seemed to be mostly similar in structure regardless of the profession and scenario under consideration. Only the important distinguishing criteria were profession-specific. For reference, the question posed to AI each time was, “what are the criteria and associated parameters to arrive at a fair rate for [profession]”.

Presented below are the outcomes for three specific categories, namely: visual artists, pop musicians and film workers. These give insight into the real considerations in establishing and rolling out fair minimum rates. In practice, it is the work carried out by the human stakeholder group that is the basis for the tools developed or under construction referenced below, however, it is clear that the AI analysis presented is also of interest and captures many of the same considerations with a considerable degree of nuance. However, the additional overriding consideration of simplification where necessary (or when possible: it is more difficult to develop the simplest possible tool that guarantees a fair outcome, while in practice the simplest possible tool has the most chance of success), selection of the most relevant elements and, crucially,  practical application of the analysis to existing remuneration frameworks to arrive at meaningful fair minimums, was where the AI could offer little real input to this work. The work on these and other tools is ongoing and we look forward to continuing to exchange views and experience on how to meaningfully reach fair minimum rates of pay for the creative and cultural sectors, in particular those solo-self-employed professionals for whom unions may now collectively bargain.



AI The Humans
1. Reputation and Track Record (consider the artists’ level of) 1. Artwork
a. Recognition a. New works
b. Exhibition history b. Existing works
c. Critical acclaim c. Modification of existing works
d. Awards 2. Artists in exhibition
e. And overall reputation in the art community a. 1, 2, 3, 4, …, 7 or more
2. Exhibition Size and Scope 3. Exhibition duration
a. Number of artworks to be displayed a. 1 month, 2 months, 3 months, …, 24 months
b. The size of the exhibition space
c. And the overall significance or uniqueness of the event
3. Exhibition Venue and Location
a. Prestige and reputation of the exhibition venue
4. Exhibition Duration
5. Curatorial Effort
a. Artwork selection
b. Arrangement
c. And installation
6. Marketing and Promotion
a. Expenses associated with marketing and promoting the exhibition
7. Exhibition Production Costs
a. Lighting
b. Display materials
c. Framing
d. Signage
e. Transportation and insurance
8. Sales Commission
9. Artwork Insurance


The minimum artist fee (based on the structure developed by the The Humans above) has been rolled out from as a calculation tool on the website ‘Kunstenaarshonorarium’ (Artists’ fee). In money terms, the figure proposed after filling in the relevant data to apply the criteria that have been developed, is based on the following:

1) figures from a study, which examined how many exhibitions (and with how many individual works, either new, existing or modified for the occasion) an average artist can participate in in a year when working full-time on them for a year;

2) and the statutory minimum wage.

This last premises was due to the at that time still very strict Competition Authority. Consultation with them had revealed that we could be confident that they would turn a blind eye to a calculation based on the minimum wage. While we might now be more likely to choose and use a higher income as a starting point. This aside, most presentation institutions cannot (say they cannot) afford the current rate without additional subsidy.



AI The Humans
1. Performance Type The reasonable rate of pop musicians could be calculated online and the musicians will be classified into one of the following four categories:
a. Life performance I. STARTING UP
b. Recorded music II. UPCOMING
c. Streaming III. DEVELOPING
d. Synchronization (licensing music for TV shows, movies etc.) IV. MID-CAREER
2. Experience and Reputation V. ARRIVED
Classification is done according to the following criteria:
a. Number of albums released 1. Period active as a band/musician under this name
b. Chart success 2. How many tracks released
c. Awards won 3. How many shows on counterparties podia/festivals in the last 4 years (with this act)
d. Critical acclaim 4. How many shows on other podia
e. Overall fan base 5. Highest “monthly listeners” on Spotify last year
3. Popularity and Demand 6. Highest amount of streams
a. Ticket sales 7. How much airplay on nationwide radio – past 2 years
b. Streaming numbers 8. How many followers on social media
c. Social media followers 9. Professional acknowledgement – prices, nominations, selection
d. Merchandise sales 10. How many podia appeances abroad on podia ‘that matter’
4. Venue Capacity
a. Larger venues often higher remuneration
5. Ticket Pricing
a. Analyze the average ticket price for similar pop music events to determine the range of remuneration appropriate
6. Performance Length
7. Production Costs
a. Explore revenue sharing models
8. Revenue Sharing
a. Explore revenue sharing models
9. Licensing and Royalties
10. Industry Standards and Collective Agreements
a. Consider standards established by musician associations/unions


The planned online tool deriving from this work (which is currently still in a private testing phase, but will hopefully be made public soon) calculates

1) the minimum fee based on statutory minimum wage and

2) a fair pay remuneration that is higher.

Again the remuneration levels proposed by the tool, once the relevant parameters have been inputted, are based on research and the number of hours a musician spends on average, including rehearsals and all other additional work, on a live performance.



AI The Humans
1. Job Role and Responsibility 1. Area of responsibility
a. Directing a. Influence of function
b. Producing b. Effects of the function
c. Cinematography 2. Leadership
d. Editing a. Hierarchical (intern)
e. Sound Design b. Operational (external)
f. Production Design c. Functional
g. Costume Design 3. Knowledge and Complexity
h. Visual Effects and others a. Level of knowledge
2. Experience and Track Record b. Complexity of knowledge
a. Previous work 4. Troubleshooting
b. Credits a. Difficulty of the problems
c. Awards b. Freedom to act
d. And critical acclaim 5. Communication and Consultation
3. Production Budget a. Intensity
4. Market Demand b. Atmosphere
5. Project Scale and Type c. Frequency
a. Budget 6. Special Skills/Requirements
b. Production Scale a. Movement skills
c. Shooting duration b. Accuracy
d. Complexity c. Material and machine feel
6. Time commitment d. Special requirements (such as taste and smell)
a. Longer shooting schedules 7. Inconveniences
b. Extended post-production periods a. Weight
c. Intensive pre-production phases b. Straining position
7. Union or Association Guidelines c. Working atmosphere (heat, draughts, noise, …)
8. Skill and Expert Level d. Personal risk
9. Market Comparison


Given the range and variation of professions that this planned tool would seek to cover, the outcome is necessarily quite complex. In practice, it was important to establish which criteria are relevant to which professions and their relative importance and impact.

The resulting overall picture of the profession, corresponding to an ‘abstract description’ of the job in line with the parameters per criterion as described, yields a total number of points. And using some benchmarks from adjacent collective labour agreements, this yields a fee, or at least a range (min-max). In the end, a matrix emerges where horizontally all film departments are listed, and vertically the weighted functions, at the level (scale) where the function ended up based on the total number of points. Since only 2 to 3 occupations per area in every department were examined in-depth, the sector should collectively grade the remaining functions, based on the criteria and parameters that where established. Thus, the matrix can be further completed.

About the author

Caspar de Kiefte

Caspar de Kiefte trained as an animator at the Gerrit Rietveld Academy in Amsterdam and as a lawyer at the University of Amsterdam. Before working for the Kunstenbond, he worked as a barrister and later as deputy-director at the Netherlands Institute for Animation Film (NIAf). His drive is to improve the negotiating, economic and labour market position of creative professionals. He does this in the field of collective copyright law and through the Labour Market Agenda for CCS (Cultural and Creative Sector) in the Netherlands. He was the driving force behind the successful enabling of collective bargaining for solo self-employed in the Netherlands in 2019. Before co-establishing Platform ACCT (the platform implementing the labour market agenda for the CCS), he was a member of the SER committee (Social Economic Council & Cultural Council) that authored the 'Exploration of Cultural Sector Labour Market' report, followed by the SER advice paper 'Passie Gewaardeerd (Passion Valued)'. These reports led to the current Labour Market Agenda CCS.

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European Union This project and publication have received the support of the European Union. The publication reflects the views of the authors only and the European Commission cannot be held responsible for any use of the information contained therein.