The year 1989 was momentous in human history. It was the year the Berlin Wall was brought down, prompting US political scientist Francis Fukiyama to proclaim ‘the end of history’. It was the year when African-American law professor Kimberlé Crenshaw first articulated the theory of intersectionality, a powerful concept that awakens people to privilege, systemic inequities and injustices while helping advance claims for greater justice and transparency. It was also the year British computer scientist Tim Burners Lee gave us the internet.

The world became compressed and distance no longer seemed to divide us. Suddenly almost everyone was living in a hyper culturally diverse world experiencing massive economic globalisation without an accompanying globalisation of values and ethics. 

The theory of intersectionality is now a prominent analytical framework used to understand and address social inequality across government bodies, academia, activist networks and corporations. The theory has also met with backlash. Many people believe that intersectionality theory has unintentionally contributed to an essentialising of identity, where being coded black, white, Asian, disabled, male or female, for instance, can for some people mean feeling put in a homogenising box that they had no say over and for others can mean policing the box’s borders (from within or without) with extreme vigilance, including violence.

My contention is that the main cause of this trouble lies in the limited datasets that are persistently and pervasively used across the world in every field. We now have the technological capacity to use holistic datasets and this is what anyone who wishes for a more harmonious, equitable and peaceful world ought to be loudly advocating for.

Intersectionality theory may have reached an impasse. As Nigerian writer Bayo Akomalafe wrote in a recent piece ^[i], collectively, humans are now [in 2023] confined by our own limited ideas of who we are. He cites Australian philosopher Elizabeth Grosz, who identified intersectionality as ‘a gridlock system, which fails to account for the mutual constitution and indeterminacies of embodied configurations of gender, sexuality, and race.’^[ii] A politics, Akomalafe suggests, that encourages minorities to demand recognition by their dominant others is a trap. Meanwhile, from the point of view of the dominant other, well-intentioned attempts to create equitable policies can resemble a game of whack-a-mole.

A holistic model can inform ideas and practice that revitalise the ground for intersectional – or any other – theory. In Eastern philosophy, Indra’s net, a model congruent with the theory of quantum mechanics^[iii], illustrates the concepts of Sunyata (emptiness), pratityasamutpada (dependent origination) and interpenetration. Within each intersection of this infinite net is a multifaceted jewel, with each jewel reflecting every other jewel.

We can use this model to visualise UNESCO’s 2005 Convention on the Protection and Promotion of the Diversity of Cultural Expressions. As its third principle the Convention asserts that the ‘protection and promotion of the diversity of cultural expressions presuppose the recognition of equal dignity of and respect for all cultures [my emphasis], including the cultures of persons belonging to minorities and indigenous peoples.’^[iv]

Today, through computer technology, we can conjure Indra’s net and honour UNESCO’s guiding principles. As author Richard Powers said in an interview with the LA Review of Books, ‘Life is simply too complex and interdependent for us to wrap our heads around without the help of our machine prosthetics.’^[v] Astonishingly, almost no one seems aware that we can make this shift from selective to holistic databases.

In his seminal 1997 book Representation: Cultural Representations and Signifying Practices^[vi], British cultural theorist Stuart Hall explained how categories like ethnicity, gender and class are constructed and represented. He described classification as a profound human impulse, without which we cannot generate any meaning – in other words, meaning is generated through classification. Datasets are a system of classification and therefore, datasets generate meaning. This is why when our datasets gather highly diverse populations under a few crude categories the meanings created from this seemingly neutral activity in fact have great power and can lead to dangerous ignorance and lack of nuance.

Datasets create the conceptual boxes we live in so if we don’t like the conceptual boxes, we need to demand that our organisations use new datasets. 

Limited datasets create limited insights, yet in 2023 they are the standard across every industry and government body in the world.

Consider a recent typical example, a national Australian survey from an industry group that analysed cultural backgrounds and included only eleven categories in its dataset, including ‘First Nations’, ‘Anglo-Celtic’, ‘Southern and Eastern European’ and ‘Oceanian’.

Can you see how much prominence Anglo-Celtic is being given here, given the highly heterogeneous content of each of the other categories? Yet even the Anglo-Celtic category represents seven distinct spoken languages and many more dialects, all dominated by Standard English. How represented is a Manx speaker likely to feel by this category? Will their special needs be considered by policy-makers or anyone else using these datasets, or will the Anglo-Celtic box be ticked as soon as the Standard English speakers have been accounted for and catered to? We know the answer. 

Now think of the other categories mentioned and try the same thought experiment. This crude labelling is why many ‘First Nations’ people, especially Elders/knowledge keepers, refuse to identify beyond their particular cultural group.

Mathematician/theoretical biologist Jared Field wrote, ‘I am Gomeroi from the Kamilaroi nation. To say so is to perform real magic. Bit by bit the original labelling is dissolved like aspirin in water.’^[vii] This does not invalidate the many reasons people do identify beyond their ancestral cultural group – the point I am making is that in 2023 we have the capacity and I believe the responsibility to create comprehensive datasets structured to reflect the diversity of who we are. For anyone objecting that these more granular datasets will lead to greater fragmentation, let me quote historian Patrick Wolfe: ‘Paradoxical as it may seem, to homogenise is to divide.’^[viii]

Limited datasets create degraded data, which leads to poor policy just as degraded soil leads to poor quality fruit, and poor policy can destroy people and cultures. Just as we collectively misuse and take our soil for granted, we also misuse and overlook the importance of data, which is apparently not glamorous enough to get the attention it warrants.

Nothing is more significant than datasets in terms of shaping policy. A dataset that includes every known category of cultural background represents a quantum shift from selective datasets in terms of the quality of data it produces. Only an ideological system that deliberately creates categories of undesirables or hierarchies based on gender and a range of other attributes would actively refuse to use holistic datasets. 

A lot has changed in the past twenty years but collectively we have failed to keep up. We now have the technological capacity to shift to holistic datasets that contain every known variable of human culture, identity, appearance and activity, and this shift can be global. Dominant categories, like ‘the West’, habitually talk about themselves and their problems as though separate from the rest of the world. This harmful pattern can be disrupted by creating equal space for all perspectives, which can happen with the help of technology. The only remaining question is whether we have the imaginative, empathetic and moral capacity to make this switch.

Holistic datasets are achievable and through the power of technology vast amounts of data can be processed with minimal effort. A paradigm shift is required to move beyond the deficit models we’ve been living with and to embrace emerging technologies, but this is what may finally enable us to see and appreciate each other once more in our constantly shifting relations to each other, beyond any limited concept of identity. 

The role of human imagination and empathy is vital to any process of data analysis so decision-making on matters as consequential as the equitable allocation of resources may still be informed by intersectionality theory. However, holistic datasets can give us clear and regularly updated pictures of who and where we are in relation to one another, and in doing so move us out of the gridlock of our fixed, often mistaken, ideas about each other. 

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^[i] https://www.democracyandbelongingforum.org/forum-blog/black-lives-matter-but-to-whom-part-1

^[ii] Grosz, Elisabeth, Volatile Bodies, Bloomington 1994.

^[iii] https://www.degruyter.com/document/doi/10.12987/9780300231380-003/html?lang=en

^[iv] https://en.unesco.org/creativity/convention/texts

^[v] https://lareviewofbooks.org/article/heres-to-unsuicide-an-interview-with-richard-powers/

^[vi] Hall, Stuart, Representation: Cultural Representations and Signifying Practices, Sage Publications & Open University; 1st edition 1997

^[vii] https://www.theguardian.com/commentisfree/2018/jul/03/i-am-and-i-am-not-aboriginal

^[viii] Wolfe, Patrick, Traces of History: Elementary Structures of Race Verso, 2016

Photo Credit: Morgana Bartolomei / Upsplash