Our Assumptions: of Neutrality, of People, & of Systems

Discussions of neutrality have been coming up a lot in libraryland recently. I would argue that people have been talking about this for years1 2 3 4,  but this year we saw a confluence of events drive the “neutrality of libraries” topic to the fore. To be clear, I have a position on this on this topic5 and it is that libraries cannot be neutral players and still claim to be a part of the society they serve. But this post is about what we assume to be neutral, what we bring forward with those assumptions, and how to we react when those assumptions are challenged. When we challenge ideas that have been built into systems, either as “benevolent, neutral” librarians or “pure logic, neutral” algorithms, what part of ourselves are we challenging? How do reactions change based on who is doing the challenging? Be forewarned, this is a convoluted landscape.

At the 2018 ALA Midwinter conference, the ALA President’s program was a debate about neutrality. I will not summarize that event (see here), but I do want to call attention to something that became very clear in the course of the program: everyone was using a different definition of neutrality. People spoke with assumptions of what neutrality means and why they do, or do not, believe that it is important for libraries to maintain. But what are we assuming when we make these assumptions? Without an agreed upon definition, some referred to legal rulings to define neutrality, some used a dictionary definition (“not aligned with a political or ideological grouping” – Merriam Webster) without probing how political or ideological perspectives play out in real life. But why do we assume libraries should be neutral? What safety or security does that assumption carry? What else are we assuming should be neutral? Software? Analytics? What value judgements are we bringing forward with those assumptions?

An assumption of neutrality often comes with a transference of trust. A speaker at ALA even said that the three professions thought of as the most trustworthy (via a national poll) are firefighting, nursing, and librarianship, and so, by his logic, we must be neutral. Perhaps some do not conflate trust and neutrality, but when we do assume neutrality equates with trust in these situations, we remove the human aspect from the equation. Nurses and librarians, as people, are not neutral. People hold biases and a variety of lived experiences that shape perspectives and approaches. If you engage this line of thought and interrogate your assumptions and beliefs, it can become apparent that it takes effort to recognize and mitigate our human biases throughout the various interactions in our lives.

What of our technology? Systems and software are often put forward as logic-driven, neutral devices, considered apart from their human creators. The position of some people is that machines lack emotions and are, therefore, immune to our human biases and prejudices. This position is inaccurate and dangerous and requires our attention. Algorithms and analytics are not neutral. They are designed by people, who carry forward their own notions of what is true and what is neutral. These ideas are built into the structure of the systems and have the potential to influence our perception of reality. As we rely on “data-driven decision-making” across all aspects of our society — education, healthcare, entertainment, policy — we transfer trust and power to that data. All too often, we do that without scrutinizing the sources of the data, or the algorithms acting upon them. Moreover, as we push further into machine learning systems – systems that are trained on data to look for patterns and optimize processes – we open the door for those systems to amplify biases. To “learn” our systemic prejudices and inequities.

People far more expert in this domain than me have raised these questions and researched the effects that biased systems can have on our society6 7 8. I often bring these issues up when I want to emphasize how problematic it is to let the assumption of data-driven outcomes as “truth” persist and how critical it is to apply information literacy practices to data. But as I thought about this issue and read more from these experts, I have been struck by the variety of responses that these experts illicit. How do reactions change based on who is doing the challenging?

Angela Galvan questioned assumptions related to hiring, performance, and belonging in librarianship, based on the foundation of the profession’s “whiteness,” and was met with hostile comments on the post9. Nicole A. Cooke wrote about implicit assumptions when we write about tolerance and diversity and has been met with hostile comments10 while her micro-aggression research has been highlighted by Campus Reform11, which led to a series of hostile communications to her. Chris Bourg’s keynote about diversity and technology at Code4Lib was met with hostility12. Safiya Noble wrote a book about bias in algorithms and technology, which resulted in one of the more spectacular Twitter disasters13 14, wherein someone found it acceptable to dismiss her research without even reading the book.

Assumptions of neutrality, whether it be related to library services, space, collections, or the people doing the work, allow oppressive systems to persist and contribute to a climate where the perspectives and expertise of marginalized people in particular can be dismissed. Insisting that we promulgate the library and technology – and the people working in it and with it – as neutral actors, erases the realities that these women (and countless others) have experienced. Moreover, it allows the those operating with harmful and discriminatory assumptions to believe that they *are* neutral, by virtue of working in those spaces, and that their truth is an objective truth. It limits the desire for dialog, discourse, and growth – because who is really motivated to listen when you think you are operating from a place of “Truth”…when you feel that the strength of your assumptions can invalidate a person’s life?

2 thoughts on “Our Assumptions: of Neutrality, of People, & of Systems”

  1. I think that the death of the neutral library may please progressive today but will see them unemployed in the future because their once trusted institutions have become seen as biased. This will occur in much the same way the ALA itself has justified its increasingly obvious political bias so to will we see library directors remove civic checks that kept employee bias at bay. I have already started to see this in my system and it is only going to get worse as time goes and the identity politics of this day and age become cemented in operational proclivities and norms. Remember this; todays oppressed are tomorrow’s oppressors and vice-versa. Who is going to be in person in charge who makes sure that the institutional biases are aligned correctly? What authority will they use and what standards will they rely on? I can only imagine the next millage tax debate where a library director has to explain the positions and statements, like the ones used by Yasmeen Shorish, to an angry public who feel that their public institutions should not be oriented on neo-Marxist or racial perspectives. Nothing kills trust like ulterior motives.

    1. But our institutions are already biased, just because one agrees with their bias doesn’t magically make them neutral. That is precisely the point of this post and it’s astonishing to me that someone could read it in its entirety and somehow not understand.
      “todays oppressed are tomorrow’s oppressors and vice-versa” – we’ll have to agree to disagree here. How exactly are the indigenous peoples of America oppressing the colonizers now? Sure, maybe a few times power relations have inverted, but to say that it always and inevitably happens is a massive oversimplification. Nice aphorism, no merit.

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