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We are often told that there is no place for politics in objective research. The scientific tradition has built rigorous methodologies to get rid of bias, and presents itself as untouched by the messy social world. But what should we make of the claim that politics is irrelevant in science?

There is another pressing issue at stake: the assumed absence of politics in science. When commentators point out problematic politics in research, we are often dismissed as bringing personal bias into an objective arena. By unpacking three crucial assumptions in the Stanford study, I argue that politics is never beside the point. The authors warn that governments could use AI to persecute lesbians and gay people. Curious teens could even use the technology on themselves. For this claim to hold up, we have to view sexual orientation as a fixed and essential fact.

Similarly, the HIV literature has highlighted that many men engage in sex with men whilst identifying as straight. Anthropologists have long documented cross-cultural variations in sexual desireswhich are embedded in local configurations of gender, family, and the body. When scientists ignore established learnings from social sciences, we have to question their agenda.

Assumption 2: trans people, people of colour, and bisexual people are irrelevant.

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This seems odd since trans people, bisexuals, and people of colour have faces and sexual orientations too. For research that claims to be about AI and sexuality in general — not about white, cis, straight and gay people — this omission is both misguided and problematic.

Firstly, their data comes from self-reported sexual orientation on online dating websites. This assumption is not tested, but is likely untrue for some people. Although I now identify as bi and queer, I have listed myself as gay or straight on dating sites.

Secondly, you cannot tell if a person is trans from their picture. There are countless reasons why people might not disclose their trans status on a public dating website. The claim that no trans or bisexual people are in the sample is, therefore, tenuous at best. They go on to omit people who look mixed race or Latino, skipping over loaded questions about race and ethnicity. Using outdated is more than a question of politeness; it points to a wider disengagement with critical issues, including how research can re-inforce inequalities.

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The experiences of those groups come to define everyone else, who is judged against the standard they set. The research sample is framed by heteronormative, cissexist, and racist ideals. People choose which pictures toworking with flattering poses, and tapping into the culture of the dating website.

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For many people, becoming part of a sub-culture means learning to read its bodily scripts. Of course, these lessons are flawed, since presentation and identity can be entirely separate. Nonetheless, some of us who move outside of mainstream, white, cis, heterosexual circles do learn to spot each other. Becoming versed in the visual language of queerness also made straightness visible to me in a way that it had not been before. I wonder how the site users themselves would have scored as judges, given that they spent time immersed in its visual culture. Once again, this oversight brings a blinkered assumption into the study, and le to them overstate the importance of their findings.

Are social scientists politicizing the natural sciences when we comment on problematic, harmful, and flawed assumptions? Or does it just seem that way because of the refusal to acknowledge that politics is already present? If we acknowledge the limited sample, that sexuality is not pre-determined, and that some people can read queer styles, we are left with a computer that learned to spot grooming patterns among white cis people who list themselves as gay or straight on a public dating website.

Science and machine learning only exist within the social world. That world shapes who has access to institutions, and inevitably runs through the research produced there. Value judgements are made about which research to fund. People decide which questions are worth asking, and how to go about answering them. Every hypothesis depends on a series of assumptions, which are never neutral. Even AI is marked by racism, because it learns from data that humans provide. This is about more than one study. Research is not only informed by social norms, but also reinforces certain ideals.

It would be misguided to aim to remove the social world from science. Instead, we should harness a critical awareness by acknowledging the power of politics. Pause for a moment to untangle the politics of the study, interrogate its assumptions, and ask what underlying ideas are being promoted.

Jessica is a Brighton-based anthropologist and queer feminist killjoy. She is fascinated by the powerful relationships we build with our bodies and invested in challenging body-based oppressions. Alongside working with a local LGBTQ charity, her doctoral research at the University of Oxford asks what matters to trans and non-binary people living with disordered eating. She tweets at JessSandelson and more info on her work is at jessicasandelson. Perhaps this is because criticism in science should be reserved for scientists, not commentators — many of whom do not seem to understand the methodologies involved, or the rationale behind certain assumptions being used.

Bias is a problem, but it is more of a problem for people who quote Foucault than for academics who limit the of definable to control potential confounding variables. This is not what the authors said, in fact as you point out later, they were concerned only with homosexuality. It was activists and social science that lump transgendered people in with Lesbian and Gay people.

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Indeed recent research has identified 20 genes associated with Trans, which are not associated with LG and B as far as I am aware. This is misleading. People suffering from HIV are a tiny minority of a tiny minority, those who have sex with men and claim to be straight are a tiny minority of even those individuals. There are many reasons they may make such claims e. Firstly, their data comes from self-reported sexual orientation on online dating websites Fair point, though this would no doubt have been a criticism of the research.

Specifically the issue regarding Bisexuals is potentially ificant. As for Trans, they are a tiny population k in the US, though again its possible one or two might have been involved in the study, though they are hardly likely to skew the. I think its unfair of you to impute motives here. The reason they obviously removed other races from the sample is as a control, you know this as a scientist yourself. You limit the of potentially confounding variables.

Once the software has been trained on whites and Caucasian is a fine wordthen we can train it on other groups. Standard science. Actually this is wrong, it is more a description of the types of behaviours that gay and lesbian people engage in to make themselves more appealing to potential partners online. Certainly it is the case that the gay and lesbian communities will have beauty standards, but these are formed and regulated by the gay community, so studying them does tell you something about that target group.

Though I take the point that there may be a selection bias issue not due to prejudice, but methodological constraints. But this itself is subject to bias. If the researchers are required to leave their cis biases at the door, what about your own? How can you fairly assess this system if you do not recognise and discard your own biases.

Do you dislike the ? Is it that dislike that motivates your scepticism? We all suffer from bias, this article is useful because it questions one form. Hopefully my response has questioned another. If you wish to submit a post to Engenderings, you can at gender. Have a look at our notes for contributors ! Bad Behavior has blocked access attempts in the last 7 days. Twitter Twitter. The politics of AI and scientific research on sexuality. The politics of AI and scientific research on sexuality by Jessica Sandelson We are often told that there is no place for politics in objective research.

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Conclusions: what is the real risk? post Next post. Ricky March 19, at - Reply. Indeed recent research has identified 20 genes associated with Trans, which are not associated with LG and B as far as I am aware, 3. They go on to omit people who look mixed race or Latino I think its unfair of you to impute motives here. Standard science 6. Certainly it is the case that the gay and lesbian communities will have beauty standards, but these are formed and regulated by the gay community, so studying them does tell you something about that target group, Though I take the point that there may be a selection bias issue not due to prejudice, but methodological constraints 7.

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