Diversity Reading List

Abstract:

This paper argues that AI follows classical versions of epistemology in assuming that the identity of the knowing subject is not important. In other words this serves to ‘delete the subject’. This disguises an implicit hierarchy of knowers involved in the representation of knowledge in AI which privileges the perspective of those who design and build the systems over alternative perspectives. The privileged position reflects Western, professional masculinity. Alternative perspectives, denied a voice, belong to less powerful groups including women. Feminist epistemology can be used to approach this from new directions, in particular, to show how women’s knowledge may be left out of consideration by AI’s focus on masculine subjects. The paper uncovers the tacitly assumed Western professional male subjects in two flagship AI systems, Cyc and Soar.

Abstract:
In this article, I explore some issues regarding the fictional capacity of photographs and their classification as fiction or nonfiction. In particular, I address the debate on the purported “fictional incompetence” of photography, whether photographs can or cannot represent ficta. In this debate, I side with theorists who defend the view that photographs can indeed represent fictive entities or ficta, but I offer an alternative argument: I claim that photographs can indeed represent ficta by photographic means, something that most theorists have denied. Then I consider some possible objections to my view and try to offer responses. Finally, I question whether representing fictive entities or events is all that is needed for a photograph to be fictional. In this context, I suggest what I take to be the correct way to classify deceptive photographs.

Abstract:

The recent proliferation of deepfakes, AI and other digitally produced deceptive representations has revived the debate on the epistemic robustness of photography and other mechanically produced images. Authors such as Rini (2020) and Fallis (2021) claim that the proliferation of deepfakes pose a serious threat to the reliability and the epistemic value of photographs and videos. In particular, Fallis adopts a Skyrmsian account of how signals carry information (Skyrms, 2010) to argue that the existence of deepfakes significantly reduces the information that images carry about the world, which undermines their reliability as a source of evidence. In this paper, we focus on Fallis’ version of the challenge, but our results can be generalized to address similar pessimistic views such as Rini’s. More generally, we offer an account of the epistemic robustness of photography and videos that allows us to understand these systems of representation as continuous with other means of information transmission we find in nature. This account will then give us the necessary tools to put Fallis’ claims into perspective: using a richer approach to animal signaling based on the signaling model of communication (Maynard-Smith and Harper, 2003), we will claim that, while it might be true that deepfake technology increases the probability of obtaining false positives, the dimension of the epistemic threat involved might still be negligible.

Abstract:

In this article, I explore the relationship between witness-bearing arts as a form of creative activism designed to respond to social injustices. In the first section, I present some common features of bearing witness, as conceptualized within media studies and journalism. Then I explain how artworks placed in the streets can bear witness in a similar way. I argue that witness-bearing art transmits knowledge about certain unjust and harmful events, which then places a moral burden or responsibility on the viewer. To defend this view, I offer some examples of activist art that bears witness to certain events. I suggest that witness-bearing art is placed in the streets in order to make certain truths publicly available, by offering evidence of them embedded in the artwork. The final section considers why the bearing witness is especially effective for activist art. Witness-bearing art plays a crucial knowledge-transmitting function, one which enables art to engage in creative activism. I conclude by considering how witness-bearing art offers a powerful and persuasive voice for the oppressed.

Abstract:

Suppose that you are soon to be a parent and you learn that there are some simple measures that you can take to make sure that your child will be healthy. In particular, suppose that by following the doctor’s advice, you can prevent your child from having a disability, you can make your child immune from a number of dangerous diseases and you can even enhance its future intelligence. All that is required for this to happen is that you (or your partner) comply with lifestyle and dietary requirements. Do you and your partner have any moral reasons (or moral obligations) to follow the doctor’s advice? Would it make a difference if, instead of following some simple dietary requirements, you consented to genetic engineering to make sure that your child was free from disabilities, healthy and with above average intelligence? In this paper we develop a framework for dealing with these questions and we suggest some directions the answers might take.

Abstract:
In this chapter, I draw on the seminal work of feminist theorist Iris Marion Young to consider how political responses to structural injustice, exacerbated by AI,¹ might be developed. My interpretation of Young’s work is centred on what I see as an overlooked feature of her account of structural injustice - ‘untraceability’. Drawing on Arendt’s concept of ‘thoughtlessness’ and the work of other scholars such as Benjamin, I explore the relationship between structural injustice and algorithmic decision making,² which, itself, is becoming increasingly untraceable. I argue that while fault-based regulation of AI is vital for combating injustice exacerbated by AI, too little thought goes into addressing the structural dynamics of AI’s impact on society which requires a different sort of approach. I conclude by offering some suggestions on how we might think about mitigating the exacerbation of structural injustice posed by AI. In particular, I advocate adopting several elements of the mini-public approach within the regulatory public-body landscape of democratic governance systems to form a new ‘AI Public Body’ (using the UK as my example).

Abstract:
During the 1970s and 1980s, a team of Automated Theorem Proving researchers at the Argonne National Laboratory near Chicago developed the Automated Reasoning Assistant, or AURA, to assist human users in the search for mathematical proofs. The resulting hybrid humans+AURA system developed the capacity to make novel contributions to pure mathematics by very untraditional means. This essay traces how these unconventional contributions were made and made possible through negotiations between the humans and the AURA at Argonne and the transformation in mathematical intuition they produced. At play in these negotiations were experimental practices, nonhumans, and nonmathematical modes of knowing. This story invites an earnest engagement between historians of mathematics and scholars in the history of science and science studies interested in experimental practice, material culture, and the roles of nonhumans in knowledge making.

Abstract:

Artificial intelligence (AI) systems are increasingly adopted to make decisions in domains such as business, education, health care, and criminal justice. However, such algorithmic decision systems can have prevalent biases against marginalized social groups and undermine social justice. Explainable artificial intelligence (XAI) is a recent development aiming to make an AI system’s decision processes less opaque and to expose its problematic biases. This paper argues against technical XAI, according to which the detection and interpretation of algorithmic bias can be handled more or less independently by technical experts who specialize in XAI methods. Drawing on resources from feminist epistemology, we show why technical XAI is mistaken. Specifically, we demonstrate that the proper detection of algorithmic bias requires relevant interpretive resources, which can only be made available, in practice, by actively involving a diverse group of stakeholders. Finally, we suggest how feminist theories can help shape integrated XAI: an inclusive social-epistemic process that facilitates the amelioration of algorithmic bias.

Abstract:
It is well-known that racism is encoded into the social practices and institutions of medicine. Less well-known is that racism is encoded into the material artifacts of medicine. We argue that many medical devices are not merely biased, but materialize oppression. An oppressive device exhibits a harmful bias that reflects and perpetuates unjust power relations. Using pulse oximeters and spirometers as case studies, we show how medical devices can materialize oppression along various axes of social difference, including race, gender, class, and ability. Our account uses political philosophy and cognitive science to give a theoretical basis for understanding materialized oppression, explaining how artifacts encode and carry oppressive ideas from the past to the present and future. Oppressive medical devices present a moral aggregation problem. To remedy this problem, we suggest redundantly layered solutions that are coordinated to disrupt reciprocal causal connections between the attitudes, practices, and artifacts of oppressive systems.

Abstract:
The highest level of mathematics has traditionally been seen as a solitary endeavour, to produce a proof for review and acceptance by research peers. Mathematics is now at a remarkable inflexion point, with new technology radically extending the power and limits of individuals. Crowdsourcing pulls together diverse experts to solve problems; symbolic computation tackles huge routine calculations; and computers check proofs too long and complicated for humans to comprehend. The Study of Mathematical Practice is an emerging interdisciplinary field which draws on philosophy and social science to understand how mathematics is produced. Online mathematical activity provides a novel and rich source of data for empirical investigation of mathematical practice - for example the community question-answering system mathoverflow contains around 40,000 mathematical conversations, and polymath collaborations provide transcripts of the process of discovering proofs. Our preliminary investigations have demonstrated the importance of “soft” aspects such as analogy and creativity, alongside deduction and proof, in the production of mathematics, and have given us new ways to think about the roles of people and machines in creating new mathematical knowledge. We discuss further investigation of these resources and what it might reveal. Crowdsourced mathematical activity is an example of a “social machine”, a new paradigm, identified by Berners-Lee, for viewing a combination of people and computers as a single problem-solving entity, and the subject of major international research endeavours. We outline a future research agenda for mathematics social machines, a combination of people, computers, and mathematical archives to create and apply mathematics, with the potential to change the way people do mathematics, and to transform the reach, pace, and impact of mathematics research.