Devin Guillory, Combatting Anti-Blackness in the AI Community (The Ethics of AI in Context)

The speaker begins by expressing excitement about discussing recent efforts to combat anti-blackness in the AI community. They emphasize the importance of addressing the extrajudicial killings of Black people, which have occurred for as long as living memory. The speaker references historical events such as the Appaloosa massacre and the Charleston church shooting, highlighting the continuous violence against Black people. They mention the rise of movements like Black Lives Matter and the global protests that have brought attention to police brutality and systemic anti-blackness. The speaker identifies themselves as an AI researcher and someone who actively fights against anti-blackness, noting the challenge of answering the question, 'What can I do to help?'

The speaker delves into the difficulty of answering what actions can be taken to combat anti-blackness, acknowledging the complexity of the question. They suggest extreme measures such as quitting one's job to volunteer full-time for civil rights organizations, but recognize this is not practical for most. Instead, they propose a more hands-on approach, suggesting personalized discussions about how individuals can contribute effectively. The speaker also addresses the limitations of reading books and the need for direct action. They introduce their own solution: writing a piece on combating anti-blackness in the AI community, aiming to guide people in making positive contributions.

The speaker presents a framework to understand the mechanisms that enable anti-blackness, emphasizing that anti-black racism affects every aspect of society. They challenge the audience to consider areas where it may not seem to impact, and assert that anti-black racism is pervasive. The speaker lists various sectors impacted by anti-black racism, including healthcare, education, criminal justice, and more. They argue that the burden of addressing these broken systems falls disproportionately on Black people, highlighting the theft of time as a significant issue.

The speaker breaks down the systems contributing to anti-black racism into three categories: physical resources, social resources, and measures. They discuss the disparities in access to physical resources like wealth, healthcare, and technology for Black people. The speaker also addresses the importance of social resources, such as networks and relationships, in accessing opportunities and the role they play in AI. Lastly, they critique measures used to evaluate individuals, suggesting that many are biased against Black people, from criminal justice to hiring practices.

The speaker calls for a focus on enacting change in areas where individuals have power, emphasizing the need to 'clean up your own house' first. They argue that the burden of fixing systemic racism should not fall solely on Black people. The speaker suggests supporting those already working on these issues and being mindful of how physical resources, social resources, and measures are involved in new initiatives. They also discuss the importance of retention and promotion of Black individuals in organizations and the need to scrutinize evaluation processes for bias.

The speaker critiques the binary approach to valuing diversity efforts, arguing for a more nuanced evaluation that considers the depth and impact of such work. They highlight the challenges Black people face in organizations, such as being forced to choose between diversity work and career advancement. The speaker also discusses the consequences of failed diversity efforts and the need to value and act on the findings of diversity initiatives. They emphasize the importance of protecting Black employees and colleagues and being prepared to defend them against unwarranted attacks.

The speaker addresses the role of academia in perpetuating anti-blackness, noting that any issues present in academia will quickly spread throughout the community. They question the admissions process's goal of assessing research potential and highlight the biases in traditional measures like GPA, letters of recommendation, and research publications. The speaker calls for more transparency and accountability in the selection processes for mentoring and collaboration, urging academia to interrogate its practices and strive for a more equitable environment.

The speaker discusses the challenges in measuring faculty potential and the need for more equitable hiring practices. They question the reliance on traditional sources of faculty hires, such as the same top CS universities, and the impact this has on diversity. The speaker also addresses the financial sacrifices required for professional advancement, particularly in academia, and how this disproportionately affects Black talent. They call for changes in the system that would benefit Black people and allow for a more diverse and inclusive academic community.

In conclusion, the speaker emphasizes the importance of starting with oneself and focusing on areas where one has power to effect change. They encourage empowering those already working on combating anti-blackness and suggest that solutions are not mysteries but require will and effort. The speaker reiterates the need for a collective push for change within the AI community and beyond.