Towards intellectual freedom in an AI Ethics Global Community

Abstract

The recent incidents involving Dr. Timnit Gebru, Dr. Margaret Mitchell, and Google have triggered an important discussion emblematic of issues arising from the practice of AI Ethics research. We offer this paper and its bibliography as a resource to the global community of AI Ethics Researchers who argue for the protection and freedom of this research community. Corporate, as well as academic research settings, involve responsibility, duties, dissent, and conflicts of interest. This article is meant to provide a reference point at the beginning of this decade regarding matters of consensus and disagreement on how to enact AI Ethics for the good of our institutions, society, and individuals. We have herein identified issues that arise at the intersection of information technology, socially encoded behaviors, and biases, and individual researchers’ work and responsibilities. We revisit some of the most pressing problems with AI decision-making and examine the difficult relationships between corporate interests and the early years of AI Ethics research. We propose several possible actions we can take collectively to support researchers throughout the field of AI Ethics, especially those from marginalized groups who may experience even more barriers in speaking out and having their research amplified. We promote the global community of AI Ethics researchers and the evolution of standards accepted in our profession guiding a technological future that makes life better for all.

Developing AI Literacy for Primary and Middle School Teachers in China: Based on a Structural Equation Modeling Analysis

“…Teachers should also recognize that the use of new technologies, such as AI, can greatly help to enable teaching and collaboration with all teachers, but there is an equal need to be concerned about the divide that AI can create that will widen the gap between peers in a class. In order to improve teachers' AI literacy, the choice of curriculum, contents, methods, and practice resources for special training should be diverse rather than conformist, as this may result in teachers' agency not being valued [70,71].…”

Outsider Oversight: Designing a Third Party Audit Ecosystem for AI Governance

“…Thirdly, there is acute potential for conflicts of interest with first or second party audits. For instance, Google researchers on the internal AI team were dismissed and blocked from publishing critiques on the large-scale language models [36,56], which would later be revealed to be critical to the company's future product roadmap [44,160,162]. Similarly, the warnings from Facebook researchers on addressing mounting bias issues and misinformation campaigns was reported to have been internally suppressed [116].…”

The emperor is naked

“…Whether it's for avoiding more robust regulation and attracting better employees, like it would be in the case of a company like Google (Voinea and Uszkai 2020), or for politicians to signal to the electorate that they care about Responsible AI (post-industrial democracies) or to make their opposition to Western democracies and their WEIRD morality (Haidt 2012) internationally known, it has become clear that we cannot solve a political problem with ethical ramifications (the regulation of AI) just by simply drafting codes of ethics and establishing moral bureaucracies. Even if we were to leave aside the classical criticism of bureaucracies and bureaucrats as being simply budget maximizers (Niskanen 1971;1994), an opaque ethical infrastructure that does not contribute to the development of moral and intellectual virtues for the individuals who actually work with AI (Constantinescu et al 2021) would be nothing more than a waste of both public and private resources, and with potentially deleterious consequences.…”