About the Journal
GRACE: Global Review of AI Community Ethics is a new peer-reviewed, international journal at Stanford University, funded by the NSF. An open-access journal, indexed in Google Scholar, GRACE offers a unique intellectual forum for AI Ethics practitioners to share their work.
GRACE welcomes journal papers on the social impact of AI as well as global frameworks that draw from western and non-western ethics.
The journal also accepts Research Notes, Reviews, and Commentary. From time to time, there are special issues devoted to a particular topic. Submissions are open to the Stanford community as well as scholars at other institutions.
Types of Papers
Social Impact Papers
GRACE welcomes social impact papers describing ethical issues with any aspect of Artificial Intelligence and Machine Learning. A paper should include a convincing motivational discussion and argument, articulate the relevance of the argument to AI/ML, describe the scientific and social impact of the work, include all relevant proofs and/or experimental data, and provide a thorough discussion of connections with the existing literature.
GRACE caters to a broad readership. Papers that are heavily mathematical in content are welcome but should include a less technical high-level motivation and introduction that is accessible to a wide audience and explanatory commentary throughout the paper.
Typical manuscript length is 3000-5500 words.
Framework papers investigate a diverse spectrum of ethical approaches and problems, including the current limitations of frameworks in AI governance. GRACE welcomes reflections on western and non-western frameworks. Papers must also be free of excessive philosophical jargon and define terms clearly for a non-philosophical audience.
Typical manuscript length is 1000-1800 words.
Research Notes and Commentary
The Research Notes and Commentary section of GRACE will provide a forum for short communications that cannot fit within the other two paper categories. The maximum length should not exceed 1000 words. Some examples of suitable Research Notes include, but are not limited to the following: op-eds, interviews, concise technical research aimed at other specialists; a detailed exposition of a relevant theorem or an experimental result and its ethical implications.
GRACE invites students to review important existing and emerging research areas, reviews of topical and timely books related to AI, and substantial, but perhaps controversial position papers that articulate ethical issues of interest in the AI research community.
Grace podcasts are conducted by journal mentors Dr. Harriett Jernigan and Dr. Brittany Hull, as well as Linda Denson and Tyah-Amoy Roberts. Podcast submissions are by invitation only.
Possible topics for our first GRACE issue include but are not limited to:
- Biased predictions and the disproportionate impact of AI on historically marginalized communities
- Problems of large language models like GPT-3
- Language models and their lack of interpretability
- Structures of power in the tech industry that affect researchers from marginalized communities
- Lack of diversity in industry and academia among developers of AI models, and lack of focus on problems unique to individuals from marginalized communities
- AI Governance and third party oversight of tech
- Uses of biomedical ML and adjusting for race
- Non-Western ethical and philosophical approaches help understand AI
- Computer vision and gender and race metrics
- AI STEM education and access for first-gen low-income students
- Can AI be designed to promote specific human values?
The submission process has two steps. First submit a 250 word abstract. All manuscripts will go through the standard double-blind peer-review process according to GRACE guidelines.