Preprinting in AI Ethics: Toward a Set of Community Guidelines
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Preprinting in AI Ethics: Toward a Set of Community Guidelines

In this edition of "Advances in Computing," one researcher takes stock of the benefits and challenges for the AI ethics field.

Also featured in this edition: two articles on the impact of generative AI on data annotation tasks and working with co-pilots, as well as selected stories from the ACM magazines Interactions and eLearn.

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The fast-moving, dynamic world of artificial intelligence (AI) stands in stark contrast to the slow-moving, conservative world of academia. This is particularly clear in the world of AI ethics, where in addition to the industry-academia contrast we also have the meeting of very different academic disciplines, including computer science, philosophy, ethics, and social sciences. The traditions, norms, and values of these disciplines are often at odds with one another, making interdisciplinarity challenging. Take, for example, preprinting, the practice of quickly disseminating research before potentially—but not necessarily—seeking publication in traditional academic journals. Interdisciplinary conflicts appear when, for example, researchers from a computer science background, where rapid publication of preprints on servers such as arXiv is the norm, meet researchers from the social sciences and humanities, where this is less common...

In this article I focus on the practice of preprinting, including the role and status of preprinting compared with traditional journal publication and other forms of dissemination, such as blogging and mainstream media contributions. Preprinting has many advantages, such as rapid dissemination of and feedback on ideas, openness, the bypassing of quarrelsome gatekeepers in the traditional publishing system, and the opportunity to publish novel ideas in new formats. In particular, it is often hailed as a beneficial practice for early-career researchers in need of quickly establishing a track record.

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Why Preprint?

There are many good reasons to preprint, and a quick review of the literature on preprinting in different disciplines shows clear similarities. In the following, I highlight some of the main benefits highlighted in the literature, followed by a brief discussion of how AI ethics researchers specifically might benefit from preprinting. The benefits are listed according to how often and how strongly they are reflected in the literature, with the most strongly emphasized ones discussed first. Here, I largely exclude the potential negative effects and costs related to preprinting, as these will be discussed in detail in the next section.

Speed and effective dissemination and feedback. A primary benefit of preprinting is that it allows for the rapid and effective dissemination of new ideas. Many blame the publishing system and the time-consuming process of peer review for the need to preprint to get one’s ideas out there more quickly. The challenges of lengthy peer review and low acceptance rates are more severe in the humanities than in other disciplines, some argue. Although peer review certainly has benefits, the peer-review system has been thoroughly criticized in the broader literature, where it is seen as essentially flawed, inconsistent, slow, and ineffective. Preprinting is seen by some as a partial solution, or at least a way to bypass this system. Rapid dissemination can also help researchers “maintain enthusiasm” for their work, as the traditional review process is so slow that it can make the work feel distant when revision and potential publication occur long after the ideas were generated and written about.

Scientific deliberation and wide review. Another major benefit pertains to how preprints can promote broad scientific deliberation, in which entire communities engage in reviews and examinations of early-stage research. Peer review often entails vetting by a very limited number of scholars, while preprints could, in theory, allow for vetting by a much larger audience. Peer review is often assumed to improve the quality of research and help identify good science, so one might expect that broader review processes could help improve science and foster researcher learning. The broad and rapid review that potentially ensues from preprints can also help quickly evaluate controversial results. For example, in 2023, a group of researchers released a preprint presenting a room-temperature superconductor—something that, if real, would have been a huge leap in science—generating massive activity and a number of replication efforts. This was soon followed by other preprints that seemed to have debunked the original paper. This all took place within the span of a couple of weeks. While these sorts of events might be assumed to promote an interest in science and generate awareness, it could also be argued that this preprint, and the hype surrounding it, was wasteful and unfortunate, and that a proper vetting by peers before publication would have prevented the whole situation.

The review process for preprints varies, and includes, for example, social media discussions, counter-preprints, or straightforward peer-review reports. The latter can be found in a range of services aimed primarily at the life sciences, such as eLife, Peer Community In, and Review Commons, but the mechanics of peer review could be developed equally well for AI-ethics-relevant servers. For example, PREreview, a preprint review service, also provides integration with arXiv.

Though broad review is a potential benefit of preprints, it must be noted that just posting a preprint comes with no guarantee that it will be widely reviewed or reacted to. Though some preprints get a lot of attention, the vast majority are likely not vetted in any meaningful sense.

Author empowerment and early-career researchers. Various stakeholders, such as researchers, funders, journals, and universities, can have different interests in and evaluations of research. Researchers are often touted as major beneficiaries of preprinting, with the literature emphasizing various forms of author empowerment. One benefit is that preprinting allows for self-archiving and both the documentation and dissemination of one’s work. It also potentially helps authors retain the rights to their research and control its use.

While researchers in general could see personal benefits from preprinting, the literature stresses the benefits for early-career researchers. Preprints can be used in resumes and job and grant applications, and can help papers get early citations. Furthermore, they help with visibility, networking, and catalyzing collaboration. In short, preprinting increases exposure to both scholarly and popular audiences.

Bypassing gatekeepers and the spread of novel work. Science could be argued to symbolize and promote liberal-democratic ideals, but it simultaneously challenges the same “through its exclusivity and elitism.” Though there are many different academic journals and outlets in which to publish, some argue that formal publication and peer review serve a problematic gatekeeping purpose that disqualifies novel work and ideas, null results, and certain formats and styles of research. They can also be a significant barrier to groundbreaking interdisciplinary work that will suffer when evaluated by specialists in established journals.10 Preprinting can therefore help researchers bypass gatekeepers and publish novel ideas, in both traditional and novel formats. Vuong, for example, offers several reasons to preprint, based on his own experience. One was that he and his coauthors disagreed with the reviewers and editors, deciding to preprint rather than compromise by revising the paper according to reviewer recommendations. Though gatekeeping and revision after peer review might improve the quality of research, they can also remove some of the original thinking found in preprints.

Open science and promoting access to knowledge. The notion of open science is increasingly prevalent in the research community. Preprinting can contribute to this by promoting access to, and potentially improving the quality of, science. Assuming that increased access allows more actual and potential researchers to join in scientific endeavors, one might expect an increase in quality. One might also, however, imagine a situation in which openness changes and possibly undermines community standards and quality assurance procedures, which could be detrimental to the quality of science.

Related to the costs and benefits of bypassing gatekeepers, preprinting can also help “democratize” science and scientific authority. Openness and free publication allow researchers to bypass the structural injustices prevalent in the publishing system, where the ability and willingness to pay to publish, for example, prevail. This system gives researchers from well-off institutions significant visibility benefits. It also entails that only one aspect of the open access ideal—access to published research—is achieved, while access to open publication is reserved for the privileged. Preprinting potentially eliminates this challenge and places everyone on more equal footing.

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More like this:

Crowdsourcing or AI-Sourcing?

Considering the impact of generative artificial intelligence on data annotation tasks.

As GenAI advances, humans will shift to auditors of AI-generated annotations, verifying labels and/or validating their correctness. The final step in this evolution is for humans to become observers, shifting to pure AI annotations (AIA), and even AI validations/verifications (AIV).

The Drunken Plagiarists

Working with co-pilots.

While help with proper code syntax is a boon to productivity (consider integrated development environments that highlight syntactical errors before you find them via a compilation), it is a far cry from semantic knowledge of a piece of code. Note that it is semantic knowledge that allows you to create correct programs, where correctness means the code actually does what the developer originally intended.

Interactions - All About HCI:

HCI for AGI

A research vision for the field of HCI in the AGI era, examining how HCI researchers can innovate in interaction techniques, interface designs, physical form factors, design methods, evaluation methods, benchmarking approaches, and data collection techniques.

The Inhuman Element: Lessons on Play and Creativity from the Rise of Generative AI

"Generative AI systems rob us of the joy in our work or the ability to work at all, before going on to rob players of the intent and meaning behind the games."


eLearn - Where Thought and Practice Meet:

Modeling Consumer GenAI for Enterprise L&D Applications: Demonstration of typical use cases

Some powerful use cases of GenAI in the L&D space.


Discover our past editions:

Investigating Research Software Engineering

"I Was Wrong about the Ethics Crisis"

Notice and Choice Cannot Stand Alone

Reevaluating Google’s Reinforcement Learning for IC Macro Placement

AI Should Challenge, Not Obey

The Myth of the Coder

Summer Special Issue: Research and Opinions from Latin America

New Metrics for a Changing World

Do Know Harm: Considering the Ethics of Online Community Research

Now, Later, and Lasting

The Science of Detecting LLM-Generated Text

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