Distill Hiatus

· Source: Distill · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation, Software Development & Engineering · Depth: Intermediate, medium

Summary

The Distill journal, known for publishing interactive and visually rich scientific articles, is taking a one-year hiatus, potentially indefinitely. After five years, the editorial team concluded that operating as a journal created structural friction and led to volunteer burnout, hindering their focus on core aspects of scientific publishing. Distill no longer believes its journal status significantly influences how institutions perceive non-traditional publications or that a venue is the primary bottleneck for authors. Instead, its impact stemmed from author mentorship, the open-source Distill template, editor-authored articles, and community building. The team now advocates for self-publication, citing tensions between mentorship and editorial roles, editor articles and journal neutrality, and the overhead of traditional peer review. Existing articles under review are unaffected, and authors can continue using the Distill template for self-publishing or submission to alternative venues like VISxAI.

Key takeaway

For AI Scientists developing and disseminating non-traditional scientific explanations or interactive articles, recognize that journal publication may not be the most effective path for impact or career advancement. Focus on producing high-quality content and leveraging self-publication platforms or specialized venues like VISxAI. This approach can reduce friction, accelerate dissemination, and allow for greater innovation in presentation format, aligning incentives more effectively than traditional journal models.

Key insights

Journal structures can impede scientific communication goals, favoring self-publication for many non-traditional articles.

Principles

Method

Distill's approach involved providing extensive mentorship, an open-source template, and fostering a community, rather than relying on its journal status for impact.

In practice

Topics

Code references

Best for: AI Scientist, AI Researcher, Research Scientist, AI Product Manager

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Editorial summary, takeaway, and curation by AIssential. Original article published by Distill.