Chapter 20 Further Reading: Writing and Editing with AI

Research and Empirical Studies

"Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence" Noy, S., & Zhang, W. (2023). Science, 381(6654), 187-192. The MIT study referenced in this chapter. Examines AI writing assistance effects across skill levels in a controlled experiment. Finds 37% speed improvement and convergence of quality between higher- and lower-skilled writers. Essential reading for understanding the evidence base for AI writing assistance. Freely available via MIT economics working paper series.

"ChatGPT as a Writing Assistance Tool: A Systematic Review" Available via Google Scholar, multiple 2023-2024 publications. A growing body of systematic reviews examines AI writing assistance in educational and professional contexts. Look for reviews that distinguish between productivity effects and quality effects — they often diverge.

"Reading Between the Lines: How Readers Perceive AI-Generated Text" Multiple studies from 2023-2024 examine human ability to detect AI-generated text and the credibility effects of AI-generated labeling. Search for "AI text detection reader perception credibility" in Google Scholar for current literature.

Books on Writing Craft (Pre-AI, But Foundational)

"On Writing Well" by William Zinsser HarperCollins, 2006 (7th ed.). The classic guide to nonfiction writing. Zinsser's principles — clarity, brevity, specificity — are the standards against which AI writing assistance should be measured. Understanding what good writing is, at the craft level, makes you a better director of AI writing tools.

"Bird by Bird" by Anne Lamott Anchor Books, 1995. The concept of the "shitty first draft" — the idea that first drafts are supposed to be rough — is directly relevant to AI-assisted writing. AI doesn't generate perfect first drafts; neither do human writers. Lamott's framework normalizes the edit-heavy relationship with drafts that makes AI collaboration productive.

"Style: Lessons in Clarity and Grace" by Joseph Williams and Joseph Bizup Pearson, 2013 (12th ed.). A rigorous treatment of prose style at the sentence level. Provides the technical vocabulary for evaluating what AI does well and poorly in line editing — sentence construction, nominalization, old-before-new information flow.

Practical AI Writing Resources

Anthropic's Claude Prompt Library Available at anthropic.com. Contains curated examples of effective prompts for common writing tasks, including document summarization, style transformation, and content generation. The library is updated periodically as new use cases are documented.

"The AI Writing Assistant Handbook" (Various publishers, 2024) Multiple practical guides to AI writing tools have been published by industry practitioners. Look for editions published in 2024 or later that cover current model capabilities. Earlier editions may describe tools that have been significantly updated.

On Voice and Style

"The Elements of Style" by William Strunk Jr. and E.B. White Allyn and Bacon, 2000 (4th ed.). Still valuable as a compact statement of principles. White's additions to Strunk's original are particularly relevant to voice — his discussion of individuality in style articulates what is at stake when AI voice bleed erases distinctiveness.

"Several Short Sentences About Writing" by Verlyn Klinkenborg Vintage, 2013. A radical treatment of the sentence as the fundamental unit of writing craft. Klinkenborg's approach to revision — reading every sentence in isolation, testing whether it is truly doing something — is an excellent method for detecting AI padding and AI voice in your own edited work.

On Professional Writing and Genre

"The Pyramid Principle" by Barbara Minto Prentice Hall, 2002. The foundational guide to consulting report structure, referenced in the Elena scenario. Minto's SCQA (Situation-Complication-Question-Answer) framework is the structural standard that Elena is working within — and that AI can apply when explicitly prompted to do so.

"Writing That Works" by Kenneth Roman and Joel Raphaelson HarperBusiness, 2000 (3rd ed.). Focused on business and professional writing — memos, emails, reports, presentations. Roman worked at Ogilvy and the business writing examples are grounded in high-stakes professional contexts. Useful for developing the quality standard against which AI writing assistance should be evaluated.

On Attribution and Disclosure

"AI Content Disclosure Guidelines" — Various Professional Organizations The Society of Professional Journalists, the American Psychological Association, and multiple academic publishers have published AI disclosure guidelines. Search for your specific professional organization's most current guidance, as these are updated frequently.

Chapter 33 of this textbook The full treatment of attribution, disclosure, and the ethics of AI-assisted professional work. Recommended reading after completing Chapter 20.

Tools Referenced in This Chapter

Grammarly — grammarly.com AI-powered proofreading and style checking. The free tier catches grammar and spelling. The premium tier adds style, tone, and clarity suggestions. Useful for the proofreading stage; less appropriate for line editing where AI voice suggestions can conflict with your own stylistic choices.

Hemingway Editor — hemingwayapp.com Readability analysis that flags passive voice, adverb overuse, and complex sentences. Useful as a diagnostic tool for evaluating AI-generated prose and for identifying where line editing is needed. Does not generate text — it only evaluates.

Claude — claude.ai Anthropic's AI assistant. Well-suited for multi-step writing workflows, long-context document work, and nuanced editing instructions. The extended context window (up to 200,000 tokens in some versions) makes it particularly useful for long-form content collaboration.