Thinking and Writing Skills Probably are Linked, but Not All Writing Requires Much Thinking

One concern often expressed about the use of language models is that when used as a substitute for a person’s own writing, critical thinking skills suffer. And, to be sure, lots of studies suggest there is a link between thinking and writing. 

My own view (as a former teacher) is that “people who do not write well do not think well.” So yes, substituting language models for one’s own writing is not helpful for purposes of building and maintaining critical thinking skills. 

Study	Focus	Key Findings	Source Link
Using Writing to Increase Critical Thinking Performance in General Education Biology	Examined the effect of a laboratory writing treatment on the critical thinking performance of biology students.	The writing group showed significant improvement in critical thinking skills, specifically in analysis and inference.	National Institutes of Health (NIH)
The Correlation between Critical Thinking and Writing Ability in English	Explored the relationship between critical thinking and writing ability among English educational program students.	Found a significant positive correlation between critical thinking and writing ability (r=0.362, p < 0.05).	ojs.fkipummy.ac.id
Relationship Between Perceived Students' Critical Thinking Skills and Academic Writing Skills	Investigated the connection between students' perceived critical thinking skills and their academic writing performance.	Found a strong positive correlation (r=0.722, p < 0.01).	ResearchGate
Cognitive ability influences on written expression	Tested models including the influence of cognitive abilities and general intelligence on writing skills in children and adolescents.	Showed that various cognitive abilities differentially influence writing skills and that these effects can vary by age.	ScienceDirect.com
Writing as a Thinking Tool - MSU Denver	Discusses the use of writing to develop various mental capacities, including critical thinking.	Highlights studies suggesting that writing improves critical thinking performance.	MSU Denver
Cognitive Styles and Influences on Academic Writing	Examined the impact of cognitive styles on writing performance.	Suggests that cognitive styles can influence writing performance.	ResearchGate
Learning through Writing: Teaching Critical Thinking Skills in Writing Assignments	Explores the role of writing-to-learn approaches in fostering critical thinking skills, particularly in the context of writing assignments.	Argues that writing can act as a "unique mode of learning," supporting the development of critical thinking abilities through the act of composition.	Cambridge University Press & Assessment
Critical Research Thinking: A Recipe for Academic Writing Success	Emphasizes the importance of critical research thinking for academic writing.	Highlights components of critical thinking as crucial for effective academic writing.	Qeios
Flower & Hayes Cognitive Process Theory of Writing	Explains writing as a cognitive process involving planning, translating, and reviewing.	Focuses on the mental processes behind writing.	Yomu AI
Cognitive and executive processes associated with children's written composition	Investigated the relationship between working memory, long-term memory, planning, and visuospatial perception and writing fluency and accuracy in children.	Found significant correlations between these cognitive processes and aspects of writing.	Ocnos
Understanding the Complex Relationship between Critical Thinking and Scientific Reasoning in Undergraduate Biology Students' Thesis Writing	Examined the connection between scientific reasoning in thesis writing and general and specific critical-thinking skills.	Found that scientific reasoning in writing is strongly related to inference skills.	National Institutes of Health (NIH)
Insight from the association between critical thinking and English argumentative writing among Chinese high school students	Explored the relationship between critical thinking and English writing achievement among Chinese secondary school students.	Found a positive linear correlation between critical thinking and English writing.	National Institutes of Health (NIH)
The link between writing and critical thinking	Discusses how writing facilitates critical thinking by requiring analysis, evaluation, and the development of arguments.	Suggests that writing can help identify knowledge gaps and motivate research.	The Science of Writing
The Writing and Critical Thinking Connection	Highlights the role of audience consideration, revision, and collaboration in developing both writing and critical thinking skills.	Suggests that the writing process encourages metacognition.	Learning A-Z
Why Critical Thinking in Writing Matters for Professionals	Explains the importance of critical thinking in various forms of professional writing.	Suggests that critical thinking helps in analyzing data, assessing risks, making informed decisions, evaluating sources, and constructing arguments in a professional context.	Instructional Solutions
Science of Reading: The Role of Writing (Brief 3 of 7)	Discusses the reciprocal relationship between reading and writing, emphasizing how writing improves critical thinking about texts.	Indicates that as students develop writing skills, they become stronger readers and develop critical thinking about authors' craft.	New York State Education Department (.gov)

On the other hand, not all writing is intrinsically related to critical thinking. Much marketing copy, messaging and simple written communications arguably don’t require much, if any, critical thinking. We might not ultimately find using language models for such purposes has any fundamental harm.

Winston Churchill Mobilizing the English Language

 How can you not love Winston Churchill?

Will AI Disrupt Internet Business Models?

One reason for studying the business implications of artificial intelligence is that we may be seeing a significant shift in the role played by near zero marginal cost in shaping feasible business and revenue models. 

We might all agree that near-zero marginal cost has been fundamental for content, social media and other app pricing and revenue models. Network effects and scale have been fundamental precisely because marginal cost has been so low. 

Low marginal cost arguably is responsible for “winner take all” market structures; the ability to support software products using advertising; the global character of markets and the importance of “time to scale.”

Marginal cost is the cost of producing one additional unit of a good or service. For non-tangible products such as software, streaming, or cloud services, this cost is often close to zero once the initial product is developed and infrastructure is in place. 

Low marginal cost means that digital businesses can grow a user base quickly without proportional increases in expenses. That is vital for businesses built on network effects, where each additional user increases the value for others (social networks, marketplaces).

Also, low marginal cost also means attackers can undercut incumbent pricing levels, often making higher margins on lower retail prices (“free” use and “freemium” models). 

Business Element	Traditional Business	Internet Business (Low Marginal Cost)
Cost per additional user	Increases with scale	Remains near zero with scale
Profit margin	Shrinks with volume	Grows with volume (after fixed costs)
Growth constraints	Physical/logistical	Virtually unlimited (digital)
Network effects	Limited	Strong, self-reinforcing

All that can enable a business model where adding more users means lower average cost per user as scale grows. That is less true for a traditional “physical” model, where cost tends to scale in a more-linear fashion. 

The implication is that AI possibly disrupts many foundational internet app, service and content models, where zero-to-low marginal cost is the economic foundation. 

The essential difference for AI-based models is that very-low marginal cost might not be so substantial.

Large language models incur non-trivial costs for training, inference, and maintenance that arguably are more linear cost drivers than we have gotten used to for many internet apps. 

Unlike traditional cloud-based internet delivered  software, where serving additional users involves negligible database or bandwidth costs, AI inference costs are directly proportional to user activity. 

On the hardware side, AI processing tasks arguably also involve data infrastructure requirements that also scale in a more-linear way. 

Traditional internet platforms might have marginal costs per user interaction estimated at $0.0001–$0.001, for example. 

AI services might have marginal costs per interaction closer to $0.01–$0.50, depending on model complexity and usage patterns.

The business model implications, if this gap does not close, is that AI model marginal costs could be higher by 100 times or more. 

And that could key implications for the value of scale and likely revenue models. Is the internet business model about to be disrupted?

AI is Clearly Disrupting Online Content Monetization

Some of us study AI because it is probably the next general-purpose technology and GPTs tend to transform economic life. GPTs also disrupt, as content creators learned from the development of the internet. It appears content creators once again will be in the forefront of those whose business models are again disrupted, this time by AI. 

The most obvious impact is the diminishing ability to support online content by advertising means. 

Quite Surprised a "Less Than" 100-Mbps Home Broadband Actually Works

Consumers can be quite price sensitive, especially for products that do not have high emotional resonance (sports gear, autos, clothing, fragrances, jewelry, sports teams, hobbies). In that regard, fixed wireless provides a good example. 

The tech geek in me loves symmetrical fiber to the home. It was my most-recent form of home broadband. But I’ve moved to a place that doesn’t have it. Sure, I’d rather have it. But I’ve also discovered that using a Wi-Fi connection (Comcast’s Xfinity) does a decent job for most of what I need. 

I’m not saying it is a permanent solution. But I am quite surprised that going from symmetrical gig to what seems to be no more than 100 Mbps downstream and a single-digit to low-double digits upstream actually works pretty well, to my shock. 

I wouldn’t have expected I’d be fairly satisfied with the vastly-different value prop. And the price-performance proposition is what strikes me as quite unexpected. 

The point is that lots of consumers who aren’t actually emotionally attached in any way to their home broadband connection probably will find that fixed wireless is a rational alternative to hybrid fiber coax or fiber to the home connections. 

Up to this point, I’d have argued that is the case for users who don’t spend lots of time on their connections (lighter or moderate users) or who don’t work from home. But I’m a heavy user and I do work from home. 

The caveats are that I wouldn’t be willing to make the same choice if there were multiple users on the same account, or if my children were still living with me. 

But for a single user, I am actually quite surprised that less than 100 Mbps downstream actually works. I wouldn’t have believed it.

Two Language Model Cases Decided This Week Bear on "Fair Use" of Copyrighted Material for Training

In the second of two “fair use” court cases involving language model training this week, a court has ruled that Meta did not infringe copyright when it used copyrighted book material to train its models. The latest decision, though, does turn on procedural grounds, not the core issue of whether copyrighted material is fair use under all circumstances, perhaps most notably when permission to use the materials for this purpose is absent. 

 

The prior decision upholding fair use of copyrighted material for model training was won by Anthropic. 

That copyright case also tested fair use law as it applies to reading books, which is essentially what model training involves. For humans, reading books is considered fair use, and not a copyright violation. It has been unclear whether an artificial intelligence model, reading books, also is fair use, or not. 

The case partially validates the idea of fair use for training purposes, without compensation or permission, even if in this case the court upheld Anthropic’s use of purchased books for training purposes. 

In other words, training AI on lawfully acquired copyrighted works was deemed fair use. 

Diversity of Thought is What Matters for Decision Making Advantages

Lots of studies of intellectual diversity suggest it helps with decision making. Conversely, one might argue, if all the members of a team, a company, a community or a group have the same points of view, then there really is not much diversity of thought, and the advantage of diversity is lost. That likely is true no matter the amount of gender, race, culture or other forms of physical diversity within groups that think the same. 

It’s the thinking; the intellectual diversity, that really matters. 

Study / Source	Researchers	Key Insight on “Diversity of Thought” for Problem-Solving	Year	Source
“Groups of diverse problem solvers can outperform groups of high-ability problem solvers”	Lu Hong & Scott E. Page (U. Michigan)	Cognitive-heuristic variety in a group beats sheer individual ability; “diversity trumps ability.”	2004	pnas.org
The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies	Scott E. Page (U. Michigan / Santa Fe Institute)	Formal models and real-world cases show perspective/heuristic diversity improves prediction, innovation, and collective accuracy.	2007	muse.jhu.edu
“How Diversity Makes Us Smarter” (Scientific American)	Katherine W. Phillips (Columbia Business School)	Exposure to socially or cognitively different others makes groups more diligent, creative, and accurate.	2014	scientificamerican.com
“Likes Attract: The Sociopolitical Groupthink of (Social) Psychologists”	Richard E. Redding (Chapman U.)	Lack of ideological diversity in psychology skews research agendas and peer review; calls for broader viewpoint inclusion.	2012	journals.sagepub.com
Team of Rivals: The Political Genius of Abraham Lincoln	Doris Kearns Goodwin (historian)	Lincoln’s intentionally ideologically mixed cabinet generated vigorous debate and better wartime strategy.	2005	ft.com
“Diversity in Teams: A Two-Edged Sword”	Katherine Y. Williams & Charles O’Reilly (Stanford)	Functional/cognitive diversity boosts creativity on non-routine tasks but can raise conflict—management practices determine net benefit.	1998 – 1999	psychologicalscience.org
“Political Diversity Will Improve Social Psychological Science”	Jonathan Haidt, José Duarte & Lee Jussim	Reviews evidence that viewpoint homogeneity fosters confirmation bias; argues political diversity strengthens methodology and theory.	2015	pubmed.ncbi.nlm.nih.gov
“Getting Unusual Suspects to Solve R&D Puzzles” (Harvard Business Review)	Karim R. Lakhani & Lars B. Jeppesen	Crowdsourcing to outsiders with varied backgrounds solves R&D problems stumping in-house experts—illustrates value of cognitive distance.	2007	hbr.org

Stablecoins for Retail Payments Face Consumer Value Challenges

The view that stablecoins might be a challenge to the Visa payment network if Amazon or Walmart create their own stablecoin payment systems is logical enough. Such payment systems would benefit the retailers by potentially lowering their payment transaction costs, currently represented by the interchange fees Visa earns when consumers pay using its affiliated bank cards. 

Stablecoins offer the potential advantage of lower transaction fees (typically under one percent compared to two percent to three percent for card processing. 

But what is not clear are consumer incentives to switch payment methods. There are, in other words, consumer “lock in" issues; incentives (cash back) for using the Visa system; switching costs; habits and complexity issues that will work against stablecoin usage. 

Consumers likely will not want to give up the “cash back” feature of using Visa-branded credit cards for payments. After all, that is a tangible benefit of using the cards, at no real cost, assuming all balances are paid off regularly, so that no finance charges are accrued. 

From a consumer's perspective, using a Visa card effectively means getting paid to spend money, while switching to stablecoins often means giving up that immediate financial benefit, unless merchants pass along some of their savings to consumers. But that weakens the business case for switching to stablecoin payment. 

The issue then is asymmetry in the value proposition: stablecoins benefit merchants but not consumers. 

Of course, retailers include the cost of payment system fees in the general pricing of all goods they sell, so the consumer benefit of “cash back” is offset by higher retail product costs. But those costs are hidden; the cash back benefit is obvious. 

So the stablecoin adoption process might initially focus on use cases where card rewards matter less, such as  peer-to-peer transfers, international remittances, or purchases where cards aren't accepted.