Does ‘Book Slop’ = AI was used, or that it’s bad material that AI created? If an author uses AI to tighten up some of the writing, or to help bounce ideas, but the material is essentially theirs, then I’m not sure anyone should be annoyed by that. I’d also point out that tools like Pangram are not perfect tools when analyzing writing.
You fell for the Chakrabarty paper, characterized by its "mathiness", and have amplified it with convincing-looking charts of your own. Now with 138 Likes and 4 Restacks, the poorly posited allegations spreads.
The paper appears to be aching, alongside others by the same author(s), to prove damages under copyright’s fourth fair-use factor, the "effect upon the potential market or value of the source works." The damage is in fact illusory (or, at least, a fraction of what is being claimed). Here's the background that largely disproves the paper's assertions: https://thefutureofpublishing.com/2026/07/is-ai-flooding-the-market-for-books-and-diluting-their-value/
Artificial intelligence is changing biological research, it allows scientists to analyze genomes, predict protein structure and rapidly develop vaccines or drug discoveries. However, AI can also be used for creating biological sequences or making them even better for biological research. This capacity led to important decisions about biosecurity, ethics and governance.
So, AI for biological research has not been called into question it has become commonplace. The issue to focus on is on how humanity puts that technology to its best use.
The opportunity
With artificial intelligence, researchers are now able to speed up discovery of vaccine and therapies, improve surveillance and prediction of disease outbreak, analyze large biological sequences at incredible speed, design and engineer new enzymes and proteins for different use including medicine or for new generation enzymes and proteins to serve the personalized medicine industry.
The risk and challenge
However, the increasing capabilities of AI are coupled with significant risks that include:
Misuse of biological design tools. Cyber-security risks targeting biotechnology infrastructure. Lack of unified biosecurity standards across different regions. Fast scientific pace and thus a gap between the state of the technology and governance frameworks. Lack of transparent governing and research practices.
The importance of this observation remains that, though the capacity for AI-created biological design is already remarkable, creating real pathogens for practical use would involve substantial scientific, technical, regulatory and safety obstacles. Notwithstanding the above, its potential to be misused remains a real concern for both researchers and policymakers.
Future strategy
Science and Innovation + Biosafety + Ethics in Governance + International Cooperation + Responsible AI = Responsible use of Biotech
The future priorities
Enhance global biosecurity collaboration and communication. Create stringent governing rules for advanced AI supported biological research. Develop rapid diagnostics, vaccines and public health readiness. Make laboratories and essential health infrastructure cyber-secure. Foster ethical AI development through auditable processes and transparent use. Enhance both biosafety and AI governing knowledge training and education.
Looking at the future
AI is extremely beneficial for global health, however, its benefits are contingent on adequate governing and responsible guidance. Scientists and researchers aimed at fostering advancements in medicine, public health and scientific discoveries while curtailing the possible risks of being abused.
Artificial intelligence future in biology should not only focus on the speed of advancements for scientific discovery. It should also encompass how mankind can implement safeguards, structures and global cooperation to ensure science and its outcomes be utilized for everyone's benefit.
Does ‘Book Slop’ = AI was used, or that it’s bad material that AI created? If an author uses AI to tighten up some of the writing, or to help bounce ideas, but the material is essentially theirs, then I’m not sure anyone should be annoyed by that. I’d also point out that tools like Pangram are not perfect tools when analyzing writing.
You fell for the Chakrabarty paper, characterized by its "mathiness", and have amplified it with convincing-looking charts of your own. Now with 138 Likes and 4 Restacks, the poorly posited allegations spreads.
The paper appears to be aching, alongside others by the same author(s), to prove damages under copyright’s fourth fair-use factor, the "effect upon the potential market or value of the source works." The damage is in fact illusory (or, at least, a fraction of what is being claimed). Here's the background that largely disproves the paper's assertions: https://thefutureofpublishing.com/2026/07/is-ai-flooding-the-market-for-books-and-diluting-their-value/
Normalize using ai to write.
Thank God we are finally getting serious about defense.
Artificial intelligence is changing biological research, it allows scientists to analyze genomes, predict protein structure and rapidly develop vaccines or drug discoveries. However, AI can also be used for creating biological sequences or making them even better for biological research. This capacity led to important decisions about biosecurity, ethics and governance.
So, AI for biological research has not been called into question it has become commonplace. The issue to focus on is on how humanity puts that technology to its best use.
The opportunity
With artificial intelligence, researchers are now able to speed up discovery of vaccine and therapies, improve surveillance and prediction of disease outbreak, analyze large biological sequences at incredible speed, design and engineer new enzymes and proteins for different use including medicine or for new generation enzymes and proteins to serve the personalized medicine industry.
The risk and challenge
However, the increasing capabilities of AI are coupled with significant risks that include:
Misuse of biological design tools. Cyber-security risks targeting biotechnology infrastructure. Lack of unified biosecurity standards across different regions. Fast scientific pace and thus a gap between the state of the technology and governance frameworks. Lack of transparent governing and research practices.
The importance of this observation remains that, though the capacity for AI-created biological design is already remarkable, creating real pathogens for practical use would involve substantial scientific, technical, regulatory and safety obstacles. Notwithstanding the above, its potential to be misused remains a real concern for both researchers and policymakers.
Future strategy
Science and Innovation + Biosafety + Ethics in Governance + International Cooperation + Responsible AI = Responsible use of Biotech
The future priorities
Enhance global biosecurity collaboration and communication. Create stringent governing rules for advanced AI supported biological research. Develop rapid diagnostics, vaccines and public health readiness. Make laboratories and essential health infrastructure cyber-secure. Foster ethical AI development through auditable processes and transparent use. Enhance both biosafety and AI governing knowledge training and education.
Looking at the future
AI is extremely beneficial for global health, however, its benefits are contingent on adequate governing and responsible guidance. Scientists and researchers aimed at fostering advancements in medicine, public health and scientific discoveries while curtailing the possible risks of being abused.
Artificial intelligence future in biology should not only focus on the speed of advancements for scientific discovery. It should also encompass how mankind can implement safeguards, structures and global cooperation to ensure science and its outcomes be utilized for everyone's benefit.