Action is needed, and I invite you to join the public debate.
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Art plays a deep and meaningful role in shaping and inspiring individuals and societies.
It is difficult to foresee the cultural and philosophical implications of a future in which every piece of art is created by or with the help of AI systems.
Many people don't think about that, but doing nothing means that future generations will mostly be exposed to mass-scale, cheap-to-produce, AI-generated, and AI-assisted art.
We need specific POLICIES that encourage artists to continue investing their time, effort, ingenuity, and creativity in human-made projects, even if it takes them 1000x longer to produce art.
🚨 Human art simply CANNOT keep up with the pace of AI-generated art.
Dismissing the problem by saying "people will still prefer human art" ignores the massive dilution already underway.
If human art is not actively protected, it will become invisible and devalued.
This was one year ago.
Has Anthropic delivered?
👉 Read the paper: arxiv.org/pdf/2604.14807
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Sadly, this is happening everywhere:
"LLM fallacy: a cognitive attribution error in which individuals misinterpret LLM-assisted outputs as evidence of their own independent competence, producing a systematic divergence between perceived and actual capability."
The best way to get the most out of "AI for good" is to regulate AI to control, prevent, and oversee capabilities, features, and use cases that could cause harm.
Unregulated AI is both dangerous and bad for progress.
👉 Read my article on NY's pro-human AI laws (and join my newsletter's 94,000+ subscribers) here: www.luizasnewsletter.com/p/new-yorks-pro-human-ai-laws
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- S8420A (“to require disclaimers when commercial content contains a synthetic performer”).
There is also a recently proposed NY bill that takes the pro-human approach to a previously unimagined level.
- The RAISE Act (“to require safety reports for powerful frontier AI models in order to limit critical harm”);
- S8391 (“to generally prohibit the use of a digital replica of a deceased personality’s voice or likeness in an expressive audiovisual work without prior consent”);
🚨 BREAKING: The state of New York is emerging as a global LEADER in pro-human AI laws.
In December 2025 alone, NY enacted:
You can learn more about AI's regulatory challenges (and join 94,000+ subscribers) here: www.luizasnewsletter.com
I cannot emphasize enough how important legal professionals are in the public AI debate.
So many AI predictions reflect FULL ignorance of social science perspectives and how regulation works.
AI is a product, and there are many governance tools available to keep it in check.
👉 Watch our full conversation (and join my newsletter's 94,000+ subscribers) here: www.luizasnewsletter.com/p/regulating...
🚨 I spoke with Prof. Florence G'sell, author of the 470-page report “Regulating Under Uncertainty: Governance Options for Generative AI,” about AI risk, regulatory trends, the Digital Omnibus, AI litigation in the U.S., China, and more.
Watch our 54-minute conversation below:
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🚨 Our AI Book Club reached 5,400+ members and 36 books! To dive deeper into AI, start here (link below):
👉 Read my article (and join 93,700+ subscribers) here: www.luizasnewsletter.com/p/shaping-pr...
🚨 As AI narratives change to escape scrutiny, pro-human AI policies, rules, and rights must also advance.
Most people haven't realized, but policies that propose "special status for AI" and "parallel coexistence between humans and AI" are essentially anti-human.
My article:
Every company's marketing strategy in 2026:
👉 Download the full document: hai.stanford.edu/ai-index/202...
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15. AI experts and the public have very different perspectives on the technology’s future, and global trust in institutions to manage AI is fragmented.
14. AI sovereignty is becoming a defining feature of national policy, but capabilities remain uneven, even as open-source development helps to redistribute who participates.
13. Formal education is lagging behind AI, but people are learning AI skills at every stage of life.
12. AI is transforming clinical care, but rigorous evidence remains limited.
11. AI models for science can outperform human scientists, though bigger models do not always perform better.
10. AI’s environmental footprint is expanding alongside its capabilities.
9. Productivity gains from AI are appearing in many of the same fields where entry-level employment is starting to decline.