The Atlantic's Books Briefing (April 7, 2023) reviews Sarah Bakewell's book Humanly Possible and frames it against recent developments in artificial intelligence. The article reports concerns that AI advancements threaten the primacy of "the faculties of the independent mind," and cites commentary about how generative models could accelerate conspiracism and disinformation, attributing those observations to The Atlantic. The piece quotes Eric Schmidt (who co-wrote a book with Henry Kissinger) saying, "the reason we're marching toward this technological revolution is it is a material improvement in human intelligence," and highlights an argument reported in the article that monetizing models risks privatizing what the author calls the "informational heritage of humanity."
The Atlantic's Books Briefing (April 7, 2023) reviews Sarah Bakewell's book Humanly Possible and situates its defense of humanism amid recent artificial-intelligence developments, per the article. The Atlantic reports that the piece raises worries that these advancements could upend the primacy of "the faculties of the independent mind," language the article uses to describe the stakes for intellectual personhood. The article also quotes Eric Schmidt saying, "the reason we're marching toward this technological revolution is it is a material improvement in human intelligence," and includes a reported observation that "Every chatbot is created by ingesting books and content that have been published on the internet by a huge number of people."
The article mentions ChatGPT and GPT-4 as exemplars of generative tools created from large corpora of published content, a factual framing reported by The Atlantic. Industry observers have repeatedly noted the same technical dynamic: large language models are trained on broad web and book corpora, which concentrates cultural artifacts into model outputs. This is an industry-pattern observation, not a claim about any single author's intent.
Editorial analysis: The Atlantic frames Bakewell's humanist argument as confronting both philosophical and social consequences of model-driven information flows. For practitioners, debates about ownership, attribution, and the cultural provenance of training data remain central to public conversations about model deployment and governance.
Editorial analysis: Observers should track how cultural critiques influence policy debates over data licensing, attribution standards, and disclosure for generative models, and whether those debates change industry practices around training-data provenance. The article is a cultural and literary critique as reported.
A cultural and philosophical treatment of AI from a 2023 books review – limited direct operational relevance for practitioners. Useful context for public discourse on data provenance and model training ethics, but not a technical or product event. Score kept at visibility floor given topic relevance to AI ethics discourse.
A 5-minute Tuesday brief on AI & data science. Curated, no fluff.
No spam. Privacy.
Practice interview problems based on real data
1,500+ SQL & Python problems across 15 industry datasets — the exact type of data you work with.
News on Let's Data Science is compiled from multiple public sources with editorial oversight. See our Editorial Standards and Corrections Policy.
Leave a Reply