What is actually happening with AI and technology?

Agrawal, Gans, and Goldfarb build directly on Brynjolfsson and McAfee's The Second Machine Age analysis of digital technologies as general-purpose technologies, reframing AI specifically as a prediction technology rather than a general automation technology

Prediction Machines: The Simple Economics of Artificial Intelligence→ cites →The Second Machine Age

Lee directly engages with Brynjolfsson and McAfee's thesis from The Second Machine Age about technological unemployment, arguing their estimates are too conservative given China's rapid AI adoption and the speed of deep-learning advances

AI Superpowers: China, Silicon Valley, and the New World Order→ cites →The Second Machine Age

Addresses Harari's Homo Deus concern about algorithms knowing humans better than they know themselves, arguing this makes preference-learning AI both more feasible and more necessary to get right

Human Compatible: Artificial Intelligence and the Problem of Control→ cites →Homo Deus

References Kahneman's Thinking, Fast and Slow research on automation bias to show how caseworkers defer to algorithmic risk scores even when their own professional judgement suggests different conclusions

Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor→ cites →Thinking, Fast and Slow

Kearns and Roth engage critically with Domingos's The Master Algorithm vision of universal machine learning, arguing that the pursuit of predictive accuracy without fairness constraints produces socially harmful outcomes that technical solutions can address

The Ethical Algorithm: The Science of Socially Aware Algorithm Design→ cites →The Master Algorithm

Isaacson explicitly connects Leonardo to Jobs throughout the biography. Both figures combined art and technology, and Isaacson uses his earlier Jobs research to illuminate how Leonardo's "think different" approach mirrors Silicon Valley innovation.

Leonardo da Vinci→ cites →Steve Jobs

Tegmark directly engages with Bostrom's superintelligence scenarios, including the famous paperclip maximiser thought experiment. He builds on Bostrom's concerns while offering a more optimistic framework for AI alignment.

Life 3.0→ cites →Superintelligence

Bahcall explicitly distinguishes his "loonshots" framework from Christensen's disruption theory, arguing that what kills companies isn't disruptive technology but a failure to nurture fragile early-stage ideas.

Loonshots→ cites →The Innovator's Dilemma

Blank references Moore's technology adoption lifecycle and the chasm concept extensively in his market-type analysis

The Four Steps to the Epiphany→ cites →Crossing the Chasm

Tegmark references Domingos's Master Algorithm.

Life 3.0→ cites →The Master Algorithm

Algorithms to Live By references Kahneman on cognitive biases.

Algorithms to Live By→ cites →Thinking, Fast and Slow

Newport references McKeown's essentialism on intentional technology use.

Digital Minimalism→ cites →Essentialism

Humble references Pragmatic Programmer on automation.

Continuous Delivery→ cites →The Pragmatic Programmer

Olsen references Moore's technology adoption lifecycle.

The Lean Product Playbook→ cites →Crossing the Chasm

Alter draws on Kahneman's System 1 on addictive technologies.

Irresistible→ cites →Thinking, Fast and Slow