The $1 Trillion Question, Mortality in the Age of Generative Ghosts, Your Mind and AI, How to Design AI Tutors for Learning, The Imagining Summit Preview: Adam Cutler, and Helen's Book of the Week.
Magritte's "Son of Man" metaphor explores digital obscurity of reality. AI model collapse mirrors human isolation effects. Minds struggle without diverse input. Balancing AI benefits and genuine human connection crucial. Develop metacognitive skills to navigate this new landscape.
Generative AI promises personalized learning at scale but risks creating dependency. Complementary cognitive artifacts enhance skills; competitive ones replace them. Effective AI tutors balance engagement and autonomy, expanding human cognition without diminishing critical abilities.
Most decisions and most deciders are hybrids. Some machine, some human. The trick is to imagine all the ways that humans figure out ways around, over, and through the machine when what they really want is to make the decision themselves even if it means sacrificing accuracy.
AI-based decision-tools and data-driven decision-making is designed to reduce the variability of human decision-making. People assume that data offers an objective view of the reality and that an AI decision is rational. Decisions get easier with an objective and rational view of reality because the answer is apparent and incontestable. In reality, more data isn't necessarily more meaningful, it’s what someone has chosen to pay attention to, and what’s deemed rational depends entirely on the parameters people care about.
How would you expect individuals to react to a decision recommended by an AI? Would it depend on the context in which the AI made the recommendation? Or the level of confidence the AI expressed in the decision? Or the expertise of the person receiving the recommendation? The biggest factor in how people respond to AI-based decision-making is their own decision-making style.
Even when people are given identical AI inputs, people make entirely different choices. How people use input from AI depends on how they process information, how they regulate their emotions and behavior, and how urgent the decision is. Counter-intuitively, executives who are most rational and data-driven in their decision-making style can be the most likely to reject the algorithm. This is probably because they also place a high value on their own agency and autonomy. Conversely, executives who don’t like to make decisions and tend to procrastinate, are the most likely to delegate to AI, perhaps because it allows them shift responsibility to the machine.
The Artificiality Weekend Briefing: About AI, Not Written by AI
