What happens when artificial intelligence allows us to see, hear, and even converse with loved ones who have died? In this episode of AnthroIntelligence: Culture, Cognition, and Code, I explore how AI is transforming the ways we remember, mourn, and maintain emotional connections with those who are no longer with us.

From AI-generated family reunions shared during Undas to griefbots and digital ghosts that simulate conversations with the deceased, technology is introducing new possibilities for remembrance. Drawing on anthropology and the psychology of continuing bonds, this episode examines the emotional meaning of these synthetic encounters, alongside questions of identity, consent, and the commercialization of grief.

AI may recreate a familiar face, imitate a beloved voice, or generate the conversation we never had. But resemblance is not identity, and simulation is not continued existence. As technology offers new ways to hold on a little longer, we must ask whether these digital encounters help us live with loss or make it harder to accept that someone is truly gone.

📖 Read the full Author’s Cut here.

#AnthroIntelligence #AIandGrief #DigitalAfterlife #Griefbots #ContinuingBonds #DigitalRemembrance

What happens when artificial intelligence begins finding answers to questions that scientists have spent years investigating? In this episode of AnthroIntelligence: Culture, Cognition, and Code, I explore how AI is transforming scientific research by detecting patterns, generating hypotheses, and exploring possibilities at speeds that challenge traditional approaches to discovery.

From Google DeepMind's advances in mathematics, protein structures, genomics, and materials science to AI-assisted cancer detection and antibiotic research, machines are expanding the boundaries of what scientists can investigate. But finding a pattern is not the same as understanding it. Predictions still require validation, correlations demand explanation, and discoveries acquire significance only through evidence and interpretation.

As AI compresses years of scientific exploration into increasingly shorter cycles, the human role may shift from finding patterns to determining what they mean. The future of research may not be about who discovers an answer first, but who can explain why that answer matters.

📖 Read the full Author’s Cut here.

#AnthroIntelligence #AIResearch #ScientificDiscovery #PatternRecognition #AIandScience #HumanInterpretation

What happens when artificial intelligence can generate scientific claims faster than humans can evaluate them? In this episode of AnthroIntelligence: Culture, Cognition, and Code, I explore how AI is entering not only the practice of science, but the social machinery through which scientific knowledge becomes trusted.

From AI-assisted mathematical proofs and automated verification to the accelerating flood of preprints, artificial intelligence is lowering barriers to producing, testing, and circulating research. But science has never been simply a collection of correct answers. It is a human system of observation, criticism, replication, evidence, and collective judgment.

As machines become increasingly capable of generating hypotheses, checking arguments, and synthesizing entire literatures, the bottleneck of science may shift from discovery to evaluation. AI can help determine whether an argument follows formal rules. It cannot decide whether a question matters, whether an assumption is justified, or whether a result deserves our trust.

The future of science may therefore depend less on our ability to produce knowledge than on something much older—and harder to automate: deciding what counts as true.

📖 Read the full Author’s Cut here.

#AnthroIntelligence #AIandScience #ScientificKnowledge #FutureOfScience #Epistemology #ScientificTrust