Intelligent Design Icon Intelligent Design

Marcos Eberlin: How Foresight Builds on Past Arguments for Intelligent Design

When renowned Brazilian chemist Marcos Eberlin was in Seattle recently he sat down with me to answer a few questions about his new book, Foresight: How the Chemistry of Life Reveals Planning and Purpose, which comes trailing endorsements from three Nobel laureates. I asked how his own presentation of intelligent design differs from how ID proponents have framed the case in the past:

He briefly touches on arguments from specified complexity and biological information, and notes that his concept of “foresight” both builds on and advances them.

The idea is that life and the cosmos were evidently designed by a mind with the ability to look forward, toward the future, and anticipate problems which could then be addressed before they come up. The solutions prove, again and again, to be both “proper” and “ingenious.” Only a mind, not a mindless process like Darwinian evolution, is capable of that.

David Klinghoffer

Senior Fellow and Editor, Evolution News
David Klinghoffer is a Senior Fellow at Discovery Institute and the editor of Evolution News & Science Today, the daily voice of Discovery Institute’s Center for Science & Culture, reporting on intelligent design, evolution, and the intersection of science and culture. Klinghoffer is also the author of six books, a former senior editor and literary editor at National Review magazine, and has written for the Los Angeles Times, New York Times, Wall Street Journal, Washington Post, Seattle Times, Commentary, and other publications. Born in Santa Monica, California, he graduated from Brown University in 1987 with an A.B. magna cum laude in comparative literature and religious studies. David lives near Seattle, Washington, with his wife and children.

Share

Tags

biological informationBrazilChemistrycosmosDarwinian evolutionforesightintelligent designlifeMarcos Eberlinmindmindless processesNobel PrizeplanningproblemspurposeSeattlesolutionsspecified complexity