Skip to Content

Reading the Mind

A 1961 essay speculated on where research into the physical basis of thinking and communication might eventually lead.
June 17, 2014

“Biologists of my generation have dealt effectively with two major problems: 1) the search for physical and mental health and the conquest of disease and aging; 2) the search for an understanding of the biochemical foundations of life. We are now beginning a third: the search for the physical basis of mind.

Technology Review cover from July 1961

To communicate with his fellows, man now transduces his thoughts to spoken or written symbols. These are reasonably satisfactory for simple messages, but inadequate for conveying complex conceptual ideas, human emotion, and spirit. Will biophysical research on mind pave the way for bypassing sensory mechanisms? It may not be unreasonable to imagine that this might eventually occur, perhaps at first requiring instrumental prosthetic aids. Pooling the diversity of individuals’ learning and endowments by such interpersonal communication could inaugurate a new hierarchy of intelligence and a new kind of science. Other implications of human interthinking as a new advance in evolution have been projected by Teilhard de Chardin and by other speculative thinkers.

All advances in our understanding of mental processes, as of other natural phenomena, are made through science, and therefore do not directly touch the ontological problem of the nature of the inner self. Implied here is no attempt by research or sheer intellectual genius to grasp reality by its quantized forelock, no suggestion that man’s mind is no more than a quantum mechanical automaton. On the contrary, even such revolutionary discoveries as are here projected would still be science, therefore susceptible, like all scientific endeavor, to beneficent application—but also to ultimate desecration!”

Excerpted from “Life, Science, and Inner Commitment,” by Francis O. Schmitt, in the July 1961 issue of Technology Review.

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

How scientists traced a mysterious covid case back to six toilets

When wastewater surveillance turns into a hunt for a single infected individual, the ethics get tricky.

The problem with plug-in hybrids? Their drivers.

Plug-in hybrids are often sold as a transition to EVs, but new data from Europe shows we’re still underestimating the emissions they produce.

Google DeepMind’s new generative model makes Super Mario–like games from scratch

Genie learns how to control games by watching hours and hours of video. It could help train next-gen robots too.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.