I wrote an invited article—effectively an updated synopsis of my book—for the Journal of Analytical Psychology. It was published in the November 2022 Special Issue Our Environmental and Climate Crisis, and you can access it online here free of charge. It can be cited as follows:
Fellows, A. (2022) Gaia, psyche and deep ecology. J Anal Psychol, 67: 1232– 1256. https://doi.org/10.1111/1468-5922.12858.
Two books published this year that are definitely worth reading are Defiant Earth by Clive Hamilton and Weapons of Math Destruction by Cathy O’Neil (full citations in Resources).
Hamilton, a Professor of Public Ethics, describes his book as “groping towards an understanding of what it means after 200,000 years of modern humans on a 4.5 billion-year-old Earth to have arrived at this point in history, the Anthropocene.” (p.vii) His call for a “new anthropocentrism” argues that unique power brings unique responsibility but, in my opinion, goes too far in rejecting the more biocentric world view of deep ecology. According to my own thesis, this is because he doesn’t take the unconscious into account. I am nonetheless in agreement with almost all of his unflinching analysis as far as it goes, and wonder whether our differences can be attributed to the old adage “If you only have a hammer, everything looks like a nail.” In other words, Hamilton uses the tools and language of his discipline (moral philosophy), I use those of mine (depth psychology). I truly admire his courage and honesty for writing “How to finish a book like his? I don’t know; it’s too hard, too uncertain, too new.” (p.157) Perhaps my forthcoming book can help…
O’Neil, a former quant, has surely come up with one of the best titles of the year! The subtitle, “how big data increases inequality and threatens democracy” prepares the reader for a chilling exploration of the arcane world of algorithms and models, in which the latter are succinctly described as “opinions embedded in mathematics.” (p.21) This is for me a crucial observation. Among the many revelations of her survey, perhaps the most surprising and disturbing to me was her convincing demonstration that even models created with positive social intentions can, through unchecked feedback, become self-reinforcing with toxic consequences. O’Neil clearly knows her stuff, and can communicate it intelligibly. It has been said, only partly in jest, that “mathematicians assume everything except responsibility”; this book is a welcome and timely exception.