It is no secret that AI is currently a hot subject – in politics, law and, of course, in investing. The idea here is right: this new technology may well revolutionize business after business and not paying attention to it would be folly. But there is an interesting question sitting at the edges of the current fervor with which we pursue artificial intelligence, and that is how we are structuring our investments in intelligence in general.
Computer science and engineering has brought us enormous value, and as artificial intelligence technologies start influencing the way that companies are organized and the business models – it takes time for technology to do so – it will become a massive competitive advantage, not least by enabling a higher pace of learning. At the same time we know that there are other kinds of intelligence that we are not investing as much in: human and natural intelligences.
Andrew Lo, respected economist and researcher at, among other places, MIT has suggested in a recent paper that we need a Brain Capital Grand Strategy. His observation is this:
Our current economy is indeed a Brain Economy—one where most new jobs demand cognitive, emotional, and social, not manual, skills, and where innovation is a tangible “deliverable” of employee productivity. With increased automation, our global economy increasingly places a premium on cerebral, brain-based skills that make us human, such as self-control, emotional intelligence, creativity, compassion, altruism, systems thinking, collective intelligence, and cognitive flexibility [1]. Investments in brain health and brain skills are critical for post-COVID economic renewal, reimagination, and long-term economic resilience.
Smith, E et al “A Brain Capital Grand Strategy: toward economic reimagination” Nature 26.10 2020
This may seem obvious, but it does raise the issue of how we, as a society, have balanced our investments in intelligence. That artificial intelligence is promising is not a reason to abandon ways of investing in natural, human intelligence – and hence, brains.
Especially since human intelligence is not a lower grade version of artificial intelligence, but rather entirely different. It has occurred to me, and many others, that we would be much better off if we categorized intelligence not as human and artificial, but as human, dolphin, bat – and looked at the different strengths – perhaps seeking to build artificial dolphin intelligence is much more interesting than replicating human intelligence? And in human intelligence we still know very little about the brain, and how it works and how it can be utilized. Another alternative woudl be to speak of biological and computational intelligences.
In a sense, the AI-project is dependent on this research as well, since the organizing metaphor for that work has now become neurological.
So seeking opportunities to invest in biological intelligence and brain research may not be such a bad idea.