Human + Artificial Intelligence: how to avoid overreliance on logical thinking

Today, we are living a new wave of Artificial Intelligence (AI) that started in the 2010s with the introduction of Deep Learning; since then, artificial neural networks reached outstanding results with a number of artificial neurons similar to the number of neurons in human brain. Even if AI is delivering exceptional results on some use cases (including complex ones like natural language understanding and protein folding), it goes without saying that AI is not able to replace human intelligence while outstanding opportunities and new capabilities may emerge from human-machine cooperation.

Among the different theories about human-machine cooperation, there is the one on collective intelligence which has been widely deepened by professor T.W. Malone at MIT; such a theory is aimed at describing the group intelligence that emerges from collaboration, collective efforts, and competition of many actors being either human or artificial.

While Artificial Intelligence is aimed at reproducing logical thinking and solve problems that can be formalized from a mathematical point of view, what are the characteristics that human brain can bring to the human-machine collective intelligence? What are the ways of thinking that human beings are using beyond logical thinking?

While trying to delve into human brain, I stepped into the “Neuroscience for Business”?course of MIT held by professor Tara Swart. Certainly, I am not an expert, but I would like to share few impressive points regarding human brain functioning patterns that are highlighting its capabilities and how it can deeply contribute to human-machine collective intelligence...

How humans decides: a whole-brain approach

“The illiterate of the 21st century won’t be those who can’t read and write. It will be those who can’t learn, unlearn, and relearn.” (Alving Toffler)

Most of the MIT course on neuroscience is based on exploring all the aspects of the Brain Agility Model, i.e., the human ability to switch between these different ways of thinking as humans, namely think, plan, learn, manage, ideate, and strategize (i.e., facing all the most advanced cognitive functions of human beings). Brain agility model indeed maps the different pathways that we have available to access such different ways of thinking.

According to this model , there are six different ways of thinking that can be concurrently adopted by human beings and they leverage emotions, brain-body connection, intuition, logic, motivation and creativity. Below I am not willing to deepen all of them (for this purpose I strongly recommend the MIT course), but I would like to pinpoint few interesting points for each one:

• Mastering emotions. All the information processed by the cortex (e.g., the information coming from the five senses) flows through the limbic systems, resulting in emotions being able to deeply affect and modify information before being processed by cortex. According to this way of thinking, one has to develop the ability to recognize, regulate and attend to emotions; considering that emotions are strictly related to the ancient limbic system, most people find it the most challenging!
• Brain-Body Connection. The science of embodiment proves the brain is not all humans rely on for problem-solving. A strong brain–body connection requires self-awareness of your five primary senses, as well as another sense (on top of the five classical ones) called interoception (Chesler et al. 2016), i.e., the ability to sense the physiological state of your own body. The more attune you are to these signals, the stronger the relationship is between your brain and your body.
• Intuition. This approach concerns the gut–brain connection, which refers to your sense of what is right and wrong without using conscious thoughts (Swart 2019). According to researchers, there is a complex communication system between the neurons in the gastrointestinal tract – also referred to as the gut – and the limbic system in the brain (Mayer 2011). What we’ve learned more recently is that not only is there a direct connection between the brain and the gut neurons, but there’s also a connection - a three-way connection - between the gut microbiome, which is the healthy bacteria that live in our guts; the gut neurons; and the brain.
• Logic. Logical reasoning is defined as the ability to take complex evidence and plot a way through the data to a solution, remaining mindful of your emotional biases and their impact on the objective analysis of the evidence (Goleman 2011).
• Motivation and Resilience. Motivation is defined as goal-directed behavior and gives a good indication of why a person acts or responds in a certain way (Cherry 2020). Resilience is your ability to endure challenging situations and use those situations to build prosperity (Carpenter 2020). According to Susan Fowler, author of Why Motivating People Doesn’t Work, there are three psychological needs that have to be met to ensure optimal motivation: Choice (in order to have a sense of control),Connection (to have a sense of belonging), and Competence (the importance of feeling capable).
• Creativity. Creativity is not just about art, music, or film. It’s about using all brain power to create the foreseen real-world outcomes. An attitude of openness is key to creative thought, and those who score high on a scale of being open to new experiences are found to be more creative and literally perceive information differently, in a more integrated way (Antinori, Carter, and Smillie 2017).

Given these six ways of thinking, it may straightforwardly result how logical thinking can be currently (even if partially) replicated by artificial intelligence, but when it comes to intuition and creativity the limitations are obvious.

Furthermore, there is something that is supporting all these ways of thinking, that is the most advanced level of analysis where one can imagine parallel worlds: imagination! In his book Sapiens, historian Yuval Harari stated that our ancestors' capacity to imagine nonexistent things was the key to everything. Let’s see…

Imagine… the Power of visualization

Researchers at the Cleveland Clinic Foundation in Ohio set out to investigate whether it is possible to induce strength benefits by visualizing a muscle being exercised. Results showed that people just by visualizing muscle exercise obtained an increase from 13.5% to 35% in muscle strength with respect to control group.Visualization is most effective when you focus on what you can control, practice it regularly, use specific visual imagery, and limit negative thoughts (Vanderkam 2015). Research on athletes shows that incorporating visualization into a training regime can significantly improve performance (Sarafrazi, Abdulah, and Amiri-Khorasani 2012).Finally, Olympic swimmer Michael Phelps is the most successful and decorated Olympian of all time, holding several records for individual events. He attributes his success to the power of visualization.

We started our journey from collective intelligence, going through the Brain Agility Model and highlighting the power of imagination… let’s come back to collective intelligence….

Back to collective intelligence

Given the continuously increasing role of Artificial Intelligence in 21st century, it is becoming even more important to incorporate the other human ways of thinking into human-machine collective intelligence: AI is based on logical thinking and overreliance on logical thinking results in risk-aversion and missing opportunities. According to psychotherapist Amy Morin, “risk is best calculated when you are able to balance logical thinking with emotional thinking. If you base all your decisions on logic, you are likely to lose out on opportunities; if you base all your decisions on emotions, you might fail to take informed risks” (Morin, 2020).

Hence, in order to succeed in creating an effective and efficient collective intelligence, each actor shall bring its own strength: machines will contribute to logical thinking, but humans have still a lot of other ways of thinking that will strongly contribute to the 21st century human-machine collective intelligence.

Will machines contribute only with logical thinking forever? While traditional AI focuses on reproducing logical abilities of human brains, newer approaches are widely studied to reproduce wider range of biological structures (e.g., Bio-Inspired AI focusing on biological structures capable of autonomous self-organization). It is impossible to say whether these approaches might be able to go beyond logical thinking; but today Artificial Intelligence is stuck to mathematics, to logical thinking and to gaining experience from a data-driven training.