“I’ve got a hunch that our company will perform well over the next 6 months”, “I know my team will win; I can feel it in my bones”, “I just go with my gut instinct and things usually work out fine.” These are ordinary comments about intuitions expressed by people - and a surprising amount of the intuition about the future also turns out to be right. The intuitive instinct has always been humanity’s most powerful drive. Just about everything that humans have become and created started with an imagination, a hunch, an intent - an emotional experience.
Until recently, many experts in artificial intelligence predicted that the world’s smartest AIs were a long way from solving the complex game of GO – an ancient Chinese game that has such complexity that it makes Chess look like hopscotch. On March 12, 2016, Google-owned DeepMind’s computer program AlphaGo played a five-game match against 18-time world Go champion Lee Sedol. The program defeated him, 4–1, after Sedol and other champions had predicted he could win 5–0 or 4–1. AlphaGo demonstrated the highest possible professional Go ranking that takes human players decades to achieve.
For the first time, a computer player had demonstrated what might be called an “intuition” about what is a winning move. Yet – it is still a long way from true machine sentience, but it shows that true sentience is in motion.
AlphaGo adopted two neural networks based on computer systems modeled on the human brain, and repeated analysis of online games played by humans to test their strategic moves before the program played against itself generating 30 million positions which it then analyzed.
Such cognitive machine abilities are in growth all over the world, from an exponential industry of advanced humanoid robots who are on their way to take emotionally care of the elderly in Japan to one of the biggest breakthroughs of 2020 DeepMind’s AlphaFold that’s able to predict a protein’s structure from its amino-acid sequence. While AI must be considered one of the most revolutionary developments in human history, not surprisingly – its transformative humanoid capabilities at the same time is seen as a threat to humanity and its existence. Consequently, humanity should identify mechanisms to deal with the advancing AI capabilities and potential risks.
The counteraction would obviously be to pursue a greater interaction of collective intuitions and artificial intelligence to meet AIs advancing cognitive capabilities.
Collective intuitions are based on the aggregation of independently formed predictions on domain-specific knowledge, experience, cognitive ability, and are shared and interpreted collectively (Sinclair and Hamilton, 2014).
By pooling intuitions of multiple individuals (either by combining independent judgements, or direct interaction mechanisms), groups of decision makers can reduce uncertainty—a phenomenon known as collective intelligence, swarm intelligence or collective cognition . The extent to which combining individual information allows collectives to outperform individuals is crucially mediated by the level of independence as highlighted by several theoretical studies [28–32]. (above-mentioned references are listed in this paper) In other words, a collective intelligence – that is the ability of groups to outperform individuals in solving cognitive tasks.
AI can advance the ability of collective intuitions in numerous of ways. Collective intuitions can be used to develop theories and test them as a hypothesis with AI. For example, collective intuitions can point in the direction of a potentially remarkable discovery for humanity. Once you have a theory, you can put it to the test with various datasets and deep-learning algorithms to arrive at the optimal decision.
For companies, AI can also help scale the data processing of the complex nature of intuitions by combining a vast amount of structured quantitative prediction data with unstructured prediction insights in form of text. AI may also support in identifying new causal connections in dealing with complex issues, such as the identification of relationships across many different dimensions in a dataset. AI can further support the organizing of the data into categories, such as clustering and ranking insights from intuitions. It can enhance individual contributions and facilitate knowledge sharing across members in real-time.
“The intuitive mind is a sacred gift and the rational mind is a faithful servant. We have created a society that honours the servant and has forgotten the gift” - Albert Einstein
In other words, the question should not be whether rational reasoning and AI are better than collective intuitive decision-making. The question is rather on how both approaches can best be combined for optimal results to deal with the humanoid advancements of AI.
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