"the collective power of the weak is mightier than that of the strongest individual."

"If only things were that simple. We are all human. We have limited knowledge. We may understand others well if they have had similar life experiences to ours. Human psychology tricks us, too. It makes us want to be around people who are like us — people with whom we can sympathize. That is all very innocent until you consider the cost to society."

"‘The lack of women’s participation in clinical trials is the result of a long-held belief that the male perspective is the norm’"

"Gatekeepers, including doctors, surgeons, policy makers, and medical researchers, are predominantly male. Their viewpoints have become entrenched in the way we approach medicine."

"If you do not actively pursue diversity, the status quo will remain. That is just how decisions are made. The way we see the world is shaped by our personal experiences. Observable traits, such as race, ethnicity, gender, and age, are the starting point of diversity of thought."

"However, the most compelling explanation can be found in the field of artificial intelligence and the algorithms associated with it."

"An approach called the ensemble method deserves mention here. It essentially harnesses cognitive diversity in the world of AI."

"The ensemble method works by dividing an existing dataset into small samples, which can then independently train different algorithms at the same time. In these smaller sample sets, these algorithms tend to be weaker. They make more errors in their predictions on their own. The wonderful thing is that you can aggregate their results."

"The collective insight, or total wisdom of these algorithms is far superior to that of a single algorithm. In fact, it is better than a single algorithm that is trained by all the data in one go."

"There are two key reasons for the power of this collective: firstly, algorithms tend to make different types of errors, and secondly, they learn from each other and improve as they go along. This is what computer scientists call co-evolution."

"The main idea is that a diverse set of algorithms will have superior performance. This is because of their complementary strengths and weaknesses. And they shine especially when making prediction in the new, unseen data."

"Just as with machine learning, humans need to actively seek out diverse perspectives of people who are wired differently because of their alternative life experiences."

"Only then can we build a better, more accurate picture of the truth. Furthermore, we can make better decisions for society when we understand things better."

"Explore and exploit are not mutually exclusive choices. Companies must have both. Still, in industries that are turbulent and changing quickly, companies tend to explore more."

"‘If you do not actively pursue diversity, the status quo will remain. That is just how decisions are made.’"

"In the second graph, we plot how different industries learn. The X-axis shows how oriented an industry is towards learning. Again, we see that pharmaceutical and technology industries are more learning-oriented than other industries. They are more likely than others to pay more attention to diversity."