Swarm Creativity Blog

In research as well as in entrepreneurship, there are many characteristics distinguishing an exceptional researcher or entrepreneur from just a good one. In particular there is a key difference between highly intelligent and highly creative people, as these characteristics are not necessarily correlated. Intelligence is commonly defined as the ability to acquire and apply existing knowledge and skills, while creativity is the ability for something novel and valuable. New research and new enterprises can therefore be grouped into four categories: Highly intelligent, incrementally creative researchers or entrepreneurs add an incremental twist to existing methods and knowledge. For instance, a researcher might add mathematical bells and whistles to widely accepted ideas and concepts - in Renaissance Europe they might have added an additional proof that Earth was indeed flat and that the Sun was circling around it. Most of the papers in Nature and Science fall into this category, ce...

Two days ago I read a Washington Post article about 3 Californian AI startups that profile users based on opaque AI algorithms. Their products calculate a quality score for people in different domains without explaining how it is calculated Predictim.com calculates a “risk rating” of babysitters based on their social media activities. HireVue analyzes tone, word choice, and facial movement of job candidates to predict their skill on the job. Fama does employee screening on social media and internal HR data to prevent what they call “brand risk” such as sexual harassment, bullying, or insider threats of employees.  The main problem with these and similar systems is that they use machine learning, in particular deep learning as a black box. Their algorithm gives back a score claiming high numerical accuracy without explaining how it has been calculated. Our own Condor software is doing similar things, showing a bird’s eye view of the communication patterns of organizations...

There are many ways to identify exemplary leaders. One of my preferred categorizations comes from here . It lists humility, curiosity, and empathy as the main criteria of successful leadership. I am afraid that on all three criteria Donald Trump scores zero: Humility  means that exemplary leaders treat everybody with respect, are not afraid of criticism and are willing to admit their own mistakes. They are willing to put their own ego into the background for the sake of others. Donald Trump stands for the opposite, as an egomaniac person who is obsessed with his own power and glory. Curiosity  means that a leader is constantly looking to further his own understanding, is willing to defer to the knowledge of others, and thirsty for new information. One of the first actions of Donald Trump was to cut funding in research, denying scientific facts about vaccination  and climate change , showing zero scientific curiosity. Empathy means that we treat others with compa...

Recently HR analyst Josh Bersin interviewe d Praful Tickoo , head of HR analytics, and Piyush Mehta, CHRO at Genpact, about the work we have been doing together for the last 5 years to identify both rock stars and flight risk of employees. His excellent blog post is here .

Have the Russians and Cambridge Analytica been abusing Facebook to influence the US and British elections by spreading fake news to receptive users? Absolutely Yes! Has this abuse had an impact on the US elections and Brexit? Most likely not! It becomes increasingly clear that people like Donald Trump (through his former confidant Steve Bannon) and Vladimir Putin have been (illegally) harvesting user profiles on Facebook and setting up Twitter bots to spread fakenews on Facebook and Twitter . Facebook by its own account admitted that fake news produced by the Russians and US Alt-right proponents might have been seen by millions of users. What has not been shown, however, is what effect this has had on the actual voting behavior. I argue that this effect has been minimal, most likely smaller than the voting margin for Trump in the US elections, and for Brexit in the UK. While a group of researchers has done an t horough analysis of the dynamics of the spread of ...

In the earlier days of computer science (1990ties), when I was a post-doc at MIT, there was huge discussion among AI researchers, with people like Marvin Minsky on one side, who said that computers eventually would become smarter than humans, and the majority agreeing that this would never be possible. Fast-forward 25 years, and there is no question that Marvin Minsky was right. Researchers today envision one of three possible scenarios: the first, least fearsome one, that the human is telling the machine what to do, secondly, we have true human-machine symbiosis with computer and human being equal partners on a task, or third, the machine telling the human what to do. Looking at the current stock market fluctuations, it unfortunately seems we already firmly reached the third scenario, with computers taking over. When after multiyear growth and a record high of the Dow on January 26 2018, a few days later on February 4, the Dow lost 1175 points in a single day, this was its bigges...