Monday, August 05, 2019

Does Measuring Emotions Increase Happiness?

Thanks to Martin Wikelski and his colleagues at Max Planck Institute and University of Konstanz for inviting me to give a talk about "whether measuring emotions increases happiness"?

If you would like to hear the answer, and see how the "Social Compass" might help in achieving this goal, watch the talk here.

Saturday, April 06, 2019

Navigating Human Emotions with the “Social Compass”

Navigating human emotions can be extremely difficult. Just ask politicians such as former US Vice President Joe Biden who was hit by a firestorm of protests by getting too touchy-feely with supporters, or US senator Elizabeth Warren who ran into unexpected criticism for claiming Native American ancestry. While trying to behave rationally, they become victims of their emotions.

In an interview Linus Torvalds said “I absolutely detest modern "social media"—Twitter, Facebook, Instagram. It's a disease. It seems to encourage bad behavior.”…. “When you're not talking to somebody face to face, and you miss all the normal social cues, it's easy to miss humor and sarcasm”…”The whole "liking" and "sharing" model is just garbage. “ In our research we are developing a “Social Compass” that helps individuals navigate their emotional world, just like Google helps a person to navigate the relational world of facts and science. Just like Google Maps shows where somebody is in the physical world, where they can go, and where the bottlenecks and traffic jams are, the “Social Compass” helps individuals navigate the social landscape of their emotions and the emotions of others. It tells individuals how others see them, and what they can do to be happier, and more collaborative and productive. It gives an individual a “virtual mirror” of their own communication behavior, and shows them how others see them.
The “Social Compass” is calculated based on an individual’s communication behavior, by analyzing the communication archives arising from the individual’s interaction with others (see picture below). 

The “Social Compass” takes as input communication signals, and through machine learning and AI gives recommendations for more happiness, better collaboration and higher productivity.  It analyzes body signals measured through smartwatches, organizational communication from E-Mail or chat like Slack or Skype, and online social media from Twitter, Reddit, or YouTube.  From these three types of communication archives, it calculates the seven honest signals of collaboration (strong leadership, balanced contribution, rotating leadership, responsiveness, honest sentiment, shared context, social capital) and the emotions of the person (joy, sadness, fear, anger). These honest signals and emotions are used as input for machine learning, to calculate the FFI personality characteristics (openness, conscientiousness, extroversion, agreeability, neuroticism), the Schwartz ethical values (openness - conservation, self-enhancement – self-transcendence) and moral foundations (care, fairness, loyalty, authority, sanctity). 
The Social Compass presents this information to the user in two ways. As a Virtual Mirror, it shows each person in an anonymized way how they are doing compared to their peers. In addition, it also gives users “social driving directions” similar to Google Maps.
The Virtual Mirror shows the seven honest signals of collaboration for each individual, calculated from e-mail or from body signals. It respects individual privacy, by only showing individual information to the individual and aggregating other people’s values to group averages. The picture below shows the individual dashboard of the e-mail based Virtual Mirror, computed from the e-mail archive of the individual.


The picture below shows the comparison of the individual’s communication behavior with other team members with regards to the 7 honest signals of collaboration. ">

The picture below shows the scatter plot visualization for comparison of the different honest signals of the individual (dark dot) compared with all other individuals in the company. In this picture the contribution index (ci) is shown.

The Social Compass also allows an individual to track the location of their emotional experiences such as how happy the individual has been at a particular day, and where on the map that happiness was measured on that day. The picture below shows a screenshot of my Happimeter Android phone app on February 20, 2019. In addition, the social compass also shows which variables have influenced my happiness, and who has positively or negatively influenced it.
Finally, the same virtual mirroring information can also be shown on the Happimeter smartwatch, this function is also used to improve the machine learning accuracy of the emotion prediction of the wearer of the smartwatch.



In addition to the virtual mirroring function, the Social Compass can also give recommendations to increase happiness and reduce stress of the user, based on the insights automatically generated by the honest signals of the user. The system might advise the user to take a walk or do a mindfulness  exercise to reduce stress, or to talk with a person that has shown a positive influence. Alternatively it might tell the user to change the location, if the Social Compass finds that the current location has had a negative influence on the user.

Tuesday, February 12, 2019

Why money matters most in the US, being happy in the rest of the World!

It seems there is a digital divide of a special kind between the US and the rest of the World. Using Google ngrams and Google trends as my cristal ball, I checked what people are searching most. First I looked at their "hope", "fear", "love" and "money" over the last 200 years on ngrams worldwide. The result is shown below.


"Hope" has been decreasing for the last 200 years, as has "fear", which makes sense, they go together and most of the time “we hope it is not as bad as we fear”. More interesting is the decrease in our search for "love", and increase in the search for "money", reaching its peak in the 1940s, tampering off since then, while "love" has been picking up recently.

Drilling down on the last fifteen years, Google trends shows that while "love" matters more than "money" (after all money is just a proxy to buy love), happiness and money are close twins:


The picture above shows the worldwide searches on Google, there being "happy" became more important than chasing "money" sometime after 2010.
Restricting the same search only on the US shows the opposite picture: In the US finding money is more important than finding happiness:


Somewhere before 2016, being "happy" and "money" were equals, but since then money has definitively beaten happiness in importance in US Google search activity.

So, yes, there is a divide in what really matters, money or being happy, between the US and the rest of the World: money matters most in the US, being happy in the rest of the World!

Addendum: it also seems that searching for "love" is far more important than searching for "happiness".


Wednesday, November 28, 2018

Highly Intelligent Is Not Highly Creative – How to Be Truly Innovative

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, cementing established ideas by repeating them using more complex algorithms and procedures or by writing the first overview paper categorizing trends in an emerging field (which has the nice side effect of boosting the author’s h-index as it will be widely cited). Among entrepreneurs, these are the people reaping the biggest rewards, Bill Gates falls into this category, as he is a master of recognizing emerging trends, which are then integrated in his products.

Highly creative, incrementally intelligent researchers and entrepreneurs, on the other hand, challenge existing wisdom, frequently upending established beliefs. However, as the execution of their ideas is frequently improvised and not presented in a polished way, they have a hard time gaining acceptance – when Galileo Galilei presented convincing proof that Earth was indeed circling around the Sun, and not the other way around, the Roman Inquisition in 1615 found this “foolish and absurd in philosophy, and formally heretical since it explicitly contradicts in many places the sense of Holy Scripture”. Highly creative researchers in more modern times still have a hard time challenging established wisdom, and more often than not fail in making their ideas stick. In particular, is it near impossible to get these ideas into Nature and Science, as today’s reviewers, just as the Roman Inquisition 400 years earlier, deem their ideas “foolish and absurd”.

Highly creative, highly intelligent researchers and entrepreneurs are the small group of people, who succeed in making their disruptive ideas stick. Other than Galileo Galilei, today’s Nobel Prize winners might get recognition of their disruptive ideas while still alive, although sometimes they have to wait 40 years for their ideas to be recognized by the scientific establishment, as happened to Barbara McClintock, who discovered genetic regulation mechanisms in maize in 1944, and got the Nobel for this insight only in 1983. In between she stopped publishing her research due to being ridiculed by her peers. I would also put entrepreneurs like Steve Jobs and Elon Musk into this category, as they are taking huge personal risks promoting and commercializing novel and untested technologies.

To convince one’s peers and society about novel thinking and products, researchers and entrepreneurs need other essential personality characteristics besides intelligence and creativity. Only by being highly persistent and highly empathic can one really succeed in getting others to accept new ideas.


In an excellent article, Albert-Laszlo Barabasi tells the story of Douglas Prasher, who pioneered a process leading to a Nobel Prize in Chemistry, but was unable to find funding for his research, and became a courtesy driver for a Toyota dealership, while Martin Chalfie and Roger Tsien, two of his more persistent collaborators shared the Nobel Prize. However, these two collaborators showed their empathy, by recognizing the contribution of Prasher in their Nobel acceptance speeches, and assisting him to subsequently return to science.

Sunday, November 25, 2018

Principles of Profiling Users with AI

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 based on their E-mail, or social media archives. There is one key difference though, we apply the “Google Maps Privacy Principle”: aggregated information is shown to all users, the individual information is only shown to the affected individual. The principle is derived from Google Maps, which becomes truly useful by aggregating the location information of Android users with location tracking turned on and iPhone users with Google Maps turned on through dynamically tracking their smartphone location. But the only individual who knows her/his own personal location is the owner of the phone. Google Maps therefore aggregates global information and returns individually useful information to the individual user.

This approach is what we are trying to pursue in our own work:
(1) Show aggregated information to the public, and individual information only to the affected individual.
There are however applications where the individual user has to be identified to others. These applications can be split into two categories.
(2) The application needs to identify the user, and the user gets a benefit from being identified, for example as a “rock star” employee, most collaborative employee, etc.
(3) The application needs to identify the user, and the user has a disadvantage from being identified, for example as a potential security risk, low performer, etc.

The applications from predictim, HireVue, and Fama are clearly in category (3). Users are convicted by a machine learning algorithm without knowing why. The algorithm operates as a black box. While arguments can be made for category (2) applications to run in such a mode – the user gets a pleasant surprise, even if s/he does not know why, this is clearly not acceptable for category (3) systems. At the very least does the user need to know why s/he has been convicted.
As I assume that more and more systems in category (3) will be built, for instance by law enforcement, I envision the need for an impartial authority, which can be public or private, to check and certify the accuracy of these AI-based prediction systems.

A second point which sets Condor apart from other AI-based prediction systems is the transparency of its algorithms. The scoring algorithms applying the "seven honest signals of collaboration" and a list of predefined "virtual tribes" is documented in great detail in over 150 academic papers and fivbooks. This is quite different from e.g. predictim's case studies, which predict the past, without disclosing how it is done. There is no guarantee that the training data of the past will still be valid to detect future criminals.

 It is still early days, so please tell me what you think, I would love to hear your opinion

Thursday, November 15, 2018

Why Donald Trump is No Leader

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 compassion, try to understand what is going on inside their own minds, try not to hurt their feelings, and try to be not just nice, but also kind. Trump’s easy hiring and firing of allies, and not liking losers like John McCain who was tortured as a prisoner of war, sadly demonstrates utter lack of empathy.

So, sorry, Mr Trump, you are not a leader. But perhaps I am just living in an alternative reality and everything in reality (TV) is totally different!

Wednesday, October 17, 2018

What Emails Reveal About Your Performance At Work

Recently HR analyst Josh Bersin interviewed 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.