Algorithms should contribute to the Happiness of Society

Happiness is like the holy grail of life — the ultimate goal and desire of every human being.

Happiness balances mind and matter, spirit and experience, yin and yang — being happy means being on the right track.

Happiness is even related to hormones that make us feel good.

That’s why all people want to find happiness.

But not all of us find it — we either don’t know where to look, for what to look, or how to find it.

Today I will tell you a story on how we as data scientist, and JADS as an institution can contribute to your happiness.

And what we should avoid doing, so we won’t make you less happy.

Happiness as a human pursuit is ingrained in our actions for as long as we can remember.

The old Greek philosophers already discussed the great importance of happiness.

Since then, many scientists followed the footsteps of Aristotle and Plato.

A special mention should go to the utilitarians of the 18th and 19th century.

They not only discussed the importance of happiness, but also introduced happiness as a moral compass.

They advocated the greatest happiness principle as our guide for ethical behavior.

Jeremy Bentham stated that actions are moral when they promote happiness.

The thinking of these utilitarians has even been written down in the United States Declaration of Independence of 1776, in which Thomas Jefferson wrote about the universal human right to pursue happiness.

Although happiness has always been an important theme, its significance seems to be increasing in today’s world.

More and more individuals are becoming aware of the great importance of pursuing happiness.

Perhaps it is the loss of religion in Western society that makes us more interested in being happy.

Or is it that we are losing some of our ability to be happy in this modern age with all its distractions and information overload?Whatever the reasons, the modern homo sapiens seems to be gripped by the hunt of happiness.

No wonder that the most popular course in the whole history of Harvard University is the course Positive Psychology 1504, a.



the happiness course.

Here students are taught on how to be happy in 22 lectures about all the psychological aspects of life fulfillment and flourishing, by teaching about empathy, friendship, love, achievement, creativity, spirituality, happiness, and, off course, humor.

But not only students are actively hunting for happiness.

It seems that increasingly all individuals are pursuing happiness with greatest fervor.

We even have magazines called Happinez, coaches who seem to be able to train us in happiness, and holidays and retreats, which all seem to promise happiness.

And it is not only individuals that chase for happiness.

Organizations, cities, and even nations are pursuing happiness.

Bhutan was the first country, which aimed to maximize its Gross National Happiness.

A great many countries, regions and cities, have followed their example.

Since last year we are also measuring happiness on a municipal level.

According to these measures the happiest municipalities in the Netherlands are Ede, Alphen a/d Rijn, and Amstelveen.

And the least happy municipalities are Rotterdam and Amsterdam.

Out of 50 bigger cities in the Netherlands, Den Bosch scored 19th, Tilburg came in 32nd and Eindhoven appeared at spot 38.

Looking at these data perhaps one could say that there is an inverse correlation between football results of the local professional football club and the happiness of its citizens.

But that would say nothing about causation.

Professor Arjan van den Born at DBDW.

“Happiness is possible and can be ‘engineered”As happiness is becoming more important in our society, it should not be a surprise that this subject fascinates many scientists.

Happiness is nowadays a serious field of study.

Here I want to pay tribute to one of the pioneers and world authorities on the scientific study of happiness; Ruut Veenhoven.

He is the founding director of the World Database of Happiness and has been described as “the godfather of happiness studies”.

Of all his findings, one conclusion has struck me the most.

He concludes: “Happiness is possible and can be ‘engineered’.

This is where we come in.

JADS is about building two bridges.

The first bridge is between engineering and social sciences, and the second bridge is the bridge between society and science.

Happiness is spot on this crossroads.

It is something where we should and can contribute.

It is one of the most important societal questions and a challenge where modern, engineering based methods brings us further.

Then the question is; how can engineering, data science and artificial intelligence contribute to our happiness?.Here we are much inspired by Frans de Waal, one of the world’s finest primatologist and, a local boy; born-and-raised here in ’s-Hertogenbosch.

He does not see himself as a primatologist, but rather as a psychologist specialized in primates.

He once pondered that his field of study, the psychology of primates, has developed tremendously since he started working at the end of the 1970s.

In the same period, “normal” psychology, the psychology of humans, has made little progress.

At least by comparison with the great advances in primatology.

Frans de Waal argued that perhaps the main explanation for this progress in primate psychology has been the absence of opportunity.

Where “normal”, i.


human psychologists were able to ask humans how they are feeling and why they are doing what they do; this was simply impossible for someone studying primates.

To overcome this burden, primatologists started observing and measuring.

They started observing; which primates smile, when do they smile, in what kind of groups do primates smile.

And they started measuring; for instance the stress levels in bodies.

Frans de Waal observing a chimp, and vice versa.

The measurement of objective characteristics instead of gauging subjective, social desirable answers too often found in interviews and surveys, paved the way for the enormous advance of our understanding of primatology.

This progress has been so rapid that many scholars argue that human psychology nowadays can learn from primate psychology.

For instance Meyer and Hamel argue that studies of stress in nonhuman primates can now play a valuable role in helping to elucidate the mechanisms underlying the role of stress in humans.

The example of Frans de Waal shows the power of measuring.

This should not be a huge surprise.

Many of the big scientific breakthroughs are related to increases in our ability to measure.

Without the microscope of Anton van Leeuwenhoek we would not have known anything about the complex world of microbes.

Up until that point, people had no idea that there was a whole world of microorganisms too small to be seen by the naked eye.

With this discovery, it became possible to start learning about, among other things, the causes of diseases.

And this list goes on and on.

New instruments lead to novel measurements that lead to the confirmation or refutation of existing theories, but also contributed heavily to the development of new theories.

In the early days of Frans de Waal the research of primates was painstakingly tedious and labor-intensive.

Every movement, every smile and every change in position of apes needed to be painstakingly observed, coded, and analyzed.

To identify correlations and causations of specific primate behavior often took many years and years of study.

The progress was slow and costly and only through determination and persistence of many researchers, we learned a lot about primates, and ourselves.

Here is where IoT, data science and AI can contribute.

With sensors measuring positions, interactions, and health and with cameras observing the actual behavior and expressions of primates the costs of collecting and analyzing objective, real data are becoming quite low.

In fact the costs will be lower than the cost of obtaining subjective data trough surveys and interviews.

These new objective measurements will help us understand the complexities of being and pursuing happiness.

Our research project Music-As-A-Medicine, performed in close collaboration with Erasmus Medical Center, IMEC, Deloitte, and the Rotterdam Philharmonic Orchestra shows one of the ways in which sensors may help.

Here researchers of Erasmus and others have already established the beneficial relationship between music and health.

In a clinical trial, patients experiencing a specific type of surgery get a green card or a red card.

Those with the red card just get the surgery and those with the green card get the surgery plus a headphone with soothing music (Mozart).

Early findings indicate that those patients with headphones recover more quickly and more robustly with less relapses.

This confirms studies in other settings.

We already know that early-born baby’s in an incubator grow more quickly and healthy with music than without music.

But there are things we still do not understand.

We do not understand which kind of music is most beneficial.

Is it Mozart, Mendeleev or Metallica?.Or depends this on the type of person?.And are all persons equally receptive?.Or are some persons more sensitive towards the effects of music than others?.To gain a better understanding of these differences we are planning a grand experiment in which the Rotterdam Philharmonic will play 10 different pieces of music to over 2000 persons with 3 types of sensors (e.


blood pressure, heart rate variability) to get a better understanding of the relationship between music and stress.

Will this experiment lead to new insights?.We will never know, until we try.

The experiment described above points to one area where data science may lead to new discoveries; the complex science of personalization.

That we are a diverse species is well known by the marketeers of this world.

A famous saying in marketing is: “The quickest way to ruin a customer experience is to treat everyone the same”.

People are simply not the same.

It is not, as Ford used to think, that we all want a black car.

No we want different colors and different types of cars.

We want sport cars and SUV’s and we want them in red, blue and silver — and 100s of different colors.

While in the world of marketing analytics this is well known, in many other fields, it looks like we are just beginning to discover our inherently human diversity.

Increasingly we know that different people may require different types of medicine depending on their gender, age, environment, and their DNA.

Here data science may come to the rescue.

To be clear, I am not promoting a “Big Brother is Watching You” kind of schemes.

I have great troubles to really believe in initiatives with lofty goals and where technology and engineering alone are touted as the answer.

For instance, Dubai aims to become “The happiest city on earth”.

While such objectives are quite admirable, I do not feel that big data technologies such as sensors placed throughout the city and integrated with all sorts of feedback mechanisms will lead to more happiness.

On the contrary: what is happening in China with its development of a “social credit” scoring system is as much appalling as it is frightening.

The remarks made last week in Brussels by Apple’s CEO Tim Cook on the emerging data industrial complex are spot on.

He mentioned that a world where likes & dislikes, fears & wishes, and hopes & dreams are traded like commodities should unsettle us.

A world where businesses embrace the data surveillance business model and harvest data routinely to nudge us into appropriate behavior maybe technologically possible, it is socially not desirable.

Here Tim Cook tweeted suitably: “Technology is capable of doing great things.

But its does not want to do great things.

It does not want anything.

” If we want technology to help us to become better societies, better families and even, better versions of ourselves, we need to take control over technology.

Not the other way round.

“algorithms should always contribute to the happiness of society”To be clear: data surveillance will not make us happier.

Cities with cameras that know if you’re happy, or not, (or if you considered a threat) should scare any citizen.

I believe that academia should lead by example.

I therefore agree wholeheartedly with my colleague Wil van der Aalst in his drive for Responsible Data Science.

We need to ensure that our science and our developed algorithms are fair, accurate, confidential and transparent.

I suggest that we add John Stuart Mill’s greatest happiness principle to these existing four criteria of responsible data science.

That is: algorithms should always contribute to the happiness of society.

Only when data science meets all five characteristics; fairness, accuracy, confidentiality, transparency, and happiness we might keep and rebuild the trust of society in algorithms and other data-powered services.

Given all the above, and coming back to our subject; how can data science lead to more happiness?.I think that data science will add to our happiness if we follow the great example of Frans de Waal and use objective, measurable data to gain a better understanding of humans.

We can use novel measurements to build better theories and give us better, practical advice.

Not only in the field of happiness, but focus on measurement will help us understanding of a lot of things better.

Some rather mundane issues, for instance how to recognize and develop talent and the really important stuff, of what causes and cures particular diseases like Alzheimers and Cancer.

Ofcourse we can use the power of statistics to promote happiness and diminish stress and burnout.

Photo credit: Namelas FradeBut there is a caveat, we should not follow the examples of China or Dubai.

We do not believe it is necessary to measure all of the things all of the time.

We must always remember that data is just there to help us answer questions.

And it is up to human creativity to ask these right questions.

We believe instead that sets of interesting, well-designed experiments will be able teach us more than any Orwellian state will learn.

To conclude; data science will lead to more happiness if we will not forget that Data Science is NOT about I.


, it is about ideas behind technology.


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