Open your eyes – your AI is biased

Computations have no ethical subroutine. And understanding bias in AI is an important eye opener. Building an AI-facilitated future without properly understanding the algorithms behind the conclusions and actions is leading us to into unexpected pitfalls.

We are all very excited about machine learning and AIs. We see them as the ultimate way of automating daily life from driverless cars to personal health and medical diagnostics. But garbage in = garbage out. And to eliminate the garbage we need to be able to identify it. Long after our little helper has started working.

The main reason we need to watch out is that AI algorithms are not necessarily retraceable and retrackable. Not even the programmer understands it fully once the machine starts accumulating and filtering data. Despite its ability to learn it can only conclude based on the original assumptions built into the underlying algorithms.

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Looking for the ultimate answer

Whenever we rely on algorithms to make decisions – or at least recommendations – it is because we seek a simple answer to a complex question.

If the collection of big data for data driven decision making is used to create simple answers to complex questions, the complexity is solved through algorithms that in effect filter and collate based on what the human programmer considered applicable. And it concerns us more than you would expect. I recently read that the AI concept is being used within the US judicial system: Judges rely on the AI’s suggestion on whether an inmate should be granted parole based on assumptions of future behavior of set individual after release. In isolation this would seem like a statistically viable method, as there will be vast amount of available data to substantiate the conclusion.

But if the original algorithms input by a human were in fact influenced by bias such as race, name, gender, age etc., are the conclusions any better than the answer 42?

When Douglas Adams in his science-fiction Hitchiker’s Guide to the Galaxy series introduced Deep Thought, the biggest  computer ever built in the history of men and mice, the builders asked for the answer – and added that they wanted it to be nice and simple. So after millions of years Deep Thought concluded that the answer to life the universe and everything was 42. But by now, this insight was useless because nobody really understood the question.

If we see AI and machine learning as the ultimate answer to complex scenarios, then we must be able to go back to the original question in order to be able to process the answer. Not just to understand but to analyse and apply what the computer is missing – the ethical subroutine.

What will the AI choose in a no-win scenario?

One of the hot topics in the current discussion around self driving cars is whether the AI would make proper ethical decisions in a no-win scenario. Should it risk the life of the passenger by veering off the street and over a cliff to avoid running over another individual in in the street? The decision would be entirely based on the original algorithms which overtime have become inscrutable even for the engineers themselves.

Of course, this is a simplified example. An AI, as opposed to a human behind the wheel, would be able to process more details regarding the potential outcome of either option. What would the statistical probability of successfully avoiding hitting the person on the street be when taking into account elements such as speed, space available without going over the cliff, the chance of the person acknowledging the danger and moving out-of-the-way in time before the collision etc.

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(Image from Nvidia Marketing Material)

But the self preservation instinct of a human being behind the wheel would most likely lead to the obvious conclusion: Hitting the person is preferable to dying by plunging over the cliff! Would the original programmer not have input exactly this type of bias?

What I believe Douglas Adams was getting at with the magic number 42 was that there is no simple answer to complex questions. If as indicated above the AI is victim to its own programming when making complex decisions or recommendations, then as a tool we must make it as transparent and thereby manageable as any tool developed by humans since the invention of the wheel.

MIT Technology Review addressed this in detail in the article published by Will Knight in April 2017  The Dark Secret at the Heart of AI 

No one really knows how the most advanced algorithms do what they do. That could be a problem.”

willKnightHe goes on to explain that while mathematical models are being used to make life changing decisions such as who gets parole, who gets a loan in the bank, or who gets hired for a job, it remains possible to understand the reasoning. But when it comes to what Knight calls Deep Learning or machine learning, the complexity increases and the continuosly evolving program eventually becomes impossible to backtrack even for the engineer who built it.

Despite the inscrutable nature of the mechanisms that lead to the decisions made by the AI, we are all too happy to plunge in with our eyes closed.

Later the same year another MIT Technology Review article explores the results of a study of the algorithms behind COMPAS (Inspecting Algorithms for Bias ) COMPAS is a risk assessment software which is being used to forecast which criminals are most likely to reoffend.

Without going into detail – I highly recommend you read the article – the conclusion was that there was a clear bias towards blacks. The conclusions later turned out to be incorrect assumptions: Blacks were expected to more frequently reoffend, but in reality did not. And vice versa for the white released prisoners.

The author of the article, German journalist Matthias Spielkamp, is one of the founders of the non-profit AlgorithmWatch which has taken up the mission to watch and explain the effects of algorithmic decision making processes on human behaviour and to point out ethical conflicts.

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Mattias Spielkamp, Founder of AlgorithmWatch

The proverbial top of the iceberg

Even strong advocates of applying artifical intelligence/cognitive intelligence and machine-learning (deep learning) to everyday life applications, such as IBM with its Watson project, are aware of this threat and use strong words such as mitigation to explain how this potential outcome of widespread use of the technology can be handled better.

In a very recent article published February 2018 entitled  Mitigating Bias in AI models , Ruchir Purri, Chief Architect and IBM Fellow, IBM Watson and Cloud Platform stresses that “AI systems are only as effective as the data they are trained on. Bad training data can lead to higher error rates and biased decision making, even when the underlying model is sound… Continually striving to identify and mitigate bias is absolutely essential to building trust and ensuring that these transformative technologies will have a net positive impact on society.”

IBM is undertaking a long range of measures to minimize bias but this is only addressing the top of the iceberg. The real challenge is that we are increasingly dehumanizing complex decisions by relying on algorithms that are too clever for their own good.

Actually – all of this isn’t exactly news.

More than 20 years ago, human bias was already identifed as an important aspect of computer programming

“As early as 1996, Batya Friedman and Helen Nissenbaum developed a typology of bias in computer systems that described the various ways human bias can be built into machine processes: “Bias can enter a [computer] system either through the explicit and conscious efforts of individuals or institutions, or implicitly and unconsciously, even in spite of the best of intentions”.  (Source:  Ethics and Algorithmic Processes for decision making and decision support )

Print is not dead – it’s alive, and thriving in Greece

When a catchy phrase such as ‘Is Print Dead’ has caught your attention, you start to see it everywhere. Some see pregnant women and prams. I see print shops. In Thessaloniki, they were abundant.

A struggling economy recovering from failing infrastructure and hardships for both businesses and private indviduals:  Greece illustrates that print is still the carrier of civilization and growth.

 

What is the best course of action when your finances are tight?

Most people would answer: You cut back on your expenses. But that does not help you out of your demise, it just helps you stay in the mud without sinking any deeper. At least for a while. But what if you choose to grow your own money tree – or rather develop new ways of working that alter the course instead of treating the symptoms. In the case of a business – or a country – the way forward is not mindless cutbacks but disruption, innovation and finding those new opportunities.

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There is lots of room for improvement here, if you dive deeper into the European Commission 2017 Digital Progress Report  which places Greece in 26th position (of 28 total) among European Union member states on the Digital Economy and Society Index (Greece is abbreviated EL).

How to disrupt, innovate and grow in a crisis

The answer seems obvious for anyone in the printing and business communications industry: We communicate and interact using the most efficient available channel of communication. In Greece, it seems, this is still print.

Since the ecnomic crisis in 2012-2014, the penetration of digital in small and medium sized businesses (SMEs), family-owned shops and public life as well as governmental instutions remains considerably lower in Greece than I have seen elsewhere in Europe or Overseas. There were no opportunities to make investments in the early days of digital in this harsh climate for both businesses and government. And SMEs were hit hard. The 2014 policy document The Development of SMEs in Greece by the National Confederation of Hellenic Commerce states:

“According to the latest EU annual report on European SMEs for 2013, the SMEs of states which are vulnerable regarding public debt are facing serious problems related to liquidity, job losses and lack of value added. The only sector not affected by the above problems is the high technology (High Tech) sector. It seems that the countries which have established a solid and comprehensive approach to the implementation of SBA measures and policies are more able to support SMEs during the recession. SMEs in Greece are currently in the fifth year of the economic crisis. Despite the fact that Greek governments have implemented certain policies for SMEs (Investment Law No 4072, Creation of private capital companies, supporting self-employment, etc.), it is clear that Greek SMEs have been affected severely and to a disproportionately greater extent as compared to large enterprises.”

Now, you would argue, service providers like print shops are quite often classified as SMEs and should be as severely impacted as their buyers. But printing is part of the recovery.

A 2016 analysis of the value added annual growth of SMEs (non-financial) by EU member state shows a devastating -1.0% for Greece as the only contender below the line:

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But if you dive deeper into the data, Greece also shows the highest growth contribution from business services which include printing: 46% annual growth in 2016 for SME business services (compared to the EU-average of 18%)

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Print is not dead nor will it ever die

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Charles Frederic Ulrich (1858-1908): The Village Printing Shop, Haarlem

Walking down the narrow streets of Thessaloniki, my eye caught the numerous book shops, magazine stands, and posters glued to the wall of every building that had some available wall space exposed to the people walking by.  Flyers were stuck into the door handles of every apartment building every morning – and just as often removed by the inhabitants – replaced the next morning with a new message, a new service, a new special offer of the day.

We were offered flyers, brochures, political pamphlets. And every 5th-10th shop was a copy shop, a small or medium sized print shop, digital or offset printing. There was a whole street with only print shops on top of the yet to be excavated ruins of Galerius’ Byzantine palace. And TYPO in Greek means what we think it should mean.

It’s not the print that is disrupting or helping Greece back on its feet, but it is the carrier of the messages that those who change, innovate and grow need to spread in the most efficient way available to them. If you are a small startup, if you are medium sized retail or manufacturing business, you cannot pay for expensive online advertising or TV ads. If you are a small non-profit or political movement funded by enthusiastic supporters, you cannot reach the masses through digital media alone.

You spread the news on paper.

Because paper is durable, flexible, ubiquitous. You can leave it on door handles, hand it out to people in the street, glue it to the walls of popular sites, send it as post cards, sell it as books. It does not disappear with the wink of an eye – or a click of a finger on a scroll button.

It still does not guarantee that your message is read or your acted upon. That remains the task of the content provider to ensure. But it certainly reaches your audience, if you know where to put it.

Beating the Kobayashi Maru – or the human vs machine experiment with Watson

“I don’t believe in no-win scenarios.” (James T. Kirk, Starship Captain)

When you are a strong believer in datadriven decision making, building strategies on real insights, and always sticking to facts rather than fiction – it’s a hard blow when one of the world’s leading artificial intelligence systems tells you, that you are not a nice person. It’s based on data – so it’s a fact.

Many industry leaders have evangelists who are excellent presenters and subject matter experts. It’s always a privilege when you get a chance to interview an evangelist. I met IBM’s Rashik Parmar, Watson evangelist, at IPExpo Nordic a few weeks ago.

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Source: IBM

There is so much potential for big data analysis and the learnings and insights we gain, from combining the many available sources of accssible data to draw new conclusions and find answers. That’s basically what Watson does. And then makes the logical connections. Simply put.

IBM developed a small demo engine that would analyse your Twitter personality and generate those awesome charts we all love; and few of us know how to interpret. It was reassuring to see what a nice guy President Obama is on Twitter. And my friend, Rashik, had a similar profile – so all good.

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Source: IBM’s demo app TweetMeWatson

Lucky for me, we couldn’t make it work for my profile until I got home. When I ran it, I found out I was

“Inconsiderate and a bit shrewd”

I will spare you the rest. Either I am very delusional about how I express myself, or there was something fishy going on here. But it’s based on data! It has to be true!

Before digging a hole in the garden to hide from the world – or the equivalent: deleting my Twitter account – I decided to think it through. What was Watson picking up on, what were the actual parameters used?

The Big Five (FFM) Personality Traits

Watson is grouping our personalities according to the Five Factor Model (FFM) Wikipedia explains:

The Big Five personality traits, also known as the five factor model (FFM), is a model based on common language descriptors of personality (lexical hypothesis). These descriptors are grouped together using a statistical technique called factor analysis (i.e. this model is not based on experiments).

This widely examined theory suggests five broad dimensions used by some psychologists to describe the human personality and psyche.[1][2] The five factors have been defined as openness to experienceconscientiousnessextraversionagreeableness, and neuroticism, often listed under the acronyms OCEAN or CANOE. Beneath each proposed global factor, a number of correlated and more specific primary factors are claimed. For example, extraversion is said to include such related qualities as gregariousness, assertiveness, excitement seeking, warmth, activity, and positive emotions.

220px-francis_galton_1850s It all sounds very reassuring, the term “Lexical Hypothesis” makes sense –  it was analysing words. This is a principle which was developed by British and German psychologists to identify a personality characteristic. It was used to determine risk of mental illness or criminal behaviour. Invented in 1884, by the way, by Sir Fancis Galton – a stern looking fellow.

But something as elusive and intangible as the human mind is so very hard to classify and illustrate in data points and charts. By creating a lexicon of words and adjectives that at the time were considered to be indicators for certain behaviours, they provided a tool to build profiles – and categorise people based by their choice of words.

Note that the method has also received a lot of criticism – many of them quite reassuring when you are on the receiving end of this exercise. Read more here. 

Phew – that means I can still be a nice person, just not when I tweet. Or speak.

It seemed safe to climb back out of the hole in the garden and meet the world face on. But knowing now what triggered my unpleasant profile, I decided to challenge Watson to a duel.

A duelling experiment

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@echrexperiment is the experimental Twitter profile where tweets were worded more carefully, where people and followers were thanked and nothing bad was happening in the world. No politics, no injustice, no gender inequality, no discrimination. And lots of cats.

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After three weeks, I was a much nicer person. The traits that I seem to be exploiting negatively in my original profile are now contributing to a positive image.

Suddenly, uncompromising was a good thing.

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“In academic vernacular, you cheated”

Like Captain James T. Kirk in Star Trek challenging Mr. Spock’s designed program, I cheated to win.

Most of my tweets were carefully drafted using positive semantics but remaining true to my usual topics of interest. I was not trying to be someone else, just focusing on being nice. Here’s a list of the parameters I introduced to make Watson love me more:

  • Following back – anyone who followed me, unless an obvious business account or egghead, was followed back as soon as I spotted them.
  • #FF – sometimes I used the FollowFriday hashtag to thank select people. It generated some nice interactions even between those mentioned, so I grouped them into categories – e.g. Danes, analysts, etc.
  • I thanked, and loved, and “awesome’d” and “great’ed” a lot.
  • Sharing – giving credit, not taking it. I always mentioned the source or the account where I had picked up a link.
  • Sharing the love – retweets were focused on positive news, positive sentiments and uplifting current events. I also checked the wording of the original tweet before RT’ing to avoid contamination of my positivity.
  • Getting personal – my personality and emotions were conveyed more by sharing private interests such as books, cats, travel and science fiction.
  • Language Disclaimer – all of the above choices were based on my non-native perception of the English language, and may have been different from Webster’s Dictionary which is the basic semantic interpreter used in lexical hypothesis.

What I didn’t do

Humour doesn’t travel well, so any jokes, irony, satire and cartoons were not part of echrexperiment. I may have gotten carried away occasionally, but consciously tried to avoid it.

Politics are a powerful emotional trigger, so I avoided RT’ing or engaging in conversations with political statements. That wasn’t the mission.

Automation is a powerful tool to increase the quantity of your social media posts, but with automation things like timing and engagement suffer. Sometimes, due to other news, automation may even lead to displaying insensitivity.

Automatic response is a convenient way to further promote your services and invite people to connect. But it just isn’t personal. Despite all these lovely people addressing me by name. I did not send messages to thank people for the follow, but I checked their profile and retweeted where I could to show my appreciation.

What Watson had to say about @echrexperiment

The app itself produces a lot of detail as you can see from above. Below I grouped the result into more familiar charts to share some highlights. To make sure I picked a really nice person as control, I chose President Obama’s Twitter @potus. But please remember – it’s probably mostly his staff tweeting. And they seem to have done an excellent job.

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Obama – it appears – is very agreeable on Twitter, and my experimental lovely/nicey/catsy account matches this impression very nicely. We are both very open, although I am lagging on conscientousness, but hey –  I am not the President.

Digging deeper into selected parameters, revealed some interesting characteristics related to being a President or just trying to be a nice person.

We can all agree that values should be an important parameter if you are President of the United States. Strangely enough Obama wasn’t all that keen on change, and more inclined to be conservative. For self enhancement … we have identified the villain – the one parameter that makes my original Twitter account so repugnant. I leave the graph to stand on its own.

Meanwhile, President Obama scored a resounding Zero on self-enhancement – but he made it to the top already.

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President Obama’s most distinguishing need is the need for structure. Love – it seems – he gets a plenty.

On the other hand, my original self seems to have enough structure in her life.

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But here’s the greatest insight from this entire exercise – other than confirming that it is possible to change who you are, or rather how you are perceived:

When it comes to curiosity, all you need to do is be a positive tweeter and include lots of cats.

 

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Timing is everything – and loyalty is earned

Looking for correlations between airline social customer service and growth.

The social media manager of an airline or airport has a challenging job dealing with complaints, bookings, questions about all and sundry … and emergencies.

 

 

It’s not a nine to five job – it’s a 24/7 task for a social media manager at airlines and airports. People have questions and need help anytime, anywhere. Including when stuck in elevators. When it comes to monitoring and responding, in some cases it’s a life-or-death situation. I hope, Amanda Carpenter survived the ordeal of waiting from Feb 14 until Sept 7 in an elevator at the airport before somebody on the social media team responded to her tweet.

Oh, and Ms. Carpenter is not just anyone – she is an accomplished CNN contributor. Not that this matters – regardless of who you are, if you need help you should get it while you are still breathing.

Just testing

Knowing her to be a journalist, I seriously hope this was only a test to check the response time of @Amtrak – but you never know.

Airlines and airports – as well as many travel & leisure providers – are industries where a Twitter conversation is an important channel for customer interactions. So, in 2013 I wanted to find out how and if these industries had embraced this opportunity on improving customer satisfaction and grow their business despite a challenging market situation.

With the help of Datasift, we analyzed the response time on Twitter of 33 different airlines worldwide over a period of 30 days. At the time – 2013 – there were more than 100,000 tweets from customers mentioning the airline either directly or via hashtag. If ran today, the numbers would have multiplied.

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CEOs want social media presence to influence buying decisions

At least that’s the prevalent argument. Social media was about sharing and engaging with family and friends – who in turn influence our buying decisions. This was the major argument in favour of companies investing in these channels. And 3 years later it’s still up there as one of the reasons CEOs invest.

So, I asked my family, friends and wider network eight short questions about whether they had ever tried to contact an airline via social media, whether the airline responded, and whether you were satisfied with the response – leading to a positive customer experience. And repeated this survey in 2016 to see if things had changed.

Turns out, they hadn’t. The sample is in no way stastistically significant with 35 responses then, and 46 responses this year. But what is interesting, is that things hadn’t really changed that much. The airlines who were most responsive in 2013, were still the best and most appreciated in 2016. And those who sucked… well, they still sucked. Except two: American Airlines  and Lufthansa Group

 

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It is often said that it is almost impossible to reverse a bad reputation, which United Airlines has felt ever since it lost the famous guitar.  But it is possible to build a great reputation as American Airlines has done, and jump 33 points on the J.D. Powers  customer satisfaction index for airline industries. Simply by focusing on social profiles and social interactions.

American Airlines started running regular workshops with their staff teaching all customer facing employees how to navigate in the social media space and to pick up trends and grumbles before they turn into storms. In 2013 they were rated below average – three years later they had climbed the ladder significantly.

Twitter – a marketing channel or a conversation?

This graph shows the response rate versus customer interactions for some of the airlines in the study. You will want to look for the white space – the gap between the organge response line and the yellow staples signifying number of customer mentions either directly via their Twitter profile or in hashtags. The whiter, the better.

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Other than American Airlines, United and Delta, British Airlines stands out as being very non-responsive. In 2013, they “loved reading tweets” on their global Twitter account, but were only ”answering 09.00 – 17.00 GMT on weekdays.”

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For my analysis, I picked those airlines respondents had mentioned. Lufthansa was among those who were very present on Twitter showing promotional images of their aircrafts engine power, happy pilots and stewardesses, and pictures of the clouds in the sky. But for customer service, in 2013 Lufthansa referred people to download a detailed form on their website, and fax (!) or email it to their customer service centres.

Air travel remains for many people an uncomfortable, disappointing and grumble-worthy experience. Things have changed both for Lufthansa Group, American Airlines, United Airlines, and to some extent British Airways. But the grumbling persists.

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As with United Airlines and the lost guitar, the reputation of British Airways for non-supportive customer support remains a stigma. And the execution for both airlines appears still to be slightly lagging at least according to the 46 responses on my little survey.

Is there a correlation between focus on social customer service and growth?

Imagine if you could simply take these findings directly into the board room and demand more resources for your social customer service initiatives.

Unfortunately, it would require a lot more detail and a larger survey sample to draw any conclusions worthy of that, but the financial results before taxes and interest for some of the noteworthy airlines from the original study show some trends, especially if related to growth in passenger numbers.

KLM is famous for it’s pioneering efforts in engaging customers on Twitter with their many innovative ideas. But this analysis cannot illustrate the impact, if any, because they had since merged with Air France. But they are both on the top ten index of the world’s best airlines, so it can’t be all wrong. Similarly, Lufthansa Group now comprises Swiss who already then were performing well in the response rate plus acquired several more in the interim years.

We shouldn’t jump to conclusions. Even obvious correlations may be false friends.

In 2000 there were 327 deaths by people entangled in their bedsheets and per capita cheese consumption in the United States was 29.8lbs. This has grown to 717 deaths and 32.8lbs of cheese by 2009. A clear correlation over the years.

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 Enjoy more of these obvious and very funny correlations by Tylver Vigen here.

What I am trying to illustrate with the cheese in the bed sheets is that we cannot draw any conclusive data from the social media engagement rate and the financial results or passenger growth in the airline industry. There are too many additional data points that influence or need to be filtered out. It requires more computing power than I have available. But it would be an obvious task for some of the now very hot artificial intelligences being launched by many IT vendors. What if I could ask IBM’s cognitive intelligence Watson  to do an analysis?

I did in fact ask Watson about something else – stay tuned for my next blog post on the Kobayashi Maru – or how I convinced Watson to change its impression of my Twitter personality. Take a look at @echrexperiment on Twitter to see how I did it.

So, is there a correlation between a company’s financial growth and turnover and how socially engaged they are in their customer service function?

The short answer is yes and no

Sorry, if this wasn’t helpful.

If you compare customer satisfaction index, the financial results before taxes and the passenger growth of these airlines in 2013 adding the filter of how they were rated in engagement on Twitter with their 2016 results and growth, all of them have grown. But not necessarily because of their satisfaction ratings or social media engagement, but due to other strategic measures such as mergers, geographic focus, improved fleet etc. The numbers provided in the below chart are based on the annual reports and official websites of each of the airlines comparing 2013 with 2015.

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It can make all the difference in the world

On this chart one airline stands out with negative growth in passengers and the lowest financial growth 2013 – 2016 on results before taxes and interest. But it is also one of the most Social Airlines in terms of response rate.

Scandinavian Airlines Systems was facing bankruptcy in November 2012. Media reported hourly on the negotiations between trade unions and SAS leadership and executive board. They were trying to agree on terms that would make SAS more competitive and allow the airline to bring in more capital to avert the crisis.

Meanwhile, over the course of that week, travelers were deeply worried. But SAS had a social media strategy in place already. Following the infamous volcanic ash cloud closing down airspace in most of Europe in 2011, they had kicked off their social media channel with a focus on providing active assistance and service to their passengers.

During that dramatic week, one social media manager in particular – Cecilia Saberi – stood out with her calm and constructive responsiveness, her quiet charm with a twinkle in her eye. She worked day and night, slept on the sofa in the office for a few hours only to resume responding to concerned passengers, media and sensationalists. Her approach was sincere, open, genuine and fact-based. And she showed with every comment, every tweet, that people interact with people, not machines or corporations.

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(Bård tweeted a link to a newspaper site: “SAS in collapse. SAS very close to bankruptcy.” Cecilia responded within minutes: “Hello Bård, we are flying as usual, but of course all these speculations in media create unnecessary uncertainty. Have a nice day! //Cecilia”)

SAS did not lose their passengers during that week as far as is known. Because business continued as usual in a very unusual situation. As is often the case, despite sensationalist media reports creating issues without proper attention to facts.

I repeat – Timing is everything

As you can see from the below Skytrax 2015 airline ratings, customer satisfaction does not necessarily lead to better financial results or more bookings.

But during a crisis, loyalty and genuine openness and care – including responding while the response is still helpful and not leaving a journalist in an elevator for 6 months – can make the impossible possible and turn around a potentially disastrous situation into even better experiences.

Cecilia no longer works for SAS – but how she interacted has become the style of the social media team and is well appreciated by the customers. The seats may be shaky, there is no silver ware in business class, but Scandinavians remain loyal a little longer while SAS gets itself sorted.

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