I was talking to a Bikram friend today, who said that the first 20 minutes of the Bikram yoga sequence is us getting back in touch with ourselves and she has wondered for a while how to take that off the mat and into her life.
I love it when someone articulates clearly something that I have been pondering but didn’t know where to start. I know that connection to others is necessary, not least of all, because we learn about ourselves. But, in order to connect to others in a meaningful way, we first of all need to be able to connect to ourselves.
Each December, I like to reflect on what I have been blogging about all year. I did so in 2015 and 2016 and in this way I connect with myself, and my words, which makes it easier to connect to others and their words, especially with WordPress Reader.
And then, the stats themselves can tell a story. As I said in Top Blog No 3 (below), we are living in an age when we have lots of data and very little narrative, or insight, which is why everyone is nuts about big data as they think it will give them insight. But, to get the insight, you need to see patterns, and then make them into a story.
So, let’s take a look. My top 10 blogs of 2017 are:
In all honesty, given the nature of 3.6 billion people online and how Google gets people to come to this site, the only real common thread in these blogs is that I wrote all of them. That said, I could make all manner of patterns out of these 10 posts because if there is one thing statisticians know: if you torture the data long enough it will tell you anything. But, what I really see in these top posts is that I have been blogging away about social media and storytelling for a few years now, and I have come full circle.
The constant theme running through all the blogs is connection and also understanding how to connect (which is why 4 and 9 have made it on, we like to make sense of our connections, 1, 5 and 6 are about making sense of bad behaviour or when connection goes sour). Now I only have two blogs left to write (one on social computing, and one on connection) and then I will have said everything and much more than I intended to, when I set out to talk about social media.
I am a year behind schedule as 2017 has been painful with some difficult life events, some heartbreak, and a lot of soul-searching, so to have felt a connection to others, more often than not online, throughout 2017, has been truly lovely. We do connect and have proper conversations on social media, contrary to what some sociologists might think.
I love blogging here. I make sense of the world and of myself, and as psychotherapist Matt Licata puts it, I satisfy that innate yearning for intimacy and aliveness.
So for that, and for the conversations, the connections, and for the laughter, especially the laughter, I am so very, very grateful, and I can’t wait to do it all again next year!
As a computer scientist, I have to say my job has changed very little in the last last twenty-odd years. The tech has, admittedly, but I am still doing what I did back then, sitting in front of a computer, thinking about how computers can make peoples’ lives easier, what makes people tick, and how can we put the two together to make something cool? Sometimes I even program something up to demonstrate what I am talking about.
It seems to me though that everyone else’s jobs (non-computer scientists) have changed and not necessarily for the better. People do their jobs and then they do a load of extras like social media, blogging, content creation, logging stuff in systems- the list is endless – on top of their workload.
It makes me wonder: Is this progress?
Humans and stories
As a teenager, on hearing about great literature and the classics, I figured that it must be something hifalutin’. In school we did a lot of those kitchen sink, gritty dramas (A Kind of Loving, Billy Liar, Kes, etc.,). So, when I found the section in the library: Classics, Literature, or whatever, it was a pleasant surprise to see that they were just stories about people, and sometimes gods, often behaving badly, and I was hooked. Little did I know that reading would be the best training I could receive to become a computer scientist.
Human and computer united together
In my first job as systems analyst and IT support, I found that I enjoyed listening to people’s stories in and amongst their descriptions about their interactions with computers. My job was to talk to people. What could be better? I then had to capture all the information about how computers were complex and getting in the way and try to make them more useful. Sometimes I had to whip out my screwdriver and fix it there and then. Yay!! Badass tech support.
The thing that struck me the most was that people anthropomorphised their computers, talking about them needing time to warm up, being temperamental, and being affected by circumstances, as if they were in some way human and not just a bunch of electronic circuits. And, that the computer was always the way of progress, even if they hated it and didn’t think so.
I think this is partly because it was one person with one computer working solely, so the computer was like a companion, the office worker you love or hate, who helps or hinders. There was little in the way of email or anything else unless you were on the mainframe and then it was used sparingly, especially in a huge companies. Memos were still circulated around. The computer was there to do a task – crunch numbers, produce reports, run the Caustic Soda Plant (I did not even touch the door handles when I went in there) – the results of which got transferred from one computer to another by me, and sometimes by that advanced user who knew how to handle a floppy disk.
Most often information was transferred orally by presentation in a meeting or on paper with that most important of tools, the executive summary whilst the rest of it was a very dry long winded explanation, hardly a story at all.
Human and computer and human and computer united
Then the Internet arrived and humans (well mainly academics) began sharing information more easily, without needing to print things out and post them. This was definitely progress. I began researching how people with different backgrounds like architects and engineers could work together with collaborative tools even though they use different terminology and different software. How could we make their lives easier when working together?
I spent a lot of time talking to architects and standing on bridges with engineers in order to see what they did. Other times I talked to draftsmen to see if a bit of artificial intelligence could model what they did. It could up to a point, but modelling all that information in a computer is limiting in comparison to what a human can know instinctively, which is when I realised that people need help automating the boring bits, not the instinctive bits.
I was fascinated by physiological computing, that is, interacting using our bodies rather than typing – so using our voices or our fingerprints. However, when it was me, my Northern accent, and my French colleagues, all speaking our fabulous variations of the English language into some interesting software written by some Bulgarians I believe, on a slow running computer, well, the results were interesting, to say the least.
The UK government’s push to get everything electronic seemed like a great idea, so everyone could access all the information they needed. It impacted Post Offices, but seemed to free up the time spent waiting in a queue and to provide more opportunities to do all those things like pay a TV licence, get a road tax disc, and passport, etc. This felt like progress.
I spent a lot time working on websites for the government with lovely scripts to guide people through forms like self-assessment so that life was easier. We all know how daunting a government form can be, so what could be better than being told by a website which bit to fill in? Mmm progress.
Lots of businesses came online and everyone thought that Amazon was great way back when. I know I did living in Switzerland and being able to order any book I wanted was such a relief as opposed to waiting or reading it in French. (Harry Potter in French although very good is just not the same.) Progress.
Then businesses joined in and wanted to be seen, causing the creation of banners, ads, popups, buying links to promote themselves, and lots of research into website design so they were all polished and sexy, even though the point of the Internet is that it is a work in progress constantly changing and will never be finished.
I started spending my time in labs, rather than in-situ, watching people use websites and asking them how they felt. I was still capturing stories but in a different way, in a more clinical, less of a natural habitat, way which of course alters what people say and which I found a bit boring. It didn’t feel like progress. It felt businessy – means to an end like – and not much fun.
Human -computer -human
Then phones became more powerful and social media was born, and people started using computers just to chat, which felt lovely and like progress. I had always been in that privileged position of being able to chat to people the world over, online, whatever the time, with the access I had to technology, now it was just easier and available to everyone – definitely progress. Until of course, companies wanted to be in on that too. So, now we have a constant stream of ads on Facebook and Twitter and people behaving like they are down the market jostling for attention, shouting out their wares 24/7, with people rushing up asking: Need me to shout for you?
And, then there are people just shouting about whatever is bothering them. It’s fantastic and fascinating, but is it progress?
The fear of being left behind
The downside is that people all feel obliged to jump on the bandwagon and be on multiple channels without much to say which is why they have to do extras like creating content as part of their ever expanding jobs. The downside is that your stream can contain the same information repeated a zillion times. The upside is that people can say whatever they like which is why your stream can contain the same information repeated a zillion times.
Me, I am still here wondering about the experience everyone is having when this is all happening on top of doing a job. It feels exhausting and it feels like we are being dictated to by technology instead of the other way around. I am not sure what the answer is. I am not sure if I am even asking the right question. I do know how we got here. But is this where we need to be? Do we need to fix it? Does it needs fixing? And, where we should go next? I think we may need a course correct, because when I ask a lot of people, I find that they agree. If you don’t, answer me this, how do you feel when I ask: Is this progress?
No, I’m no super lady, I don’t have no game whatsoever,
I put my high heels on and see how that goes, yeah
– Pauline, Sucker for love
Ask a mathematician why they like maths, and they will tell you that mathematics gives a definite yes or no. There is beauty in clarity. And, everyone likes to feel that they understand and have control over what is happening in their world. This feeling of certainty is reflected in the bottom two rows of Maslow’s hierarchy of needs: physiological and safety needs.
Tapping into fear and belonging
That said, we also love variety and surprise, which is the most popular information shared on social media. We crave new stimulus which is why we love games. We love the idea of chance or fortune transforming our lives for the better, and surely if we learn the rules, then we will succeed. And, that is why marketing has such a pull on us. Marketers tell us that we will have improved lives if we do/buy/or have what they are selling, and, marketers themselves will have improved lives too if we do/buy/or have what they are selling.
Tapping into belonging is another way to market, which is why the connection economy and building friendship with your customers is gaining so much traction as a marketing strategy.
Modelling emotion and what-ifs
Modelling human emotion is impossible to do with game theory especially on social media, a fluid, still unknown, type of communication. We will never quite know who our audience is. We may target our demographic, but if they retweet or share something outside of that, then you never exactly know who is looking at your content, or how they will react to it. All game theory can do is offer interesting and potentially useful partial explanations to model a selection of what-ifs scenarios when employing different strategies.
In the last post (part 3), we looked at various game theory strategies from the aggressive to the altruistic, and saw that people generally behave like the people around them (hawk-dove) and that Kermit was in a bit of hurry to get together with his girl, which caused him to behave passive-aggressively, and probably not get what he wanted.
Don’t be like Kermit
Game theory is a tool for social media marketing and the best application of it is recording trial and error attempts (with statistical significance) whilst using our emotional intelligence.
Be aware of your emotions and triggers (your personal competence) so you don’t get involved in a big wrangle either privately, which could damage a relationship, or publicly, which might be retweeted everywhere and could wreck your brand or reputation. Even in the mathematics of game theory we need to understand other players moods and motives (social competence) and not assume anything. We need to ask for more clarification, so that when we do make a move, we do so with clarity and certainty that we are doing the right thing, and as any mathematician would tell you if you asked them, there is beauty in clarity for it gives us certainty and a sense of control, things which are harder to come by in our ever changing world.
Kermit drinking his tea and throwing shade makes me laugh. However, I think we all understand his frustration. It seems that in business and personal relationships, people play games. We may not know why, and we may not know the rules. But as we saw in part 2, before we react, we might want to find out more: if a game is being played, which one, and if we want to play or not.
Games, payoffs, and winning
A game is normally defined as having two or more players, who have a choice of possible strategies to play which determine the outcome of a game. Each outcome has a payoff which is calculated numerically to represent its value. Usually, a player will want to get the biggest payoff possible in order to be certain of winning.
Dominance, saddles, and mixed strategies
Playing the strategy with the biggest payoff is known as the Dominance Strategy, and a rational player would never do otherwise, but it’s not always easy to identify which strategy is best.
So, players sometimes take a cautious approach which will guarantee a favourable result (also known as the Saddle Point Principle). Other times, there is no saddle point so players have to choose at random what strategy to play and hope for the best. They can calculate the probability of mixing up strategies and their chances of winning. If their probability skills are not great they can play experimentally and record their results 30 times (for statistical significance) to see which strategies work.
How does this work on social media? Well, no one knows how social media works so a trial and error approach whilst recording results can be useful. Luckily, Twitter and Facebook both provide services and stats to help.
Free will, utility, and Pareto’s principle
A major question is whether players have free will or not and whether their choices are predetermined based on who they are playing with and the circumstances in which the game takes place. This can depend on the amount of information players have available to them, and as new information becomes available, they play a specific strategy, thus seeming as if they didn’t have free will at all.
Players assign numbers to describe the value of the outcomes (known in economics as utility theory) which they can use to guide themselves to the most valued outcome.
This is useful if we have a game where the winner doesn’t necessarily take all. If the players have interests which are not opposed and by cooperating the players can end up potentially with a win-win situation or at least a situation where everyone gains some benefits and the solution is not the worst outcome for everyone involved. This is known as the Pareto Principle.
On social media? Retweeting and sharing other’s businesses news is a nice way of ensuring everyone gains some benefits because with a potential market of 307 millions and there is enough of a market to go around for everyone to win-win and of course, reciprocate.
The Nash equilibrium
Taking this further is the Nash equilibrium which was named after John Nash, who proved that every two player game has one equalizing strategy (either pure or mixed) in each game. By looking at the equilibrium strategies of the other players, everyone plays to equalize. This is because, no player has anything to gain by changing only his or her own strategy, so it is win-win.
Are you chicken?
Ducks have been known share out the bread thrown to them so they all get some rather than one duck eating everything. This is known as the Hawk-Dove approach in game theory. When there is competition for a shared resource, players can choose either conciliation or conflict.
Research has shown that when a player is naturally a hawk (winner takes all) and plays amongst doves, then the player will adapt and cooperate. Conversely a dove amongst hawks will adapt too and turn into a fighter.
If there are two hawks playing each other the game is likely to go chicken, which is when both players will risk everything (known as mutually assured destruction in warfare) not to yield first.
We adapt very easily to what is going on around us, and on social media this is totally the same. In a 2014 study Pew Research Center found that people are less likely to share their honest opinions on social media, and will often only post opinions on Facebook with which they know their followers will agree – we like to conform.
The volunteer’s dilemma
In contrast, the volunteer’s dilemma is an altruistic approach where one person does the right thing for the benefit of everyone. For example, one meerkat will look out for predators, at the risk of getting eaten, whilst the rest of the meerkats look for food. And, we admire this too. We love a hero, a maverick, someone who is ready to stand up and be different.
The prisoner’s dilemma
But we hated to feel duped which is why the prisoner’s dilemma is one of the most popular game theories of all. Created by Albert W. Tucker in 1950, it is as follows:
Two prisoners are arrested for a joint crime and put in separate interrogation rooms. The district attorney sets out these rules:
If one of them confesses and the other doesn’t, the confessor will be rewarded, the other receive a heavy sentence.
If both confess each will get a light sentence. Which leads to the belief that:
If neither confesses both will go free.
It is in each prisoner’s interest to confess (dominant strategy = 1) and if they both do that satisfies the Pareto principle (2). However, if they both confess, they are worse off than if neither do (3).
The prisoner’s dilemma embodies the struggle between individual rationality and group rationality which Nigel Howard described as a metagame of a prisoner cooperating if and only if, they believe that the other prisoner will cooperate, if and only if, they believe that the first prisoner will cooperate. A mind boggling tit-for-tat. But, this is common on Twitter with those: Follow me, I will follow you back and constant following and unfollowing.
And, in any transaction we hate feeling like we have been had, that we were a chump, that we trusted when we shouldn’t have, which is why some people are so angry and like to retaliate. Anger feels better than feeling vulnerable does. But, great daring starts with vulnerability, the fear of failure, and even the failure to start, the hero’s quest shows us that.
Promises, threats, and coalitions
As we add more players, all rationality may go out of the window as players decide whether to form coalitions or to perform strategic style voting. If we introduce the idea of the players communicating then we add the issues of trust in promises, or fear of threats and it all starts to sound rather Hunger Games.
On social media aggression and threats are common, because of prejudice, or group think, especially on Twitter where there is no moderation. And, online and off, we have all been promised things and relationships which have ultimately left us disappointed, and told us that we have been misinformed, like the fake news, we’ve been hearing about a lot lately. Fake news is not new, in other contexts it is known as propaganda. And, if it is not completely fake, just exaggerated, well that’s not new either, New Labour loved spin which led to a sexed up dossier, war and death.
Kermit’s next move
Philip D. Straffin says in his book Game theory and strategy, that game theory only works up to a point, after which a player must ask for some clarification about what is going on because mathematics applied to human behaviour will only explain so much.
And so we turn back to Kermit. What is he to do? He has passive-aggressively asked for clarification and had a cup of tea. What’s his next move? Well, he could wait and see if he gets a reply (tit for tat). Who will crack first (chicken)? But, with the texts he has sent her, it is likely that her response is somewhat predetermined, or perhaps not, perhaps she will repond with Nash’s equilibria, or at the very least the Pareto principle of everyone not getting the worst outcome.
Alternatively, he could take a breath and remember that he is talking to someone he likes and with whom he wants to spend some time, someone human with the same vulnerabilities as him. He could adopt the volunteer’s dilemma approach and send her an honest text to explain that his feelings are hurt, he thought they had something special, and that she liked communicating with him as much as other people. By seeking clarification in this way, Kermit may just end up having a very nice evening after all – or not. Whoever said: All’s fair in love and war, didn’t have instant access to social media and all the complications it can cause.
The earliest proof we have, so far, dates back to 3600BCE: Six-faced dice with coloured pebbles made from heel bones of sheep and deer have been found on archaeological digs in Assyria, Sumeria, and Egypt.
By the time of the birth of Christ, many types of random number generators, including dice, were common, and were used for betting on or with board games. They were often spoken of as the workers of the blind goddess of fate, fortune, or destiny. And, it says in the Bible, that they cast lots to decide how to divide up Jesus’s possessions (Matthew 27:35). Even nowadays we talk about the roll of the dice when we talk chance and the things which happen to us.
By 10th century Europe, cards were the most popular thing with which to play games. There might be some skill, but really, a lot of it is up to chance, and don’t we all know that cliche about playing the hand you were dealt?
Highs and lows on the roll of a dice
The first formal attempt at analysing games, especially of chance, was written in 1520 (but published in 1663) by Gerolamo Cardano and has been recognised as the first step in probability theory. Cardano was a compulsive gambler, so would have felt the highs and lows of the roll of the dice more than most. He was foremost in the minds of Pascal and Fermat who published a book in 1654, continuing his work. And, it was Fermat’s last theorem which remained a phenomenon until it was solved in 1994. Imagine, it took three hundred and fifty years to solve a puzzle.
Later, writer Fyodor Dostoyevsky described our love of excitement and chance when playing games and how our fortunes can flip in an instant. He wrote about it in letters to his sister and his short novel, The Gambler. He was convinced that you needed to detach and keep a clear head, but had difficulty doing either, for it is much easier said than done. Consequently, gambling and games are ubiquitous, from church bingo to nationwide lotteries. Life can really change with a roll of the dice – or so it seems.
But, it has to be said, game theory isn’t the same as gamification, at all. Please don’t mix them up. Gamification is about turning things into games such as business objectives and anything else we want to make more engaging and more fun. When gamification is well designed, it works really well. But game theory is much bigger, and much more than just games.
In 1944, von Neumann and Oscar Morgenstern translated and expanded von Neumann’s theories in order to produce: The theory of games and economic behaviour. For his 1928 paper was mainly about two people playing a game together with only one winner (known as: two person game-zero sum) but game theory is much bigger than this, and it is not just about games and game playing.
It might be based in mathematics, but game theory has people in it, of course, which is why it can be used to think about everything: economics, political science and psychology. And, it has the crazy assumption that people behave rationally, which if there is one thing I know about life, people never behave rationally, nor should you expect them to. The other thing is that, we can only partially model any prescription because the world is huge and constantly changing, and we can never model everything in a computer. It really doesn’t matter how clever computers get. We have a long way to go yet when modelling humans and behaviour, but game theory is a start.
That said, power is the name of the game: group voting, economic theory and how to influence people, especially in areas like interpersonal cooperation, competition, conflict, labour negotiations, and economic duopolies, can all be understood in terms of game theory.
Game theory for explaining social media
Social media is the big new tool of the Internet, for business, politics, etc, and as of yet, no one knows how it works. So, this series is going to take a look at some of the big hitters of game theory: the prisoners dilemma, the Nash equilibrium, and so on, to see if these strategies can help us understand better how social media works. Are people cooperating or conflicting in ways these models describe on social media? If yes, can we understand and anticipate behaviour? If not, what other theories could we come up with?