Redirect FB algorithms now and 4 lessons from #CambridgeAnalytica #digitalcitizens

Anyone interested in data and ethics has been reading a gazillion of articles the last week. So, time to recap the big results coming out of the Cambridge Analytica files: correlations have their scientific merits (argh!), humans can be profiled in just 12 likes (honestly, this is how diverse we all are?!), anything measured can be used against us (a Cobra), and teachers around the globe seem more ethical than scientists (my partner says it’s true, I say it isn’t). Well... manipulation is part of history, I guess... but still!

First of all, a nice MIT research project on “How to manipulate Facebook andTwitter instead of letting them manipulate you’ (yes, it is a timely title 😊 ) mentioned in MIT’s Technology Review. The project let’s you – the user – manipulate algorithms emphorced on you by Twitter and Facebook (I like it, activism from within the system). This initiative is called GOBO (if you want to jump right in, you can login for this project here) and it is a prject from researchers at the MIT Media Lab’s Center for CivicMedia. It has an interesting parallel referring to Cambridge Analytica approach, BUT in this case it is truly scientific, and they ensure deleting ANY and EVERY data collected once they have results on how you would like to see algorithms adjusted. So take back the algorithms of Twitter and Facebook with GOBO.

I am just resurfacing after the Cambridge Analytica fraud (I call it fraud as they have been anything but ethical in their so called scientific data gathering: no informed consent, data gathered and not anonymised before using it for 3 parties, data not deleted after a project was finished….).

Correlations are used successfully? Argh!! For years, many educationalists and researchers emphasize that correlation is no replacement for causality. Causality is the basis of all strong research. It is clear that education and correlation aren’t a love story. We- as educators and researchers - know and understand the importance of context, of language use, of how personal each of our learning journeys takes form. In a sense, we should know better then to construct a test that puts everyone in the same batch, and then believe in it to state those things that we think sound nice (however tempting that type of action is... I mean, saves time on reflecting, nuancing, evaluating... and all these time-staking stuff) … but Cambridge Analytica got away with it. PISA was/is another such example. It even manages to enter the OECD report (https://www.oecd.org/education/) as core element of proof leading to rigorous outcomes. PISA test is an in correlation resulting test. A nice list of educationalists that argued against using PISA here. With the Cambridge Analytica files, the correlation monster pops up once again … AND it is now used ‘successfully’ to blind-side people and to get them to doubt their political choices just enough to swing their vote. So, correlations can be used quite viciously for some of the time.  

Forget complex human traits: humans can be profiled in just 12 likes! And all of this comes from research (great paper on how it was set up here, Schwartz , Eichstaedt, Kern, Durzynski, Ramones, Agrawal, Shah, Kosinski,Stillwell, Seligman and Ungar (2013) . Well… how difficult is becomes to state (and belief) that humanity is truly diverse! Admittedly, the Big Five Traits also distil human diversity into just 5 personality traits, but still… being profiled on 12 likes… How individual are we, if that is all it takes to cast each one of us in a box that subsequently can be manipulated from that moment onward? It becomes quite difficult to see humans as complex beings when I take that into account… but we are social, at least that is now proven once again.

Anything measured can be used against us. One of the most interesting blogposts I have read, is an older one from MikeTaylor, stating that as soon as you try to measure how well people are doing, they will switch to optimising for whatever you’re measuring, rather than putting their best efforts into actually doing good work, and this optimising is always at risk of being distorted, even corrupted (Mike refers to Goodhart’s law, Campbell’s law and the Cobra effect – great read).

And teachers around the world have more ethical sense than scientists that do not teach… well it is a discussion, my partner says that fact is well known, I say scientists who do not teach can be ethical as well…. Those darn Cambridge Analytical (and derivates) people! (good example of this is Autumm Caines , she wrote on Platform literacy refering to her encounter with Cambridge Analytica to get all her data from them all the way back in February 2017 (which was a hastle!). Yes, she got active one year before this whole event blew up into an international scandal. Autumm keeps ethics high!   

In search for #AI for critical thinking in #education #criticalthinking #language

Who knows of Artificial Intelligence (AI) initiatives being developed to support critical thinking in education, or based on data text analysis and cognitive language use? Please drop me a line (or message). To give you an idea of what proceeded this question, I am providing some AI background, including my thoughts. A good read is the paper by Yeomans, Stewart, Mavon, Kindel, Tingley and Reich investigating "the civic mission of MOOCs: engagement across political differencess in online forums", which adds to the idea of using AI as a way to stimulate debate across opposing viewpoints, thus enhancing critical thinking (for those willing). 

AI to help human thinking processes

AI is rapidly expanding its reach: you have initiatives of meaningful curated content generated by AI into elearning (e.g. Wildfire http://www.wildfirelearning.co.uk/ ), you have legal research analysed and organised by AI (e.g. http://www.rossintelligence.com/ ), you have multiple AI molding social media interactions based on factors such as friends, exchanging ideas, similar content (sometimes opinions) shared… basically, industry is looking at AI as a means to refocus on less-repetitive parts of their business or profit goals (https://insidebigdata.com/2017/01/29/amplifying-human-potential-towards-purposeful-artificial-intelligence-a-perspective-for-cios/ ).

But, I am wondering whether there is research projects taking into account AI using text analysis but including cognitive language use to enhance critical thinking (for instance: if you have echo chambers, why not use AI to pick up frequently used arguments from ‘the other side’ to generate more in-depth arguments for either side. Or for those looking to become dominating world leaders (devils advocate here): creating something which goes beyond fake news: using arguments that feel right but actually are built using persuasive language construction to trigger a feeling of ‘that is right’ and parallels what a person thinks is morally correct (I said it was a devils advocate example :D )

AI in education

With all the talk on the new citizens needing to be ‘creative’ mindset above anything else, the creativity does not seem to emerge yet in AI, the focus is still more on rehashing what is already there, but with more focus on the norm by using AI in education (I could be wrong, feel free to provide arguments on why creativity is indeed boosted by AI in education).

A couple of examples where AI is used to boost learning, but along the lines of existing norms, nevertheless of interest.

Deep Knowledge Training. One of the interesting strands of AI in education research is Deep Knowledge Training (a good read is the 2015 paper by Piech, Bassen, Huang, Ganguli, Sahami, Guibas and Sohl-Dickstein https://web.stanford.edu/~cpiech/bio/papers/deepKnowledgeTracing.pdf ) this allows a machine to model the knowledge of a student as they interact with coursework. It can be used to extrapolate student performance for instance. This seems to be good, but you know that this is based on ‘what we expect of students’, which is not necessarily what could be good for humanity or social thinking.

Assessing future scores. Another example is the algorithm built by Google and Stanford which relates to a students learning ability (well more specifically how a student would answer questions) http://www.dailymail.co.uk/sciencetech/article-3380374/The-end-exams-Algorithm-predict-students-answer-questions-explain-questions-wrong.html . Here as well, the learning seems to parallel taking exams… which does not seem to promote creative thinking.

IBM Watson for education (https://www.ibm.com/watson/education ). Starts from the idea of personalised learning (and passion, so I really love that starting point), but when I looked at the videos, the definition of personalised learning seemed to be limited to personal interests (in educator video), which limits the concept of personalised learning. And though it is good to provide skill-level content, if the content base you pull it from is standard…. The standards will again be the norm, which does not necessarily result in creative ideas or insights.

AI based on language data

One example I found using AI in relation to natural language processing is NexLP (https://www.nexlp.com/ ) (quoting from their page: “leveraging the latest advances in Natural Language Processing (NLP), Cognitive Analytics, and Machine LearningㅡStory Engine turns disparate, unstructured data - including email communications, business chat messages, contracts and legal documents - into meaningful insight that can be used to act, as well as combined with structured data to create a truly comprehensive view of the entire data universe.) and the people behind NexLP state that they use cognitive analysis to add more context to the actual text analysis”.

But when looking at it, it seems more of an enhanced interactive dashboard at first glance. This means it feels more like a quantifiable AI implementation than a qualitive one. One of the solutions to filter meaningful content is wikification (where you link entities https://en.wikipedia.org/wiki/Entity_linking ) which seems to be an effective way to add context to text analytics technology (https://www.nexlp.com/blog/2017/12/26/nlp-technology-architecture )

Past fake news or beyond critical thinking

The term fake news is now a given in many politician’s speech, both in its originally intended definition, as well as in popular debate where it functions as a way to ridicule and diminish the truth or value of an argument by an opposing person. But maybe we can turn this around. Create algorithms that can be used to enhance our debating skills, our critical thinking by generating arguments that are most frequently used by groups gently opposing our views. I mention gently opposing, as persuasive arguments are rarely harsh, completely opposing arguments.

I see this as a possible way to tear down the echo chambers created by filter bubbles, and build bridges. Or at least get a conversation started.  

Feel free to share your thoughts or link to examples.

Picture from http://cdn.nanalyze.com/uploads/2017/08/mckinsey.jpg 

#OEB_midsummit Andrew Keen on How to fix the future @ajkeen #AI

Andrew wears his casual black attire and looks energetic and ready to roll with seeming ease and humor. And right before taking the stage, Andrew put on his jacket (I like that personal touch).

Thinking is about talking, entering into dialogue and getting messages across and combined by people. It is not about the slides.

We have education, but in the end everyone says: the solution is education, everything can be fixed by education. But the education system is inseparable of the economic, social problems of society. A teacher alone cannot fix inequation and other difficulties of society.

Education can only do so much, but it cannot change rampant mass murder (history is full of that). Education is not magic, it is work.

The great transformations have always been part of revolutions in history. But this transformation is taking us into new realms, but transformations have always happened. But change brings along trauma in many cases.

Andrew Keen mentions groups for which the societal transformation did not work, dramatic inequality and revolution. (this is an ethical take based on moral right and wrong as perceived by Andrew). Equality only came gradually, and we are not really there yet.

Surveillance economy coming from innovations at Silicon Valley, similar to the industrialists during the industrial revolution. Unions, taxes… came later to right the wrongs of that transformation. The same might be coming now. Education was than instituted as a form of standardization for production reasons (same skills, same content, same books…).

Today the forces are similar, how are we supposed to educate people for this new world.

The ideology of Silicon valley is increasingly being applied to education (see NYTimes of 7 June 2017 – silicon valley billionaires and schools). Zuckerberg empowers the student, but undermines the teacher. Undermining truth (e.g. fake news). Hastings (Netflix) is a different type of influencing Education, in his term by using Artificial Intelligence that will improve the teaching by providing tools. Bennihof (?) importing the sillicon valley business approach into schools, treating education as a venture capitalist adventure. But it is important to realise that the state is being pushed aside, replaced by super-citizen billionaire vision. So, this is never about technology, it is always about who has the power, who has the money. Make AI the operating system for this new teaching/learning system.

[this is possibly – I think – when implementing policies based on future goals].

What jobs are we going to have in a world where AI dominate the classroom, the law firm, the university… the hole in the future is jobs. Be wary that the educational nirvana by AI will not be without a cost. We have not seen anything yet, when 50% of us no longer have jobs due to AI and automation. Let’s not go overboard. STEM is no longer interesting, as machines can do this much more efficiently. So tech education has no real value. So what should we be educating people for? That is the great challenge, and that is why education is in the middle of a transformation. As we create machines and AI, what are we going to do? Are we going to be poets, fighters, share thoughts from the coach… what is going to be our ‘value’ in this new economy? Machines can do many things, but they cannot think for themselves, and they do not have their own goals.

We should be focusing on human values and skills: empathy, intuition, creativity, … some experimental schools. If you want to escape the algorithm, you need to think and prepare, and be willing to take risks. In 100 years’ time, schools will be different.

Recognising Fake news, the need for media literacy #digitalliteracy #literacy #education

I was working on a blogpost on books focusing on EdTech people (the woman, the tasks…), but then I opened up YouTube and I saw that president Trump had his first solo press conference.

I guess we can all benefit from Mike Caulfield's ebook (127 page) on web literacy for students (online version) or here for other versions including pdf), a fabulous book with lots of links and useful actions to become (more) web literate (thank you Stephen Downes for bringing it to my attention). 

After watching it, I thought there was a clear need (for me as an avid supporter of education) to refer to initiatives on the topic of real and fake news, because honestly I do not mind if someone calls something fake or real, as long is that statement is followed by clear arguments describing what you think is fake about it, and why. Before doing that, I want to share the reason for this shift in attention.

I love Amerika, for several reasons: where Europe stays divided, the United States have managed to get its nations to work together, while leaving enough federal freedom to adapt specific topics according to individual nation’s believes; I have worked and honestly like to work with Americans (of all backgrounds) and American organisations, truly I am in complete awe of the Bill of Rights, and the way the constitution is securing freedom for all. I know that a goal as ‘freedom for all’ is difficult to attain, but at least it is an openly set vision, put on paper. I mean, I truly respect such strong incentive to promote freedom for all citizens within a legal framework and the will to achieve that freedom. And due to this love for the United States, I felt that Trump is okay. In democratic freedom, the outcome might not be of anyone’s liking, but … history has shown that democratic freedom can swing in a lot of ways and that it this diversity nurtures new ideas and insights along the way.

However, while watching the press conference I got more and more surprised by what was said and how: there were clear discriminatory references, which I do not think befit a President of all the American people. But okay, to each his own and rhetorical styles can differ (wow, can they differ), but the ongoing remark and reference on Fake News that kept coming up as an excuse and used as a non-sequitur at any point during the press conference just got to me. Manipulation has many faces, and only education can help built critical minds that will be able to judge for themselves, and as such be able to distinguish real from fake news. To me, even if you refer to ‘this is fake news’, I want to hear just exactly what you mean: which part of what news is fake and why. Enlighten me would be the general idea.  

Fake news and believing it: status

A Stanford study released in November 2016, concluded that 82% of middle-schoolers couldn’t distinguish between an ad labeled “sponsored content” and a real news story on a website. Which seems to indicate that somewhere we are not addressing media or digital literacy very well. On the reasons why this lack of media literacy is occuring, I like the viewpoint of Crystle Martin who looks at misinformation and warcraft in this article; saying:

Teaching information literacy, the process of determining the quality and source of information, has been an emphasis of the American Association of School Librarians for decades. However, teaching of information literacy in school has declined as the number of librarians in schools has declined.

Luckily, there are some opinions and initiatives on distinguishing between fake and real news. Danah Boyd had another look at the history of media literacy, focusing on the cultural context of information consumption that were created over the last 30 years. Danah shared her conclusions in a blogpost on 17 January 2017, entitled 'Did media literacy backfire?' She concluded that media literacy had backfired, in part as it was built upon assumptions (e.g. only media X, Y and Z deliver real news) which often does not relate to the thinking of groups of people that prefer other news sites A, B and C.  

Danah describes it very well:

Think about how this might play out in communities where the “liberal media” is viewed with disdain as an untrustworthy source of information…or in those where science is seen as contradicting the knowledge of religious people…or where degrees are viewed as a weapon of the elite to justify oppression of working people. Needless to say, not everyone agrees on what makes a trusted source.

The cultural and ethical logic each of us has, is instilled in us from a very early age. This also means we look upon specific thinking as being ‘right’ or ‘wrong’. And to be honest, I do not feel this cultural/ethical mind set will deter all of us from being able to become truly media literate. As long as we talk to people across the board. As long as colliding thoughts fuel a dialogue, we will learn from each other and be able to understand each other in better ways (yes, I am one of those people that think that dialogue helps learning, and results in increased understanding, thank you Socrates).

If this is the case, than we need to do a better job of improving media literacy, including listening to people with other opinions and how they see it. It is a bit like the old days, where the people from the neighborhood go to the pub, the barbershop, or any get together were people with different opinions meet, yet feel appreciated even during heated debates.  

Maha Bali, in her blogpost “Fake news, not your main problem” touches on the difficulty of understanding all levels of the reports provided in the news and other media. Sometimes it does demand intellectual background (take the Guardian, I often have to look up definitions, historical fragments etc. to understand a full article, it is tough on time and tough to get through, but … sometimes I think it is worth the effort). Maha Bali is a prolific, and very knowledgeable researcher/educator. She touches on the philosophical implication of ‘post-truth’ and if you are interested, her thesis subject on critical thinking (which she refers to in her blogpost) will probably be a wonderful read (too difficult for me). So, both Maha and Danah refer to the personal being not only political, but also coloring each of our personal critical media literacies. 

If media literacy depends on personally developing skills to distinguish fake (with some truth in it) from real (with some lies in it), I gladly refer to some guidelines provided by Stephen Downes, as they are personal. One of the statements I would think is pivotal to distinguish between fake and real news, is understanding that truth is not limited to one or more media papers/sites/organisations, it is about analysing one bit of news at a time. It is not the organisation that is authoritative at all times, it is the single news item that is true or at least as real as it can get. So, here is a list of actions put forward by Stephen Downes on detecting fake news : Trust no one, look for the direct evidence (verification, confirmation, replication, falsification), avoid error (with major sources of error being: prediction, relevance, precision, perspective), take names (based on trust, evidence and errors), and as a final rule he suggests to diversify in sources (which I really believe in, the pub analogy). 

Another personal take on detecting fake news comes from Tim O'Reilly who describes a personal story, and while doing so he sheds some light on how an algorithm might be involved. 

Thinking about algorithms, you can also turn to some fake news detectors:

The BS detector: a fabulous extension to the Mozilla browser. Looks at extreme bias, conspiracy theory, junk science, hate group, clickbait, rumor mill… http://bsdetector.tech/

Snopes: started out as a website focused on detecting urban legends, and turned into an amazing fact checking website (amazing as you can follow the process of how they look at a specific item and then decide whether it is fake).  ( http://www.snopes.com/

And finally, for those who like to become practical asap: a lesson plan on fake news provided by KQED http://ww2.kqed.org/lowdown/wp-content/uploads/sites/26/2016/12/Fake-news-lesson-plan.pdf

In my view, the increase in accepting the idea of fake news is related to the increased divide within society. So, in a way I agree with Danah Boyd: we read and agree with specific people and news sources, and so we filter our sources to those people and media. Seldom do we read up on sources from media we do not agree with, or people we disagree with. It used to be different, as discussions around specific topics were discussed in our community, with a mix of ideas and preferences.

So maybe media literacy could be done on a community level, where everyone gets together and shares their opinion on certain topics. We recreate the local pub or café, where everyone meets and gets into arguments on what they believe (or not). Media literacy – to me – is about embracing diversity of opinion, listening, seeing the arguments from the other side and … making up your own mind again.

So, coming back to president Trumps referencing to fake news. In terms of increasing media literacy, I do not have a problem with referencing to something that is seen as fake news, I do have a problem with that fact not being explained: what is fake about it? Why? And again, with saying that, I mean a real explanation, not simply repeating ‘this is fake news. It is. I tell you it is’ (feel free to imagine the tone of voice that such a sentence might be delivered in), now give me the facts, because I do want to know why you or anyone else is labeling something as true or false.

(picture source: http://www.cyberlawcentre.org/unlocking-ip/blog/uploaded_images/wikipedian_protester-774177.png )