Triad model of learning in ML implementation

April 23, 2018 § Leave a comment

Göte Nyman, University of Helsinki, Finland
Ossi Kuittinen, SimAnalytics Ltd Helsinki, Finland

Machine Learning (ML) as part of AI is now familiar to us all, from managers and workers to engineers and designers. We know the secret of ML: it’s amazing potential to learn from data, huge amounts of it, which sometimes is a guided process but can also proceed without significant human intervention during the learning process. However, human contribution and collaboration remain necessary for any ML system design and implementation and especially in securing optimal ML system learning and its continuous improvement.

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(Creative Commons licence image)

What is the process where skilled human professionals and a ML system join their competences for a learning journey? How should we characterize the teaching, learning and interaction, where the ML system, human designers, engineers and workers act and learn together to come up with the best possible ML solution to the target environment?

With the fast improving ML we are suddenly confronted with a new kind of a teaching-learning-collaboration challenge or paradigm, where the competences, roles, learning processes, and responsibilities of the participating people must find their effective form and content, together with the ML system.

One could think that human-technology problems are nothing new and that the introduction of ML is just one phase like any other major leap in technology. But it may come as a surprise that we face a new kind of an interactive learning paradigm which changes fast. We call the work with ML as ‘triad of learning and collaboration’, consisting of at least the following components/actors (We use the concept of ‘triad’ in a slightly transformed form as borrowed from the learning approach where ‘the individual’, ‘the learning community’, and ‘the authentic use of the objects’ are separated entities of the learning situation; Paavola & Hakkarainen, 2005). A ML system that learns, interacts and teaches is a complex creature, indeed and this makes all the difference:

  1. The ML system as a whole – its sw, hw, system integration, computational models used, interfacing and its UI
  2. Operator-professionals specialized in the target domain and facing the planning, design and implementation of the ML system
  3. Designers and engineers responsible for the ML system design, implementation, process quality, and its continuous tuning.

What is special in this triad, is that all three ‘partners’ interact, teach and learn from each other, from the beginning of the ML project, often simultaneously.  Furthermore, while there are a plethora of theories and models of learning, including computer-assisted learning, for example, the theory of very intelligent human-ML-system, interactive learning – where a human teaches a machine and the machine teaches humans – does not exists.  It is time to launch its development so that it can keep up with the pace of fast advancing machine learning. There is already an intense discussion on the possibility to look inside a working deep neural network, one of the ML application, to improve its interaction with its operators but this only starting. Furthermore, it is highly likely that due to theoretical and technological advances, the current AI models will undergo major changes within the next decade or so.

We have summarized the triad learning relationships in a simplified form in the figure, where the instances of ML-human learning occur: 1. between the User/Operator and the ML system, and 2.  between the Designer/Engineer and the ML system. The two instances are very different in nature and require relevant organizing and management, because of the differences in the human competences involved. Both learning processes can occur over the whole development and maintenance cycle of the ML system, with different weights over time and they are of utmost value to the success of the ML implementation.

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Figure. A simplified scheme of the learning/teaching relationships and some of the learning contents in the ML implementation.

Design and introduction of the ML system

The design and project plan for the implementation of the ML can best be described as co-design (some form of it, from weak to strong). The designers/engineers introduce the candidate ML model for the management of the target system –  an organization, industrial plant or other relatively large-scale enterprise where the benefits of ML are expected to cover the costs. This is a complex learning challenge requiring the participation of the designers and relevant specialists who know and work with the target system and know the processes and who will then work with the ML-system. It is dangerous to apply a linear and fast-to-the-implementation approach in such a complex endeavor.

While the mathematical and technological features can be too complex for all users/operators to follow, it is necessary to introduce the ML in a way that its basic learning and its teaching characteristics can be understood and that a fruitful interaction in co-design becomes possible. In other words, a valid, ML model-in-practice must be introduced to the participant operators and other personnel.  Usually there is no unique or single ML model available for this purpose; hence the introduced model must be formulated and tailored accordingly, to match the competences of the participating personnel and the specific context of ML implementation. At the beginning, it is important to relate the ML concept, its functions and measures as closely to the target system model ‘as-is-model’ as possible so that the participating people can relate the ML system functions and its measures, the metrics used and the UI to the target system with which they are high-class professionals.

During piloting, testing and implementing these new concepts become critical since they make up the language with which the operators and users ‘negotiate the system’ and try to understand how it works. The operators learn a new ‘mental model’ of it by which they know what the ML system can and cannot do, what risks are included, how it can best be taught and how to communicate about it with the designers. These concepts guide the operators in their observations, too: what to follow, what to search for and how to react to certain observations of the ML system state and behavior. This is a most demanding challenge and mistakes made and vague concepts introduced can lead to blind spots in the development project, valuable knowledge of the ML system performance lost, underperformance and the costs becoming high. It is a very serious learning task for both the ML system providers and the personnel acquiring it.

New paradigm of interaction:people teaching ML when ML teaches people

With its computational power the ML system can shoot out practically unlimited amount of data: new measures if its status and dynamics, holistic and specific component state information, and any aspect of its measured performance, fast and slow in nature, depending on the environment.  Overflow of information is a real practical risk and possibility and it must be dealt with by means design, and human learning and collaboration. Some of the ML data is totally new to the people specialized in the ‘old’ system having its own, perhaps historical control systems and performance metrics.

Some of the ML data can be significant and even crucial for the system performance, some not, and during the piloting, testing and implementation process the personnel learns to recognize what is relevant information and why, and then guide the designers in representing it in the UI. This data environment then becomes the de facto world where the personnel learns to work – with the (partly or totally) new information.

The ML data must be made accessible for easy observations and its background processes amenable for easy, immediate and relevant control whenever necessary. An explicit interaction loop (measure-control-measure) must be provided which is either automatically controlled by the ML system, and only made visible to the operators or which is amenable for human control. The observation of these (numerous) control loops is an essential part of human-ML learning and it will introduce new tasks, practices and responsibilities to the personnel.

What is new in this triad-entity is that the ML system teaches both the Operators/Users and the Designers/Engineers in various ways, some of which are new. How does this interaction take place and how should this learning be considered and conceptualized as it concerns both the personnel and the ML system? This is a fascinating learning theoretical challenge which cannot be dealt here with now, but we will return to it later, especially after having collected practical experiences again from the work with SimAnalytics Finland.

 

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Teaching manners to AI: Internet of good Behavior

February 5, 2018 § Leave a comment

This is may be a speculative blog from the technological perspective but its behavioral background is solid; at least I believe so. The idea presented here is somehow funny and very serious at the same time. The simple question I have on my mind is how to teach manners to AI? It is not about a polite AI only, the problem scales up to as high spheres of human behavior and culture as far as we can see.

Seeing only a gloomy AI future?

We have read and heard Elon Musk and Stephen Hawking painting a scary future for the potentially destructive AI if it manages to escape our control and starts running wild. Some may think that ‘we can always take the plug off’ or that ‘AI has no will’. However, observing the recent false missile attack alarm in Hawaii made it clear to everyone, how simple human errors in using technology can cause devastating effects. It was a wake-up call to me too, especially noticing the official reaction to the error. The person who made the mistake was fired – a strange solution to the catastrophe – but the designers of the UI run free, I assume.

In AI the risks can become much worse than in Hawaii, especially when human errors can trigger complex, and difficult to follow chains of AI-based actions and the design for human-technology relationships is unfit to prevent this. The Hawaii example was extremely simple: the operator chose a wrong function from a simple, easily understandable set of alternatives. The mistake was taken seriously in the relevant organizations but I have not noticed this incident to launch much discussion on how we should prepare for the coming of AI where similar ‘human errors’ (actually they are design errors) will become possible.

In a recent panel discussion at Fire 2017 (Future of Work for Humans and Machines) the participants Joseph Smarr from Google and David Brin from Future Unlimited seemed to agree that it takes some time, some years perhaps, before the risk of a AI running dangerously wild becomes real. However, they did not discuss the ways in which AI could start living its own dangerous life in the net already today. Brin did imagine an AI, for example, which would be able and have a chance to scan and look at all the movies there are in the net and to learn whatever human behaviors we know is available there. What it would learn form the movies would not always be the best of humanity, so we need to find out human-controlled ways to teach the future AI manners and good behaviors. We should start it today.

Making AI a better person

We must teach AI manners. It is not different from educating our children and showing them how to behave in different life situations. At the moment there is no unique and scalable way to achieve this for AI.

Following the FiRe 2017 panel discussion and some of the comments from the audience made me think about the following: how to teach AI such manners and to do good or as someone from the audience suggested, to even nudge us to be better humans? AI cannot do anything like this unless it has a chance to learn behaviors that are good in nature, in some agreed-upon, human sense.

I’ve earlier introduced the concept of Internet of Behaviors where the idea is to introduce individual behavior data into the net and to make it (globally) available for a number of purposes, from health care, entertainment and education to marketing. The psychological thinking behind IoB is described here. It is like IoT but the idea is to assign addresses to an ongoing (it can be a historical or fictional, as well) behavior, which makes it possible to address and follow such a behavior and everything physical, digital and virtual related to it. This would also make it possible to build a contact with the person X showing that specific behavior (in case he/she is willing to allow it; I will not deal with the privacy issue here).

What if there was a systematic way to offer models of good behavior for AI to follow, to teach it behaviors we know and define as good behavior? In many cases it would be easy to define the criteria and to use such behaviors as models for AI to follow and learn. With the Internet of good Behaviors (IogB) approach we could offer AI access to behaviors (and companionships J ) we think are good for its development just like we do to our children. By allowing this we would let it use all the relevant data related to that behavior and to learn from it. It is quite possible we could learn from that too, but that’s another matter.

Of course there is no IogB system as of yet, but the potential exists already and is in use where personal data is collected by various devices. We do know how the deep neural nets already learn from examples but it’s some way to teaching them manners. IogB would take their learning to a higher level.

My idea for the AI community is to start a trial within a well-defined AI context where we know the criteria for good behavior and where good manners are relevant. It can be as simple as being polite in certain cultural situations, ways of speaking and interacting or getting food and support for the poor and looking at various ways people and citizens are now doing it globally, helping those in trouble, all over the world. Only imagination sets the limits here.

To run such a trial, we should arrange for people to adopt a coding (addressing) system for their detailed behaviors by using a simple app and monitoring system. Of course they should be willing to reveal (without revealing their identities) their behavior for the specific AI we want to teach manners. A feasible coding system for such behaviors is needed; you can consider this as a process of addressing specific behaviors in the same way as objects are addressed in IoT, which can be, for example, verbal or bodily expressions, emotional states, but they can also be physical or virtual transactions relevant to the specific entity of good behavior, practically anything related to human internal or external behavior. My main point here is that the occurrence of the addressed behavior makes it available in the net and the AI can then use it as learning data. There is much to do in this and to build a Teach manners to AI framework.

We can imagine the huge scope and scale of the approach by considering all possible contexts of good human behavior, from documents, and movies to real, human ongoing behaviors. Then there is the scary thing: Internet of bad Behaviors. It’s possible that we cannot stop it unless we can teach good behaviors first and even that may not be enough. Without going deeper into this I see a real, even important possibility for building and educating a human AI. We have time to do this. In the IoB blogs I have explained the background of this behavioral approach in more detail.

 

Living with the blind banks

October 24, 2017 § Leave a comment

Most of us use the bank apps for managing our weekly, monthly, even daily money affairs, the accounts, payments and mortgages through the Internet and mobile. To guarantee the security, some banks offer a number of ways securing the connection, but whatever the nature of the apps and the security tools they always open an active, exceptional bridge between our everyday life and the banks.

We can easily imagine, over the coming few years, how these apps and services will evolve in general, but one thing is certain: we will be communicating with the banks or related operators, be it mobile or over the net, using these systems and personal devices in a way that marries us with them. What a huge potential for a holistic and human-centric service – if it is seen as one!

Surprising enough, the banks have not realized – or they have been v-e-r- y slow to do it – that many of us, their clients have these daily or at least weekly intimate contacts with the bank. Even more interesting is that at the specific moment when using the apps and managing our economics at home or in our businesses, perhaps discuss it with our spouses or colleagues, we are fully tuned to the world of personal economics.

The knowledge of this state of mind of the customer is the wet dream of all market operators, who typically try to guess it in order to approach him or her at the right and relevant moment with an optimal offer. Usually they fail because even with the best, current and near-future (realistic) artificial intelligence and machine learning systems they cannot know how busy, open or motivated to engagement we happen to be. It is not untypical that we use the bank apps under other significant pressures at home or at work and have no time or interest to make it more complicated by paying attention to the interfering market messages and offers, as lucrative as they might be, received from the bank or other service providers.

Indeed, the most underestimated aspect of customer behavior is that we, as customers know, exactly, when we are interested in, ready and even willing to be engaged with any of the service providers we are connected with in our life, including the banks. You would expect that especially the banks, under the tremendous competition of today, and having such an exceptional window to and connection with our everyday life, would make the most out of this extraordinary channel and the opportunities it offers. They don’t.

How do the banks deal with this sensitive situation and the intimate connection they have been able to build with us, to be used perhaps hundreds of times a year? It is possible that somewhere around the world that I’m not aware of, it has indeed been used effectively, but my educated guess is that it’s been practically neglected and instead the apps and their services are just simple self-service systems with minor personal, economic and account data management possibilities. Above all, the main information traffic takes place without any consideration of the true state of mind of the client.

You would imagine that banks like OP in Finland had already done it, as it has been several times mentioned by their CEO Reijo Karhinen that they are extending their business beyond the traditional banking towards natural aspects of life such as transport, housing/living and perhaps to many other segments of life as well. There the need for relevant ict solutions only increases under such extensive developments and they must try to approach the clients better and more intimately than ever before. What could be done?

Internet of economic behavior

In 2012, I wrote two blogs introducing the concept of Interenet of Behaviors (IoB), something you could take as a cousin of the Internet of Things, with the exception that the idea behind IoB is to address ongoing human (or other system’s) behaviors instead of addressing objects in the world. The idea was to create an addressing or access system that codes or assigns addresses to specific ongoing behaviors (with different time constants from seconds to months or even years) of which an operator is interested. This would bring behavior data into the Internet, in a systematic form.

Internet of Behaviours
Psychology behind Internet of behaviours

Allowing the operators to follow the behavior data, the individuals, bank customers for example, could benefit from it in many ways. I even used a primitive bank example and we tried to get funding from our national innovation funding organization, Tekes to further develop the IoB approach in other contexts – but they did not see any sense in it. Probably it was a too complex or fuzzy idea to them to grasp any of its possibilities in real life. So, here, again, are a few real opportunities, not detailed, but meant for improving the bank services.

Intimate (and secure) life with banks

Imagine you open the connection to your bank in order to check your accounts, for whatever purpose, or to take care of the usual payments. What if, while making this connection, during your activity, or when you are about to finish it, with a push or two of a button, you could express your any, acute economic interest, wish or worry, or simple curiosity, that is on your mind right then and you believe your bank, or some other source could have something to offer to you, even give valuable advice and help? You would inform yout bank about this peculiar ‘state of you mind’. It is a simple, but extremely informative episode of client engagement to any service provider.

You could have your own and shared coding system that you have built with your bank and of which only you and the bank know what each code (behavior – internal, external) represents. I call these codes as addresses to your (ongoing) behavior that only you fully know, be it internal behavior (e.g. planning, thinking, imagining, day-dreaming, worrying) or external (e.g. buying, selling, exercising, studying, going or being somewhere, whatever relevant to you).

I will not introduce here any specific instances of everyday life where the present or future banks could have a useful role in serving us, but you can easily imagine a number of them from your own, even present life, and some of them are truly unique to individuals, families, couples, children and businesses. That is one important aspect of the IoB approach: to (willingly) transform the traffic of intimate human knowledge from the clients to the operators.

There is no one system of the IoB codes or addresses to cover our economics-related behaviors so that it would not become a huge unmanageable mess, but an operator and we as clients would soon learn what these aspects of our everyday life are – in reality and how to best benefit from them. It’s a new kind of a learning journey between the two of us. A peculiar aspect and a compelling example, is the time window of life: often we (but none else) know when we need and want something to happen or to be done. Interestingly, current Internet services do not have much offer in such situations; take for example the case of buying car.

You can be only dreaming and be interested in it, within the next two years, for example or you would be in a desperate need right now. I’ve explained this in another blog showing how stupid the current search engines like Google are in (not) serving us in this kind of situations.

https://gotepoem.wordpress.com/2015/06/10/ignorant-search-engines-do-not-understand-your-life/

Why IoB?

There are several reasons why I have confidence in the IoB kind of an approach in the future.

First, current discourse on Artificial Intelligence, as it occurs in Finland, for example but globally, too, underestimates the value of private, intimate individual knowledge. Instead, big data, machine learning, sensor and following technologies, face recognition, and even brain state measures are expected to open the gate to the individual mind. I don’t believe this will happen during the lifetime of the young generation developing these approaches now. They will bring the operators closer, perhaps at our doors and into the domestic equipment, but not much further and they fail to get in intimate touch with the experiencing, motivated and intentional person.

Second, future services are getting ever more complex and so are the behaviors, which the service providers try to support and benefit from. It’s a problem of dealing with dynamic value networks (e.g. Nyman, G., Peltonen, J., Nelson, M., Karjalainen, J., Laine, M., Nyberg, T., & Tuomisaari, H. (2017). On the Behavioral Theory of the Networked Firm. In: Big Data and Smart Service Systems. Elsevier Scientific Publ).

The systems approach is not only needed in building services but also to understand the dynamics and content of human life and behavior, where new dependencies emerge fast, especially with the new technological solutions and tools. One way, and the best one I know of, to relax the complexity of the problem in serving these multi-dimensional, interdependent behaviors is to let people express their relevant behaviors and states of mind themselves, securely, either semi-automatically or by communicating it voluntarily.

There is a plethora of behavior monitoring, tracking gadgets and systems and it is highly probable that many of them will (and are already doing it at a miniature scale) transform into IoB oriented tools and systems that will boost this development. I expect this to happen within the next five years. It remains an interesting development to follow, where the major breakthrough happens first. Guesses hover in the air already. My own guess is it will happen within the health care services, especially patient follow-up and monitoring of medication. Banks are probably slow, but anyone having the intimate, secure Internet or mobile connection with us should seriously consider this opportunity for valuable services.

 

 

Fiction science – a genre

December 22, 2016 § Leave a comment

 

I’ve understood that it is not wise or respectable professional behavior from a writer to publicly announce that he or she is writing a novel, which will be finished and published by a specific date.

So, I will release my book, a novel on September 9th 2017 in Helsinki, Finland, probably at about 3 PM. If I don’t find an established publishing house, tempted enough by its story, the genre, and style I will again rely on CreateSpace, just as I did with my earlier book Perceptions of a Camino.

Writing of the story I’ve repeatedly wondered what the genre of my novel might be. Slowly I have realized that it can be classified as a member of a specific – nonexistent, as far as I know – genre. In the following I will shortly define that genre – Fiction science – as I think of it. I found this problem curious enough to share the idea and in case it has already been defined somewhere, I will probably learn it from my kind readers. I have earlier written a related story in Finnishnews: http://www.finnishnews.fi/travel/professor-gote-nyman-perceptions-of-real-places-and-virtual-characters/

I tried – not very hard, though – a couple of verbatim and other Google searches “Fiction science” but did not find its definition. The search led to a relevant consultancy “fictionscience” offering their science consultancy for the writers in need and even stuff related to discography. Despite the poor results, I still believe that someone has used the term and definition, especially as it is such a simple transformation of Science fiction, a mere order of the words… However, it seemed reasonable to at least boost the genre of Fiction science by defining it as I’m now doing here, perhaps even sharpening the definition.

The title of my definitely forthcoming book is “Perceptions of the Les Demoiselles d’Avignon” and it tells about real scientist and artists in a way I will not disclose here. But I write about actual, creative people, their real life, as I have imagined it, based on a number of sources. In this sense the story with its imaginary characters meeting real historical persons is, in a way, a distant cousin to Woody Allen’s movie, Midnight in Paris, which he wrote and directed: Wikipedia describes it as a romantic comedy. It was actually one of the inspirations to the story I write although mine is not a comedy.

In the Midnight in Paris movie the main character, Gil Pender, a screenwriter, is, as far as I know, a purely fictional figure, but the artists he meets are real historical painters, writers and poets. Among them we can find Ernest Hemingway, Zelda and Scott Fitzgerald, Paul Gauguin, Salvador Dali, Luis Bunuel and other colorful, historical personalities. In the story, both Gil and the artists he meets have been molded to behave in a fictional, but strictly humoristic way. I that sense, the movie don’t do perfect justice to these wonderful, creative people who have been written to play their funny or perhaps romantic parts in the comedy. In other words, the real historical characters shown in the movie are actually both fictional and real at the same time. Their roles, ways of behaving, their human relationships, and the contents of their discourses are mostly fictional and true to the genre, not so much true to their personal history or doings, but nevertheless, I could loosely call that specific genre Fiction art.

In my forthcoming book I deal with real scientists and artists, based on what we know about them, through various sources, about their achievements, real events and episodes in their lives, pains and joys, trying to respect the content of their domains in science and arts. Of course, I take liberties and this makes it especially challenging to consider what I believe is the genre of my book: Fiction science. The question remaining is this – because of the way I have created the events in my book: are they at all different from what Woody Allen has done in the movie, the comedy?

A definition for Fiction science

Fiction science stories are different from Science fiction in that they always aim at giving the earned credit to the historical scientists, when giving them roles in a fictional context, a story. Fiction science writer tries his/her best to keep every fictional event, episode, and line spoken historically, if not necessarily verbally or even geographically, a honest reality what is known about the historical characters depicted.

Fiction science can include fully fictional characters, events, episodes and spoken lines. The author builds his story, as well as possible, so that the fictional characters interact with the real ones in a way that respects the known factual history, any documents, articles, or other sources concerning the characters having a real and known background.

Why would Fiction science, as defined in this way, be interesting at all or different from other historically grounded stories? Would it only become a kind of a loose, true, but an academic exercise of one or more biographies in the same story?

A story, fitting perfectly in the above definition of Fiction science includes real historical characters, some well known and some less so. The fictional characters can – not necessarily – interact with the real ones, but whenever it happens, the lines spoken, the ways of behaving and other factors related to the historical persons, reflect the reality in a compelling way, allowing creative expressions and interpretations, in other words, without destroying the writer’s freedom of expression and his imagination, but so that it does not give, intentionally, a false picture of a real character.

Interestingly, in Fiction science there is an unlimited number of life events and episodes where historical figures can be presented and about which we know very little. In a formal sense, writing Fiction science is a creative, projection of story-telling on the world of science and the life of scientists. Sometimes, Fiction science novels might even evoke real questions worth while studying – today.

 

 

 

 

 

 

 

 

 

Silence of the wolves?

April 1, 2016 § Leave a comment

Dear Reader,

This time I’ve included several Finnish texts in this post in order to refer my FB friends here for links and details and not to crowd the FB pages too much with the related material. But the story behind all this is worth a few words – and there are a few English texts as well as you can see from below. The story:

I have written my critical comments on the current Finnish higher education system, presented them openly, not insulting anybody in person, arguing for my experiences, views and observations on the university system and its evident problems and failures. My critical texts have all appeared on the frontlines of the Finnish media and channels, like in our leading newspaper Helsingin Sanomat, for example (which has not been interested to publish – as special columns – some of my texts).

You would expect that such an express and repeated activity in criticizing the system would result in numerous interested contacts from the higher education management or at least from people in higher education offices or if not that then at least minimally from your own university, faculty or department. The reality?

No!No! and Ei! Practically total official silence! If I were a simple or even a complex fool, with no academic background, you could understand this. But I have a respected academic history as the Dean (the only psychologist in that position ever) of the largest faculty in Finland, numerous manager roles, even today at UH, work as an advisor for a Stanford research program, and some of my work has even occurred in Nature (long time ago) J. My blog (this one) is quite innovative and I have had numerous high-class international contacts, collaboration and talks in big firms in Silicon Valley. So, I’m a relatively sane academic and would expect some interaction. I know, of course, that I have a difficult message.

Well, to tell the truth – I don’t want any such contacts and communication right now. I have inspiring, creative stuff on my mind and on my desk. So, I have decided to stop this critical writing after one more article on an innovative (vitality-based) higher education system model-paper gets finished and published somewhere. (Note on 10th August 2016): I have still continued some public writing as I was invited to join Saimaa Summit 29th August 2016 and give a talk there on these matters and where we considered these problems in front of an influential local people… But it is time to move asap to other direction).  But for you, my young and even older colleagues, working in the system, building it and making it happen – wake up! (I’m retired) There is something scary in this attitude of those responsible for running your education system, which is a significant part of your life and passions. Don’t let silence lead to disasters as it is doing now!

As a result of these writings I have never been seriously contacted by my own university or faculty or received an invitation to tell more and present the case at a relevant (or any other, for that matter) forum, nobody from the ministry of education, practically total official silence everywhere. Except: I’ve received a number of private communications in FB and through my email, telling their individual stories, experiences and encouraging me to continue. And I’ve been invited to serve as a mentor to some young scientists. Which has been an exceptional joy.

I admire Matti Alahuhta, a real exception, the famous Finnish leader (ex-Nokia, Kone, now EK) who has invited me twice for a serious and inspiring discussion on some of the topics – and offering a lunch J He is the only one during about 7-8 years of my open and active criticism on these matters. And of course, as you can see from the last parts of the list below, I’m not only criticizing but also presenting a number of ideas and suggestions for a better system, at many levels

What is happening to the Finnish academia, that is expected to be open for discussion and criticism?? Are people afraid? Are the managers tired and overloaded? Does the system really suck?

First, here are some general thoughts on how I think about the life of a scientist in a university context – it also explains why I’m so strongly against the current higher education management system. I have given a talk on this to some of the people outlining Aalto performance metrics in 2010 – with very little success and then  to colleagues at Stanford. I’ve made only some minor changes to the text captions: Life_of_a_scientist

Here are the articles I’ve written on these topics and some quotations from them:

Paikallista elinvoimaa korkeakouluista – nyt! (It-Savo, 10.8. 2016)

“Näkyvissä ei ole vuosikausiin toimijoita, jotka muuttaisivat kehityksen suunnan. On aika toimia korkeakoulujen vaikutuspiirissä ja niiden lähipaikkakunnilla.  Lähtökohdaksi voi ottaa juuri ne paikallisesti arvokkaat tekijät, joita maan korkeakouluhallinto ylenkatsoo. Korkeakoulujen parjattu hallintomallikin tarjoaa viisaalla johtamisella ja yhteistyöllä uusia mahdollisuuksia — joita on vähemmän osattu hyödyntää.”

Korkeakoulut tuovat elinvoimaa koko Suomeen (Kaleva 7.6. 2016)
“Korkeakoulujen strategiapeli ja kamppailu hupenevista voimavaroista rapauttaa tieteenaloja ja yliopistoja Suomessa. Uudenlaisia alueellisia, taloudellisia ja kulttuurisia sekä muita kansallisen vahingon ensioireita ilmenee jo ja on pelättävissä, että tämä kehitys syvenee.”

Korkeakoulujen hallitukset pettivät odotukset. (TS 1.4. 2016)
“Hallituksiin ei siis ole onnistuttu tuomaan vaikuttavaa talousosaamista, ne eivät ole hoitaneet yhteiskuntasuhteita odotetulla tavalla eivätkä ne ole edistäneet yliopistolaisten vaikutusmahdollisuuksiakaan.”
http://www.ts.fi/mielipiteet/lukijoilta/858036/Korkeakoulujen+hallitukset+pettivat+odotukset

Työttömät tohtorit ovat kansallinen häpeä. (HS 2.1. 2016)
”Tohtoreiden työllistyminen ja elämässä selviytyminen eivät virallisessa Suomessa näyttäydy erityisongelmana. Korkeakoulujen strategiapelien tai apurahaongelmien vuoksi työttömiksi jääneet huippuosaavat tohtorit kokevakin ”kaiken maailman dosenttien” hylkiökohtelun.”
http://www.hs.fi/mielipide/a1451618574662

Perceptions of higher education – Finnish drama. (Finnishnews. 2.2. 2016)
“Some believe that we will reach the top of the world science. Some doubt it. My question is, what if we reach the top in a haphazard field, what good do we then gain as a nation?”
(http://www.finnishnews.fi/tech-science/perceptions-of-higher-education-a-finnish-drama-professor-gote-nyman/)

Suomen korkeakoulupolitiikan strategia on vahingollinen. (Image 2, 2015)
”On syytä pelätä, että näin tosiasiassa heikennetään kansallisen osaamisen perustaa ja kykyä reagoida ennakoimattomiin tieteen haasteisiin. Samalla suomalaiset ja korkeakoulut etääntyvät maailman merkittävistä kysymyksistä.”
http://www.hs.fi/mielipide/a1451618574662

Tohtorien työttömyys rapauttaa osaamispohjaa. (HS 12.10. 2014, Krista Lagus in kanssa)
http://www.hs.fi/paivanlehti/mielipide/Tohtorien+työttömyys+rapauttaa+osaamispohjaa/a1412993330223

Tiedeyhteisö on hiljaa. (HS 2.3. 2013)
“Korkeakoulu-uudistus hiljensi yliopistojen sisäisen kritiikin.”
http://www.hs.fi/mielipide/a1362125852594

Korkeakoulujen henkilöstö on kriisissä. (HS 9.5. 2012)
”Yliopistojen hallinnonuudistus on epäonnistunut pahasti ja saattaa aiheuttaa suomalaiselle innovaatioympäristölle merkittävää vahinkoa.”
http://www.hs.fi/paakirjoitukset/a1305561654924

Suomen Akatemian rooli olisi syyt uudistaa. (HS 7.4. 2011)
”Kapea huippuyksikköpolitiikka voi mennä muutenkin pahasti metsään. Sen toimintamallien tuloksena Suomeen ei ole kehittynyt kannustavaa arviointitapaa, joka tukisi laaja-alaista kansallista tutkimusrintamaa.”

Re-think higher education strategy for 2020/2030.
(Oivallus-hanke/EK 8.2. 2011)

“It is beyond comprehension to see that nothing is being done to stop this: a clear majority of researchers and teachers in our universities see the present management model as a nightmare, disaster and a floppy (see the recent review by Tieteentekijät ja Professoriliitto and the article by J.P. Roos in Tieteessä tapahtuu 6/2010, ss. 43-46).”

http://ek.multiedition.fi/oivallus/fi/liitetiedostot/arkisto/Keskustelupaperi_Nyman_Final.pdf

Not only criticism but also new and fresh ideas and thinking:

Millaista korkeakoulupolitiikkaa Suomi tarvitsee: Elinvoimainen korkeakoulupolitiikka koko maan hyvksi (26.4. 2016 Image, together with prof. Markku Wilenius)

http://www.image.fi/vierailevat-kirjoittajat-gote-nyman-ja-markku-wilenius

Here we outline a novel, higher education model built on the strength of geographically local but also global networking principles. Its aim is to guarantee a distributed, wide-spectrum cultural, scientific and economical vitality in Finland.

Perceptions of the network capital of a small country (26.3. 2016 Finnishnews)

A widely distributed university system has a significant national impact if it lives on the following two simple principles in its research, education and local interaction.”
(http://www.finnishnews.fi/tech-science/perceptions-of-the-network-capital-of-a-small-country-prof-gote-nyman/)

Päätöksenteon, innovaatioiden ja oppimisen tulevaisuus. (Kanava 23.10. 2015 yhdessä Timo Hämäläisen kanssa)

“Uudet oivallukset, tieteelliset läpimurrot ja radikaalit innovaatiot syntyvät yhä useammin usean eri alan tietojen luovista yhdistelmistä. Tämä edellyttää tiivistä vuorovaikutusta toisiaan täydentävien alojen asiantuntijoiden kesken. Debatin sijaan tarvitaan dialogia, analyysien oheen eri tiedonaloja yhdisteleviä synteesejä.”

What are we good for: Challenges of education in Finland (Radical renovation of education, together with Markku Wilenius, report to Sitra, not published 1.8. 2014)

Siiloutunut Suomi voisi oppia Piilaakson yhteistyöstä (Ossi Kuittisen ja Markku Wileniuksen kanssa, Te 22.4. 2013)

Ecosystems of Triple Collaboration (Helice Vol. 2. Issue 3.)

“Guidelines for collaboration project, 1-7,

  1. Establish firm economical and spiritual ground for basic research that is not threatened by economically successful external partnering activities. This is an absolute demand. Applied research can and must make profits relatively fast. Its economical and human time constants are significantly shorter than in ambitious basic research …2. …7.

University-Business-Government Collaboration: From institutes to platforms and ecosystems

Triple Helix J. 2 (2015) Springer.

” Experiences and learning lessons from small-scale, university-business-government collaboration cases are described and used as supporting knowledge for the hypothetical, bottom-up type of collaboration model.”
http://link.springer.com/article/10.1186%2Fs40604-014-0014-x

Professori arvostelee: Aalto-yliopisto unohti yritykset. (Te 12.10. 2011)
”Yritysjohtajat ja ulkopuoliset jäsenet eivät mitenkään pysty näkemään, mitä yliopistolla tapahtuu”, Nyman sanoo. ”He ostavat hallintobyrokraattien retoriikan, koska eivät oikeasti tunne tieteen tekemistä.”
http://www.talouselama.fi/uutiset/professori+arvostelee+aaltoyliopisto+unohti+yritykset/a2003491

 

 

 

 

 

Your future car – fighting the climate change?

March 30, 2016 § Leave a comment

I sent this as a blog text to Huffington post but they did not respond indicating (as they tell on the site) that they were not interested in it. But I see the story as quite revolutionary thinking and thought my own blog can still distribute it to those interested. Of course there is a lot to do in this field, globally and I’m not a technology expert on this. But if this is valuable thinking, someone will find it anyway. So:

Imagine that our Fords, BMWs, and Toyotas and their electric and hydrogen versions – instead of having only a low or even a zero CO2 emission – would actually fight the climate change by removing CO2 from the air? The car on the road and in park with its engine running would be transformed from a climate change threat to a global asset and virtue in protecting the atmosphere. “You cannot do that! There is no such technology! Cities are crowded already!” are the expected comments to such an unorthodox idea. But the thought experiment offers new fuel for thinking about the nature of human mobility.

Cleaning the air from CO2

Removing CO2 from the air is a fresh, inspiring dream as the MIT report tells us, but not an unrealistic one. Scientists are imaging and experimenting with novel ways to transform CO2 to valuable materials such as carbon nanofibers for industrial uses. Quite recently, Bill Gates invested in a new system for sucking CO2 from the air and transforming it to harmless carbonates. The global pressure to succeed in these innovations is almost as high as in fighting cancer. No surprise then that there is an incipient trend to imagine and work on revolutionary methods that actually clean the air and the environment, instead of just preventing pollution.

Amazing technologies aim at protecting our environment. A prototype bikini, designed by the engineers at UC Riverside cleans the seawater from various pollutants that reach the sea, cf. Huffpost Science, 10/2/2015, “This Bikini Of The Future Cleans The Ocean As You Swim”. Another invention from University of Sheffield and the London College of Fashion offers air cleaning clothing that removes nitrogen oxides from the air – about the same amount produced by the average family car each day! Then, a research team from China (Shan Gao et al., 2016) published compelling new research results in Nature:

A new material made from microscopic layers of cobalt can convert carbon dioxide gas into formate – a fuel that can be burned with no toxic byproducts and used as a clean energy source.”

It is time to take take a second look at the future roles of cars and other transportation vehicles in this, including the potential of the self-driving cars.

Cars can be a threat and an asset

According to the United States Environmental Protection Agency (EPA) in US, the CO2 produced by human activities originates from electricity (37%), transportation (31%), and industry (15%). In transportation the “on-road vehicles” produce overwhelmingly more CO2 than other forms of transportation, e.g. on-road vehicles: 1,442.7 Teragrams of CO2 vs. aircrafts: 148.7 . In EU Cars are responsible for 12% of total EU emissions of carbon dioxide and the law requires that the new cars do not emit more than an average of 130 grams of CO2 per kilometre by 2015.

We can see cars on the road, having zero CO2 emission like Tesla and Nissan Leaf (EVs) and even the hydrogen powered Toyota Miral. But the critics, referring to the life cycle analysis of EVs, know that almost half of their CO2 emissions come from the manufacturing and mining of the raw materials of the batteries and from the primary energy sources utilized for making these cars. These energy sources – coal, nuclear, wind – vary considerably around the world and depend on the total energy demand.

Opinions differ on how to exactly estimate the total burden on the environment caused by the production, waste processes and the energy sources, but there is no doubt that the big picture is problematic. Nevertheless, a fair question remains – what if we could make air-cleaning cars capable of removing CO2 from the air? Would it be possible to aim at a car manufacturing model where it is obligatory for any car maker to guarantee that its cars clean at least as much air from CO2 as its cars on the road and the manufacturing process together produce it? Could the charging of a car actually be connected with a grid of air-cleaning systems so that every time it is charged or refueled it would participate in the air-cleaning process.? This would mean a revolution in the way we think about transport, logistics, urban architectures and the health of our environments.

Time pressures

The alarming fact is, of course, that not only the increasing number of cars but the whole car manufacturing industry, including the production of electric and hydrogen powered cars, is producing excess amounts of CO2 right now and fast solutions are needed.

Even if the car industry and the road traffic would be effectively cleaning the air, many would still resist this development because it crowds the roads, cities and public spaces. More cars would remain a genuine nuisance and the cities and motorways cannot take more than already now dominate the scarce public spaces. Many cities have made these long-lasting decisions to provide space for pedestrians, public transport and biking.

However, it is not realistic to assume that cars could be removed from the planet within the next thirty years. It is a long time in developing new technologies and it is highly likely that the developing economies will have more cars when the entering new middle class enjoys the fun and comfort of driving and owning a car. Globally, the situation is becoming serious as indicated by the health-threatening pollution in Delhi, where a driving-ban has been issued to get a million cars off from the roads. Many think that it is not even closely enough

The International Transport Forum has indeed estimated that the number of motor vehicles in the world, being now 1.2 billion will be roughly 2.5 billion by 2050. So, even if we try to limit car use, diminish the car ownership, design self-driving cars and their traffic environment, we should still think about cars also as assets in fighting climate change. The question remains, what would be the optimal strategy in preventing the gloomy future of CO2 emissions? We need a step-by-step, evolutional and creative thinking with a clear goal in mind.

Future of nomadism

People will always be moving and commuting even when the best VR systems have matured so much that information sharing, collaboration and even social manufacturing have become everyday practices. We want to get together, touch and hug each other, feel the closeness, and share the physical presence and participation at work, entertainment and in any human relationships. When commuting becomes fast, easy, cheap and acceptable, people can adopt new roles as modern nomads, different from their classic predecessors who had to move from one place to another. The future nomads can arrange their model of life and living according to their values – in the seamless world of virtual communication and physical mobility – while contributing to the clean air.

Genomic Games: Gene play

December 12, 2015 § Leave a comment

The amazing advances in behavioral genetics and personal genome analysis have taken most of us by surprise: you can purchase a profile of your personal DNA and even receive reports on your health-related risk factors – with a price less than a cheap smart phone. While there are still a number of serious problems and limitations in such tests and we have to be careful with any of their simplifying interpretations, they will surely improve and more is to come, fast.

A parallel technological and sw progress has occurred in the design and implementation of computer games, both entertaining and serious games. It is time for these two amazing, but only apparently distant developments to meet and make possible something wonderful. This is only a short conceptual note on combining game and gene technologies to achieve it:

Computer games where each game character has a specific personal genome, real, theoretical or imaginary! Such games would have immense entertaining and educational potential. The games could be used for running complex and even massive scientific simulations to study, for example, the impact of specific human genome features on human behaviors in specific game worlds and plays.

Such games could also shed light on the interaction of the individual genome with any of the virtual environments where they are played. And of course, time is a flexible variable in such games so that a number of growth, evolutionary, mutation, gene expression, and any other developmental factors can be modeled and studied. Anything that the gene and behavioral genetic scientists can imagine can be implemented as a computer game. Here are some further examples of this huge potential the gene games can offer for science and entertainment and why not also for personal self-knowledge and learning:

Imagine games where either the personal genome of the player or the genome of the characters, which the player controls have personalized genetic, hereditary or environmental background. The genome can be as realistic as is possible based on current research data or it can be just theoretical or imaginary. And of course, all other characters in the specific game world have their backgrounds as well. There would be a lot for new kind of operators to do in integrating science and game data, perhaps even offering open platforms for this.

The specified and implemented gene/environment/interaction factors affect the capabilities, tendencies, vulnerabilities or whatever personal characteristics of each gamer. However, because games can be massive, it becomes also possible to follow the consequences of certain gene pools or types of genome in any such large scale development – and in any game world. But of course, it is also possible to follow individual behaviors and its consequences of such genetically profiled individuals, real, theoretical or imaginary. We can test our own exaggerated genes, for example

Imagine further, that computer gamers join an open project like the Personal Genome Project (http://www.personalgenomes.org), where they offer their personal genome data for the scientists to study and follow them in any of their preferred or perhaps even specifically designed games. Only imagination sets the limits to this approach and we all know the huge global number of players today.

Why I write on this? Well, already for 2-3 years I have tried to get some individual game world people to get excited on this but has met very little genuine interest and fascination with what I’ve been truly excited about ever since 2010. But then just yesterday, I had a wonderful Xmas (very long) lunch with friends on the 11th Dec, invited by a friend, Ernst Grönblom and one of the people present happened to have a strong funding background in gene-related health businesses. His genuine excitement and encouraging attitude made me write this now and share it with my readers. I have not made a thorough literature analysis on this topic, so if this is nothing new, then I know that at least I’m in the same boat, sailing towards new horizons.

Below is an inspirational quotation from the Personal Genome Program (see the link above). Only “Games” are missing there.

“The answers to many fundamental questions about basic human biology, our experiences as individuals, and our history as a species will be illuminated by better access to large datasets that contain many human genomes tied to other forms of personal information, such as medical history and physical traits. Thus far, only a handful of individuals in the world have been extensively sequenced and studied. The PGP aims to change this by giving individuals a platform to share their genome, health and trait data.”